Changes from ETP 2016

ETP 2017 scenarios have been updated since 2016, particularly on key assumptions underlying the analysis such as energy prices, technology development, and projections for socio-economic drivers of population and GDP. Further details on key changes to the end-use sector models are described below.

Buildings

The ETP 2017 building scenario results are taken from the ETP buildings sector model, which has been revised since 2016 to include a full stock-sales accounting framework for building envelopes and building end-use equipment across the major building end uses. The ETP building team is also working closely with partners to gather and update end-use data on product deployment across global markets, as well as building energy policy information through its Buildings Energy Efficiency Policy (BEEP) database. Those data and information, along with the most recent base year energy balances and statistics, are included in the ETP 2017 buildings sector model results. Additional changes that have affected the outcome of the analysis include:

  • Collaboration with the Tsinghua University Building Energy Research Centre, IEA Energy Data Centre and National Bureau of Statistics in China to improve assessments on traditional use of biomass in China, which are reflected in the ETP 2017 analysis and are anticipated to be revised in the 2017 IEA World Energy Statistics and Balances
  • Updates to overall sectoral activity projections, including floor area, household size (i.e. occupancy rates) and appliance ownership, with respect to changes in demographic and global economic outlooksRevisions in global cooling estimates, in conjunction with the IEA Energy Efficiency in Emerging Economies (E4) programme, to reflect improved assessment of cooling energy demand in IEA key partner countries, including in particular Mexico, Indonesia, India and Brazil
  • Changes to global lighting scenarios to reflect updates in market sales of residential lighting technologies (e.g. halogens and light-emitting diodes [LEDs]) in recent years
  • Revisions to heat pump estimates to reflect updates in market sales data for recent years in Europe, Japan and China 

Industry

The ETP 2017 industry scenario results are based on the ETP industry model, which has been reviewed and revised since the previous results in 2016. During each modelling cycle, the base year (2014 for this publication) is updated to reflect the most recent IEA energy balance data. Additional revisions include:

  • Extension of the modelling horizon to 2060
  • Conversion of the chemicals and petrochemicals and pulp and paper sector models to a TIMES-based linear cost optimisation framework, including additional detail on process technologies and technological synergies
  • Updates to overall sectoral activity projections for industry, with more detailed revisions in energy-intensive sectors; significant revisions include:
    • Material efficiency analysis for the iron and steel and aluminium sectors, including additional levers such as manufacturing yield improvement and increased recycling and scrap reuse, affecting overall primary metals demand in the B2DS, as well as additional detail on plastics recycling influencing primary chemicals demand
    • Lower production of ethylene and propylene and slower growth in aromatics production in the long term, primarily in OECD countries and Latin America
    • A shift in methanol production away from Europe towards North America, and more detailed representation of the methanol-to-olefins process route in China
    • Additional product detail for pulp, paper, and paperboard and moderated demand in the long term, especially in developing Asia and Africa
    • Later peaking of cement production in China
    • Decreased crude steel production in the Middle East in the long term in favour of production in ASEAN
  • Revision of the potential for innovative low-carbon processes and BAT-level intensity in energy-intensive sectors
  • Reallocation of carbon capture and storage (CCS) on auto-producer co-generation at industrial sites to the industry sector (previously included in power sector results)
  • Estimation of CO2 captured and utilised from ammonia production for urea and methanol production
  • Improved investment cost estimation related to chemicals and petrochemicals, pulp and paper, and cement sector equipment
  • Development of regional sets of crude oil product prices by scenario, based on historical regression of crude oil product prices to crude oil and natural gas prices

Transport

Besides the extension of the modelling time frame to allow the estimation of results to 2060, key developments in the IEA MoMo occurred primarily in relation to road freight transport and international shipping.

The historical data for medium and heavy freight trucks (MFTs and HFTs) have been re-evaluated and a new baseline set. The main updates were to country- and regional-level fuel economy, mileage and age profile. These were calibrated to approximate road consumption of diesel and gasoline as provided in the IEA energy balance on the one hand, and national and regional statistics (e.g. total activity in vehicle kilometres and tonne kilometres, average mileage and load factor) on the other.

The revision of historical data for MFTs and HFTs also led to the revision of estimates of mileage and age profile for light commercial vehicles (LCVs) and passenger vehicles, including in particular buses and PLDVs. The rationale for these revisions was the need for consistency of the data, primarily based on vehicle registrations, fuel economy estimates and energy use data from the IEA balances.
The costs of alternative powertrains for MFTs and HFTs have been updated based on an assessment of technology and fuel production, transmission and distribution, and fuelling station costs at a regional level. These have been used to update MFT and HFT costs as assessed in the scenarios. LCV powertrain costs were also revised to match PLDVs.

New projections of road freight transport activity have been developed, based on regression analysis of historical panel data. The explanatory variables are GDP per capita, country size and long-term fuel tax regimes, used to project vehicle kilometres and tonne kilometres for MFTs and HFTs in the period 2015-60.

An assessment of the potential for systemic and logistical measures to improve the efficiency of LCVs, MFTs and HFTs, in urban and non-urban operations, has also been incorporated into the MoMo. The impacts of discrete policies are combined (non-additively) to estimate their impacts: reductions in vehicle kilometres, increases in vehicle utilisation (load factors) and reductions in operational vehicle energy intensity.

The assessment of international shipping energy use and emissions has been upgraded, shifting from a top-down approach to a bottom-up methodology. Energy use is now calculated as a result of the evolution of trade flows, the type and value of goods traded, ship categories, ship sizes/load capacities, capacity utilisation rates, travel distances, and the energy efficiency of the ships operating on international routes.

This update was developed building on monetary trade flows identified by the OECD Economic Directorate, the allocation of these into physical trade flows by mode as developed by the International Transport Forum and the IEA, information on ship specifications by category available from the International Maritime Organization, and statistics on the global stock of vessels by category from the United Nations Conference on Trade and Development. Assumptions on the most uncertain parameters (load capacities and energy intensity by ship type) were calibrated against the benchmark provided by the IEA statistics on fuel use in international marine bunkers.

A stock model was also developed in order to estimate the number of new ships leaving and entering the global fleet every year. This allowed for the development of scenarios using different sets of assumptions on technology deployment.