- Differences in assumptions about resource costs and performance parameters reflect the modeling teams’ assumptions about the relative costs associated with energy production from different technologies.

- How models represent the growth of technologies is also important. For CCS, nuclear, wind, solar, and hydroelectric technologies as well as, although to a lesser degree, fossil technology for electricity generation, the variation among models is great. As we have seen, some of them can assume no constraint, a growth-rate constraint, a constraint on the share of technologies, or no technology at all.

- The process of calibrating base year shares as well as how this calibration affects the future evolution of technologies are important. Many models, such as GCAM and general equilibrium models, calibrate energy systems to the base year share of technologies, whereas other models, such as MESSAGE and AIM-Enduse, do not calibrate base year shares. Thus, in the former models, the base year shares affect the evolution of future energy systems. This process represents the degree to which base year capital stocks turn over and affect the future capital stocks of different technologies.

- The representation of regional resource bases varies across models. Resource bases are not critical for fossil technologies, as these are globally traded commodities, but they are essential for determining the share of renewable energy sources and CCS technologies. For solar power, for example, some models assume regional production limits, some assume regional supply curves, some CGE models assume a fixed factor, and other models assume no limits. Similar differences in assumptions for other technologies are also present across models. However, each model provides its own representation of the different technologies. For example, GCAM represents solar and wind with supply curves and bioenergy with endogenous land competition. In addition, although there is no limit for CCS supplies, regional resource bases in Japan and the Republic of Korea are constrained.

- Though most models include technology cost as an exogenous assumption, some modeling frameworks, such as WITCH, model technology costs endogenously.

- Finally, solution algorithms differ across models. Most technology-detailed bottom-up models are based on an intertemporal modeling framework, whereas others, such as GCAM, are myopic and their solution algorithm is recursive dynamic.

There are now many criticisms of Integrated Assessment Models (IAM) and these range from technical disputes regarding appropriate quantities for variables to more fundamental critiques of the assumptions, concepts and purposes of IAMs (for the latter see also Dale, 2018; Hickel, 2018; Murphy, 2018). IAMs give the impression of being rooted in data, which tends to give them status as science as well as policy influence in key decision making and advisory circles (governments, the IPCC, etc.). Climate and economy focused IAMs are, however, deeply unrealistic in how they represent energy, environment and human systems and the relation between them.

The recent IPCC Global Warming of 1.5°C report (IPCC, 2018) and the deficits published in the annual UNEP Emissions Gap reports (see Christensen & Olhoff, 2019) have placed greater pressure on governments across the world to immediately increase investment in mitigation and adaptation and take more urgent action to reduce emissions – and this has resulted in further negotiations via the COP process and the UNFCCC and different countries are now beginning to announce they will aim for ‘net zero’ emissions by mid-century (though currently statutory commitments, detailed plans and implementation are mainly lacking and there is considerable skepticism regarding what ‘net’ might mean). Still, it is increasingly clear that more delay and gradual incremental change will be insufficient. Moreover, it remains the case that the IPCC approach to change is itself not sufficiently ambitious. IPCC reports include various ‘simulated scenarios’ generated from IAMs.

35