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1、DocumentationGlobal Energy and Climate Model DocumentationGlobal Energy and Climate Model The IEA examines the full spectrum of energy issues including oil,gas and coal supply and demand,renewable energy technologies,electricity markets,energy efficiency,access to energy,demand side management and m
2、uch more.Through its work,the IEA advocates policies that will enhance the reliability,affordability and sustainability of energy in its 31 member countries,11 association countries and beyond.Please note that this publication is subject to specific restrictions that limit its use and distribution.T
3、he terms and conditions are available online at www.iea.org/t&c/This publication and any map included herein are without prejudice to the status of or sovereignty over any territory,to the delimitation of international frontiers and boundaries and to the name of any territory,city or area.Source:IEA
4、.International Energy Agency Website:www.iea.orgIEA member countries:Australia Austria Belgium CanadaCzech Republic Denmark Estonia Finland France Germany Greece Hungary Ireland ItalyJapanKorea Lithuania Luxembourg Mexico Netherlands New Zealand Norway Poland Portugal Slovak Republic Spain Sweden Sw
5、itzerland Republic of TrkiyeUnited Kingdom United StatesThe European Commission also participates in the work of the IEAIEA association countries:INTERNATIONAL ENERGYAGENCYArgentinaBrazilChinaEgyptIndiaIndonesiaMoroccoSingaporeSouth AfricaThailandUkraineIEA.CC BY 4.0.Table of Contents 1 Table of Con
6、tents 1 Overview of model and scenarios.5 1.1 GEC Model scenarios.6 1.2 Selected developments in 2022.10 1.3 GEC Model overview.12 2 Cross-cutting inputs and assumptions.17 2.1 Population assumptions.17 2.2 Macroeconomic assumptions.18 2.3 Prices.19 2.4 Policies.22 2.5 Techno-economic inputs.23 3 En
7、d-use sectors.25 3.1 Industry sector.25 3.2 Transport sector.30 3.3 Buildings sector.39 3.4 Hourly electricity demand and demand-side response.42 4 Electricity generation and heat production.45 4.1 Electricity generation.45 4.2 Value-adjusted Levelized Cost of Electricity.50 4.3 Electricity transmis
8、sion and distribution networks.53 4.4 Hourly model.56 4.5 Mini-and off-grid power systems.57 4.6 Renewables and combined heat and power modules.57 4.7 Hydrogen and ammonia in electricity generation.59 4.8 Utility-scale battery storage.60 5 Other energy transformation.61 5.1 Oil refining and trade.61
9、 5.2 Coal-to-liquids,Gas-to-liquids,Coal-to-gas.62 5.3 Hydrogen production and supply.62 5.4 Biofuel production.65 6 Energy supply.69 6.1 Oil.69 6.2 Natural gas.73 6.3 Coal.74 6.4 Bioenergy.75 2 International Energy Agency|Global Energy and Climate Model Documentation 7 Critical minerals.79 7.1 Dema
10、nd.80 7.2 Supply requirements.80 8 Emissions.81 8.1 CO2 emissions.81 8.2 Non-CO2 greenhouse gases.81 8.3 Air pollution.82 8.4 Global temperature impacts.82 8.5 Oil and gas methane emissions model.82 9 Investment.89 9.1 Investment in fuel supply and the power sector.89 9.2 Demand-side investments.91
11、9.3 Financing for investments.92 9.4 Emissions performance of investments.93 10 Energy and CO2 decomposition.95 10.1 Methodology.96 11 Energy access.97 11.1 Defining modern energy access.97 11.2 Outlook for modern energy access.98 12 Employment.99 12.1 Definition and scope of employment.99 12.2 Esti
12、mating current employment.100 12.3 Outlook for employment.101 13 Assessing government spending on clean energy and energy affordability.103 13.1 Government spending policy identification and collection.103 13.2 Assessing the impact on overall clean energy investment.104 Annex A:Terminology.107 Defin
13、itions.107 Regional and country groupings.114 Acronyms.118 Annex B:References.121 Table of Contents 3 List of figures Figure 1.1 Global Energy and Climate Model Overview 13 Figure 2.1 Components of retail electricity end-use prices 21 Figure 3.1 General structure of demand modules 25 Figure 3.2 Majo
14、r categories of technologies by end-use sub-sector in industry 26 Figure 3.3 Industry sector model internal module structure and key data flows 28 Figure 3.4 Structure of the transport sector 32 Figure 3.5 Illustration of scrappage curve and mileage decay by vehicle type 33 Figure 3.6 The role of pa
15、ssenger-LDV cost model 34 Figure 3.7 Illustration of an efficiency cost curve for road freight 35 Figure 3.8 Refuelling infrastructure cost curve(illustrative)36 Figure 3.9 Structure of the buildings sector 39 Figure 3.10 Major categories of technologies by end-use subsector in buildings 41 Figure 3
16、.11 Illustrative load curves by sector for a weekday in February in the European Union compared to the observed load curve by ENTSO-E for 2014 43 Figure 4.1 Structure of the power generation module 45 Figure 4.2 Load duration curve showing the four demand segments 47 Figure 4.3 Example merit order a
17、nd its intersection with demand in the power generation module 48 Figure 4.4 Example electricity demand and residual load 49 Figure 4.5 Exemplary electricity demand and residual load 50 Figure 4.6 Moving beyond the LCOE,to the value-adjusted LCOE 51 Figure 4.7 Electricity network expansion per unit
18、of electricity demand growth by GDP per capita 54 Figure 5.1 Schematic of refining and international trade module 61 Figure 5.2 Schematic of merchant hydrogen supply module 63 Figure 6.1 Structure of the oil supply module 71 Figure 6.2 Evolution of production of currently producing conventional oil
19、fields from a field-by-field database and from the GEC Model 73 Figure 6.3 Schematic of biomass supply potentials 75 Figure A.1 GEC Model regional groupings 115 List of tables Table 1.1 Definitions and objectives of the GEC Model 2022 scenarios 6 Table 2.1 Population assumptions by region 17 Table 2
20、.2 Real GDP average growth assumptions by region and scenario 18 Table 2.3 Fossil fuel prices by scenario 19 Table 2.4 CO2 prices for electricity,industry and energy production in selected regions by scenario 20 Table 2.5 Capital costs for selected technologies by scenario 24 Table 6.1 Remaining tec
21、hnically recoverable fossil fuel resources,end-2021 74 Table 7.1 Critical minerals in scope 79 Table 8.1 Categories of emission sources and emissions intensities in the United States 83 Table 8.2 Scaling factors applied to the United States emission intensities 83 Table 8.3 Equipment-specific emissi
22、ons sources used in the marginal abatement cost curves 84 Table 8.4 Abatement options for methane emissions from oil and gas operations 85 Table 9.1 Sub-sectors and assets included in fuel supply investment 90 Table 9.2 Sub-sectors and assets included in power sector investment 91 Table 9.3 Sub-sect
23、ors and assets included in end-use energy investment 92 4 International Energy Agency|Global Energy and Climate Model Documentation List of boxes Box 1.1 An integrated approach to energy and sustainable development in the Net Zero Emissions by 2050 Scenario 9 Box 4.1 Long-term potential of renewable
24、s 58 Box 6.1 GEC Model differences in methodology compared with the Medium-Term Oil Market Report 70 Box 6.2 Methodology to account for production decline in oil and gas fields 72 Section 1|Overview of model and scenarios 5 Section 1 1 Overview of model and scenarios Since 1993,the IEA has provided
25、medium-to long-term energy projections using a continually-evolving set of detailed,world-leading modelling tools.First,the World Energy Model(WEM)a large-scale simulation model designed to replicate how energy markets function was developed.A decade later,the Energy Technology Perspectives(ETP)mode
26、l a technology-rich bottom-up model was developed,for use in parallel to the WEM.In 2021,the IEA adopted for the first time a new hybrid modelling approach relying on the strengths of both models to develop the worlds first comprehensive study of how to transition to an energy system at net zero CO2
27、 emissions by 2050.Since then,the IEA has worked to develop a new integrated modelling framework:IEAs Global Energy and Climate(GEC)Model.As of 2022,this model is the principal tool used to generate detailed sector-by-sector and region-by-region long-term scenarios across IEAs publications.The GEC M
28、odel brings together the modelling capabilities of the WEM and ETP models.The result is a large-scale bottom-up partial-optimisation modelling framework allowing for a unique set of analytical capacities in energy markets,technology trends,policy strategies and investments across the energy sector t
29、hat would be critical to achieve climate goals.IEAs GEC Model covers 26 regions individually that can be aggregated to world-level results and all sectors across the energy system with dedicated bottom-up modelling for:Final energy demand,covering industry,transport,buildings,agriculture and other n
30、on-energy use.This is driven by detailed modelling of energy service and material demand.Energy transformation,including electricity generation and heat production,refineries,the production of biofuels,hydrogen and hydrogen-derived fuels and other energy-related processes,as well as related transmis
31、sion and distribution systems,storage and trade.Energy supply,including fossil fuels exploration,extraction and trade,and availability of renewable energy resources.The GEC Model is a very data-intensive model covering the whole global energy system.Much of the data on energy supply,transformation a
32、nd demand,as well as energy prices is obtained from the IEAs own databases of energy and economic statistics(http:/www.iea.org/statistics)and through collaboration with other institutions.It also draws data from a wide range of external sources which are indicated in the relevant sections of this do
33、cument.The development of the GEC Model benefited from expert review within the IEA and beyond,and the IEA continues to work closely with colleagues in the international modelling community.The GEC Model is designed to analyse a diverse range of aspects of the energy system,including:Global and regi
34、onal energy prospects:these include trends in demand,supply availability and constraints,international trade and energy balances by sector and by fuel in the projection horizon.Environmental impact of energy use:this includes CO2 emissions from fuel combustion,process emissions and from flaring,meth
35、ane emissions from the oil and gas sector and coal mining,CH4 and N2O emissions from final energy demand and energy transformation local air pollutants,and temperature outcome.Effects of policy actions and technological changes:scenarios analyse the impact of a range of policy actions and technologi
36、cal developments on energy demand,supply,trade,investments and emissions.Investment in the energy sector:this includes investment requirements in the fuel supply chain to satisfy projected energy demand and demand-side investment requirements.Modern energy access assessments:these include trends in
37、access to electricity and clean cooking facilities,and the additional energy demand,investments and CO2 emissions due to increased energy access.Energy employment:this includes the impact of the scenarios on employment in various energy sectors 6 International Energy Agency|Global Energy and Climate
38、 Model Documentation 1.1 GEC Model scenarios The IEA medium to long-term outlook publications the World Energy Outlook(WEO)and the Energy Technology Perspectives(ETP)-use a scenario approach to examine future energy trends relying on the GEC Model.The GEC Model is used to explore various scenarios,e
39、ach of which is built on a different set of underlying assumptions about how the energy system might respond to the current global energy crisis and evolve thereafter.By comparing them,the reader is able to assess what drives the various outcomes,and the opportunities and pitfalls that lie along the
40、 way.These scenarios are not predictions GEC Model scenarios do not contain a single view about what the long-term future might hold.Instead,what the scenarios seek to do is to enable readers to compare different possible versions of the future and the levers and actions that produce them,with the a
41、im of stimulating insights about the future of global energy.The WEO-2022 and ETP-2023 based on the integrated GEC modelling cycle explore three scenarios,all of which are fully updated to include the latest energy market and cost data.The Net Zero Emissions by 2050 Scenario(NZE Scenario)is normativ
42、e,in that it is designed to achieve specific outcomes an emissions trajectory consistent with keeping the temperature rise in 2100 below 1.5 C(with a 50%probability),universal access to modern energy services and major improvements in air quality and shows a pathway to reach it.The Announced Pledges
43、 Scenario(APS),and the Stated Policies Scenario(STEPS)are exploratory,in that they define a set of starting conditions,such as policies and targets,and then see where they lead based on model representations of energy systems,including market dynamics and technological progress.The 2022 GEC modellin
44、g cycle does not include the Sustainable Development Scenario(SDS),which is another normative scenario used in previous editions to model a“well below 2 C”pathway as well as the achievement of other sustainable development goals.The APS outcomes are close,in some respects,to those in the SDS,in part
45、icular in terms of the temperature outcome.But they are the product of a different modelling approach and so as long as policy ambition does not fully capture all SDS outcomes,the APS falls short of achieving those.Table 1.1 Definitions and objectives of the GEC Model 2022 scenarios Net Zero Emissio
46、ns by 2050 Scenario Announced Pledges Scenario Stated Policies Scenario Definitions A scenario which sets out a pathway for the global energy sector to achieve net zero CO2 emissions by 2050.It does not rely on emissions reductions from outside the energy sector to achieve its goals.Universal access
47、 to electricity and clean cooking are achieved by 2030.A scenario which assumes that all climate commitments made by governments around the world,including Nationally Determined Contributions(NDCs)and longer-term net zero targets,as well as targets for access to electricity and clean cooking,will be
48、 met in full and on time.A scenario which reflects current policy settings based on a sector-by-sector and country by country assessment of the specific policies that are in place,as well as those that have been announced by governments around the world.Objectives To show what is needed across the m
49、ain sectors by various actors,and by when,for the world to achieve net zero energy related and industrial process CO2 emissions by 2050 while meeting other energy-related sustainable development goals such as universal energy access.To show how close do current pledges get the world towards the targ
50、et of limiting global warming to 1.5 C,it highlights the“ambition gap”that needs to be closed to achieve the goals agreed at Paris in 2015.It also shows the gap between current targets and achieving universal energy access.To provide a benchmark to assess the potential achievements(and limitations)o
51、f recent developments in energy and climate policy.Section 1|Overview of model and scenarios 7 The scenarios highlight the importance of government policies in determining the future of the global energy system:decisions made by governments are the main differentiating factor explaining the variatio
52、ns in outcomes across our scenarios.However,we also take into account other elements and influences,notably the economic and demographic context,technology costs and learning,energy prices and affordability,corporate sustainability commitments,and social and behavioural factors.However,while the evo
53、lving costs of known technologies are modelled in detail,we do not try and anticipate technology breakthroughs(e.g.,nuclear fusion).An inventory of the key policy assumptions available along with all the underlying data on population,economic growth,resources,technology costs and fossil fuel prices
54、are available in the Macro Drivers and Techno-economic inputs pages.For the first time,the projections were generated by a unified model that integrates the strengths the previous World Energy Model(WEM)and the Energy Technology Perspectives(ETP)model.Combining the detailed features of the two previ
55、ous models allows us to prepare a unique set of insights on energy markets,investment,technologies and the policies that would be needed for the clean energy transition.Net Zero Emissions by 2050 Scenario The Net Zero Emissions by 2050 Scenario(NZE)is a normative IEA scenario that shows a pathway fo
56、r the global energy sector to achieve net zero CO2 emissions by 2050,with advanced economies reaching net zero emissions in advance of others.This scenario also meets key energy-related United Nations Sustainable Development Goals(SDGs),in particular by achieving universal energy access by 2030 and
57、major improvements in air quality.It is consistent with limiting the global temperature rise to 1.5 C with no or limited temperature overshoot(with a 50%probability),in line with reductions assessed in the IPCC in its Sixth Assessment Report.There are many possible paths to achieve net zero CO2 emis
58、sions globally by 2050 and many uncertainties that could affect any of them;the NZE Scenario is therefore a path,not the path to net zero emissions.Much depends,for example,on the pace of innovation in new and emerging technologies,the extent to which citizens are able or willing to change behaviour
59、,the availability of sustainable bioenergy and the extent and effectiveness of international collaboration.The Net Zero Emissions by 2050 Scenario is built on the following principles:The uptake of all the available technologies and emissions reduction options is dictated by costs,technology maturit
60、y,policy preferences,and market and country conditions.All countries co-operate towards achieving net zero emissions worldwide.This involves all countries participating in efforts to meet the net zero goal,working together in an effective and mutually beneficial way,and recognising the different sta
61、ges of economic development of countries and regions,and the importance of ensuring a just transition.An orderly transition across the energy sector.This includes ensuring the security of fuel and electricity supplies at all times,minimising stranded assets where possible and aiming to avoid volatil
62、ity in energy markets.In recent years,the energy sector was responsible for around three-quarters of global greenhouse gas(GHG)emissions.Achieving net zero energy-related and industrial process CO2 emissions by 2050 in the NZE Scenario does not rely on action in areas other than the energy sector,bu
63、t limiting climate change does require such action.We therefore additionally examine the reductions in CO2 emissions from land use that would be commensurate with the transformation of the energy sector in the NZE Scenario,working in cooperation with the International Institute for Applied Systems A
64、nalysis(IIASA).8 International Energy Agency|Global Energy and Climate Model Documentation Announced Pledges Scenario The Announced Pledges Scenario introduced in 2021 aims to show to what extent the announced ambitions and targets,including the most recent ones,are on the path to deliver emissions
65、reductions required to achieve net zero emissions by 2050.It includes all recent major national announcements as of September 2022 for 2030 targets and longer-term net zero and other pledges,regardless of whether these have been anchored in implementing legislation or in updated NDCs.In the APS,coun
66、tries fully implement their national targets to 2030 and 2050,and the outlook for exporters of fossil fuels and low emissions fuels like hydrogen is shaped by what full implementation means for global demand.For the first time,the APS assumes this year that all country-level access to electricity an
67、d clean cooking targets are achieved on time and in full.The way these pledges are assumed to be implemented in the APS has important implications for the energy system.A net zero pledge for all GHG emissions does not necessarily mean that CO2 emissions from the energy sector need to reach net zero.
68、For example,a countrys net zero plans may envisage some remaining energy-related emissions are offset by the absorption of emissions from forestry or land use.It is not possible to know exactly how net zero pledges will be implemented,but the design of the APS,particularly with respect to the detail
69、s of the energy system pathway,has been informed by the pathways that a number of national bodies have developed to support net zero pledges.Policies in countries that have not yet made a net zero pledge are assumed to be the same as in the STEPS.Non-policy assumptions,including population and econo
70、mic growth,are the same as in the STEPS.Stated Policies Scenario The STEPS provides a more conservative benchmark for the future,because it does not take it for granted that governments will reach all announced goals.Instead,it takes a more granular,sector-by-sector look at what has actually been pu
71、t in place to reach these and other energy-related objectives,taking account not just of existing policies and measures but also of those that are under development.The STEPS explores where the energy system might go without a major additional steer from policy makers.As with the APS,it is not desig
72、ned to achieve a particular outcome.The policies assessed in the Stated Policies Scenario cover a broad spectrum.These include Nationally Determined Contributions under the Paris Agreement,but much more besides.In practice,the bottom-up modelling effort in this scenario requires a lot of detail at t
73、he sectoral level,including pricing policies,efficiency standards and schemes,electrification programmes as well as specific infrastructure projects.The scenario takes into account the policies and implementing measures affecting energy markets that had been adopted as of end of September 2022,toget
74、her with relevant policy proposals,even though specific measures needed to put them into effect have yet to be fully developed.The sorts of announcements made by governments include some far-reaching targets,including aspirations to achieve full energy access in a few years,to reform pricing regimes
75、 and,more recently,to reach net zero emissions in some countries and sectors.As with all the policies considered in the Stated Policies Scenario,these ambitions are not automatically incorporated into the scenario:full implementation cannot be taken for granted,so the prospects and timing for their
76、realisation are based upon our assessment of countries relevant regulatory,market,infrastructure and financial circumstances.Where policies are time-limited,they are generally assumed to be replaced by measures of similar intensity,but we do not assume future strengthening or weakening of future pol
77、icy action,except where there already is specific evidence to the contrary.Section 1|Overview of model and scenarios 9 The STEPS shows that in aggregate,current country commitments are enough to make a significant difference.However,there is still a large gap between the projections in the STEPS and
78、 a trajectory of the other two scenarios.Box 1.1 An integrated approach to energy and sustainable development in the Net Zero Emissions by 2050 Scenario The Net Zero Emissions by 2050 Scenario(NZE Scenario)integrates three key objectives of the UN 2030 Agenda for Sustainable Development:universal ac
79、cess to modern energy services by 2030(embodied in SDG 7),reducing health impacts of air pollution(SDG 3.9),and action to tackle climate change(SDG 13).As a first step,we use the GEC Model to assess how the energy sector would need to change to deliver universal access to modern energy services by 2
80、030.To analyse electricity access,we combine cost-optimisation with new geospatial analysis that takes into account current and planned transmission lines,population density,resource availability and fuel costs.Second,we consider ambient and household air pollution and climate goals.The policies nec
81、essary to achieve the multiple SDGs covered in the NZE Scenario are often complementary.For example,energy efficiency and renewable energy significantly reduce local air pollution,particularly in cities,while access to clean cooking facilitated by liquefied petroleum gas also reduces household air p
82、ollution and overall greenhouse gas emissions by reducing methane emissions from incomplete combustion of biomass as well as by reducing deforestation.Trade-offs can also exist,for example between electric vehicles reducing local air pollution from traffic,but at the same time increasing overall CO2
83、 emissions if there is not a parallel effort to decarbonise the power sector.Ultimately,the balance of potential synergies or trade-offs depends on the route chosen to achieve the energy transition,making an integrated,whole-system approach to scenario building essential.The emphasis of the NZE Scen
84、ario is on technologies with short project lead times in the power sector in particular,such as renewables,while the longer-term nature of climate change allows for other technology choices.Modern uses of biomass as a decarbonisation option is also less relevant in the NZE than in a single-objective
85、 climate scenario.This is because biomass is a combustible fuel,requiring post-combustion control to limit air pollutant emissions and depending on the region in question-making it more costly than alternatives.Since its launch in 2021,the NZE Scenario,also looks at the implications for the energy s
86、ector for achieving several of the targets under United Nations Sustainable Development Goal 6(clean water and sanitation for all)and what policymakers need to do to hit multiple goals with an integrated and coherent policy approach.In order to reflect in our modelling the announcements made by seve
87、ral countries to achieve carbon neutrality by 2050 and also allows us to model the potential for new technologies(such as hydrogen and renewable gases)to be deployed at scale,the time horizon of the model is 2050.The interpretation of the climate target embodied in the NZE Scenario also changes over
88、 time,as a consequence of both ongoing emissions of CO2 as well as developments in climate science(refer to the 8 Emissions section for more details).Despite the fundamental changes across all sectors the NZE scenario still ensures an orderly transition.This includes ensuring the security of fuel an
89、d electricity supplies at all times,minimising stranded assets where possible and aiming to avoid volatility in energy markets.10 International Energy Agency|Global Energy and Climate Model Documentation 1.2 Selected developments in 2022 In addition to the overall merge process of the previous WEM a
90、nd ETP models and their data pipelines,sectoral and topic-specific developments this year,undertaken as part of the GEC Model development,include the following:Final energy consumption Behavioural analysis Several new specific behavioural changes have been modelled in detail,including measures to ma
91、nage growth in aviation demand,such as frequent flyer levies,and the impact of measures to reduce the sales and use of SUVs.In addition,the modelling of the potential for ride-sharing to impact demand was covered in detail.The regional granularity of modelling has been improved to reflect difference
92、s in the potential scope,scale and speed of adoption of behavioural changes.Inputs into this modelling include the ability of existing infrastructure to support such changes and differences in geography,climate,urbanisation,social norms and cultural values.Buildings module The buildings module under
93、went significant updates for the 2022 modelling cycle,the module now fully combines the strengths of the pre-existing WEO and ETP modelling frameworks,allowing for more detailed representation of the stock of buildings and technologies.The new merged framework notably includes:A stock accounting mod
94、el used to describe the evolution of buildings,tracking the vintage of each building,its energy service demand,energy performance,lifetime and whether the building has undergone a retrofit to improve its energy efficiency.Upon construction,buildings are classified into three categories:non-compliant
95、 to building energy codes,compliant to building energy codes and zero-carbon-ready building.Constructed buildings can then be retrofit to improve energy efficiency,and are categorised as:retrofit to compliant,or retrofit to zero-carbon-ready.Improved representation of the building stock allows for b
96、etter representation of the impact of changes to building energy codes and other policy actions,the evolution of building floor area by vintage,the gains that can be achieved by retrofitting buildings,including the ability to target retrofits toward the least efficient buildings.Building upon local
97、climate data,population density mapping and regional estimates of energy demand by end-use and sector provide a basis for distributing heating and cooling demand at the local level and assessing clean technology deployment strategies.For instance,the assessment of heat and cold demand densities at t
98、he city or district level is key to making sound judgement calls on the decarbonisation potential of district energy systems(together with other variables such as the share of variable renewables in the electricity mix and the availability of waste heat sources).Local climate and population data are
99、 also used to derive heat pump energy performance.Industry module The industry module went through a complete overhaul to take the best of both WEO and ETP frameworks.The new module enables a precise representation of heavy industries(chemicals,iron and steel and cement)and light industries(construc
100、tion,food,machinery equipment,mining and quarrying,textile and leather,and wood and wood products),industrial capacity projections and related lock-in emissions analysis.The previous TIMES models for heavy industry are retained as satellite modules that can be used for exploratory analysis in order
101、to inform the GEC module parameters,for example testing the impact of a particular shock,new technology or other important change in the system.Section 1|Overview of model and scenarios 11 Transport module The transport module integrated the framework of WEO and ETP modules,to allow for improved sec
102、toral representation across all modes:road,aviation,navigation and rail.The integrated model utilises mainly Vensim,as well as dedicated modules developed in Java and R.For road,scrappage functions are extended across all vehicle types to improve sectoral representation,and dynamic scrappage functio
103、n is implemented based on a correlation of average lifetime with economic growth.Mileage curves have been updated to take into account that old vehicles are driven less.Aviation modelling has integrated main features of the Aviation Integrated Modelling(AIM)tool developed by University College Londo
104、n(UCL)including:Operational and technical potential for energy intensity improvements based on iterative cost minimisation modelling across different airframe-propulsion systems and stock accounting.Electricity generation The structure of the grids component of the module has been significantly expa
105、nded to include increased detail on line and cable types.This includes by voltage level,overhead line or underground cable,and AC or DC lines and cables.In addition,cost inputs for both new and replacement lines have increased in granularity by line type as well as by region.Finally,the impacts of i
106、ntegrating high shares of renewables have been further developed in terms of transmission grid reinforcements and grid forming requirements.Energy supply Against the backdrop of an increasingly fragmented world,the oil and gas supply modules account this year for a wide range of financial risks(e.g.
107、,geopolitics,rule of law,regulatory oversight).This improves the representation of decisions made by companies looking to invest in oil and natural gas fields in different countries.Other transformation Hydrogen module The temporal resolution of the hydrogen module has been enhanced by introducing s
108、ub-annual time slices to capture the variability in dedicated renewable electricity generation(solar PV,onshore wind,offshore wind)for the production of hydrogen and hydrogen-based fuels and to enable the modelling of hydrogen storage.A tool to analyse the regional hydrogen infrastructure needs and
109、related investments for pipelines,ships,port terminals and storage has been developed.Biofuel production module The modelling of trade in liquid biofuels between the 26 GEC Model regions has been expanded by adding biojet kerosene to the already existing trade modelling for ethanol and biodiesel.Cri
110、tical minerals The critical minerals module has been updated with a more granular technology representation(e.g.,battery chemistry,grid type and voltage levels,types of EV motors)and mineral intensity inputs,while also being fully linked to existing modules of the GEC model(transport,electricity gen
111、eration and hydrogen transformation).12 International Energy Agency|Global Energy and Climate Model Documentation Energy access In previous years,energy access was assessed in two different scenarios:STEPS looking at the impacts of access policies(for electricity and clean cooking),and the achieveme
112、nt of SDG7(universal access to electricity and clean cooking).This edition of APS not only include all current announced energy and climate commitments but also electricity and clean cooking countries targets.The APS assumes that all these targets are implemented in full and on time.Employment Curre
113、nt employment now reflects the labour required for future projects in the pipeline.Value chain segments have been aligned with the International Standard Industrial Classification(revision 4).The model now incorporates parameters estimating labour productivity improvements.Global trade is reflected
114、by a new calculation reflecting the regional distributions of manufacturing capacity for key clean energy technologies.The granularity for fossil fuel supply and power generation has been improved.Assessing government spending on clean energy and energy affordability The IEA has extended the scope o
115、f its government spending monitoring to cover both clean energy investment support and energy affordability for consumers in response to the energy crisis.Mobilisation effects on private investment have also been updated since last year.1.3 GEC Model overview Modelling methodology The GEC Model is a
116、 bottom-up partial-optimisation model covering energy demand,energy transformation and energy supply(Figure 1.1).The model uses a partial equilibrium approach,integrating price sensitivities.It shows the transformation of primary energy along energy supply chains to meet energy service demand,the fi
117、nal energy consumed by the end-user.The various supply,transformation and demand modules of the model are dynamically soft-linked:consumption of electricity,hydrogen and hydrogen-related fuels,biofuels,oil products,coal and natural gas in the end use sector model drives the transformation and supply
118、 modules,which in turn feed energy prices back to the demand module in an iterative process.In addition,energy system CO2,CH4 and N2O emissions are assessed.The model contains a number of additional analysis features evaluating further system implications such as investments,critical minerals,employ
119、ment,temperature outcomes,land-use,and air pollution(see more details below).The main exogenous drivers of the scenarios are economic growth,demographics and technological developments.Energy service demand drivers,such as steel demand in industry or number of appliances within households,are estima
120、ted econometrically based on historical data and on the socioeconomic drivers.Interactions between energy service demand drivers are also accounted for,such as the influence of the number of vehicles sales on materials demand.This service demand is met by existing and new technologies.All sector mod
121、ules(see subsequent sections for more details on these modules)base their projections on the existing stock of energy infrastructure(e.g.,the number of vehicles in transport,production capacity in industry,floor space area in buildings),through detailed stock-accounting frameworks.To assess how the
122、service demand is met in the various scenarios,the model includes a wide range of fuels and technologies(existing and additions).This includes careful accounting of the current energy performance of different technologies and processes,and potential to improve efficiency.Section 1|Overview of model
123、and scenarios 13 Figure 1.1 Global Energy and Climate Model Overview IEA.CC BY 4.0.The sectoral and cross-sectoral energy and emission balances are calculated based on the final energy end uses the service demand by determining first the final energy demand needed to serve it,then the required trans
124、formations to convert primary energy into the required fuels,and finally the primary energy needs.This is based on a partial equilibrium approach using for some elements a partial optimisation model,within which specific costs play an important role in determining the share of fuels and technologies
125、 to satisfy the energy service demand.In different parts of the model,Logit and Weibull functions are used to determine the share of 14 International Energy Agency|Global Energy and Climate Model Documentation technologies based upon their specific costs.This includes investment costs,operating and
126、maintenance costs,fuel costs and in some cases costs for emitting CO2.In certain sectors,such as hydrogen production,specially designed and linked optimisation modules are used.While the model aims to identify an economical way for society to reach the desired scenario outcomes,the results do not ne
127、cessarily reflect the least-cost way of doing so.This is because an unconstrained least-cost approach may fail to take account of all the issues that need to be considered in practice,such as market failures,political or individual preferences,feasible ramp-up rates,capital constraints and public ac
128、ceptance.Instead,the analysis pursues a portfolio of fuels and technologies within a framework of cost minimisation,considering technical,economic and regulatory constraints.This approach,tailored to each sector and incorporating extensive expert consultation,enables the model to reflect as accurate
129、ly as possible the realities of different sectors.It also offers a hedge against the real risks associated with the pathways:if one technology or fuel fails to fulfil its expected potential,it can more easily be compensated by another if its share in the overall energy mix is low.All fuels and techn
130、ologies included in the model are either already commercially available or at a relatively advanced stage of development,so that they have at least reached a prototype size from which enough information about expected performance and costs at scale can be derived.Costs for new clean fuels and techno
131、logies are expected to fall over time and informed in many cases by learning curve approaches,helping to make a net zero future economically feasible.Besides this main feedback loop between supply and demand,there are also linkages between the transformation and supply modules.Further linkages betwe
132、en energy sectors are captured in the model,e.g.,material flows or biogenic or atmospheric CO2 via Direct Air Capture for synthetic fuel production.Primary energy needs and availability interact with the supply module.Complete energy balances are compiled at a regional level and the CO2 emissions of
133、 each region are then calculated using derived CO2 factors,taking into account reductions from CO2 removal technologies.The GEC Model is implemented in the simulation software Vensim(),but makes use of a wider range of software tools,including TIMES(https:/iea-etsap.org/index.php/etsap-tools/model-g
134、enerators/times).Data inputs The GEC Model is a data-intensive model covering the whole global energy system.Much of the data to calibrate to historical energy supply,transformation and demand,as well as energy prices,is obtained from the IEAs own databases of energy and economic data.Additional dat
135、a from a wide range of often sector-specific external sources is also used in particular to establish historic size and performance of energy-consuming stocks.The model is each year recalibrated to the latest available data.The formal base year is currently 2020,as this is the last year for which a
136、complete picture of energy demand and production is in place.However,we have used more recent data wherever available,and we include 2021 and 2022 estimates for energy production and demand.Estimates are based on updates of the Global Energy Review reports which relies on a number of sources,includi
137、ng the latest monthly data submissions to the IEA Energy Data Centre,other statistical releases from national administrations,and recent market data from the IEA Market Report Series that cover coal,oil,natural gas,renewables and electricity.For a summary of selected key data inputs including macro
138、drivers such as population,economic developments and prices as well as techno-economic inputs such as fossil fuel resources or technology costs please view the Global Energy and Climate Model key input dataset(https:/www.iea.org/data-and-statistics/data-product/global-energy-and-climate-model-2022-k
139、ey-input-data).Section 1|Overview of model and scenarios 15 Regional coverage and time horizon The GEC Model covers the energy developments in the full global energy system up to 2050,with the capacity to extend beyond 2050 for some regions.Simulations are carried out on an annual basis.The current
140、version of the model provides results for 26 regions of the globe,of which 12 are individual countries.Several supply components of the model have further regional disaggregation:the oil and gas supply model has 113 regions and the coal supply model 32 regions.Capabilities and features IEAs GEC Mode
141、l offers unparalleled scope and detail on the energy system.Its raison dtre is evaluating energy supply and demand,as well as the environmental impacts of energy use and the impacts of policy and technology developments on the energy system.Through long-term scenario analysis,the model enables analy
142、sis of possible futures related to the following main areas:Global and regional energy trends:this includes assessment of energy demand,supply availability and constraints,international trade and energy balances by sector and by fuel.Environmental impact of energy use:CO2 emissions from fuel combust
143、ion are derived from the projections of energy consumption.CO2 process emissions are calculated based on the production of industrial materials and CH4 and N2O emissions are assessed for final energy demand as well as for energy transformation.Methane from oil and gas operations are assessed through
144、 bottom-up estimates and direct emissions measurements(see Methane Tracker).This allows to publish the CO2-equivalent emissions for the entire energy sector.Local air pollutants are also estimated linking the GEC Model with the GAINS model of the International Institute for Applied Systems Analysis(
145、IIASA)and the temperature outcomes of modelled scenarios are assessed.Policy and technology developments:alternative scenarios analyse the impact of a range of policy actions and technological developments on energy demand,supply,trade,investments and emissions.Additionally,the GEC Model has multipl
146、e detailed features that either underlying or build from analysis of the broader energy trends.These include the following:Technologies:Detailed techno-economic characterisation of clean energy technologies under development(either at prototype or demonstration stage)including different applications
147、 in heavy industries,long distance transport and carbon dioxide removal technologies among more than 800 hundred technologies covered.People-centred:Detailed modelling of behavioural changes,energy sector employment and energy affordability among other implications for citizens.Critical minerals:Com
148、prehensive analysis of projected demand and supply of critical minerals for the energy sectors transition.Infrastructure:Detailed modelling and analysis on enabling energy infrastructure development needs and strategies including:electricity systems,fossil fuels,hydrogen-related fuels distribution a
149、nd CO2 transport options.Variable renewables potential:Detailed geospatial analysis of variable renewables potentials across the globe and modelling of their impact of exploiting those for hydrogen production.Modern energy access:Comprehensive modelling of the implications and opportunities to provi
150、de energy access to all communities.This includes access to electricity and clean cooking facilities,and an evaluation of additional energy demand,investments and related greenhouse gas emissions.16 International Energy Agency|Global Energy and Climate Model Documentation Material efficiency:Granula
151、r modelling of strategies along supply chains to make more efficient use of materials like steel,cement,aluminium,plastics and fertilisers,and their resulting impact on materials demand.Investments:Detailed modelling of overall energy sector and clean energy investments by sub-sector and technology
152、areas,and comprehensive analysis on effective financing strategies.This includes investment requirements in fuel supply chains to satisfy projected energy demand and for demand-side technologies and measures(e.g.,energy efficiency,electrification).Government spending is also tracked.Decomposition:De
153、tailed mathematical framework to analyse systematically the specific contribution of different strategies to emissions or energy savings between scenarios and over time.Connections with the international energy modelling community The development of the GEC Model benefits from expert review within t
154、he IEA and beyond and the IEA works closely with colleagues in the global modelling community.For example,the IEA participates in and regularly hosts the International Energy Workshop,and the analysis for the Net Zero Emissions by 2050 Scenario was informed by discussions with modelling teams from a
155、cross the world,including from China,the United States,Japan,the United Kingdom,the European Union and the IPCC.The IEA also has a long-standing history of working with researchers and modellers around the world as part of its Technology Collaboration Programmes(TCP)network.The TCPs support the work
156、 of independent,international groups of experts that enable governments and industries from around the world to lead programmes and projects on a wide range of energy technologies and related issues.The Energy Technology Systems Analysis(ETSAP)TCP,established in 1977,is among the longest running TCP
157、s.Its mission is to support policy makers in improving the evidence base underpinning energy and environmental policy decisions through energy systems modelling tools and capability through a unique network of nearly 200 energy modelling teams from approximately seventy countries.The ETSAP TCP devel
158、ops,improves and makes available the TIMES energy systems modelling platform.IEAs GEC Model also interacts closely with other internationally recognised models:The IEA uses the Model for the Assessment of Greenhouse Gas Induced Climate Change(MAGICC),developed and maintained by ClimateResource and o
159、ften used by IPCC for key publications,to inform its analysis on the impact of different greenhouse gases budgets on the average global temperature rise.IEA modelling results are coupled with the Greenhouse Gas Air Pollution Interactions and Synergies(GAINS)model developed and maintained by Internat
160、ional Institute for Applied Systems Analysis(IIASA).This allows for detailed analysis on the impact on air pollution of different IEA scenarios.IEA results are coupled with the Global Biosphere Management Model(GLOBIOM)developed and maintained by IIASA to complement IEAs analysis on bioenergy suppli
161、es and effective use strategies.The Aviation Integrated Model(AIM)developed by University College London(UCL)forms the basis for our modelling of the aviation sector.IEA modelling results have been linked to the Global Integrated Monetary and Fiscal(GIMF)model of the International Monetary Fund(IMF)
162、to assess the impacts of changes in investment and spending on global GDP.The Open Source Spatial Electrification Tool(OnSSET),a GIS-based optimisation tool developed out of a collaboration among several organisation,is used to inform the IEAs energy access modelling.Section 2|Cross-cutting inputs a
163、nd assumptions 17 Section 2 2 Cross-cutting inputs and assumptions The Global Energy and Climate Model(GEC Model)uses macro drivers,techno-economic inputs and policies as input data to design and calculate the scenarios.Economic activity and population are the two fundamental drivers of demand for e
164、nergy services in GEC Model scenarios.Unless otherwise specified,these are kept constant across all scenarios as a means of providing a starting point for the analysis and facilitating the interpretation of the results.Energy prices are another important input.The projections consider the average re
165、tail prices of each fuel used in final uses,power generation and other transformation sectors.These end-use prices are derived from projected international prices of fossil fuels and subsidy/tax levels and vary by country.2.1 Population assumptions Table 2.1 Population assumptions by region Compound
166、 average annual growth rate Population (million)Urbanisation (Share of population)2000-21 2021-30 2021-50 2021 2030 2050 2021 2030 2050 North America 0.9%0.6%0.5%502 532 580 82%84%89%United States 0.8%0.5%0.4%335 352 381 83%85%89%Central and South America 1.1%0.7%0.5%523 559 601 81%83%88%Brazil 1.0%
167、0.5%0.2%214 224 229 87%89%92%Europe 0.3%0.0%-0.1%700 701 690 76%78%84%European Union 0.2%-0.1%-0.2%451 448 429 75%77%84%Africa 2.5%2.3%2.1%1 372 1 686 2 487 44%48%59%Middle East 2.1%1.5%1.1%252 289 348 73%76%81%Eurasia 0.4%0.3%0.2%237 244 253 65%67%73%Russia-0.1%-0.2%-0.2%144 142 134 75%77%83%Asia P
168、acific 1.0%0.6%0.4%4 250 4 496 4 734 50%55%65%China 0.5%0.2%-0.1%1 423 1 443 1 383 63%71%80%India 1.3%0.8%0.6%1 393 1 504 1 639 35%40%53%Japan-0.1%-0.5%-0.6%125 120 105 92%93%95%Southeast Asia 1.2%0.8%0.6%674 726 792 51%56%66%World 1.2%0.9%0.7%7 835 8 507 9 692 57%60%68%Source:UN DESA(2018,2019);Wor
169、ld Bank(2022a);IEA databases and analysis.Rates of population growth for each GEC Model region are based on the medium-fertility variant projections contained in the United Nations Population Division report(UN DESA,2019)1.In the 2022 GEC modelling cycle,population rises from 7.8 billion in 2021 to
170、more than 9.6 billion in 2050.Population growth slows over the projection period,in line with past trends:from 1.2%per year in 2000-2021 to 0.9%in 2021-2030,due in large part to falling global fertility rates as average incomes rise.1 The World Population Prospects 2022 from UN DESA was published at
171、 a time when the modelling was already well advanced for this cycle.18 International Energy Agency|Global Energy and Climate Model Documentation More than half of the increase in the global population to 2050 is in Africa,underlining the importance of this continent to the achievement of the worlds
172、sustainable development goals.India accounts for almost 15%of the growth and becomes the worlds most populous country in the near term as Chinas population growth stalls.Estimates of the rural/urban split for each GEC Model region have been taken from UN DESA(2018).This database provides the percent
173、age of population residing in urban areas by country with annual granularity over the projection horizon.By combining this data with the UN population projections an estimate of the rural/urban split may be calculated.In 2021,about 57%of the world population is estimated to be living in urban areas.
174、This is expected to rise to 68%by 2050.2.2 Macroeconomic assumptions Table 2.2 Real GDP average growth assumptions by region and scenario Compound average annual growth rate 2010-2021 2021-2030 2030-2050 2021-2050 North America 1.9%2.0%2.0%2.0%United States 2.0%2.0%2.0%2.0%Central and South America
175、0.9%2.4%2.4%2.4%Brazil 0.7%1.8%2.5%2.3%Europe 1.6%2.0%1.4%1.6%European Union 1.2%1.9%1.2%1.4%Africa 2.7%4.1%4.2%4.1%South Africa 1.1%1.6%2.8%2.4%Middle East 2.0%3.2%3.2%3.2%Eurasia 2.1%0.1%1.4%1.0%Russia 1.7%-1.1%0.7%0.1%Asia Pacific 4.9%4.7%3.1%3.6%China 6.8%4.7%2.8%3.4%India 5.5%7.2%4.4%5.2%Japan
176、0.5%0.9%0.6%0.7%Southeast Asia 4.1%5.0%3.3%3.8%World 2.9%3.3%2.6%2.8%Note:Calculated based on GDP expressed in year-2021 US dollars in purchasing power parity terms.Source:IEA analysis based on Oxford Economics(2022)and IMF(2022).Economic growth assumptions for the short to medium term are are broad
177、ly consistent with the latest assessments from the IMF and Oxford Economics.Over the long term,growth in each GEC Model region is assumed to converge to an annual long-term rate.This is dependent on demographic and productivity trends,macroeconomic conditions and the pace of technological change.In
178、GEC Model 2022 scenarios,the growth trajectory remains positive,but much less so than a year ago when global aggregate demand was experiencing near record growth in response to the removal of pandemic lockdowns and restrictions being eased in many countries.The global economy is assumed to grow by 2
179、.8%per year on average over the period to 2050,with large variations by country,by region and over time(Table 2.2).This growth is primarily driven by emerging market and developing economies.Over the near term,the growth trajectory includes the impact of Russias invasion of Ukraine and rising inflat
180、ion.There are,however,downside Section 2|Cross-cutting inputs and assumptions 19 risks for the outlook to 2030 resulting from higher interest rates,a mood of insecurity holding back investment decisions and spending on household durables,and uncertainty as to whether macroeconomic authorities are ab
181、le to contain inflation and avoid a price-wage spiral.The assumed rates of economic growth are held constant across the scenarios,which allows for a comparison of the effects of different energy and climate choices against a common backdrop.The way that economic growth plays through into energy dema
182、nd depends heavily on the structure of any given economy,the exposure and resilience to shocks,the balance between different types of industry,services and agriculture,and on policies in areas such as pricing and energy efficiency.2.3 Prices International fossil fuel prices Table 2.3 Fossil fuel pri
183、ces by scenario Net Zero Emissions by 2050 Announced Pledges Stated Policies Real terms(USD 2021)2010 2021 2030 2050 2030 2050 2030 2050 IEA crude oil(USD/barrel)96 69 35 24 64 60 82 95 Natural gas(USD/MBtu)United States 5.3 3.9 1.9 1.8 3.7 2.6 4.0 4.7 European Union 9.0 9.5 4.6 3.8 7.9 6.3 8.5 9.2
184、China 8.0 10.1 6.1 5.1 8.8 7.4 9.8 10.2 Japan 13.3 10.2 6.0 5.1 9.1 7.4 10.9 10.6 Steam coal(USD/tonne)United States 63 44 22 17 42 24 46 44 European Union 113 120 52 42 62 53 60 64 Japan 132 153 59 46 74 59 91 72 Coastal China 142 164 58 48 73 62 89 74 Notes:MBtu=million British thermal units.The I
185、EA crude oil price is a weighted average import price among IEA member countries.Natural gas prices are weighted averages expressed on a gross calorific-value basis.The US natural gas price reflects the wholesale price prevailing on the domestic market.The European Union and China natural gas prices
186、 reflect a balance of pipeline and LNG imports,while the Japan gas price solely reflects LNG imports.The LNG prices used are those at the customs border,prior to regasification.Steam coal prices are weighted averages adjusted to 6 000 kilocalories per kilogramme.The US steam coal price reflects mine
187、 mouth prices plus transport and handling costs.Coastal China steam coal price reflects a balance of imports and domestic sales,while the European Union and Japanese steam coal prices are solely for imports.Source:IEA GEC Model 2022.International prices for coal,natural gas and oil in the GEC Model
188、reflect the price levels that are needed to stimulate sufficient investment in supply to meet projected demand.They are one of the fundamental drivers for determining fossil fuel demand and supply projections in all sectors and are derived through iterative modelling.The supply modules calculate the
189、 production of coal,natural gas and oil that is stimulated under a given price trajectory,taking into account the costs of various supply options and the constraints on resources and production rates.If prices are too low to encourage sufficient production to cover global demand,the price level is i
190、ncreased and energy demand is recalculated.The new demand resulting from this iterative process is again fed back into the supply modules until a balance between demand and supply is reached for each projected year.20 International Energy Agency|Global Energy and Climate Model Documentation The pric
191、e trajectories do not attempt to represent the fluctuations and price cycles that characterise commodity markets in practice.The potential for volatility is ever present,especially in systems that are undergoing a necessary and profound transformation.Fossil fuel price paths vary across the scenario
192、s(Table 2.3).For example,in the Stated Policies Scenario,although policies are adopted to reduce the use of fossil fuels,demand is still high.That leads to higher prices than in the Announced Pledges Scenario and the Net Zero Emissions by 2050 Scenario,where the lower energy demand means that limita
193、tions on the production of various types of resources are less significant and there is less need to produce fossil fuels from resources higher up the supply cost curve.CO2 prices Table 2.4 CO2 prices for electricity,industry and energy production in selected regions by scenario USD(2021)per tonne o
194、f CO2 2030 2040 2050 Stated Policies Scenario Canada 54 62 77 Chile,Colombia 13 21 29 China 28 43 53 European Union 90 98 113 Korea 42 67 89 Announced Pledges Scenario Advanced economies with net zero emissions pledges1 135 175 200 Emerging market and developing economies with net zero emissions ple
195、dges 2 40 110 160 Other emerging market and developing economies -17 47 Net Zero Emissions by 2050 Scenario Advanced economies with net zero emissions pledges 140 205 250 Emerging market and developing economies with net zero emissions pledges 90 160 200 Other emerging market and developing economie
196、s 25 85 180 1 Includes all OECD countries except Mexico.2 Includes China,India,Indonesia,Brazil and South Africa.Note:The values are rounded.Source:IEA GEC Model 2022.CO2 price assumptions are one of the inputs into GEC Model as the pricing of CO2 emissions affects demand for energy by altering the
197、relative costs of using different fuels.There were 68 direct carbon pricing instruments existing as of May 2022:32 emissions trading systems and 38 carbon taxes on fuels according to their related emissions when combusted,covering more than 40 countries.Many others have schemes under development or
198、are considering to do so.The Stated Policies Scenario takes into consideration all existing or announced carbon pricing schemes,at national and sub-national level,covering electricity generation,industry,energy production sectors and end-use sectors,e.g.,aviation,road transport and buildings,where a
199、pplicable.In the Announced Pledges Scenario,higher CO2 prices are introduced across all regions with net zero emissions pledges.In addition,several developing economies are assumed to put in place schemes to limit CO2 emissions.All regional markets have access to offsets,which is expected to lead to
200、 a convergence of prices.No explicit pricing is assumed in sub-Saharan Africa(excluding South Africa),the Caspian region and Other Asia regions.Instead,these regions rely on direct policy interventions to drive decarbonisation in the APS.In the Net Zero Emissions by 2050 Scenario,CO2 prices cover al
201、l regions and rise rapidly across all advanced economies as well as in emerging economies with net zero Section 2|Cross-cutting inputs and assumptions 21 emissions pledges,including China,India,Indonesia,Brazil and South Africa.CO2 prices are lower,but nevertheless,rising in other emerging economies
202、 such as North Africa,Middle East,Russia and Southeast Asia.CO2 prices are lower in all other emerging market and developing economies,as it is assumed they pursue more direct policies to adapt and transform their energy systems(Table 2.4).End-user prices Fuel end-use prices For each sector and GEC
203、Model region,a representative price(usually a weighted average)is derived taking into account the product mix in final consumption and differences between countries.International price assumptions are then applied to derive average pre-tax prices for coal,oil,and gas over the projection period.Excis
204、e taxes,value added tax rates,subsidies and CO2 prices(where applicable)are taken into account in calculating average post-tax prices for all fuels.In all cases,the excise taxes and value added tax rates on fuels are assumed to remain unchanged over the projection period.We assume that energy-relate
205、d consumption subsidies are gradually reduced over the projection period,though at varying rates across the GEC Model regions and the scenarios.In the Announced Pledges Scenario and the Net Zero Emissions by 2050 Scenario,the international oil price drops in comparison to the Stated Policies Scenari
206、o due to lower demand for oil products.In order to counteract a rebound effect in the transport sector from lower gasoline and diesel prices,an increase of fuel duty on top of CO2 price is applied whenever is necessary for ensuring that end-user prices are kept at least at the same level as in the S
207、tated Policies Scenario.All prices are expressed in US dollars and assume no change in exchange rates.Electricity end-use prices The model calculates electricity end-use prices as a sum of the wholesale electricity price,system operation cost,transmission&distribution costs,supply costs,and taxes an
208、d subsidies(Figure 2.1).Figure 2.1 Components of retail electricity end-use prices IEA.CC BY 4.0.There is no single definition of wholesale electricity prices,but in the Global Energy and Climate Model the wholesale price refers to the average price paid to generators for their output.For each regio
209、n,wholesale electricity price are derived under the assumption that all plants operating in a given year recover the full costs fixed costs as well as variable costs of electricity generation and storage.The key region-specific factors affecting wholesale prices are therefore:22 International Energy
210、 Agency|Global Energy and Climate Model Documentation The upfront capital investment and financing costs of electricity generation and storage plants;The operation and maintenance costs of electricity generation and storage plants;and The variable of coal,natural gas,oil and other fuels inputs and,i
211、f applicable,CO2 cost of generation plants output.System operation costs are taken from external studies and are increased in the presence of variable renewables in line with the results of these studies.Transmission and distribution tariffs are estimated based on a regulated rate of return on asset
212、s,asset depreciation and operating costs.Supply costs are estimated from historic data,and taxes and subsidies are also taken from the most recent historic data,with subsidy phase-out assumptions incorporated over the Outlook period in line with the relevant assumptions for each scenario.Subsidies t
213、o fossil fuels The IEA measures fossil fuel consumption subsidies2 using a price-gap approach.This compares final end-user prices with reference prices,which correspond to the full cost of supply,or,where appropriate,the international market price,adjusted for the costs of transportation and distrib
214、ution.The estimates cover subsidies to fossil fuels consumed by end-users and subsidies to fossil-fuel inputs to electricity generation.The price-gap approach is designed to capture the net effect of all subsidies that reduce final prices below those that would prevail in a competitive market.Howeve
215、r,estimates produced using the price-gap approach do not capture all types of interventions known to exist.They,therefore,tend to be understated as a basis for assessing the impact of subsidies on economic efficiency and trade.Despite these limitations,the price-gap approach is a valuable tool for e
216、stimating subsidies and for undertaking comparative analysis of subsidy levels across countries to support policy development(Koplow,2009).2.4 Policies In order to underpin scenario analysis of the GEC Model,an extensive effort is made to update and expand the list of energy and climate-related poli
217、cies and measures that feed into our modelling.Assumptions about government policies are critical to this analysis and are the main reason for the differences in outcomes across the scenarios.Two notable IEA policy tracking efforts input into the scenarios:Policies and Measures database:The IEAs Pol
218、icies and Measures Database provides access to information on past,existing or planned government policies and measures to reduce greenhouse gas emissions,improve energy efficiency and support the development and deployment of renewables and other clean energy technologies.This unique policy databas
219、e brings together data from theIEAs Sustainable Recovery Tracker,IEA/IRENA Renewable Energy Policies and Measures Database,theIEA Energy Efficiency Database,theAddressing Climate Changedatabase,and the Building Energy Efficiency Policies(BEEP)database,along with information on CCUS and methane abate
220、ment policies.This policy information has been collected since 1999 from governments,partner organisations and IEA analysis.Governments have an opportunity to review the policy information periodically.SDG7 database:The International Energy Agency is at the forefront of global efforts to assess and
221、analyse persistent energy access deficit,providing annual country-by-country data on access to electricity and clean cooking(SDG 7.1)and the main data source for tracking official progress towards SDG targets on renewables(SDG 7.2)and energy efficiency(SDG 7.3).The IEA is one of the appointed co-cus
222、todians for tracking global progress on SDG 7 alongside IRENA,UNSD,the World Bank,and WHO.2 https:/www.iea.org/topics/energy-subsidies Section 2|Cross-cutting inputs and assumptions 23 In total,new policies and measures globally have been considered during the model preparation,including recent anno
223、uncements such as the Inflation Reduction Act(United States),Fit for 55(European Union),Climate Change Bill(Australia),and GX Green Transformation(Japan)as well as governmental spending as a reaction to the current energy crisis.The national net zero emissions pledges announced by India and Indonesi
224、a are also important changes compared to last year.A summary of some of the key policy targets and measures for different sectors by selected countries and regions can be found in the Annex B of WEO-2022.The considered policies are additive across scenarios:measures listed under the Announced Pledge
225、s Scenario(APS)supplement those in the Stated Policies Scenario(STEPS).In addition,separate policy assumptions are given for the Net Zero Emissions by 2050 Scenario(NZE)which provide indicative policymaking and decarbonising milestones that would steer global energy systems to these outcomes.The pub
226、lished tables begin with broad cross-cutting policy frameworks,followed by more detailed policies by sector:power,industry buildings,and transport.The tables list only the“new policies”enacted,implemented or revised since the last publication cycle 2021.Some regional policies have been included if t
227、hey play a significant role in shaping energy at a global scale(e.g.regional carbon markets,standards in very large provinces or states).The tables do not include all policies and measures,rather they highlight the policies most shaping global energy demand today,while being derived from an exhausti
228、ve examination of announcements and plans in countries around the world.2.5 Techno-economic inputs Incorporation of a diverse range of technologies is a key feature of the GEC Model.Extensive research is undertaken to update the range of technologies in the model,as well as their techno-economic ass
229、umptions.The GEC Model includes the breadth of technologies that are available on the market today.Additionally,the model integrates innovative technologies and individual technology designs that are not yet available on the market at scale by characterising their maturity and expected time of marke
230、t introduction.For each sector and technology area,new project announcements and important technological developments are tracked in databases that are regularly published.The modelled scenarios are informed by such detailed technology tracking process.For instance,the project planning financing sta
231、tus is an important consideration for whether projects are reflected in STEPS or rather in APS.For technology development progress and the time to bring new technologies to markets,the scenarios assume different pace of progress as the support and degree of international cooperation on clean energy
232、innovation increases with the ambition in decarbonisation.The following databases are particularly relevant for the definition of the different scenarios:Clean innovative technologies tracking:Clean Technology Guide:interactive database that tracks the technology readiness level(TRL)of over 500 indi
233、vidual technology designs and components across the whole energy system that contribute to achieving the goal of net-zero emissions.The Guide is updated every year.Clean Energy Demonstration Projects Database:newly launched in 2022,that provides more detailed tracking of the location,status,capacity
234、,timing and funding,of over 400 demonstration projects across the energy sector.Tracking Clean Energy Progress:annual tracking of developments for 55 components of the energy system that are critical for clean energy transitions and their progress towards short-term 2030 milestone along the trajecto
235、ry of the Net Zero by 2050 Scenario.24 International Energy Agency|Global Energy and Climate Model Documentation Hydrogen Projects Database:covers all projects commissioned worldwide since 2000 to produce hydrogen for energy or climate-change-mitigation purposes.Global EV Outlook:annual publication
236、that identifies and discusses recent policy and market developments in electric mobility across the globe.It is developed with the support of the members of the Clean Energy Ministerial Electric Vehicles Initiative(EVI).Technology costs are an important input to the model.All costs represent fully i
237、nstalled/delivered technologies,not solely the equipment cost,unless otherwise noted as for fuel cells.Installed/delivered costs include engineering,procurement and construction costs to install the equipment.Some illustrative examples include the following:Industry costs reflect average iron and st
238、eel production costs for a given technology and differentiate between conventional and innovative production routes.Electric Vehicle costs reflect production costs,not retail prices,to better reflect the cost declines in total cost of manufacturing,which move independently of final market prices for
239、 electric vehicles to customers.For the global average battery pack size,historical values in 2021 have been used.In hybrid cars,the future cost increase is driven by regional fuel economy and emissions standards.Electrolyser costs reflect a projected globally weighted average of installed electroly
240、ser technologies(excluding China,where lower costs are assumed),including inverters.Fuel cell costs are based on stack manufacturing costs only,not installed/delivered costs.The costs provided are for automotive fuel cell stacks for light-duty vehicles.Utility-scale stationary battery costs reflect
241、the average installed costs of all battery systems rated to provide maximum power output for a four-hour period.Table 2.5 Capital costs for selected technologies by scenario Stated Policies Announced Pledges Net Zero Emissions by 2050 2021 2030 2050 2030 2050 2030 2050 Primary steel production(USD/t
242、pa)Conventional 640 650 660 650 670 650 680 Innovative n.a.1 400 1 050 1 330 980 1 020 910 Vehicles(USD/vehicle)Hybrid cars 16 122 14 686 14 861 14 528 14 718 14 460 14 638 Battery electric cars 21 322 15 772 14 185 15 265 13 618 14 783 13 251 Batteries and hydrogen Hydrogen electrolysers(USD/kW)1 5
243、05 575 445 390 265 315 230 Fuel cells(USD/kW)100 60 40 50 35 45 30 Utility-scale stationary batteries(USD/kWh)285 185 135 185 135 180 135 Notes:kW=kilowatt;tpa=tonne per annum;kWh=kilowatt-hour;n.a.=not applicable.All values are in USD(2021).Sources:IEA analysis;James et.al.(2018);Thompson,et al.(20
244、18);Financial Times(2020);BNEF(2021);Cole et al.(2020);Tsiropoulos et al.(2018);Section 3|End-use sectors 25 Section 3 3 End-use sectors All 26 regions are modelled in considerable sectoral and end-use detail.Specifically:Industry is composed of five energy-intensive and eight non-energy-intensive s
245、ub-sectors;Buildings is separated into residential and services buildings,with eleven end-uses modelled separately;Transport is separated into nine modes with considerable detail for road transport;Agriculture modelling reflects the range of fuels and energy consuming applications in the sector.Tota
246、l final energy demand is the sum of energy consumption in each final demand sector.In each sub-sector or end-use,at least seven types of energy are shown:coal,oil,gas,electricity,heat,hydrogen and renewables.The main oil products liquefied petroleum gas(LPG),naphtha,gasoline,kerosene,diesel,heavy fu
247、el oil(HFO)and ethane are modelled separately for each final sectors.Demand-side drivers,such as steel production in industry or household size in dwellings,are estimated econometrically based on historical data and on socioeconomic drivers(GDP and population).All end-use sector modules base their p
248、rojections on the existing stock of energy infrastructure.This includes the number of vehicles in transport,production capacity in industry,and floor space area in buildings.To take into account expected changes in structure,policy or technology,a wide range of technologies are integrated in the mod
249、el that can satisfy each specific energy service.End-user fuel prices and technology costs play an important role in determining the distribution of technologies and fuels,although real-world non-cost influences also play a role.Respecting the efficiency level of all end-use technologies gives the f
250、inal energy demand for each sector and sub-sector(Figure 3.1).Figure 3.1 General structure of demand modules IEA.CC BY 4.0.3.1 Industry sector The origins of the GEC industry sector model are the industry sector modules of the former WEM(simulation)and the ETP(TIMES optimisation)models,both now supe
251、rseded by the GEC framework.The GEC industry sector model combines the strengths of each of these former models into a single simulation framework,with its constraints and input parameters informed by,among other things,periodic model runs of the former ETP TIMES optimisation framework.The result of
252、 these developments in 2022 is a technology-rich,optimisation-informed,simulation model,fully integrated into the broader GEC Model framework.The GEC industry model is implemented in Vensim,using the 26 GEC model regions(activity modelling is conducted at the country level),in annual time-steps.Indu
253、stry model coverage and approach For the purposes of the GEC industry model,the industrial sector includes International Standard Industrial Classification(ISIC)Divisions 7,8,10-18,20-32 and 41-43,and Group 099,covering mining and quarrying DriversEconometric analysisEnergy service demand(demand for
254、 useful energy)Least-cost approachTechnology/fuel allocationEfficiency levelsFinal energy demand26 International Energy Agency|Global Energy and Climate Model Documentation (excluding mining and extraction of fuels),construction,and manufacturing.This coverage follows the structure of the IEA Energy
255、 Balances,covering all of the industry components of total final consumption.Chemical feedstock(a component of non-energy use)and blast furnace and coke oven energy use(both transformation and own use)are also included within the boundaries of industry.Aside from petrochemical feedstock,other non-en
256、ergy use is not included in the GEC Models industry sector boundary,but rather is modelled as a separate category in the same framework.Figure 3.2 Major categories of technologies by end-use sub-sector in industry IEA.CC BY 4.0.The industry sector is modelled using a hybrid approach(Figure 3.2).Tech
257、nology-rich simulation models,informed by periodic model runs of the former ETP TIMES optimisation framework,are used for five energy-intensive sub-sectors components thereof(iron and steel;primary chemicals within chemicals and petrochemicals;cement within non-metallic minerals;aluminium within non
258、-ferrous metals;paper,pulp and CCUS options(cross-cutting)Technology-rich energy-intensive sub-sector modelsIron and steelChemicals and petrochemicalsNon-metallic mineralsNon-ferrous metalsPaper,pulp and printingCross-sectoral conversion device simulation modelMaterial and fuel preparation Coke oven
259、s(coke dry quenching option)Sintering PelletisingIron production Blast furnaces(top gas recovery,top pressure recovery,hydrogen amplification,charcoal and hydrogen/biomass blending options)Smelt reduction Direct reduced iron(electrolysis option)Steel production Basic oxygen furnace Open hearth furna
260、ce Electric arc furnace Induction furnaceRaw material and fuel grindingBall millRoller press&ball millVertical millClinker production Dry kilns Wet kilns Vertical shaft kilns Electric kilnsFinished cement grinding Ball mill Roller press and ball mill Vertical millAlumina refining Bayer process Bayer
261、-Sinter process Sinter processAluminium production Hall-Hroult smelting(inert anode option)Soderberg smelting Secondary furnaces(induction furnace and reverbatory furnace options)Finishing Cold rolling Extrusion Hot rolling Shape castingPulp production Conventional boilers(e.g.coal,oil,gas)Bark boil
262、er Black liquor recovery Pulping Pulp bleaching Pulp dryingPaper production Conventional boilers(e.g.coal,oil,gas)Bark boiler Paper-making processesHigh value chemical production Steam cracking Electric seam cracking Bioethanol dehydration Naphtha catalytic cracking Propane dehydrogenation Methanol
263、to olefins Methanol to aromaticsMethanol production Fossil fuel-based Biomass-based Electrolysis-basedAmmonia production Fossil fuel-based Biomass-based Electrolysis-based Pyrolysis-basedSectorsOther industry Transport equipment Machinery Mining and quarrying Food and tobacco Textile and leather Woo
264、d and wood products Construction Non-specified industryEquipment Cooling and refrigeration Boilers Heat pumps Solar/geothermal heating Resistance heating Electro-magnetic heating Motors Motor driven systemsGEC industry hybrid modelling approachMerchant hydrogen and synthetic hydrocarbon options(cros
265、s-cutting)Other non-metallic mineral production Fuel elasticity simulationOther non-ferrous metal production Fuel elasticity simulationOther chemical production Fuel elasticity simulationSemi-finishing and finishing processes Fuel elasticity simulationPrinting and finishing processes Fuel elasticity
266、 simulation Section 3|End-use sectors 27 printing).The remaining non-energy-intensive industry sub-sectors(construction,mining and quarrying,transport equipment,machinery,food and tobacco,wood and wood products,textile and leather and industry not-elsewhere specified)are modelled using a cross-cutti
267、ng conversion device simulation approach.For the residual components of the five energy-intensive sub-sectors(chemicals besides primary chemicals,non-metallic minerals besides cement,non-ferrous metals besides aluminium,downstream finishing processes in the iron and steel and paper,pulp and print se
268、ctors),the same cross-cutting approach is applied as to the non-energy-intensive sub-sectors.The five energy-intensive sub-sector models characterise the energy performance of process technologies at the process unit level(e.g.coal blast furnace,naphtha steam cracker).The cross-cutting simulation mo
269、del for the remaining industry sub-sectors characterises the stock of the main conversion devices(e.g.motors,heating equipment)used to provide various energy services required during the production of thousands of materials and products.See sections 3.1.3 and 3.1.4 for more information on the approa
270、ches taken for each of these main components of the GEC industry model.Energy-intensive sub-sectors For each of the five energy-intensity industry sub-sectors,the modelling framework consists of a series of interacting sub-modules and a core technology model(see Figure 3.3).The sub-modules consist o
271、f an activity model,a stock model and a capacity model.The activity drivers for each sub-sector of the GEC industry model are tonnages of material produced in a given scenario at a given point in time.Activity modelling is handled in a similar manner for all energy-intensive industry sub-sectors.Dem
272、and for materials is projected through interaction between an activity model and a stock model,together with modelling of material efficiency strategies.The activity model uses country-level historical data on material consumption to calculate demand per capita,then projects forward total demand usi
273、ng population projections and industry value-added projections.The industry value-added projections inform the rate of change in demand per capita.The results of the activity model on demand projections feed into the stock model,which uses bottom-up material demand inputs from the buildings,transpor
274、t and supply modules and complementary assumptions about other end-product shares and lifetimes to calculate the implied build-up of material stocks.Stock saturation in the stock model in turn informs per capita material demand saturation in the activity model through a series of iterations.Material
275、 efficiency strategies across value chains also are modelled.This modelling work builds mainly on the literature and previous IEA publications relating to material efficiency(IEA 2019a).Strategies considered include:Design stage:light-weighting(produce the same product with a lower average mass per
276、product),design for future material savings(modular design to enable reduce,design for recyclability)Construction and manufacturing:increased yields(reduce the losses in semi-manufacturing and manufacturing),reduced materials waste(more careful construction practices and material handling)Use:longer
277、 life times(refurbishing buildings for other uses,re-using components for particular products),more intensive use of products(for example car sharing or using a building for a higher share of the day),End-of-life:direct materials re-use(use of post-consumer materials without re-melting in the case o
278、f metals for the same or other applications),recycling(increased collection and improved sorting).Those strategies occurring in the other end-use sectors(e.g.building lifetime extension,vehicle light-weighting)are fed into the stock model via the bottom-up demand estimates,while material efficiency
279、strategies within the industry boundary(e.g.manufacturing yield improvements,direct reuse and recycling)are modelled within the stock model.These strategies lead to reduced material demand,which is fed into the activity model via a material 28 International Energy Agency|Global Energy and Climate Mo
280、del Documentation efficiency factor.The resulting activity projections from the activity model and scrap availability(including semi-manufacturing,manufacturing and post-consumer scrap)from the stock model feed into the main technology model.Material trade between model regions is not modelled endog
281、enously in the technology model,but rather is reflected in the activity projections developed in the activity and stock models.Apart from specific instances where announced policies or projected energy price signals provide relevant evidence to the contrary,trade patterns in material production and
282、consumption are projected to follow current trends.Global total material demand is thus allocated into regional production based on these current trends.The capacity model contains data on historic and planned plant capacity additions and retrofits by plant type.Using assumptions about investment cy
283、cles,it calculates plant refurbishments and retirements.The resulting remaining capacity informs the main technology model.The capacity model also provides projections on the average age of plants at a given time.Figure 3.3 Industry sector model internal module structure and key data flows IEA.CC BY
284、 4.0.Notes:Internal industry model flows:1)Historic production,population projection,industry value-added projection,2)End-use demand,product lifetimes,process yields,recycling and re-use rates,3)Energy and raw material intensities,energy prices,CAPEX and OPEX,lifetimes,technology deployment constra
285、ints,CO2 emissions reduction trajectory,4)Historic and planned capacity,lifetimes,refurbishments,5)Consumption projections,6)Material stocks saturation,material efficiency factors,7)Production projections,8)Scrap availability,9)Residual capacity.Model results:A)Material production,B)Material stocks
286、saturation,C)Energy consumption,CO2 emissions,technology shares,investments,D)Capacity installed,added and retired.The main technology model of each sector consists of a detailed representation of process technologies required for relevant production routes.Energy use and technology portfolios for e
287、ach country or region are characterised in the base year using relevant energy use and material production statistics.Throughout the modelling horizon,demand for materials(as dictated by the activity model outputs)is met by technologies and fuels,whose shares are informed by real-world technology pr
288、ogress and the previous ETP TIMES optimisation model.That model used a constrained optimisation framework,with the objective function set to make choices that minimise overall system cost(comprised of both energy costs and investments).Changes in the technology and fuel mix,as well as efficiency imp
289、rovements,are in part driven by a combination of exogenous assumptions on the penetration and energy performance of best available technologies,Input dataModel resultsActivity moduleCapacity moduleTechnology modelStock module5234D61789BCA Section 3|End-use sectors 29 constraints on the availability
290、of raw materials(such as scrap availability according to the stock model outputs),technoeconomic characteristics of the available technologies and process routes,and assumed progress on demonstrating innovative technologies at commercial scale.The results are sensitive to assumptions about how quick
291、ly physical capital is turned over(including retirements of existing capacity according to the capacity model outputs)and about the relative costs of the various technology options and fuels.A given scenario can also be subject to a CO2 emission trajectory that the model must adhere to.Model outputs
292、 include energy consumption,fuel combustion and process CO2 emissions both emitted and captured,technology shares,raw materials and intermediate industrial materials flows and investment requirements.Some industrial sectors have the particularity to produce and use“on-site”hydrogen within the indust
293、rial facility as for specific ammonia,methanol or primary steel production processes.This hydrogen is not reported in the standard energy balance but it is reported as fossil fuel or electricity depending on whether it is produced via steam reforming or water electrolysis.Accounting of this hydrogen
294、,necessary to build the global hydrogen accounting,is performed in a dedicated hydrogen module.Outputs of this module are hydrogen quantities produced onsite(low-emissions or not),electrolyser capacity and related-investments requirements,energy input and related CO2 emissions emitted as well as cap
295、tured and stored.Non-energy intensive sub-sectors Activity modelling for the non-energy-intensive sub-sectors follows a different approach to the energy-intensive sectors.These sub-sectors produce a large range of final products without a clear common intermediate in many cases.This contrasts to the
296、 energy-intensive sub-sectors,which have a large range of final products but a clear common intermediate product for which production in physical terms can be clearly projected(e.g.crude steel in the iron and steel sector).As such,macro-economic indicators(e.g.industrial value-added)are used as the
297、activity drivers for non-energy intensive sub-sectors,rather than physical production.Using historic relationships between macro-economic indicators and industrial energy demand,together with demand signals from the other end-use models(e.g.vehicle sales from the transport model for the transport eq
298、uipment sector)and material efficiency considerations(based on the results of the energy-intensive sub-sector analyses)where relevant,projections of energy service demand are made across the following categories:Heat delivered at five temperature bands(0-60 C,60-100 C,100-200 C,200-400 C and above 4
299、00 C);Mechanical work to be delivered by electric motors;Other energy services in aggregate(cooling,lighting etc.).These energy service demands form the final activity drivers for the non-energy-intensive industry sub-sector models.A range of technologies are characterised for meeting each category
300、of activity demand,including a range of different heating technologies using different fuels(fossil fuels,solar thermal,geothermal,electro-magnetic heating,electric resistance heating,heat pumps,hydrogen,bioenergy)and a range of motor options(differing efficiencies of the motor driven system,efficie
301、ncies of the motor itself,variable speed drive option).The shares of energy service demand met by each of these technologies are informed by their levelised cost(including the impact of any CO2 prices),constraints on fuel availability(e.g.,bioenergy resources),technology readiness(e.g.,electro-magne
302、tic heating for large non-conductive media not commercially available today),limits on potential(e.g.,industrial heat pump penetration in medium and high temperature heat bands)and any CO2 emissions constraints of the scenario.The shares of fuels(and associated emissions)used to meet the remaining e
303、nergy service demand of multifuel processes or processes that are not covered by the bottom-up technology modelling across the non-energy-intensive sectors(and residual portions of the energy-intensive sectors not covered in the energy-intensive sub-30 International Energy Agency|Global Energy and C
304、limate Model Documentation sector models)is modelled by fuel using a Weibull function.This function is informed by previous years fuel share,the fuel price change(including the impact of any CO2 prices)and the price change in the previous year.Any CO2 constraints specified by the scenario are also r
305、espected.Industry sector investments The boundaries for investments reporting include capital expenditure(CAPEX),and engineering,procurement and construction costs.For carbon capture,utilisation and storage(CCUS)technologies,CO2 transport and storage costs are also included.For material efficiency,i
306、nvestments are based on data on CO2 abatement costs for material efficiency strategies,converted into costs for material savings.Fixed operating and maintenance expenditures(OPEX)are not included under reported investments,though they are considered in the context of the economic characterisation of
307、 technologies in the model.Energy system investments do not include core industrial equipment CAPEX,but do include the additional investment required to incrementally(e.g.,energy efficiency improvements through adoption of BAT)or substantially(e.g.electrolyser and carbon capture equipment)adjust the
308、 energy or emissions performance of a technology.Other investments in core industrial equipment are also accounted for,but not reported within the boundary of energy system investments.Input data Input data to the model comes from a wide variety of sources.Sources for historical production and consu
309、mption used in the activity modelling include the World Steel Association,the International Fertilizer Association,the United States Geological Survey,the International Aluminium Institute and a number of proprietary sources.Data on the energy intensities of processes come from a variety of industry
310、 sources(e.g.the Getting the Numbers Right publication overseen by the Global Concrete and Cement Association),academic literature and industry contacts.CAPEX and OPEX similarly come from a combination of industry and academic sources.Population,economic indicators(e.g.value added by industry),fuel
311、costs i.e.end-use energy prices,and CO2 prices are provided by the main GEC Model(see Section 2).Other key inputs from the GEC modelling framework and associated work streams include the hydrogen and CCUS projects databases and the technology readiness assessments that form part of the Clean Technol
312、ogy Guide and Demonstration Projects Database.Techno-economic parameters are periodically reviewed,both as a component of aforementioned work streams,and during the course of preparing deep-dive analyses on specific sector or technology areas(e.g.the IEAs Iron and Steel Technology Roadmap,the Ammoni
313、a Technology Roadmap,The Future of Petrochemicals).3.2 Transport sector The GEC transport model combines strengths of both former World Energy Model(WEM)and Mobility Model(MoMo),and consists of dedicated sectoral model for road transport,aviation,maritime and rail.The Historical Database One key fou
314、ndation for transport modelling work is the road transport database,a database that is updated annually based primarily on publicly available data on road vehicle sales,stocks,activity,and operations.The road database further benefits from data and analytical work for the Electric Vehicles Initiativ
315、e1 and the Global Fuel Economy Initiative2.Similar historical databases form the basis for modelling rail,international maritime,and commercial passenger aviation.1 https:/www.iea.org/programmes/electric-vehicles-initiative 2 https:/www.iea.org/reports/global-fuel-economy-initiative-2021 Section 3|E
316、nd-use sectors 31 Each region is characterised on the basis of information that includes,for each road transport mode,vehicle sales,mileage,and energy intensity by vintage,as well as the overall vehicle stock,load factors and fuel efficiency.The database allows linking historical data on several int
317、erconnected variables,trying to assure internal consistency across indicators,according to the ASIF framework,wherein Activity,Structure,and Intensity determine estimates of Fuel use):=()()=F total Fuel use A vehicle Activity(expressed in vkm)Fi fuel used by vehicles with a given set of characterist
318、ics(i)(e.g.segments by service,mode,vehicle and powertrain)Ai/A=Si sectoral Structure(same disaggregation level)Fi/Ai=Ii Energy Intensity,i.e.average fuel consumption per vkm(same disaggregation level)The parameters monitored include including sales/new registrations of vehicles,second hand imports,
319、survival ages,stock,mileages,vehicle activity(vehicle-kilometres or vkm),loads/occupancy rates,passenger and freight activity(passenger-kilometres or pkm and tonne-kilometres or tkm),fuel economies and energy use(based on the IEA data on energy demand by country).The following parameters are collect
320、ed and calibrated/validated against the road energy balances on an annual basis:Sales/new vehicle registration data are taken from publicly available data sources(e.g.ACEA,US Bureau of Transportation Statistics,and others).Fuel economy data for passenger light-duty vehicles are based on aggregated d
321、ata from a proprietary database,plus conversions(based on an external research report)across regional vehicle test cycles to the World Light-Duty Test Cycle(WLTC),plus estimates for the gap between this test cycle and real-world specific fuel consumption(again,based on external research reports).Fue
322、l economy data for buses,trucks,two/three-wheelers are taken from various academic,government and industry reports or technical calculations,over the course of nearly 20 years.Stocks are based on our estimates of how long different vehicle types are kept in the fleet(i.e.scrappage functions),and whe
323、n reliable external estimates are available(as is the case,for instance,in the United States and Europe),these are calibrated to official data(e.g.ACEA,US Bureau of Transportation Statistics).In countries where academic or industry studies exist on the age distribution of the on-road fleet,scrappage
324、 functions are compared/calibrated with these.Occupancy(average people per vehicle)and Load Factors(average cargo weight per vehicle)are based on official statistics(e.g.,Eurostat),academic reports or surveys,or are developed by analogy/regression-based estimates when no data are available.Average M
325、ileage(i.e.,annual kilometres driven)estimates are similarly taken from or compared/calibrated to official data and literature Scrappage and mileage are then adjusted,across all vehicle categories(e.g.,two/three-wheelers,cars,buses,light commercial vehicles,medium-and heavy-trucks)and across all fue
326、l/powertrain types(e.g.gasoline,diesel,conventional hybrid,plug-in hybrid,battery and fuel-cell electric,etc.)to match the country-/regional time series of road gasoline,diesel,electricity,natural gas and LPG consumption as reported in the IEA energy balances.32 International Energy Agency|Global En
327、ergy and Climate Model Documentation The transport module The transport module of the GEC Model consists of several sub-models covering road,aviation,rail and navigation transport modes(Figure 3.4).The GEC Model fully incorporates a detailed bottom-up approach for the transport sector in all GEC Mod
328、el regions.Figure 3.4 Structure of the transport sector IEA.CC BY 4.0.Note:Other includes pipeline and non-specified transport.For each region,activity levels such as passenger-kilometres and tonne-kilometres are estimated econometrically for each mode of transport as a function of population,GDP an
329、d end-user price.Transport activity is linked to price through elasticity of fuel cost per kilometre,which is estimated for all modes except passenger buses and trains and inland navigation.This elasticity variable accounts for the“rebound”effect of increased car use that follows improved fuel effic
330、iency.Energy intensity is projected by transport mode,taking into account changes in energy efficiency and fuel prices.Road transport Road transport energy demand is broken down among passenger light duty vehicles(PLDVs),light commercial vehicles(LCVs),buses,medium trucks,heavy trucks and two-and th
331、ree-wheelers.The model allows fuel substitution and alternative powertrains across all sub-sectors of road transport.The gap between test and on-road fuel efficiency,i.e.,the difference between test cycle and real-life conditions,is also estimated and projected.As the largest share of energy demand
332、in transport comes from oil use for road transport,the GEC Model contains technology-detailed sub-models of the total vehicle stock and the passenger car fleet.The stock projection model is based on an S-shaped Gompertz function,proposed in Dargay et al.(2006).This model gives the vehicle ownership
333、based on income(derived from GDP assumptions)and 2 variables:the saturation level(assumed to be the maximum vehicle ownership of a country/region)and the speed at which the saturation level is reached.The equation used is:=Road transportRailNavigationOtherPassenger-kilometresTonne-kilometresActivity variablesPopulationGDPAviationSub-sectorsEnd-use energy pricesHistorical trends Section 3|End-use s