Abstract
Today’s climate policies will shape the future trajectory of emissions. Consumption is the main driver behind recent increases in global greenhouse gas emissions, outpacing savings through improved technologies, and therefore its representation in the evidence base will impact on the success of policy interventions. The IPCC’s Special Report on Global Warming of 1.5 °C (SR1.5) summarises global evidence on pathways for meeting below-2 °C targets, underpinned by a suite of scenarios from integrated assessment models (IAMs). We explore how final energy demand is framed within these, with the aim to making demand-related assumptions more transparent, and evaluating their significance, feasibility, and use or underutilisation as a mitigation lever. We investigate how the integrated assessment models compensate for higher and lower levels of final energy demand across scenarios, and how this varies when mitigating for 2 °C and 1.5 °C temperature targets through an analysis of (1) final energy demand projections, (2) energy-economy relationships and (3) differences between energy system decarbonisation and carbon dioxide removal in the highest and lowest energy demand pathways. We look across the full suite of mitigation pathways and assess the consequences of achieving different global carbon budgets. We find that energy demand in 2100 in the highest energy demand scenarios is approximately three to four times higher than the lowest demand pathways, but we do not find strong evidence that 1.5 °C-consistent pathways cluster on the lower end of demand levels, particularly when they allow for overshoot. The majority of demand reductions happen pre-2040, which assumes absolute decoupling from economic growth in the near-term; thereafter final energy demand levels generally grow to 2100. Lower energy demand pathways moderately result in lower renewable energy supply and lower energy system investment, but do not necessarily reduce reliance on carbon dioxide removal. In this sense, there is more scope for IAMs to implement energy demand reduction as a longer-term mitigation lever and to reduce reliance on negative emissions technologies. We demonstrate the need for integrated assessments to play closer attention to how final energy demand interacts with, relates to, and can potentially offset supply-side characteristics, alongside a more diverse evidence base.
Highlights
Consumption is arguably the strongest accelerator of climate change, and has effectively cancelled out any gains from low carbon technolo gies (Wiedmann et al, 2020)
Our analysis explores how the full suite of integrated assessment models (IAMs) reported by the Intergovernmental Panel on Climate Change (IPCC) SR1.5 respond to different final energy demand (FED) assumptions
We analyse only final demand levels assumed in the IPCC SR1.5, we argue in the discussion the need for more diverse quantitative and qualitative ap proaches to contribute to the evidence base, including higher demand reduction scenarios, like those recently published in Millward-Hopkins et al (2020)
Summary
Consumption is arguably the strongest accelerator of climate change, and has effectively cancelled out any gains from low carbon technolo gies (Wiedmann et al, 2020). Global mitigation scenarios tend to focus on technology and price solutions related to energy supply (Grubler et al, 2018, Gambhir et al, 2019, Kriegler et al, 2015, van Sluisveld et al, 2018), yet much less has been done to frame 1.5 and 2 ◦C pathways from a demand perspective across the Intergovernmental Panel on Climate Change (IPCC) mitigation assessments. “[Integrated assessment models] lie at the basis of the assessment of mitigation pathways in this chapter, as much of the quantitative global scenario literature is derived with such models” (Rogelj et al, 2018b) This dominance means they play a leading role in the climatescience policy interface (van Beek et al, 2020, Keppo et al, 2021). We provide the first broad analysis of final energy demand (FED) in the mitigation pathways of the IPCC SR1.5 to increase transparency around demand-related assumptions
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