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1、2024 International Monetary FundSleepwalking to the Cliff Edge?A Wake-up Call for Global Climate Action IMF Staff Climate Notes 2024/006Simon Black,Ian Parry,and Karlygash Zhunussova*DISCLAIMER:The IMF Staff Notes Series aims to quickly disseminate succinct IMF analysis on critical economic issues t

2、o member countries and the broader policy community.The IMF Staff Climate Notes provide analysis related to the impact of climate change on macroeconomic and financial stability,including on mitigation,adaptation,and transition.The views expressed in IMF Staff Climate Notes are those of the author(s

3、),although they do not necessarily represent the views of the IMF,or its Executive Board,or its management.The terms country and“economy”do not in all cases refer to a territorial entity that is a state as understood by international law and practice.The terms also cover some territorial entities th

4、at are not states.The boundaries,colors,denominations,and any other information shown on the maps do not imply,on the part of the International Monetary Fund,any judgment on the legal status of any territory or any endorsement or acceptance of such boundaries.RECOMMENDED CITATION:Black,Simon,Ian Par

5、ry,and Karlygash Zhunussova.2024.“Sleepwalking to the Cliff Edge?A Wake-up Call for Global Climate Action.”IMF Staff Climate Note 2024/006,International Monetary Fund,Washington,DC.ISBN:979-8-40028-964-4(Paper)979-8-40028-989-7(ePub)979-8-40028-987-3(PDF)JEL Classification Numbers:Q31,Q35,Q38,Q48,H2

6、3Keywords:Paris Agreement;climate mitigation;carbon pricing;climate finance;climate investmentAuthors email addresses:sblackimf.orgiparryimf.orgkzhunussovaimf.org*This Note was prepared under the guidance of Dora Benedek.The authors are grateful to several IMF colleagues for veryhelpful comments and

7、 suggestions.International Monetary Fund.Not for Redistribution IMF|Staff Climate Note NOTE/2023/006 Sleepwalking to the Cliff Edge?A Wake-up Call for Global Climate Action Simon Black,Ian Parry,and Karlygash Zhunussova October 2024 Summary Urgent action to cut greenhouse gas(GHG)emissions is needed

8、 now.Early next year,all countries will set new emissions targets for 2035 while revising their 2030 targets.Global GHGs must be cut by 25 and 50 percent below 2019 levels by 2030 to limit global warming to 2C and 1.5C,respectively.However,current targets would only cut emissions by 12 percent,so gl

9、obal ambition needs to be doubled to quadrupled.Further delay will lead to an“emissions cliff edge,”implying implausible cuts in GHGs after 2030 and putting 1.5C beyond reach.This Note provides IMF staffs annual assessment of global climate mitigation policy.It illustrates options for equitably alig

10、ning country targets with the Paris Agreements temperature goals.It also provides guidance on the modeling needed to set emissions targets and quantify climate mitigation policy impacts.Introduction Limiting global warming to 1.5C to 2C requires cutting greenhouse gas(GHG)emissions by 25 to 50 perce

11、nt by 2030 versus 2019.However,gaps in climate ambition and implementation persist(Figure 1).Countries have raised their ambition since 2015,but even if 2030 emissions targets in nationally determined contributions(NDCs)were achieved,global GHGs would fall by just 12 percent from 2019 levels(panel 1

12、)versus a needed 25 to 50 percent cut.Worse still,in a business-as-usual(BAU)scenario,emissions are projected to increase by 5 percent.Indeed,a global carbon price of$85 per tonne by 2030 would get emissions on track to 2C and much more would be needed for 1.5C(panel 2).But the current global carbon

13、 price is just$5 per tonne.Figure 1.Global GHG Emissions and Targets(in NDCs)and Temperature Goals(Panel 1)and the Global Mitigation Implementation Gap Expressed as a Carbon Price(Panel 2)1.Ambition Gap 2.Implementation Gap Sources:Intergovernmental Panel on Climate Change 2022;and IMF staff calcula

14、tions using the IMF-World Bank Climate Policy Assessment Tool(CPAT).Note:Includes land use and land-use change emissions.In panel 1,NDCs(2015)shows the needed trajectory from current emissions levels to 2030 emissions targets that countries had set during the Paris Agreement.NDCs(current)show the tr

15、ajectory that countries would need to take to achieve their current 2030 targets.The gap between the two is the increase in global climate mitigation ambition since 2015 as countries have since revised their 2030 targets.In panel 2,calculations are for energy-related CO2 but the functional relations

16、hip in the figure would be similar for total GHGs.BAU=business as usual;CO2e=carbon dioxide equivalent;GHG=greenhouse gas;NDC=nationally determined contribution.EU-27Other EuropeUnited StatesOther AmericasIndiaChinaOther AsiaAfricaOther0102030405060197019801990200020102020203020402050BAU2 C1.5 CNDCs

17、(current)NDCs(2015)Ambition gap to 2030ProjectionsGlobal GHG emissions(billion tonnes of CO2e per annum)0102030405060708090100110120130140150-505101520253035 40Global CO2 price in 2030($/tonne)CO2reduction relative to 2019(percent)$85 required for 2C Much more needed for 1.5C(not shown)Current globa

18、lcarbon price($5)International Monetary Fund.Not for Redistribution IMF|Staff Climate Note 2 In 2023,countries recognized“the window to keep warming to 1.5 C within reach is closing rapidly now is the time to rapidly accelerate action.”1 Countries are due to set new emissions targets for 2035 while

19、enhancing 2030 targets well ahead of COP30,that is,early next year.If 2030 targets are not strengthened and achieved,the 1.5C goal will become permanently beyond reach.This Note aims to provide the following:(1)IMF staffs annual assessment of global climate mitigation policy;(2)options for equitably

20、 aligning 2030 and 2035 emissions targets with global temperature goals;and(3)guidance for policymakers on modeling to set and achieve emissions targets.The Note builds on earlier assessments(Black and others 2021,2022a,2023c)2 by updating data sources and providing illustrative scenarios for gettin

21、g global emissions on track equitably.It also provides practical guidance on the modeling required for setting emissions targets while assessing impacts of mitigation policies,providing illustrative results for Group of Twenty(G20)countries.The Note uses the IMF-World Bank Climate Policy Assessment

22、Tool(CPAT),which is a model unique in allowing for comprehensive assessments of climate mitigation for around 200 countries.3 Key messages from the analysis include:Two major gaps in global climate policy persist.Global mitigation ambition and implementation remain well below what is needed.Mitigati

23、on ambition for 2030 needs to be doubled to quadrupled.Emissions growth since 2020 means GHG now need to be cut faster,by 25 and 50 percent by 2030 versus 2019 for 2C and 1.5C,respectively(up from 21 and 43 percent,identified by the Intergovernmental Panel on Climate Change IPCC).Current targets wou

24、ld cut emissions by just 12 percent.Collectively,the world is approaching an“emissions cliff edge.”If 2030 targets are not enhanced,emissions cuts needed thereafter are implausible,putting 1.5C out of reach.We present illustrative targets for ratcheting up climate ambition equitably by income level

25、for all countries.These would align global emissions with 1.5C or 2C,with richer countries cutting emissions faster.However,the rate of decarbonization required for 1.5C is rapid for all countries and it remains to be seen if such a rate is feasible technologically,economically,and politically.Curre

26、nt mitigation policies vary considerably.There is substantial variation in mitigation policies across countries and different sectors.Globally however,policies fall well short of what is needed for 2C,let alone 1.5C,indicating a large implementation gap.The current estimated abatement costs of align

27、ing global emissions in 2030 with 2C are manageable(around 0.4 percent of GDP).These costs,which are broadly the welfare costs of inducing households and firms to adopt cleaner but more expensive technologies,can be progressively distributed globally,and for many countries(especially developing ones

28、)are offset mostly or fully by domestic environmental co-benefits(excluding climate benefits).The costs of 1.5C are much less certain.Stronger international coordination can help close the global mitigation ambition and implementation gap.Given the concentration of global GHGs and political influenc

29、e,plurilateral agreements between a small number of players could accelerate ambition and action.This could include coordination over policies(for example,minimum carbon prices)or emissions targets.Modeling is critical for setting emissions targets and assessing policy impacts.However,governments of

30、ten lack modeling capacity and data.We provide guidance,including on setting emissions forecasts,aligning near-term targets with long-term goals(for example,net zero by 2050),and quantifying the impacts of mitigation.1 See https:/unfccc.int/documents?f%5B0%5D=symboldoc%3AFCCC/SB/2023/9.2 See also UN

31、EP(2023)and UNFCCC(2023)for similar findings on global mitigation ambition gaps.3 The model that is available to government officials and is briefly described in Annex 1 and in detail in Black and others(2023a).See also www.imf.org/cpat for further information.International Monetary Fund.Not for Red

32、istribution IMF|Staff Climate Note 3 Equitably Aligning Global Emissions with Temperature Goals Global Emission Reductions Needed Long-term net zero goals are vital but should not distract from the need for stronger,temperature-aligned mitigation targets and policies in the near term.As of December

33、2024,147 countries,accounting for about 70 percent of 2020 GHG emissions,have committed to net zero emissions by 2050 or 2060,while some have made earlier or later commitments(for example,India in 2070).4 Only 11 percent of these targets are enshrined in law;however,most are in policy documents and

34、some in political pledgessee Figure 2 for a global summary.Even if there were a reasonable prospect for ultimately meeting these targets,the path to net zero also matters,as global warming depends on cumulative stock of GHGs in the atmosphere.If emissions reductions are delayed until later in the tr

35、ansition,atmospheric GHG accumulations and global warming will increase.Further,delaying action will slow down the pace at which low-carbon technologies are developed and improved through innovation and learning-by-doing,raising the costs of clean energy transitions.5 In addition,three trends create

36、 risks that even current 2030 targets could be missed:(1)recent geoeconomic fragmentation,such as rising tariffs on low-carbon technologies;(2)continued investment in fossil fuels which could lead to“carbon lock-in”6;and(3)growing climate-induced physical hazards as the world warms which could reduc

37、e resources available for mitigation as opposed to,for example,reconstruction.7 Even 1.5C would have significant consequences for human and natural systems,losses and risks which increase with warming(Intergovernmental Panel on Climate Change,IPCC 2018).The 2015 Paris Agreement was predicated on the

38、 need to ratchet up climate ambition over time.Since then,ambition has increased but falls well short of what is needed.During the Paris Agreement negotiations,it was known that countries emissions targets(in NDCs)would not be sufficient to keep global warming“well below”2C above pre-industrial leve

39、ls,ideally to 1.5C.8 It was envisioned that countries would ratchet up ambition on a five-year basis(the first at COP26 in 2021),supported by periodic progress reviews(the“Global Stock Take,”first concluded at COP28 in 2023).9 NDCs set in 2015 would have cut emissions in 2030 by just 2 percent versu

40、s 2019 levels,whereas current NDCs would cut emissions by about 12 percenta step in the right direction,but well short of 25 to 50 percent cuts needed(Figure 1).4 Net zero allows positive emissions from some(hard-to-abate sectors)like agriculture so long as they are offset by negative emissions else

41、where,for example,through forest carbon sequestration or direct air capture.5 Whether temperatures rise above target levels temporarily(“overshoot”)is also determined by the historical stock of emissions.Note that,given the uncertainty in the relationship between emissions and global warming respons

42、iveness(“climate sensitivity”),temperature goals are expressed probabilistically.In this Note,aligned with the Intergovernmental Panel on Climate Changes scenarios,the 1.5C target is assumed to be achieved with 50-percent probability with“no or limited overshoot”while 2C is achieved with 67-percent

43、probability.6“Carbon lock-in”conceptualizes the idea that investments in high-carbon assets,such as oil distribution infrastructure,today can lead to future emissions since it becomes cheaper to continue polluting than to decarbonize.7 Refer to Gardes-Landolfin and others(2023).8 See https:/unfccc.i

44、nt/process-and-meetings/the-paris-agreement.9 In addition,at COP28,countries committed to accelerating the“phase-down on unabated coal power,”scaling up“net zero emission energy systems,”and“transitioning away from fossil fuels in energy systems,in a just,orderly and equitable manner,accelerating ac

45、tion in this critical decade,so as to achieve net zero by 2050 in keeping with the science.”See https:/unfccc.int/documents?f%5B0%5D=symboldoc%3AFCCC/SB/2023/9.Figure 2.Net Zero Emissions(NZE)Targets by Target Year,Legal Status,and GHG Coverage Sources:Net Zero Tracker;and IMF staff calculations.Not

46、e:GHG=greenhouse gas.05101520253035402060 no NZEPercent of global GHGs coveredIn lawIn policy documentIn political pledgeNo NZE targetInternational Monetary Fund.Not for Redistribution IMF|Staff Climate Note 4 Since 2015,countries have increasingly emphasized the need to keep warming at 1.5C.At COP2

47、8,countries set a collective goal of cutting global GHG emissions by 43 percent(48 percent in CO2)by 2030 and 60 percent(65 percent in CO2)by 2035 versus 2019 levels,but this is already insufficient.These goals represent emissions cuts in the midpoint of scenarios aligned with 1.5C identified by the

48、 IPCC.10 This scenario,however,envisioned rapid emissions reductions from 2019 onward,whereas after an initial drop in 2020(because of the coronavirus pandemic)emissions have continued to grow.In 2023,global GHG emissions were 10.8 billion tonnes(25 percent)higher than what the IPCC suggested was ne

49、eded for 1.5C.Accounting for this,IMF staff calculations suggest the new target would need to be an even larger 49-percent reduction in GHGs(53 percent in CO2)for 2030 and 66-percent reduction in GHGs(72 percent in CO2)for 2035.11 These are drastic cuts and may not be technically(let alone political

50、ly)feasible.If 1.5C is to be kept alive and the world is to avoid an“emissions cliff edge”in the 2030s,it is critical that global emissions are cut rapidly in the next five years(Figure 3).If current targets for 2030 remain(and are achieved on linear emission reduction trajectories),keeping 1.5C ali

51、ve would require(1)cutting 2035 emissions by 75 percent,(2)achieving net zero emissions in 2040,and(3)net removals of CO2 from the atmosphere after 2040,implying widescale use of costly technologies like direct air capture.The rate of decarbonization under this cliff edge scenario is dramaticglobal

52、CO2 emissions would need to decline over 7 percent each year from 2030 to 2040.12 For comparison,the once-in-a-generation annual fall in global CO2 emissions in 2020 because of the coronavirus pandemic was just 5.8 percent(after which emissions rose).13 If,instead,countries continue emitting at curr

53、ent levels,the remaining carbon budget to 1.5C(the allowable amount of cumulative CO2 implied by the temperature goal)would be fully exhausted by 2035at that point,global emissions would need to go immediately and permanently to zero.Current Emissions and Mitigation Targets by Country Income Group C

54、limate mitigation and international equity are intrinsically linked.The issue of equity(known as“common but differentiated responsibilities and respective capabilities”)has historically divided countries into two camps in the United Nations Framework Convention on Climate Change.Under the precursor

55、to the Paris Agreement,the Kyoto Protocol,“Annex I”(mostly developed)countries were required to cut emissions,whereas“non-Annex I”countries(mostly developing countries)were not.Given that developing countries already accounted for a majority of annual emissions,and nearly half of historical emission

56、s,when the Protocol came into force in 2012and they account for two-thirds of annual CO2 emissions now(see Figure 4)achieving a global emissions trajectory aligned with 1.5C2C would have been infeasible.Under the Paris Agreement,all countries are committed to cutting emissions,with high-income count

57、ries(HICs)going faster while providing financial and technological assistance to developing countries.10 Allowing for some risk of overshoot,where the temperature goal is temporarily exceeded before returning to that level at some future point.Countries noted“Limiting global warming to 1.5C(50-perce

58、nt probability)with limited or no overshoot implies a reduction of around 43,60,and 84 percent in global GHG emissions below the 2019 level by 2030,2035 and 2050,respectively,as assessed by the IPCC.”Refer also to table SPM.1 in https:/www.ipcc.ch/report/ar6/wg3/.11 This assumes a fixed carbon budge

59、t out to 2050 and that emissions cuts catch up with the IPCCs“C1”(“Below 1.4C with no or limited overshoot,”also known as SSP1-1.5)scenario linearly from 2024 to 2040.12 Under the 1.5C scenario,CO2 emissions would fall from estimated current levels in 2023 by an annual average rate of 4 percent ever

60、y year to 2030 and then 3.5 percent to 2050.13 See https:/www.iea.org/reports/global-energy-review-2021/co2-emissions.Figure 3.Countries Are Setting up an“Emissions Cliff Edge”in the 2030s Sources:Intergovernmental Panel on Climate Change 2022 and IMF staff calculations.Note:CO2=carbon dioxide;NDC=n

61、ationally determined contribution.-10-505101520253035402020202520302035204020452050Billion tonnes of CO2Needed for 1.5CStatic 2030 NDCs2030semissions cliff edgeNegative emissions from 2040 onwardsInternational Monetary Fund.Not for Redistribution IMF|Staff Climate Note 5 Emissions cuts implied by cu

62、rrent NDCs vary substantially across income groups(Figure 5).CPAT allows for quantification and comparison of mitigation ambition in NDCs for over 150 countries.By estimating countries emissions in the BAU and comparing to that implied by NDCs,countries can be compared in a transparent and consisten

63、t manner.14 HICs,15 as a group,have more than tripled their ambition(from 10 to 32 percentage points ppts versus 2030 BAU)since 2015.Upper-middle-income countries(UMICs)have increased ambition from 9 to 14 ppts,while ambition among lower-middle-income(LMICs)and low-income countries(LICs)as a group i

64、s largely unchanged(at 7 to 8 ppts).Figure 5.Distribution of NDC Ambition across Income Groups(2015 versus 2024,Panel 1)and Emissions per Capita across Key Countries in 2030(Panel 2)Source:IMF staff calculations using CPAT.Note:For developing countries,unconditional and conditional NDCs are averaged

65、.Where BAU and NDC are equal,the target is either nonquantifiable or nonbinding;that is,it is assumed to be achieved in the baseline.Data labels use International Organization for Standardization(ISO)country codes.BAU=business as usual;HICs=high-income countries;LICs=low-income countries;UMICs=upper

66、-middle-income countries;LMICs=lower-middle-income countries;NDC=nationally determined contribution;1 Of 220 countries analyzed,63 had nonquantifiable NDCs,that is,do not have any targets or have targets that are not economy-wide.2 Of the 157 countries with quantifiable NDCs,36 were considered nonbi

67、nding,that is,the target is met in the business-as-usual(BAU)scenario.These countries account for 20 percent of global GHGs.3 We do not assume that countries raise emissions above BAU by,for example,reversing current mitigation policies.14 Comparing targets relative to business-as-usual(BAU)levels i

68、s a fairer measure of country ambition compared with absolute cuts,as for example,low-income countries could have targets implying emissions cuts versus BAU even while raising absolute emissions.BAU emissions projections by country authorities(using their own methodologies)may differ from those in t

69、he CPAT.15 World Bank classifications are used https:/datahelpdesk.worldbank.org/knowledgebase/topics/19280-country-classification.81432791001020304050010203040Low-and lower-middle-incomecountriesUpper-middle-incomecountriesHigh-incomecountriesShare of global GHGs(2030 BAU)NDC ambition(percent reduc

70、tion in GHGs versus BAU in 2030)2024 NDC2015 NDCShare of global GHGs in 2030(right scale)1.Distribution of NDCs across income groups02468101214161801,0002,0003,0004,0005,0006,0007,0008,000GHG emissions per capita(tons CO2e/head)Cumulative population(millions,2030)2021 Emissions per capita2030 BAU pe

71、r capita2030 NDC pledge per capita2030 populationCHNUSAIDNRUSINDBRAEUOtherHICsOther LMICs&LICsOtherUMICsIRNJAP2.Country NDCs by per capita incomeFigure 4.Historical and Projected BAU Annual(Panel 1)and Cumulative(Panel 2)CO2 Emissions for High-,Middle-,and Low-Income Countries,19602030 Source:IMF st

72、aff calculations using CPAT.Note:BAU=business as usual;bn=billion;HICs=high-income countries;LICs=low-income countries;LMICs=lower-middle-income countries;UMICs=upper-middle-income countries.05101520253035401970198019902000201020202030Annual CO2emissions(billion tonnes)HICsUMICsLMICs&LICsProjections

73、01002003004005006001970198019902000201020202030Cumulative CO2emissions(billion tonnes)HICsUMICsLMICs&LICs1.Annual CO2Emissions2.Cumulative CO2EmissionsInternational Monetary Fund.Not for Redistribution IMF|Staff Climate Note 6 Lastly,climate finance and technology transfer to developing countries is

74、 a critical aspect of global climate policy and interlinked with ambition.At COP29,countries will set a new collective quantified goal to replace the$100-billion target,previously set for 2020,but achieved late in 2022.Private finance is especially lagging,indeed the private share of climate finance

75、 in developing countries needs to rise from current from about 50 percent to 80 to 90 percent.Our last annual update made suggestions for this goal,including setting the target based on needs(in total and with respect to mitigation and adaptation separately)andgiven the central importance of policy

76、change for attracting private climate finance and the collaborative spirit of the Paris Agreementframing it as a joint goal for all countries,rather than a target“for”developed countries.Alternatively,developed countries could consider making climate finance conditional on developing country policie

77、s.Also,technology transfer and research and development needs to be accelerated,including through private foreign direct investment and trade policy,and could include a new global agreement on lowering tariffs on low-carbon technologies(Black and others 2023c).Equitably Distributing Enhanced Mitigat

78、ion Ambition:An Illustrative Example Economists have proposed various ways to distribute the burden of global emissions cuts equitably.The various approaches(as identified by a team of researchers from developing and developed countriessee van der Berg and others 2020)can be ordered roughly from lea

79、st to most“equitable”in terms of the emissions cuts versus BAU16:1.Acquired rights(“grandfathering”):Under this approach,countries cut emissions proportionate to their historical(for example,2010)annual emissions.2.Cost optimality:Emissions are cut at their least-cost location to minimize global cos

80、ts.3.Gradual convergence:Per capita emissions converge linearly over time.4.Ability to pay:Emissions cuts are based on annual per capita GDP,with lower reductions calculated based on the poverty of a country and considering that costs increase with larger emissions reductions.5.Immediate convergence

81、:Per capita emissions converge immediately.6.Greenhouse development rights(GDR):Emissions cuts are based on a mixed measure of historical responsibility and capability,which includes GDP per capita and carbon intensity.These six approaches lead to markedly different impacts on emissions cuts for key

82、 countries(refer to Annex Figure 2.1).For example,acquired rights and cost-optimal paths lead to fewer emissions reductions in HICs compared with other methods,since HICs historical per capita emissions and marginal abatement costs are both relatively high compared with middle-income countries and L

83、ICs.Gradual convergence and ability to pay lead to intermediate solutions,with all countries required to cut emissions compared with baseline and larger cuts(in absolute terms)in HICs than middle-income countries and LICs.Lastly,“immediate convergence”and“GHG development rights”lead to large cuts in

84、 HICs(for example,more than 100 percent for Japan under GDR,that is,requiring annual carbon removals)and much smaller reductions in developing countries(for example,India grows its emissions to be above even BAU in 2030 under the GDR approach).There are thus many ways to think about equity in global

85、 mitigation.However,one simplifying,illustrative way is to average across approaches and link to per capita incomes.Current NDCs and their relationship to per capita incomes are shown in Figure 6.As can be seen there is a small positive but weak relationship between current country ambition(defined

86、in terms of emissions cuts versus BAU)and per capita income.The implied illustrative emissions reductions targets compared with BAU in 2030 can be inferred for key countries across the six different identified approaches.Then,by plotting these illustrative targets relative to per capita incomes,a li

87、near relationship can be inferred between emissions cuts and(log)per capita income levels with the slope determining the relative level of 16 In this narrow definition,an approach leading to more emissions cuts in developed countries is considered more“equitable.”International Monetary Fund.Not for

88、Redistribution IMF|Staff Climate Note 7 effort required across the income distribution.Lastly,assuming countries achieve the maximum of the illustrative target(in percentage reduction versus BAU given their per capita income)and their current NDC,this line can be scaled upward or downward(in percent

89、age points)to achieve different temperature targets(for example,2C,1.8C,or,in the case of 1.5C).17 This illustrative example yields targets more equitable than current NDCs,while delivering the needed emissions reductions for 2C or 1.5C.Figures 7 and 8 show what enhanced,2C-aligned 2030 targets and

90、1.5C-aligned 2030 targets,respectively,would be under the approach described in the previous section.The 2C-aligned targets would cut global emissions by the required 25 percent and the 1.5C-aligned targets would cut emissions by 50 percent versus the 2019 levels.In both cases,ambition would be rais

91、ed substantively for a majority of countries,but the increase in the pace of emissions cuts is starker for 1.5C.In both cases,cuts remain broadly equitable,with a sharper relationship between income and country ambition.Under the 2C scenario some low-income countries would be able to grow emissions(

92、albeit at a slower pace)for example,Indias emissions could grow by 21 percent from 2019 to 2030 while 17 This approach is similar to the third most equitable approach listed(“ability to pay”)but draws upon all approaches to determine a relationship between emissions cuts and projected per capita inc

93、omes.Figure 7.Illustrative 2C-Aligned Enhanced GHG Emissions Targets for 2030 Figure 8.Illustrative 1.5C-Aligned Enhanced GHG Emissions Targets for 2030 Source:IMF staff calculations using CPAT.Note:Bubble sizes reflect 2021 GHG emissions.Data labels are for major emitting countries(300 metric tons

94、of carbon dioxide equivalent in 2030 BAU)and use International Organization for Standardization(ISO)codes.BAU=business as usual;GHG=greenhouse gas;NDC=nationally determined contribution.USAAUSDEUCANAREFRAGBRJPNKORITASAURUSCHNARGMYSTURKAZMEXBRATHAZAFIRQBGDIDNVNMPHLIRNECODNGAINDPAK0%10%20%30%40%50%60%

95、70%80%90%100%5005,00050,000GHG emissions cuts in NDC(versus 2030 BAU)Projected per capita income in 2030(log scale,US$)USAAUSDEUCANAREFRAGBRJPNKORITASAURUSCHNARGMYSTURKAZMEXBRATHAZAFIRQBGDIDNVNMPHLIRNEGYCODNGAINDPAK0%10%20%30%40%50%60%70%80%90%100%5005,00050,000GHG emissions cuts in NDC(versus 2030

96、BAU)Projected per capita income in 2030(log scale,US$)Figure 6.Current Country Emissions Targets for 2030 by per Capita Income Source:IMF staff calculations using CPAT.Note:Bubble sizes reflect 2023 GHG emissions.Data labels are for major emitting countries and use International Organization for Sta

97、ndardization(ISO)codes.For countries with a nonbinding target(achieved in the BAU)it is assumed to be zero.An average is taken of conditional and unconditional targets where both are specified.A trend line is shown for all countries.BAU=business-as-usual;GHG=greenhouse gas;NDC=nationally determined

98、contribution.USAAUSDEUCANAREFRAGBRJPNKORITASAURUSCHNARGMYSTURKAZMEXBRATHAZAFIRQBGDIDNVNMPHLIRNCODNGAINDPAK-10%0%10%20%30%40%50%60%70%5005,00050,000GHG emissions cuts in NDC(versus 2030 BAU)Projected per capita income in 2030(log scale,US$)International Monetary Fund.Not for Redistribution IMF|Staff

99、Climate Note 8 the United States and China reduce their emissions 47 and 19 percent respectively.In contrast,under the 1.5C scenario all countries would need to cut emissions in absolute terms.Figure 9 shows gaps between current 2030 targets and illustrative targets needed for the world to be on tra

100、ck to 1.5C or 2C.Under this methodology,between income groups,shortfalls between current and illustrative targets are larger for UMICs and LIC/LMICs than for HICs.HICs as a group are about 8 ppts away from being 2C aligned,UMICs are 16 ppts away,and LIC/LMICs are 4 ppts away.For 1.5C,the respective

101、distance is bigger,at 29 ppts,37 ppts,and 25 ppts,respectively.Developed countries are generally close to being aligned with 2C,with some exceptions.For developing countries,the NDCs of Brazil,Mexico,and South Africa are aligned with the 2C scenario.However,the NDCs are not binding in some countries

102、(and hence are shown without a target),although it is possible that some countries may over-achieve their existing 2030 targets with current policies(for example,India).Figure 9.GHG Emissions Cuts for Countries under Illustrative Proposals versus Business as Usual(Panel 1)and in Absolute Values(Pane

103、l 2)Sources:IMF staff calculations using CPAT.Note:Where no NDC is shown,the target is nonbinding and is assumed achieved in the baseline or(for Saudi Arabia)is nonquantifiable.An average is taken of conditional and unconditional targets where both are specified.EU=European Union;GHG=greenhouse gas.

104、Income groups use the WB classification:HICs=high-income countries;LICs=low-income countries;UMICs=upper-middle-income countries.;LMICs=lower-middle-income countries;NDC=nationally determined contribution.Among all countries,the gap between current NDCs and illustrative temperature-aligned targets v

105、aries.Of the 179 countries with economy wide NDCs,about 40 percent have NDCs that are aligned with 2C.But these countries account for just 18 percent of global GHG emissions.Worse,just 12 countries have targets aligned with 1.5C,and they account for less than 2 percent of global GHGs.No major emitti

106、ng country is aligned with 1.5C on this measure.For figures showing NDC ambition levels compared with temperature-aligned targets for all countries,refer to Annex 3.If countries enhanced their 2030 targets to be in line with the 2C or the 1.5C scenario,and enacted policies to achieve them,global emi

107、ssions would be on track to achieve the Paris Agreements temperature goals.Under these scenarios,emissions in 2030 would decline to their needed levels(Figure 10,panel 1).5,00010,00015,000GHG emissions in 2030,MtCO2e 02,0004,000United StatesUnited KingdomKoreaCanadaEU-27AustraliaJapanSaudi ArabiaOth

108、er HICsBrazilMexicoSouth AfricaArgentinaChinaRussiaTurkeyOther UMICsIndiaIndonesiaOther LIC/LMICHigh-income countriesUpper-middle income countriesLower-middle-and low-income countries/01020304050607080United StatesUnited KingdomKoreaCanadaEU-27AustraliaJapanSaudi ArabiaOther HICsBrazilMexicoSouth Af

109、ricaArgentinaChinaRussiaTurkeyOther UMICsIndiaIndonesiaOther LIC/LMICAll HICAll UMICAll LIC/LMICWorldIncreasing ambitionHigh-income countriesUpper-middle income countriesLower-middle-and low-income countriesGroups1.GHG emissions cuts in 2030 versus baseline(percent)2.GHG emissions in 2030(MtCO2e)Old

110、 NDC Current NDC Baseline Illustrative 2C target Illustrative 1.5C targetInternational Monetary Fund.Not for Redistribution IMF|Staff Climate Note 9 In addition,illustrated scenarios imply large commitments for HICs and convergence in per capita emissions(Figure 10,panel 2).In both scenarios,there i

111、s a gradual convergence of per capita emissions between HICs and UMICs LMICs/LICs maintain lower emissions per capita than HICs and UMICs but would cut by less in absolute terms.If these targets are implemented in least-cost ways then the mitigation costs,at least for 2C,are manageable and broadly e

112、quitable across countries(Figure 11)Mitigation costs(see Annex 5)reflect the annualized costs of switching to cleaner but more expensive inputs and technologies,net of any savings from lower lifetime energy costs.This also includes the loss of consumer benefits from,for example,driving less than oth

113、erwise preferred.Mitigation costs depend on policy implementation.But assuming countries achieve targets in a least-cost manner,Figure 11 shows their mitigation costs under the 2C scenario.Costs are both manageable(about 0.4 percent of GDP for the G20 as a whole)and generally equitable(higher for ad

114、vanced economies and lower for low-income countries).For comparison,the abatement costs of achieving NDC targets are about 0.25 percent of GDP globally,with larger costs(0.4 percent of GDP)in HICs and almost negligible for UMICs and LICs/LMICs(0.03 percent of GDP and near zero18,respectively).These

115、policies can also be made equitable within countries.and are counteracted by domestic environmental co-benefits.Co-benefits include(most importantly)reductions in local air pollution morality from reduced 18 Near zero estimates are explained by several countries achieving NDCs in the baseline.Figure

116、 10.Impacts of Illustrative Targets on Global and per Capita GHG Emissions Source:IMF staff calculations using CPAT.Note:BAU=business as usual;GHG=greenhouse gas;HICs=high-income countries;LICs=low-income countries;LMICs=lower-middle-income countries;NDC=nationally determined contribution;UMICs=uppe

117、r-middle-income countries.01020304050602015202020252030Annual global emissions(bn tons CO2e)1.5C2CBusiness-as-usualNDCs(2024)HistoricalIllustrative 2CIllustrative 1.5C-35-30-25-20-15-10-502024NDCs2C1.5CHICsUMICsLMICs&LICsIllustrative scenarios024681012BAU2024 NDCs2C1.5CPer capita emissions(tCO2e in

118、2030)HICsUMICsLMICs&LICsIllustrativescenarios1.Emissions Projections and Temperature Goals2.Per Capita Emissions under Illustrative Scenarios in 2030Figure 11.Abatement Costs and Domestic Environmental Benefits from Illustrative 2C Scenario Source:IMF staff calculations using CPAT.Note:Domestic envi

119、ronmental co-benefits include reductions in local air pollution mortality and fewer road accidents and congestion from less vehicle use.They exclude climate benefits.Abatement costs are adjusted for tax interaction and revenue recycling effects.EU=European Union;HICs=high-income countries;LICs=low-i

120、ncome countries;LMICs=lower-middle-income countries;UMICs=upper-middle-income countries.-1.0-0.50.00.51.01.5AustraliaCanadaEU-27JapanKoreaUnited KingdomUnited StatesSaudi ArabiaOther HICsHIC averageArgentinaBrazilChinaMexicoRussiaTurkeyOther UMICsUMIC averageAfrican UnionIndiaIndonesiaOther LMICs&LI

121、CsLIC/LMIC averageG20WorldPercent of GDP in 2030Abatement costsDomestic environmental co-benefitsNetInternational Monetary Fund.Not for Redistribution IMF|Staff Climate Note 10 use of fossil fuels(especially coal and diesel)and reductions in various side effects(like traffic congestion)from reduced

122、vehicle use.For some emerging economies co-benefits can(up to a point)exceed mitigation costs implying these countries are better off on net from climate mitigation,before even counting global climate benefits.See Figure 11.19 Illustrative 1.5C-and 2C-Aligned 2035 Targets This approach can be used t

123、o assess potential 1.5C-aligned targets for 2035.Assuming that GHGs are cut by 50 percent by 2030 compared with 2019,emissions need to continue to fall by 66 percent by 2035 versus 2019 to stay on track to 1.5C.Alternatively,if they are cut by 25 percent by 2030 then they would need to be but by 35

124、percent compared with 2019 levels to be aligned with 2C.Recalculating based on 2035 projected emissions and per capita incomes and then scaling using the approach described in the previous sections can yield a similarly equitable allocation for this new target year.In this way,ambition can be scaled

125、 to achieve global targets while maintaining equity.This yields temperature-aligned 2035 targets for all countries which would get the world on track for 2C(Figure 12)or 1.5C(Figure 13).Targets can be expressed versus BAU or alternatively against a historical baseline(for example,1990,2005,or 2010 a

126、s in many NDCssee Annex 4 for tables with 2035 targets for all countries).For 2C,targets are stringent but achievable,with most developed countries cutting by 40 to 45 percent versus BAU and most developing countries cutting by at least 25 percent.By contrast,for 1.5C,cuts in emissions implied by 1.

127、5C-aligned targets for countries can be stark.On average,a 66-percent global cut in 2035 versus 2019 means cuts of over 80 percent versus BAU for many developed countries(e.g.US,UK,Korea,and the EU).Also,most developing countries would need to cut emissions by over 50 percent versus BAU.Figure 12.Il

128、lustrative 2C-Aligned Targets for 2035 Figure 13.Illustrative 1.5C-Aligned Targets for 2035 Source:IMF staff calculations using the CPAT.Note:Bubble sizes reflect the 2021 GHG emissions.Data labels are for major emitting countries(300 metric tons of carbon dioxide equivalent in 2030BAU)and use Inter

129、national Organization for Standardization(ISO)codes.BAU=business as usual;GHG=greenhouse gas;NDC=nationally determined contribution.19 For quantification of co-benefits,see Black and others(2023b).There are also unquantified co-benefits beyond these,such as soil and water quality,impacts on physical

130、 and diet,biodiversity,and energy securitysee Karlsson and others(2020).Climate benefits are excluded from Figure 11.However,Rennert and others(2022)put the discounted flow of climate benefits at$185 per tonne of CO2under a global carbon price of$85 per tonne,this would imply climate benefits five t

131、imes the global abatement costs.USAAUSDEUCANAREFRAGBRJPNKORITASAURUSCHNARGMYSTURKAZMEXBRATHAZAFIRQBGDIDNVNMPHLIRNEGYCODNGAINDPAK0%10%20%30%40%50%60%70%80%90%100%5005,00050,000GHG emissions cuts in NDC(versus 2035 BAU)Projected per capita income in 2035(log scale,US$)USAAUSDEUCANAREFRAGBRJPNKORITASAU

132、RUSCHNARGMYSTURKAZMEXBRATHAZAFIRQBGDIDNVNMPHLIRNEGYCODNGAINDPAK0%10%20%30%40%50%60%70%80%90%100%5005,00050,000GHG emissions cuts in NDC(versus 2035 BAU)Projected per capita income in 2035(log scale,US$)International Monetary Fund.Not for Redistribution IMF|Staff Climate Note 11 While this distributi

133、on of cuts would get the world on track to 1.5C in theory,it is questionable whether this rate of decarbonization is achievable technologically,economically,and politically.For example,the rate of turnover of energy-consuming capital goods like vehicles or buildings can be slow given their long life

134、times,while emissions from agriculture and land use can be difficult to abate.In addition,some low-carbon technologies such as green steel,green cement,and direct air capture have not reached maturity.20 Lastly,political constraints can limit the strength of mitigation policies,especially those that

135、 have impacts on employment and equity.International coordination mechanisms are needed to scale up global mitigation action.Additional mechanisms are needed to overcome obstacles under the Paris Agreement to negotiation(the large number of parties)and unilateral action(concerns about competitivenes

136、s and policy uncertainties in other countries).Action could be accelerated through plurilateral agreements,that is,complementary agreements among a smaller group of countries(for example,large emitters,G20)to accelerate ambition and align policies with reinforced targets.Such agreements could includ

137、e concrete,monitorable actions such as an international carbon price floor agreement as proposed by the IMF staff.21 It could also include an agreement on scaled-up,temperature-aligned,equitable emissions targets backed up by credible mitigation strategies to implement them.These additional agreemen

138、ts could include robust and transparent finance to encourage participation of large-emitting,lower-income countries.In addition,action is needed on gases and sectors not previously subject to strong mitigation policies.Methane emissionswhich are predominately from coal,oil,and gas extraction and agr

139、iculturecan have an outsized impact on slowing warming and require specific measures to curb them(see Annex 6).More focus is needed on the forestry and agricultural sectors,given the ongoing lack of global finance for slowing and reversing deforestation(often driven by agriculture).Coordinated actio

140、n in international aviation and maritime is both a necessity and an opportunity:the sectors share of global CO2 could rise drastically but a global carbon price could accelerate their decarbonization while doubling current climate finance.Given the need to achieve midcentury“net zero”emissions all s

141、ectors need to be decarbonized,requiring additional action now in hard-to-abate sectors like aviation and maritime,which account for a rising share of global GHGs.If no action is taken to decarbonize them then under a 1.5C and 2C scenario by 2035 their shares of global CO2 emissions would grow from

142、under 4 percent currently to 10 and 19 percent,respectively(and growing rapidly;Figure 14).But a global carbon price on fuels used in international aviation and maritime could raise revenues of over$100 billion a year by 2035,even after fully compensating affected developing countries(see Box 1).Thi

143、s doubling of current global climate finance could be a gamechanger for global cooperation on climate,as developing countries would feel more confident in setting and achieving more ambitious targets.20 Refer to Black and others(2023d)and Pigato and others(2020)for discussion of low-carbon technolog

144、ies and green innovation.21 See Parry and others(2021).Figure 14.International Aviation and Maritimes Projected Share of Global CO2 Emissions under Different Temperature Scenarios Source:Black and others(2024).Note:The data assumes that the countries achieve temperature-aligned targets in 2030 and 2

145、035 and thereafter total country emissions align with the Intergovernmental Panel on Climate Change scenarios(adjusted for higher-than-projected emissions in 201923)while aviation and maritime are allowed to grow in the business-as-usual case.The Intergovernmental Panel on Climate Change scenarios d

146、o not specify emissions from the sectors,so are assumed to decline by 25 and 50 percent for 2C and 1.5C versus business-as-usual,respectively,which are added back to the denominator.010203040502020 2025 2030 2035 2040 2045 2050Share of global CO2emissions(percent)1.5CAviation 2CAviation 1.5CMaritime

147、 2CMaritime International Monetary Fund.Not for Redistribution IMF|Staff Climate Note 12 For governments,setting new national targets requires an increase in technical capacity to estimate future emissions,quantify potential targets,and estimate the impacts of policies to achieve these targets.The n

148、ext section provides a modeling framework for country analysts informing the development of new 2035 targets and revision of 2030 targets.Box 1.Decarbonizing International Aviation and Maritime Emissions from international aviation and maritime are growing in importance for the climate.These sectors

149、 fall outside the purview of the United Nations Framework Convention on Climate Change and Paris Agreement.However,if nothing is done to decarbonize them,they will grow as a share of global CO2 emissions,under a 2C scenario accounting for over one-quarter of global CO2 by 2050(Figure 14)and much mor

150、e under a 1.5C scenario.Carbon pricing could make a major contribution to decarbonizing both sectors while raising substantial revenues:up to$200 billion in 2035 under net zero aligned pricing.Given the highly mobile tax base,especially for maritime,a carbon price would need to be global,but could b

151、e implemented by the United Nations agencies responsible for the sectors(International Civil Aviation Organization and Internation Maritime Organization).This could raise substantial new revenues which could be used for sectors such as climate adaptation.In addition,it would level the playing field

152、between the sectors and their competitors(for example,long-distance rail for certain flight routes),help accelerate technological development,and incentivize many behavioral changes which can improve efficiency in the sector.The burden would mostly be borne by developed countries and the wealthy wit

153、hin the countries,although some compensation for developing countries would be needed.Even after fully compensating developing countries for abatement costs and losses in tourism and trade,up to$100 billion would be left for climate finance,allowing for a doubling of current total global current cli

154、mate finance.However,there are key administrative and political obstacles to overcome.Price impacts will be substantive on flight tickets,raising average ticket prices by 10 to 20 percent by 2035.Maritime costs would be more moderate at under 3 percent.However,equity impacts of this would need to be

155、 addressed as they may disproportionately affect developing countries dependent,for example,on tourism or trade.The allocation of revenues toward compensation,technological development,general government budgets,climate finance(mitigation,adaptation,or loss and damage),or other uses will be a centra

156、l issue of contention.If carbon pricing is not feasible then feebates could be an alternative but would raise less revenues.Feebates,which are also a form of pricing,are a sliding scale of fees/rebates on operators with emission rates above/below a pivot point.They can provide a strong price signal

157、to reduce the emissions intensity of the sector(but not demand)while limiting impacts on end user prices.They can be designed to raise revenues but these are likely much lower than under a carbon price.1 This box draws on Black and others(2024)for full details refer to the Note.2 The United Nations

158、supervisory agenciesthe International Civil Aviation Organization and International Maritime Organizationare responsible for strategies to decarbonize the industries.Both agencies have adopted(aspirational or approximate)net zero emissions targets by midcentury and the IMO has set intermediate targe

159、ts for emissions and zero-emissions ships.International Monetary Fund.Not for Redistribution IMF|Staff Climate Note 13 Modeling Frameworks to Guide Setting and Implementation of NDCs:A Primer To evaluate scenarios for enhancing emissions commitments in NDCs,and policy options for achieving them,poli

160、cymakers need flexible modeling frameworks,ideally with several key features including:Midrange projections of BAU emissions:Emissions projections should be based on midrange values for key underlying parametersif not,emissions reductions needed for NDCs,policies to achieve them,and the costs and ot

161、her impacts of these policies are likely over-or under-estimated.Midrange projections of the emissions impacts of mitigation policies:The model needs to capture how mitigation policies work,for example,in raising energy prices and reducing fuel use again with midrange assumptions for parameters unde

162、rlying behavioral responses.Full range of potential and existing mitigation policies:The model should be able to compare commonly used mitigation approaches such as(comprehensive and partial)carbon pricing,feebates(see the following section),technology incentives,fuel pricing reforms and existing en

163、ergy and climate policies,like fuel taxes and subsidies should be included in the models baseline.Full range of sectors and gases:The model should distinguish the main emissions-generating sectors(power,industry,transport,buildings,agriculture,forestry,extractives,waste)and the different gases(mainl

164、y CO2,methane,NOx)so targets and policies for individual sectors and gases can be analyzed.Metrics for policy evaluation:The model should ideally capture the full range of metrics of concern to policymakers from mitigation policies including impacts on emissions,fuel use,energy prices,revenue,econom

165、ic costs,domestic environmental problems,distributional incidence across household income groups,and production costs in trade-exposed industries.22 Transparency and accessibility:The model results should be readily explainable in terms of basic economic factors familiar to policymakers and,ideally,

166、be accessible to users at low set up costs.This section discusses how scenarios can be developed for BAU emissions and for the impacts across key metrics of carbon pricing and other policies for implementing emission reduction targets.The discussion is timely,given parties to the Paris Agreement are

167、 expected to revise NDCs over the next 12 months and may help countries better understand,and perhaps refine,their own baseline data and modeling assumptions(indeed mitigation models are not always transparent about their underlying assumptions).The following discussion focuses on CO2 emissions from

168、 the energy sector and illustrates results from the Climate Policy Assessment Tool(CPAT)model(which was designed to incorporate the above features on a country-by-country basis for all IMF membersAnnex 1 provides more details on CPAT).Though there is inherently uncertainty in modeling,CPAT provides

169、reasonable estimates given the current state of knowledge on key inputs(for example,responsiveness of fuel demand to income and prices and rates of technical change).Developing BAU Emissions Scenarios The starting point is assembling the most recent sectoral data on fuel use,emissions as well as fue

170、l supply costs,prices,and taxes/subsidies.CPAT uses the following data:Fuel use:The main source is various aggregations from the International Energy Agencys World Energy Balances(IEA 2024),which are updated annually.Emissions:CO2 emissions by sector and fuel use can be calculated from fuel inputs a

171、nd CO2 emissions factors(again from IEA).22 The last two metrics are included CPAT for many countries(see Black and others 2023b)but are beyond the scope of the discussion in the following sections.International Monetary Fund.Not for Redistribution IMF|Staff Climate Note 14 Fuel supply costs:For oil

172、(which is traded in well-integrated international markets),supply costs(the costs of consuming the product domestically rather than selling it abroad)are measured by the import/export price plus transportation/processing/distribution margins.For electricity(largely a nontraded product),the supply co

173、st is the domestic production cost,plus margins.For coal and natural gas(where global markets are partially integrated)supply costs average over international prices and domestic production costs.Energy prices and taxes/subsidies:CPATs comprehensive database on retail and wholesale prices by fuel pr

174、oduct,sector,and country is compiled from IMF and World Bank country economists and other sourcesfuel taxes/subsidies,including carbon pricing,are the difference between fuel prices and supply costs.Fuel use and emissions by sector can be projected forward accounting for four main factors:1.GDP grow

175、th:The IMFs World Economic Outlook provides GDP forecasts for the next five years and these can be extended assuming gradual convergence between developed and developing country growth rates.2.Income elasticities of energy demand:These parameters summarize the change in demand for energy products pe

176、r one percent increase in income or GDPif income elasticities are below 1,the energy intensity of GDP falls over time(given other factors).In CPAT,income elasticities are typically around 0.5 to 0.8 across energy products and countries at different development levels,based on a database of over 250

177、empirical studies.3.Trend rates of technological change:Improving energy efficiency(for example,as newer more efficient factories and vehicles replace older capital),also lower the energy intensity of GDPin CPAT energy efficiency increases at 0.5 to 1 percent across sectors based on standard assumpt

178、ions.CPAT also assumes modest annual improvements in the productivity of fossil generation plants and faster improvements for renewables.4.Future fuel prices:International energy price projections in CPAT average over IMF and World Bank projections with all,or most,passed forward into domestic price

179、s across fuels and countries.For the power sector,CPAT also accounts for countries planned investments in generation technologies and dispatch(see Annex 1).In BAU scenarios,CO2 emissions increase moderately,or decline,across most G20 countries.Figure 15 shows projections of BAU fossil fuel CO2 emiss

180、ions growth between 2021 and 2030 for G20 countries and aggregates.The noteworthy points are as follows:GDP is Figure 15.Drivers of BAU CO2 Projections,202130 Source:Authors calculations using CPAT.Note:Countries with fossil fuel subsidies are assumed to reduce them by half to 2030,which reduces the

181、 energy intensity of GDP.BAU=business-as-usual;EU=European Union;HICs=high-income countries;LICs=low-income countries;LMICs=lower-middle-income countries;UMICs=upper-middle-income countries.-40-20020406080100AustraliaCanadaEU-27JapanKoreaUnited KingdomUnited StatesSaudi ArabiaOther HICsHIC averageAr

182、gentinaBrazilChinaMexicoRussiaTurkeyOther UMICsUMIC averageAfrican UnionIndiaIndonesiaOther LMICs&LICsLIC/LMIC averageG20WorldChange in 2021-2030,percentGDPEnergy intensity of GDPCO intensity of energyTotal CO emissionsInternational Monetary Fund.Not for Redistribution IMF|Staff Climate Note 15 proj

183、ected to grow rapidly by 40 to 80 percent in China,India,and Indonesia,and a lower rate at 8 to 40 percent in other G20 countries.Energy intensity of GDP is projected to decrease significantly by 5 to 15 percent across countries,mainly reflecting below-unitary income elasticities and improving energ

184、y efficiency.CO2 intensity of energy is also projected to decline about 5 to 15 percent in most cases(with expected investments in renewable generation).CO2 emissions expand rapidly in a couple of cases(India,Indonesia)but approximately stabilize,or decline in othersaveraged across the G20,emissions

185、 increase 4 percent.Least-Cost Mitigation Scenarios and Their Impacts Although policymakers may prefer a combination of mitigation instruments(with or without pricing)understanding least cost with carbon pricing is important:For countries where pricing is the centerpiece of the mitigation strategy,u

186、nderstanding its impacts is critical for policy design(for example,the needed price trajectory,use of revenues);For countries using other instruments,a carbon pricing reference case indicates the pattern of emissions reductions across responses and sectors that,to the extent possible,would ideally b

187、e mimicked by other instruments23;and For countries choosing a balance between pricing and other instruments,understanding the trade-offs across different instruments(for example,in terms of emissions,costs,revenues,impacts on energy prices)is important.Carbon pricing has a large impact on coal pric

188、es and intermediate impacts on natural gas,electricity,and gasoline prices.The increase in fuel prices from carbon pricing is the product of the CO2 price,the CO2 emissions factor,and the pass-through rate.24 Annex 7 shows the effect of a carbon price of$25,$50,and$75 per tonne on increasing energy

189、prices above 2030 baseline levels in G20 countries.For example,on average a$50 carbon price increases coal prices 100 percent,and prices for natural gas,electricity,and gasoline by around 25,20,and 15 percent respectively.The emissions impact of carbon pricing in the energy sector largely depends on

190、 induced changes in fuel prices,the price responsiveness of fuel use,and the emissions intensity of fuels.Fuel price elasticities summarize the change in 23 Carbon pricing achieves a given emissions target at least cost as it equates the cost of the last tonne reduced across households,firms,and sec

191、tors.24 Pass-through rates may be limited where energy markets are subject to discretionary pricing regimes or dominated by state-owned enterprises.Figure 16.Emissions Impacts of Carbon Pricing,2030 Source:Authors calculations using CPAT.Note:EU=European Union;HICs=high-income countries;LICs=low-inc

192、ome countries;LMICs=lower-middle-income countries;UMICs=upper-middle-income countries.01020304050Saudi ArabiaJapanKoreaUnited StatesAustraliaCanadaEU-27United KingdomOther HICsHIC averageRussiaChinaTurkeyMexicoArgentinaBrazilOther UMICsUMIC averageIndiaAfrican UnionIndonesiaOther LMICs&LICsLIC/LMIC

193、averageG20WorldPercent emissions reduction versus 2030 baselineEmissions reduction from$25 carbon taxExtra reduction from$50 carbon taxExtra reduction from$75 carbon taxInternational Monetary Fund.Not for Redistribution IMF|Staff Climate Note 16 demand for energy products per one percent increase in

194、 the fuel price and reflect,for example,switching from coal to other fuels in power generation,from coal to electric furnaces in steelmaking,adopting more efficient heating systems,and shifting to electric vehicles.Fuel price elasticities in CPAT are based on synthesizing hundreds of empirical studi

195、estypical elasticity assumptions for coal are around 0.8,natural gas 0.7,gasoline 0.6,diesel 0.4,other oil products 0.6,and electricity demand 0.4.25 Figure 16 indicates reductions in CO2 emissions below BAU levels in 2030 for carbon prices of$25,$50,and$75 per tonne(imposed on top of any preexistin

196、g mitigation policies).Some noteworthy points include:Carbon pricing can produce substantial emissions reductionsfor example,a$50 carbon price would cut CO2 emissions by around 15 to 30 percent below BAU levels.Emissions price responsiveness varies significantly across countriesit is larger in coal-

197、intensive countries like Australia,China,India,Indonesia while it has more modest impacts,for example,in France(where power generation has low CO2 intensity).Pricing becomes progressively less effective at cutting emissions as the lower cost mitigation opportunities are exhaustedfor example,the$25 c

198、arbon price cuts emissions in Indonesia 18 percent,while raising it to$50 or$75 cuts emissions by an additional 7 and 6 percentage points respectively.Across fuels,coal accounts for most of the least-cost emissions reductions in certain countries,while across sectors,power,and industry account for m

199、ost emissions reductions in all G20 countries.Annex 7 also shows the breakdown of CO2 reductions by fuel and sector under illustrative carbon pricing.Reduced coal use accounts for around 60 percent or more of the fossil fuel CO2 reductions from carbon pricing for six G20 countries though in most oth

200、er cases there is a more even balance between CO2 reductions from coal,oil,and gas.Power and industry typically account for around 40 to 70 percent of emissions reductions across G20 countries while transport and buildings each contribute a relatively modest share.This generally reflects some combin

201、ation of significant coal use in the former sectors,the relatively modest proportionate impact of carbon pricing on road fuel prices,and the relatively small share of buildings in baseline emissions.Despite this,making headway on mitigation for transport and buildings is still important,given the ne

202、ed to decarbonize them by the midcentury.25 These reflect longer term responses which are appropriate for analyzing responses to permanent policy changes.Figure 17.Revenues from Carbon Pricing,2030 Source:Authors calculations using CPAT.Note:Estimates are for carbon prices of$75,$50,and$25 per tonne

203、 of CO2 in high-,middle-,and low-income countries respectively.EU=European Union;HICs=high-income countries;LICs=low-income countries;LMICs=lower-middle-income countries;UMICs=upper-middle-income countries.-1.00.01.02.03.04.0Saudi ArabiaKoreaAustraliaCanadaUnited StatesJapanEU-27United KingdomOther

204、HICsHIC averageRussiaChinaArgentinaTurkeyMexicoBrazilOther UMICsUMIC averageIndiaAfrican UnionIndonesiaOther LMICs&LICsLIC/LMIC averageG20WorldPercent of GDP in 2030Base erosionCarbon revenues,powerCarbon revenues,industryCarbon revenues,transportCarbon revenues,buildingsNetInternational Monetary Fu

205、nd.Not for Redistribution IMF|Staff Climate Note 17 Potential revenues from carbon pricing can be calculated with reasonable confidence.Expressed relative to GDP,for carbon taxes and emissions trading systems with full allowance auctions,revenues are simply the carbon price times the emissions inten

206、sity of GDPthe latter is BAU emissions intensity scaled by the proportionate emissions reduction induced by the carbon price.Figure 17 shows calculations of revenues from carbon prices of$75/50/25 per tonne in 2030 for HICs,UMICs,and LMICs/LICs respectively.Revenues are mostly between about 0.5 and

207、1.5 percent of GDP,with the contribution from different sectors varying significantly across countries.Carbon mitigation also causes indirect revenue losses/gains to the extent it reduces base for preexisting energy taxes/subsidiesrevenue losses are around 0.20.3 percent of GDP or less(though signif

208、icantly more in Canada)while Saudi Arabia and Russia would gain significant revenues from reducing bases for fuel subsidies.26 Modeling Other Mitigation Instruments Other mitigation instruments can be modeled by understanding which behavioral responses they promote relative to those promoted by carb

209、on pricing.27 For example:Fuel-or sector-specific carbon pricing:These policies are straightforward to model through limiting the scope of carbon pricingtheir emissions effects can be largely anticipated from Annex 7.Feebates and performance standards:Feebates apply a sliding scale of fees/rebates t

210、o products or activities with emission rates above/below a pivot point level while performance standards require firms to meet an emission rate(or energy efficiency)standard per unit of their production or across their product sales.Both policies can cost-effectively promote all behavioral responses

211、 to reduce the emissions intensity of a sector(though performance standards require fluid credit trading markets)they can both be modeled by a shadow price that rewards reductions in emissions intensities.Incentives for clean technologies:Subsidies or requirements for clean technologies,such as feed

212、-in tariffs and renewable portfolio standards,promote a narrower range of behavioral responses than feebates/performance standards(for example,in power generation they do not promote shifting from coal to gas or from these fuels to nuclear,or improvements in plant efficiency)though they can be easie

213、r to administer(for example,they do not require new emissions monitoring capacity).Technology subsidies are straightforward to model,and,for example,a renewable portfolio standard can be modeled by the implicit renewable subsidy that would achieve the same renewable generation share as the standard(

214、but with no revenue loss for the government).In practice,combinations of sectoral mitigation instruments,in conjunction with economy-wide instruments,are often used.For example,for G20 countries(see Annex 8):Economywide:Carbon pricing programs are operating in 12 G20 countries.Power generation:Almos

215、t all G20 countries have targets for renewables and eight have coal phase out plans.Common policies include renewable subsidies(for example,production tax credits,feed-in tariffs providing above market prices)and minimum renewable generation shares.Transportation:Aside from fuel taxes,CO2 emission r

216、ate or fuel economy standards for vehicle sellers apply nationally in nine G20 countries and at the EU level,while 15 countries have targets for phasing in electric vehicles or phasing out internal combustion engine vehiclesfeebates apply in some form in nine countries.Buildings:France,Germany,Italy

217、,and Japan have targets for reducing energy use from the total building stock,while nine other G20 countries have targets for making all new buildings net zero emissions by 2030 or later.Multiple instruments are used to implement these goals such as building codes;incentives for insulation,heat pump

218、s,and rooftop solar;and efficiency standards for appliances.Industry:This sector is generally subject to lighter emissions targets and policies than for other sectorsonly five G20 countries have binding emissions targets for industry.26 For a comprehensive discussion of impacts on fiscal balances se

219、e Black and others(2024).For mitigation instruments that do not raise revenues such as regulations,the negative base erosion effect in Figure 17 would still apply but not the positive effects.27 Broader public investment and financial sector reforms are also needed(for example,IMF 2023;Jaumotte and

220、others 2024).International Monetary Fund.Not for Redistribution IMF|Staff Climate Note 18 Lastly,modeling toolkits can be used to compare mitigation effort across countries.Monitoring an agreement over emissions targets may require assessing whether implemented or planned policies are achieve emissi

221、ons targets.This requires consistent methodologies for measuring emissions baselines and impacts of policies.This becomes tricky for some sectors where mitigation policies overlap and,for practical purposes,it can make sense to assume sectoral targets(for example for vehicles)are met.Figure 18 shows

222、 illustrative calculations of the emissions impacts of current and planned mitigation policies for G20 countries(as of 2022).The combined effect of specified policies and targets as of 2030 varies substantially.CO2 reductions below a baseline are less than 20 percent in eight G20 countries and range

223、 from 20 to about 50 percent in the other 11 countries.In addition,countries vary significantly in their choice of instrument and relative contribution of sectoral targets,for example,renewables targets make a significant contribution to reductions in the policy mix for 15 cases and carbon pricing f

224、or eight cases(although,again,the relative contribution of specific policies and targets is ambiguous where they overlap,for example,for carbon pricing of power emissions and renewable generation targets).Conclusion To avoid an implausible“emissions cliff edge”and keep 1.5C alive,global climate miti

225、gation ambition and implementation must be substantially raised.The new collective quantified goal on climate finance can help,including by helping raise developing country ambition.However,the key challenge facing the world is aligning emissions targets with the Paris Agreements temperature goals.G

226、etting climate ambition on track requires:Revising 2030 targets in NDCs to be Paris-aligned and equitable.For example,ambition could be enhanced by setting targets depending on countries per capita income levels,with more ambitious emissions reduction targets for richer countries.Many options are po

227、ssible,but it is critical to narrow the gap between countries aggregated ambition and what is needed for 1.5C and 2C.Getting policy implementation on track requires:Adopting comprehensive policy packages needed for Paris-aligned NDCs.Thes should ideally includes a robust and rising carbon price alon

228、gside further measures to address impediments to clean technology and investment.These reforms can be made equitable(notably using carbon pricing revenues for reducing poverty),improve fiscal balances,and yield substantial domestic welfare co-benefits,even before considering climate benefits.Scaling

229、-up and reinforcing international cooperation and coordination.This could include new instruments such as an international carbon price floor among major emitters.The next 12 months are critical.Will countries align both their 2030 and 2035 targets with 1.5C and avoid an implausible global emissions

230、 cliff edge?If they do not,then 1.5C will be out of reach.If,on the other hand,countries align their 2030 and 2035 targets with 1.5C along the lines discussed in this Note or another distribution,and critically implement policies to achieve them,the world can get on track to achieving the Paris Agre

231、ements temperature goals.Figure 18.CO2 Emissions Impacts of Current and Planned Non-NDC Mitigation Policies,G20 Countries Sources:Parry and others(2022).Note:The no-policy counterfactual implies that countries would stop any existing carbon pricing.The figure includes sectoral and economy-wide polic

232、ies outside the general economy-wide NDC targets as of beginning of 2022.EV=Electric Vehicle;NDC=nationally determined contribution.01020304050ArgentinaAustraliaBrazilCanadaChinaFranceGermanyIndiaIndonesiaItalyJapanMexicoRussiaS.ArabiaS.AfricaKoreaTrkiyeUKUSExisting carbon pricingEnhanced pricingRen

233、ewables pledgesCoal phase-outCO/km targetsEV targetsBuildingsIndustryPercent reduction below no-policy baselineInternational Monetary Fund.Not for Redistribution IMF|Staff Climate Note 19 Annex 1.The Climate Policy Assessment Tool(CPAT)The IMF-World Bank Climate Policy Assessment Tool(CPAT)provides,

234、on a country-by-country basis for around 200 countries,projections of fuel use and carbon dioxide emissions by major energy sector.28 For key attributes of CPAT,see Annex Table 1.1.This tool starts with the use of fossil fuels and other fuels by the power,industrial,transport,and residential sectors

235、 and then projects fuel use forward in a baseline case using(1)GDP projections,(2)assumptions about the income elasticity of demand and own-price elasticity of demand for electricity and other fuel product,(3)assumptions about the rate of technological change that affects energy efficiency and the p

236、roductivity of different energy sources,and(4)future international energy prices.In these projections,current fuel taxes/subsidies and carbon pricing are held constant in real terms.The impacts of carbon pricing on fuel use and emissions depend on(1)their proportionate impact on future fuel prices i

237、n different sectors,(2)a model of dispatch and investment in the power generation sector,and 28 For more details on the model,its parameterization,and key caveats,see Black and others(2023b).Annex Table 1.1.Attributes of CPAT Source:Authors.Note:CPAT=Climate Policy Assessment Tool ETSs=emissions tra

238、ding systems;GHG=greenhouse gas;NDC=nationally determined contributions;VAT=value-added tax.Desirable modelling featureHow CPAT addresses featureCountry coverageOver 200 countries with full set of data(for example,on fuel use,emissions,energy prices)for each country.Provides consistent cross-country

239、 comparisons of baselines and policy effects.Baseline projections and NDCsProjections based on most recent observed emissions and projected forward by fuel/sector using latest data on GDP projections,income elasticities for energy products,trend rates of efficiency improvements,and future energy pri

240、ce scenarios.NDC pledges are mapped to emissions reductions below baseline/historical levels.How mitigation policies workBehavioral responses to mitgation policies are approximately in the mid-range of those from broader energy modelling literature and empirical evidence on fuel price/income elastic

241、ities.Mitigation policiesPotential policies include carbon taxes,ETSs,energy efficiency/emission rate regulations,feebates,clean technology subsidies/mandates,electricity/fuel taxes,fossil fuel subsidies,energy price liberalization,removals of preferential VAT for fuels,combinations of policies.Base

242、line includes energy taxes/subsidies and carbon pricing regulations are implicit in observed fuel use.Sectors and gasesMain module covers power,industry,transport,and buildings.Supplementary models cover agriculture,extractives,forestry,and waste.All GHGs are included.Metrics for policy evaluationIm

243、pacts on energy production/consumption,prices,trade;GHG and local emissions;GDP and economic welfare;revenue;incidence across households(income deciles,within deciles,urban/rural);incidence across industries;domestic environmental co-benefits(e.g.,local air pollution mortality).Transparency,sensitiv

244、ity,accessibilityKey model parameters and inputs are easily adjusted in the dashboard.Results presented rapidly via a chart-driven interface,allowing for experimentation in designing policy reforms.Spreadhseet model has user-friendly dashboard.International Monetary Fund.Not for Redistribution IMF|S

245、taff Climate Note 20 (3)various own-price elasticities for electricity use and fuel use in other sectors.For the most part,fuel demand curves are based on a constant elasticity specification.The basic model is parameterized using data compiled from the International Energy Agency on recent fuel use

246、by country and sector.GDP projections are from the latest IMF forecasts.29 Data on energy taxes,subsidies,and prices by energy product and country is compiled from publicly available and IMF sources,with inputs from proprietary and third-party sources.International energy prices are projected forwar

247、d using an average of World Bank and IMF projections for coal,oil,and natural gas prices.Assumptions for fuel price responsiveness are chosen to be broadly consistent with empirical evidence and results from energy models(fuel price elasticities are typically between about 0.5 and 0.8).Carbon emissi

248、ons factors by fuel product are from the International Energy Agency.The domestic environmental costs of fuel use are based on IMF methodologies(see Black and others 2023a).One caveat is that the model abstracts from the possibility of mitigation actions(beyond those implicit in recently observed fu

249、el use and price data)in the baseline,which provides a clean comparison of policy reforms to the baseline.Another caveat is that,while the assumed fuel price responses are plausible for modest fuel price changes,they may not be for dramatic price changes that might drive major technological advances

250、,or rapid adoption of technologies like carbon capture and storage or even direct air capture,though the future viability and costs of these technologies are highly uncertain.The model does not explicitly account for full general equilibrium effects(for example,changes in relative factor prices that

251、 might have feedback effects on the energy sector),changes in international fuel prices that might result from simultaneous climate or energy price reform in large countries,or cross-country linkages through trade.Some of these effects may be of relatively minor importance howeverfor example,trade-s

252、ensitive sectors account for a minor portion of emissions,trade impacts depend on mitigation policies in other countries,and countries usually implement measures(like free allowance allocations)to limit the competitiveness impacts of their own mitigation policies.Moreover,parameter values in the spr

253、eadsheet are,chosen such that the results from the model are broadly consistent with those from far more detailed energy models that,to varying degrees,account for these factors.The CPAT converts all mitigation pledges into a single,comparable metric:required emissions reductions against future busi

254、ness-as-usual or historical baseline emissions.It also accommodates a diverse range of mitigation policies such as carbon pricing,fossil fuel subsidy reform,energy price liberalization,electricity subsidy and tariff reform,renewable subsidies,removal of favorable VAT treatment of fuels,and combinati

255、ons of these and other policies.It also has full coverage of sectors and gases,including CO2 and non-CO2 greenhouse gases(GHGs),as well as local air pollutants(including those with an effect on warming and others).For each policy,CPAT assesses impacts on all the metrics noted previously and some oth

256、ers(household and industry incidence is available for all almost 100,but not all,countries).The model also includes a country-specific database on prices,taxes,and subsidies by fuel product/sector.The CPATs core is a macro-energy model distinguishing 17 fossil and non-fossil fuels and four sectorspo

257、wer,industry,transport,buildings,with transport and industry split into various subsectors consistent with the classifications provided by the United Nations Framework Convention on Climate Change.In CPAT,the user interacts with the“Dashboard,”which is a chart-driven,user-friendly interface.The user

258、 selects the country,mitigation policy(for example,carbon or energy taxes),the stringency of the policy over time and its sectoral/fuel coverage,and complementary policies(for example,fossil fuel subsidy reform,energy price liberalization,and feed-in subsidies for renewables).Revenues from mitigatio

259、n policies can be recycled in broader tax reductions,public spending or investment,or transfers.The user then sees the main results in key charts(for example,impacts on emissions,revenue,GDP,households by income group,local air pollution mortality,and economic welfare)and numerous more detailed char

260、ts.29 A modest adjustment in emissions projections is made to account for partially permanent structural shifts in the economy caused by the coronavirus pandemic.International Monetary Fund.Not for Redistribution IMF|Staff Climate Note 21 CPAT does not require any external data,but users can adjust

261、various inputs including data and key assumptions(such as domestic energy prices,fuel price responsiveness).Given the importance of power generation in the early stages of decarbonization,CPAT includes a technology-based model of the sector which the user can select as an alternative to the power mo

262、del based on fuel price elasticities.The technology-based model is grounded in observed generation technologies and forward-looking investments in new capacity,as well as dispatch from existing technologies,based on projections of levelized technology costs,assumptions about capital retirement rates

263、,capacity factors,the increasing need for storing intermittent power,and possible constraints on expansion rates for renewables.30 The technology-based model provides more accurate baseline projections of the power generation mix,though it tends to be less responsive to mitigation policies than impl

264、ied by empirical evidence on the price responsiveness of generation fuels.Lastly,it should be noted that there are many other models that can quantify and project energy consumption,emissions,and other impacts of climate mitigation policy.This includes,for example,macroeconometric models such as the

265、 Macro-Fiscal Model(Burns and others 2019),computable general equilibrium models like IMFs ENVISAGE(Chateau and others 2022),sectoral models such as the Future Technology Transformations models(Mercure and others 2012),the IMFs Fiscal Analysis of Resource Industries model(Luca and Mesa Puyo 2016),an

266、d others.Each model has varying strengths and weaknesses,and no model can provide all answers to questions relating to climate mitigation policy.Overall,the CPAT can be a useful tool for governments setting revised and new NDC targets and assessing the policies to achieve them.It is being made avail

267、able exclusively to governments.31 30 In default settings,hydroelectric capacity is fixed on the assumption opportunities have already been exploited,while nuclear power can gradually ramp up in countries with fission reactors.31 For more details,see www.imf.org/cpat.International Monetary Fund.Not

268、for Redistribution IMF|Staff Climate Note 22 Annex 2.Emissions Impacts Implied by Different Allocations of Mitigation Burden Annex Figure 2.1.Emissions Changes Under Six Equity Allocations(Panel 1)and Inferred Relationship of Emissions Cuts Versus BAU to Projected per Capita Incomes(Panel 2)Source:v

269、an der Berg and others(2020);and IMF staff calculations using CPAT.Note:In panel 2,dots show the average implied emissions cuts in 2030 BAU for countries/blocs taking an average of the six equity allocations from panel 2.The line-of-best fit shows the relationship between average emissions cuts impl

270、ied by the six equity allocations(versus 2030 BAU from CPAT)and GDP per capita in 2030.Data labels in the figure use International Organization for Standardization(ISO)country codes.BAU=business as usual;CPAT=Climate Policy Assessment Tool;GHG=greenhouse gas.-200-1000100200CHNUSAEUJPNRUSINDBRA2030 G

271、HG emissions versus 2010(percent change)BaselineAcquired rightsCost optimalityGradual convergenceAbility to payGreenhouse development rightsImmediate convergenceIllustrative 2C fair share1.Emissions Changes Under Six Equity AllocationsCHNUSAEUJPNRUSINDBRA010203040506070 500 5,000 50,000Implied cut i

272、n 2030 GHG emissions versus BAU(percent change)GDP per capita in 2030(log scale)2.Relationship of Emissions to Per Capita Incomes International Monetary Fund.Not for Redistribution IMF|Staff Climate Note 23 Annex 3.Illustrative Temperature-Aligned Targets by Country(2030)Annex Figure 3.1.Mitigation

273、Ambition(in NDCs)and Illustrative Targets for All Countries Source:IMF staff calculations using CPAT.Note:Where no NDC is shown,the target is nonbinding and is assumed to have achieved in the baseline or is nonquantifiable(for example,Bahrain,Bhutan,Saudi Arabia,and others).Countries with asterisks(

274、*)decreased ambition in 2024 NDCs relative to 2015 NDCs,so the figure shows only 2024 NDCs.NDCs for EU countries are inferred using national allocations for non-ETS sectors(in effort-sharing regulations)and an assumed similar reduction in EU ETS sectors.NDCs average over conditional and unconditiona

275、l targets where both are specified.ETS=emissions trading system;EU=Euorpean Union;FYR=former Yugoslave Republic;GHG=greenhouse gas;LIC=low-income country;LMICs=lower-middle-income countries;NDC=nationally determined contribution;PDR=Peoples Democratic Republic;SAR=Special Administrative Region;UMICs

276、=upper-middle-income countries.020406080New ZealandIrelandCyprusUnited Arab EmiratesBelgiumNorwayNetherlandsUnited StatesDenmarkUnited KingdomIcelandMaltaGermanySwitzerlandOman*FranceAustriaFinlandLatviaIsraelKoreaCanadaBahamas,TheItalyAustraliaCroatiaSlovak RepublicLuxembourgChileJapanEstoniaSeyche

277、llesQatarPolandCzech RepublicSpainSingaporeLithuaniaTrinidad and TobagoPortugalPanamaKuwaitHungaryUruguayGreeceBahrainBarbados*Brunei DarussalamHong Kong SARMacao SARNauruRomaniaSaudi ArabiaSloveniaSwedenTaiwan Province ofHIC1.High-income countries:GHG emissions cuts in 2030 versus baseline(percent)

278、2015 NDC2024 NDCIllustrative 2CIllustrative 1.5CIncreasing ambition020406080GrenadaMoldovaDominicaColombiaBrazilBotswanaMexicoEcuadorAzerbaijan*FijiSt.LuciaJamaicaGabon*BulgariaThailand*South AfricaJordanSt.Vincent and the GrenadinesMacedonia,FYRTurkmenistanVenezuelaArgentinaCosta RicaNamibia*ChinaM

279、aldivesKazakhstanDominican Republic*IraqParaguayAlbania*Armenia*BelarusBelizeBosnia and HerzegovinaEquatorial GuineaGeorgia*Guatemala*GuyanaLibyaMalaysiaPeruRussiaSerbiaSurinameTongaTurkeyUMIC2.Upper-middle-income countries:GHG emissions cuts in 2030 versus baseline(percent)2015 NDC2024 NDCIllustrat

280、ive 2CIllustrative 1.5CIncreasing ambition020406080Central African RepublicMauritaniaSamoaMaliLiberia*Kyrgyz RepublicSolomon IslandsCambodia*Cabo VerdePhilippinesNigeriaChad*EritreaBeninCongo,Republic ofEgyptLebanonMadagascarAngolaKenyaTunisia*MoroccoSo Tom and Prncipe*Kiribati*BurundiTajikistan*Yem

281、enCte dIvoire*HondurasRwandaAlgeriaGuineaMalawiSenegalDjiboutiTanzania*Sierra LeoneEswatiniSri Lanka*IranMongolia*Ethiopia*Haiti*AfghanistanBangladesh*BhutanBoliviaBurkina FasoCameroon*ComorosEl SalvadorGambia,The*GhanaGuinea-BissauIndiaIndonesiaLao P.D.R.Lesotho*MozambiqueMyanmarNepalNicaraguaNiger

282、*PakistanPapua New GuineaSomaliaSudanSyriaTogoUgandaUkraineUzbekistanVanuatuVietnamLMIC&LIC3.Lower-middle and low-income countries:GHG emissions cuts in 2030 versus baseline(percent)2015 NDC2024 NDCIllustrative 2CIllustrative 1.5CIncreasing ambitionInternational Monetary Fund.Not for Redistribution

283、IMF|Staff Climate Note 24 Annex Table 3.1 Illustrative Emissions Targets Aligned with 1.5C and 2C in 2030 Country Baseline GHG Emissions in 2030,MtCO2e Illustra-tive 2C-Aligned Target in 2030,MtCO2e Percent Cut versus Base Years (negative=increase)Illustra-tive 1.5C-Aligned Target in 2030,MtCO2e Per

284、cent Cut versus Base Years(negative=increase)Per Capita GHG Emissions in 2030,tCO2/Person 1990 2005 2010 1990 2005 2010 Baseline Illustrative 2C Illustrative 1.5C Afghanistan 32.1 32.1-182.1-75.4-6.0 25.3-122.4-38.3 16.5 0.6 0.6 0.5 Albania 8.5 6.5 44.4 5.9 6.8 4.3 63.8 38.7 39.3 3.0 2.3 1.5 Algeria

285、 286.6 235.3-60.5-26.5-13.8 159.6-8.9 14.2 22.8 5.8 4.8 3.2 Angola 113.2 87.2-44.3 30.0 33.4 72.7-20.2 41.7 44.5 2.6 2.0 1.6 Argentina 432.3 320.0-3.1 27.7 27.9 206.0 33.6 53.5 53.6 9.1 6.7 4.3 Armenia 10.1 7.9 67.7-4.3-9.1 5.1 79.2 32.8 29.8 3.7 2.9 1.8 Australia 484.5 282.9 54.5 53.1 52.7 156.4 74

286、.8 74.1 73.8 17.3 10.1 5.6 Austria 62.5 36.7 45.0 50.4 43.3 20.8 68.8 71.9 67.9 6.9 4.1 2.3 Azerbaijan 69.6 45.4 35.0-1.6 3.1 37.7 46.0 15.6 19.5 6.5 4.2 3.5 The Bahamas 1.8 1.2 13.3 2.1 27.2 0.7 48.8 42.2 57.0 4.3 2.7 1.6 Bahrain 65.6 42.9-42.0 1.8 17.0 25.5 15.7 41.8 50.7 41.8 27.4 16.2 Bangladesh

287、 347.4 297.7-88.3-50.6-26.9 197.3-24.8 0.2 15.9 1.9 1.6 1.1 Barbados 0.9 0.6 28.7 30.8 40.5 0.4 56.5 57.9 63.8 3.2 2.2 1.3 Belarus 43.4 33.3 71.3 36.5 27.2 22.2 80.9 57.7 51.5 4.7 3.6 2.4 Belgium 110.2 60.7 57.5 57.7 54.4 37.0 74.1 74.2 72.2 9.3 5.1 3.1 Belize 5.6 4.3 38.7-11.3-5.6 2.9 59.6 26.6 30.

288、4 12.5 9.7 6.4 Benin 34.8 23.5-18.7-19.2-1.7 22.2-12.4-12.8 3.7 2.1 1.5 1.4 Bhutan 2.3 1.9 1.3 2.8 2.3 1.6 Bolivia 118.7 99.4 13.0 0.6 21.1 68.4 40.2 31.7 45.7 8.8 7.3 5.1 Bosnia and Herzegovina 16.4 12.4 62.1 47.4 56.9 8.1 75.4 65.9 72.0 5.2 4.0 2.6 Botswana 46.8 29.2 42.0 42.9 43.0 23.6 53.2 54.0

289、54.1 15.9 9.9 8.0 Brazil 1701.0 1025.7 41.3 53.1 55.4 850.5 51.3 61.1 63.0 7.6 4.6 3.8 Brunei Darussalam 15.6 10.2-6.8 19.5 33.2 6.0 36.7 52.3 60.4 33.1 21.6 12.8 Bulgaria 28.2 20.1 75.6 56.1 57.5 12.6 84.7 72.4 73.3 4.5 3.2 2.0 Burkina Faso 61.8 59.6-145.6-60.4-45.3 42.3-74.4-13.9-3.2 2.3 2.2 1.6 B

290、urundi 10.7 8.7-7.9-26.7-7.3 8.5-5.7-24.2-5.2 0.7 0.6 0.5 Cabo Verde 1.3 0.8 0.2 16.8 0.7 10.4 25.3 2.1 1.2 1.1 Cambodia 86.8 52.3-77.7-38.7-22.0 50.7-72.4-34.5-18.4 4.8 2.9 2.8 Cameroon 80.7 73.4 13.7 3.3 2.2 51.2 39.9 32.6 31.8 2.4 2.2 1.5 Canada 619.5 372.4 28.9 48.8 45.5 212.0 59.6 70.8 69.0 15.

291、2 9.1 5.2 Central African Republic 43.2 14.5 65.4 71.9 71.2 14.5 65.4 71.9 71.2 6.2 2.1 2.1 Chad 122.7 76.6-266.8-40.8-17.5 76.6-266.8-40.8-17.5 5.5 3.5 3.5 Chile 73.1 51.2-15.9 14.9 28.9 32.0 27.5 46.8 55.5 3.7 2.6 1.6 China 15789.2 11290.5-202.9-39.3-0.5 7012.5-88.1 13.5 37.6 11.1 8.0 4.9 Colombia

292、 292.2 169.4 26.9 30.9 35.3 150.3 35.2 38.7 42.6 5.4 3.1 2.8 Comoros 1.1 1.0-138.6-52.8-44.4 0.7-67.1-7.0-1.1 1.1 1.0 0.7 Congo,Democratic Republic of the 584.8 441.5-3.4-2.3-1.0 423.4 0.8 1.9 3.2 4.7 3.5 3.4 Congo,Republic of 35.6 25.5-25.2 13.4 20.4 22.0-7.8 25.4 31.4 5.1 3.6 3.1 Costa Rica 10.7 7

293、.5 39.4 36.8 44.9 4.7 62.5 60.9 65.9 2.0 1.4 0.9 Cte dIvoire 45.1 37.7 47.0 18.5 21.9 26.1 63.3 43.5 45.9 1.3 1.1 0.8 International Monetary Fund.Not for Redistribution IMF|Staff Climate Note 25 Country Baseline GHG Emissions in 2030,MtCO2e Illustra-tive 2C-Aligned Target in 2030,MtCO2e Percent Cut

294、versus Base Years (negative=increase)Illustra-tive 1.5C-Aligned Target in 2030,MtCO2e Percent Cut versus Base Years(negative=increase)Per Capita GHG Emissions in 2030,tCO2/Person 1990 2005 2010 1990 2005 2010 Baseline Illustrative 2C Illustrative 1.5C Croatia 20.9 14.2 43.5 35.2 33.3 8.7 65.6 60.5 5

295、9.3 5.4 3.7 2.2 Cyprus 8.5 4.5 16.9 50.0 51.0 3.4 38.1 62.8 63.5 6.5 3.4 2.6 Czech Republic 95.8 62.6 67.1 55.5 52.9 37.7 80.2 73.2 71.7 9.1 6.0 3.6 Denmark 47.9 27.2 65.5 63.2 60.3 14.9 81.1 79.9 78.3 7.9 4.5 2.4 Djibouti 2.6 2.2-14.0-9.7-5.0 1.4 24.3 27.2 30.3 2.1 1.7 1.2 Dominica 0.1 0.1 47.4 36.

296、3 44.9 0.1 54.9 45.4 52.7 1.8 1.0 0.9 Dominican Republic 45.6 34.4-218.0-18.4-2.1 21.7-100.3 25.4 35.7 3.8 2.9 1.8 Ecuador 99.8 63.7 15.2 25.2 34.4 52.0 30.8 39.0 46.5 5.1 3.3 2.7 Egypt 422.8 308.7-102.2-10.8 2.6 231.9-51.9 16.8 26.8 3.4 2.5 1.9 El Salvador 15.1 12.2-37.2 13.8 9.2 8.2 7.7 42.0 38.9

297、2.3 1.9 1.3 Equatorial Guinea 15.7 12.5-212.6 40.0 45.5 8.6-114.3 58.9 62.6 7.9 6.3 4.3 Eritrea 9.1 6.1-16.0 1.7 3.5 6.1-16.0 1.7 3.5 2.2 1.4 1.4 Estonia 11.8 7.7 78.8 52.3 50.0 4.6 87.2 71.2 69.8 9.1 6.0 3.6 Eswatini 3.8 3.3-1.9-1.8-18.2 2.2 30.9 30.9 19.8 3.0 2.6 1.7 Ethiopia 250.7 236.5-155.0-86.

298、8-50.9 167.7-80.8-32.5-7.0 1.7 1.6 1.1 Fiji 0.7 0.4 39.1 29.0 0.3 52.3 44.3 0.7 0.4 0.4 Finland 42.7 25.2 42.3 35.9 47.0 14.2 67.5 63.9 70.1 7.7 4.5 2.6 France 394.3 237.3 54.5 52.7 49.4 136.1 73.9 72.9 71.0 6.0 3.6 2.1 Gabon 25.7 17.7 25.8 39.7 26.8 13.2 44.6 55.0 45.4 9.3 6.4 4.8 Gambia,The 3.1 3.

299、0-73.3-46.0-17.6 2.1-23.5-4.0 16.2 1.0 0.9 0.7 Georgia 20.8 16.2 61.5-109.6-90.4 10.4 75.2-34.8-22.5 5.7 4.4 2.9 Germany 639.1 378.9 70.5 61.8 59.2 216.7 83.2 78.1 76.7 7.7 4.6 2.6 Ghana 37.5 32.8-53.4 49.7 54.4 22.4-5.0 65.6 68.8 1.0 0.9 0.6 Greece 72.0 47.9 52.9 64.1 58.6 29.3 71.2 78.0 74.7 7.1 4

300、.7 2.9 Grenada 0.2 0.1-4.2 17.8 40.0 0.1-4.2 17.8 40.0 1.9 0.8 0.8 Guatemala 54.0 43.4-41.0-2.9 1.5 28.7 6.6 31.8 34.7 2.7 2.2 1.4 Guinea 43.7 37.9-103.1-52.3-26.3 28.7-53.9-15.4 4.3 2.7 2.3 1.7 Guinea-Bissau 5.0 4.9-39.2-17.3-6.6 3.5 0.7 16.3 24.0 2.0 2.0 1.4 Guyana 22.5 15.5-66.1-25.4-20.2 7.5 19.

301、1 38.9 41.5 26.6 18.3 8.9 Haiti 16.1 14.9-86.7-31.9-14.4 10.9-35.8 4.1 16.8 1.3 1.2 0.9 Honduras 34.7 29.1-86.6-27.7-16.4 20.3-30.0 11.0 18.9 3.0 2.5 1.7 Hong Kong SAR 28.0 16.6 58.4 65.6 65.5 9.2 77.0 81.0 80.9 3.7 2.2 1.2 Hungary 52.9 36.0 60.7 49.2 41.6 21.9 76.1 69.1 64.5 5.5 3.7 2.3 Iceland 13.

302、1 7.4 44.3 46.0 49.0 4.0 70.1 71.0 72.6 33.6 19.0 10.2 India 5159.9 4467.3-266.5-102.1-56.6 2983.8-144.8-35.0-4.6 3.4 3.0 2.0 Indonesia 1449.3 1175.2-6.1 0.1-4.7 771.0 30.4 34.5 31.3 5.0 4.0 2.6 Iran 1026.5 882.6-182.5-38.1-15.7 612.0-95.9 4.3 19.8 11.1 9.5 6.6 Iraq 371.8 305.5-80.2-86.5-45.7 205.2-

303、21.1-25.3 2.1 7.1 5.8 3.9 Ireland 69.6 34.7 43.7 56.1 50.4 18.6 69.8 76.5 73.4 13.2 6.6 3.5 Israel 89.2 53.0-24.1 28.4 38.4 28.9 32.2 60.9 66.3 8.9 5.3 2.9 Italy 372.4 229.8 55.6 58.8 52.3 135.9 73.7 75.7 71.8 6.5 4.0 2.4 Jamaica 7.9 5.3 45.5 48.2 22.7 4.2 57.0 59.1 39.0 2.8 1.9 1.5 International Mo

304、netary Fund.Not for Redistribution IMF|Staff Climate Note 26 Country Baseline GHG Emissions in 2030,MtCO2e Illustra-tive 2C-Aligned Target in 2030,MtCO2e Percent Cut versus Base Years (negative=increase)Illustra-tive 1.5C-Aligned Target in 2030,MtCO2e Percent Cut versus Base Years(negative=increase)

305、Per Capita GHG Emissions in 2030,tCO2/Person 1990 2005 2010 1990 2005 2010 Baseline Illustrative 2C Illustrative 1.5C Japan 987.5 593.4 50.8 53.9 51.7 344.1 71.4 73.3 72.0 8.3 5.0 2.9 Jordan 40.1 30.3-141.5-18.4-11.6 22.0-75.1 14.2 19.1 3.4 2.6 1.8 Kazakhstan 331.4 245.6 35.4 33.7 35.6 157.0 58.7 57

306、.6 58.8 15.8 11.7 7.5 Kenya 123.8 97.2-153.2-29.6 4.6 74.2-93.3 1.1 27.2 2.0 1.6 1.2 Kiribati 0.1 0.1-180.5-8.4-9.1 0.1-116.8 16.2 15.7 0.8 0.7 0.5 Korea 633.0 394.7-37.1 24.5 35.6 229.1 20.4 56.1 62.6 12.3 7.7 4.5 Kuwait 158.2 103.3-107.2 12.1 16.8 61.9-24.2 47.3 50.1 34.8 22.7 13.6 Kyrgyz Republic

307、 19.3 10.4 69.0 13.2 27.2 10.4 69.0 13.2 27.2 2.6 1.4 1.4 Lao P.D.R.57.0 48.9-131.7-82.1-51.4 33.3-57.8-24.0-3.1 6.9 5.9 4.0 Latvia 12.4 8.0 38.9-77.0 13.7 5.0 62.1-9.6 46.5 7.3 4.7 2.9 Lebanon 31.6 23.5-191.4-12.1 8.1 17.5-116.2 16.8 31.8 6.7 5.0 3.7 Lesotho 3.3 3.1-40.2-10.4-8.1 2.3-1.5 20.1 21.8

308、1.3 1.3 0.9 Liberia 16.6 7.9 48.6 51.2 53.3 7.9 48.6 51.2 53.3 2.7 1.3 1.3 Libya 102.4 76.8 11.3 27.0 29.4 49.0 43.5 53.5 55.0 13.9 10.4 6.7 Lithuania 14.6 9.6 77.5 47.2 6.4 5.8 86.5 68.3 43.8 5.7 3.7 2.2 Luxembourg 8.1 4.2 67.0 66.2 64.9 2.1 83.7 83.3 82.6 11.7 6.0 3.0 Macao SAR 2.8 1.6-59.0 30.2 1

309、4.6 0.8 18.7 64.3 56.4 3.7 2.1 1.1 Macedonia,FYR 10.6 8.2 43.2 33.9 30.5 5.3 63.0 57.0 54.8 5.1 4.0 2.6 Madagascar 49.1 37.3 30.5 25.4 29.2 36.2 32.6 27.7 31.3 1.4 1.1 1.0 Malawi 30.6 26.6-80.7-45.2-25.6 22.1-50.2-20.7-4.4 1.2 1.1 0.9 Malaysia 416.3 302.7-48.6 14.8 22.3 188.8 7.3 46.8 51.5 11.4 8.3

310、5.2 Maldives 2.7 1.9-1165.8-128.4-57.2 1.2-674.6-39.7 3.8 5.3 3.8 2.3 Mali 58.6 26.6-70.8-18.8 6.3 26.6-70.8-18.8 6.3 2.1 0.9 0.9 Malta 2.4 1.4 44.7 51.7 51.3 0.8 68.4 72.4 72.2 4.4 2.7 1.5 Mauritania 18.2 7.8-11.0 27.6 33.8 7.8-11.0 27.6 33.8 3.2 1.4 1.4 Mexico 849.7 541.4-10.3 15.9 23.0 405.9 17.4

311、 36.9 42.3 6.3 4.0 3.0 Moldova 14.0 7.9 79.0 23.2 25.2 7.5 79.9 26.6 28.5 4.4 2.5 2.4 Mongolia 78.2 63.5-28.3-30.7-2.3 41.5 16.2 14.6 33.2 21.0 17.1 11.2 Morocco 121.4 96.9-140.0-38.9-20.8 68.0-68.5 2.5 15.2 3.0 2.4 1.7 Mozambique 101.7 101.7-33.1-15.1-5.3 73.8 3.4 16.5 23.6 2.5 2.5 1.8 Myanmar 291.

312、2 268.1-19.6-10.3-2.5 192.3 14.2 20.9 26.5 5.1 4.7 3.4 Namibia 23.2 18.8-9.5 11.4 8.9 12.7 26.1 40.2 38.6 8.0 6.5 4.4 Nepal 67.9 62.9-107.5-87.2-66.5 44.0-45.2-31.0-16.5 2.1 1.9 1.3 Netherlands 158.4 92.0 59.7 58.3 58.1 51.2 77.6 76.8 76.7 8.8 5.1 2.9 New Zealand 56.6 28.0 36.6 50.0 41.3 19.6 55.8 6

313、5.1 59.0 10.3 5.1 3.6 Nicaragua 39.2 34.4-13.8 11.4 13.8 23.8 21.2 38.6 40.3 5.1 4.5 3.1 Niger 56.0 56.0-220.0-145.4-112.0 40.2-129.9-76.3-52.3 1.6 1.6 1.2 Nigeria 492.6 301.2 10.3 32.6 27.1 301.2 10.3 32.6 27.1 1.9 1.2 1.2 Norway 32.7 18.3 55.0 46.0 40.7 10.0 75.5 70.6 67.7 5.7 3.2 1.7 Oman 148.3 9

314、1.8-174.3-37.7-10.7 62.8-87.8 5.7 24.2 29.3 18.1 12.4 Pakistan 648.4 595.3-166.9-66.2-46.2 417.5-87.1-16.5-2.5 2.4 2.2 1.5 Panama 23.0 15.9-20.1 7.7 19.5 9.6 27.0 43.8 51.0 4.7 3.3 2.0 International Monetary Fund.Not for Redistribution IMF|Staff Climate Note 27 Country Baseline GHG Emissions in 2030

315、,MtCO2e Illustra-tive 2C-Aligned Target in 2030,MtCO2e Percent Cut versus Base Years (negative=increase)Illustra-tive 1.5C-Aligned Target in 2030,MtCO2e Percent Cut versus Base Years(negative=increase)Per Capita GHG Emissions in 2030,tCO2/Person 1990 2005 2010 1990 2005 2010 Baseline Illustrative 2C

316、 Illustrative 1.5C Papua New Guinea 37.3 32.4-22.5 9.1-1.4 22.3 15.5 37.3 30.1 3.2 2.8 1.9 Paraguay 87.4 69.1-7.5 17.5 26.4 45.5 29.2 45.7 51.5 11.8 9.4 6.2 Peru 185.7 143.2-34.0-8.7 3.3 94.4 11.7 28.4 36.3 5.1 3.9 2.6 Philippines 321.2 196.4-74.9-18.7-9.8 174.6-55.5-5.5 2.4 2.5 1.5 1.4 Poland 296.6

317、 203.0 54.5 42.4 45.8 123.7 72.3 64.9 67.0 7.7 5.2 3.2 Portugal 52.3 33.9 48.6 62.0 45.5 20.3 69.2 77.2 67.4 5.2 3.4 2.0 Qatar 216.7 126.4-334.7-51.5 7.9 67.9-133.4 18.6 50.5 76.2 44.4 23.9 Romania 67.5 47.1 79.4 60.0 47.3 28.9 87.3 75.5 67.7 3.5 2.5 1.5 Russia 1577.9 1139.3 63.0 19.5 13.0 731.9 76.

318、2 48.3 44.1 11.1 8.0 5.2 Rwanda 11.9 10.2-17.2-30.7-13.9 7.9 8.7-1.8 11.3 0.7 0.6 0.5 Samoa 0.7 0.3 24.3 43.3 47.8 0.3 24.3 43.3 47.8 2.8 1.3 1.3 So Tom and Prncipe 0.4 0.3-260.9-104.9-62.8 0.3-177.5-57.5-25.1 1.6 1.3 1.0 Saudi Arabia 879.2 589.3-147.2-26.3 4.9 350.7-47.1 24.8 43.4 21.9 14.7 8.7 Sen

319、egal 42.3 36.8-132.1-57.0-36.6 26.4-66.7-12.8 1.9 2.0 1.8 1.3 Serbia 49.6 37.0 56.8 0.8 49.1 23.4 72.6 37.1 67.7 7.2 5.4 3.4 Seychelles 1.1 0.8-133.3 26.7 23.7 0.5-43.0 55.1 53.2 9.9 6.9 4.3 Sierra Leone 10.7 9.7-29.2-15.2-6.7 7.9-5.1 6.3 13.2 1.1 1.0 0.8 Singapore 73.6 41.8-22.5 18.2 29.3 22.5 34.2

320、 56.1 62.0 11.8 6.7 3.6 Slovak Republic 35.8 24.0 62.7 47.8 40.9 14.5 77.4 68.4 64.2 6.4 4.3 2.6 Slovenia 10.5 6.7 53.0 49.5 46.4 4.0 72.4 70.4 68.5 5.0 3.2 1.9 Solomon Islands 37.0 22.2-430.4-916.3-882.9 22.2-430.4-916.3-882.9 43.6 26.2 26.2 Somalia 53.8 53.8-26.1-12.9-15.7 39.5 7.5 17.2 15.2 2.4 2

321、.4 1.8 South Africa 522.7 385.0 8.1 31.5 35.3 275.9 34.1 50.9 53.6 8.1 6.0 4.3 Spain 266.2 168.5 33.5 57.2 45.7 99.5 60.7 74.7 67.9 5.7 3.6 2.1 Sri Lanka 36.1 29.7-7.7 14.4 17.2 20.7 24.8 40.2 42.2 1.6 1.3 0.9 St.Lucia 0.3 0.2-617.7-53.7-1.9 0.1-405.1-8.2 28.3 1.5 1.0 0.7 St.Vincent and the Grenadin

322、es 0.2 0.1-225.4-4.6 17.4 0.1-107.3 33.4 47.4 1.7 1.3 0.8 Sudan 181.9 181.9-115.8-31.2-22.0 132.2-56.9 4.6 11.3 3.2 3.2 2.3 Suriname 12.0 9.6-92.6-49.1-43.7 6.4-28.7 0.4 3.9 18.3 14.7 9.8 Sweden 0.4 0.3 99.0 98.9 98.1 0.1 99.4 99.4 98.9 0.0 0.0 0.0 Switzerland 43.0 23.3 56.2 56.2 55.6 12.2 77.1 77.1

323、 76.8 4.7 2.6 1.3 Syria 58.4 50.6 20.3 43.2 45.2 34.8 45.1 60.9 62.3 2.0 1.7 1.2 Taiwan Province of China 293.7 186.0-32.3 44.0 38.6 108.8 22.6 67.3 64.1 12.2 7.7 4.5 Tajikistan 24.4 19.8 11.1-69.2-67.9 16.3 27.0-38.9-37.9 2.2 1.8 1.4 Tanzania 164.9 148.1-64.7-28.9-22.7 108.8-21.0 5.3 9.9 2.0 1.8 1.

324、3 Thailand 512.8 371.5-57.2-6.1 6.1 253.5-7.3 27.6 35.9 7.1 5.2 3.5 Togo 13.8 13.1-109.0-85.9-46.3 9.3-47.3-31.0-3.1 1.3 1.3 0.9 Tonga 0.3 0.2-28.9-2.5-2.0 0.2 12.2 30.1 30.5 2.6 2.1 1.5 Trinidad and Tobago 45.6 32.1-75.8 38.2 48.3 20.2-10.3 61.2 67.5 29.4 20.8 13.0 Tunisia 45.6 36.0-56.7-2.4 11.8 2

325、5.9-12.7 26.3 36.6 3.5 2.8 2.0 International Monetary Fund.Not for Redistribution IMF|Staff Climate Note 28 Country Baseline GHG Emissions in 2030,MtCO2e Illustra-tive 2C-Aligned Target in 2030,MtCO2e Percent Cut versus Base Years (negative=increase)Illustra-tive 1.5C-Aligned Target in 2030,MtCO2e P

326、ercent Cut versus Base Years(negative=increase)Per Capita GHG Emissions in 2030,tCO2/Person 1990 2005 2010 1990 2005 2010 Baseline Illustrative 2C Illustrative 1.5C Turkey 540.7 396.8-159.4-49.3-21.4 251.4-64.4 5.4 23.1 6.1 4.5 2.8 Turkmenistan 131.8 99.3-14.6 0.8 3.2 64.7 25.3 35.3 36.9 18.8 14.2 9

327、.2 Uganda 79.6 76.4-131.7-78.0-38.2 53.4-62.1-24.5 3.4 1.4 1.3 0.9 Ukraine 277.4 231.9 74.5 46.5 41.8 155.4 82.9 64.1 61.0 7.2 6.0 4.0 United Arab Emirates 332.1 182.0-114.7-7.3 19.1 111.3-31.3 34.4 50.5 33.3 18.2 11.2 United Kingdom 436.3 261.0 68.0 62.8 57.6 150.5 81.5 78.5 75.6 6.3 3.8 2.2 United

328、 States 5503.0 3110.7 44.5 53.5 50.6 1671.1 70.2 75.0 73.5 15.7 8.9 4.8 Uruguay 40.7 27.9-69.4 1.1 6.7 17.1-4.0 39.3 42.7 11.9 8.1 5.0 Uzbekistan 244.7 215.5-21.6-19.7-9.7 146.7 17.2 18.5 25.3 6.4 5.7 3.8 Vanuatu 0.7 0.6-25.2-6.0 14.3 0.4 14.0 27.1 41.1 1.8 1.6 1.1 Venezuela 209.2 167.3 46.3 50.0 52

329、.0 131.8 57.7 60.6 62.2 6.6 5.3 4.1 Vietnam 559.7 456.7-1060.7-76.6-39.6 296.2-652.8-14.6 9.5 5.5 4.5 2.9 Yemen 49.8 40.5-122.1 10.7 28.5 36.0-97.3 20.7 36.5 1.3 1.0 0.9 Zambia 79.4 39.2 25.5 28.5 36.0 39.2 25.5 28.5 36.0 3.3 1.6 1.6 Zimbabwe 98.6 82.3-79.5-107.3-105.1 61.3-33.7-54.4-52.7 5.2 4.3 3.

330、2 Source:IMF staff calculations using CPAT.Note:The terms country and“economy”do not in all cases refer to a territorial entity that is a state as understood by international law and practice.The terms also cover some territorial entities that are not states.GHG=greenhouse gas;MtCOe=million tonnes o

331、f CO equivalent;tCO=tonnes of CO International Monetary Fund.Not for Redistribution IMF|Staff Climate Note 29 Annex 4.Illustrative Temperature-Aligned Targets by Country(2035)Annex Table 4.1 Illustrative Emissions Targets Aligned with 1.5C and 2C in 2035 Country Baseline GHG Emissions in 2035,MtCO2e

332、 Illustrative 2C-Aligned Target in 2035,MtCO2e Percent Cut versus(negative=increase)Illustrative 1.5C-Aligned Target in 2035,MtCO2e Percent Cut versus(negative=increase)Per capita GHG Emissions in 2035,tCO2/Person 1990 2005 2010 1990 2005 2010 Baseline Illustrative 2C Illustrative 1.5C Afghanistan 2

333、9.4 29.1-155.4-58.8 4.1 17.7-55.6 3.2 41.5 0.5 0.5 0.3 Albania 7.7 5.6 52.6 19.8 20.6 2.7 76.6 60.5 60.9 2.8 2.0 1.0 Algeria 283.4 199.8-36.3-7.4 3.4 112.0 23.5 39.8 45.8 5.4 3.8 2.2 Angola 113.5 87.2-44.3 30.0 33.4 53.9 10.8 56.8 58.9 2.2 1.7 1.1 Argentina 416.5 268.4 13.5 39.3 39.5 132.9 57.2 70.0 70.0 8.5 5.5 2.7 Armenia 9.4 6.7 72.5 11.1 7.1 3.4 86.0 54.8 52.8 3.4 2.5 1.3 Australia 473.7 224.0