Editing IPCC:AR6/WGIII/Chapter-16 (section)

==== 16.2.4.2 Technology Deployment and Diffusion ====

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To simulate possible paths of energy technology diffusion for different decarbonisation targets, models rely on assumptions about the cost of a given technology relative to the costs of other technologies, and its ability to supply the energy demand under the relevant energy system and physical constraints. These assumptions include, for example, considerations regarding renewable intermittency, inertia on technology lifetime (for instance, under less stringent temperature scenarios, early retirement of fossil plants does not take place), distribution, capacity and market growth constraints, as well as the presence of policies. These factors change the relative price of technologies. Furthermore, technological diffusion in one country is also influenced by technology advancements in other regions ( [[#Kriegler--2015|Kriegler et al. 2015]] ).

Technology diffusion may also be strongly influenced, either positively or negatively, by a number of non-cost, non-technological barriers or enablers regarding behaviours, society and institutions ( [[#Knobloch--2016|Knobloch and Mercure 2016]] ). These include network or infrastructure externalities, the co-evolution of technology clusters over time (‘path dependence’), the risk-aversion of users, personal preferences and perceptions and lack of adequate institutional framework which may negatively influence the speed of (low-carbon) technological innovation and diffusion, heterogeneous agents with different preferences or expectations, multi-objectives and/or competitiveness advantages and uncertainty around the presence and the level of environmental policies and institutional and administrative barriers ( [[#Marangoni--2014|Marangoni and Tavoni 2014]] ; [[#Baker--2015|Baker et al. 2015]] ; [[#Iyer--2015|Iyer et al. 2015]] ; [[#Napp--2017|Napp et al. 2017]] ; [[#Biresselioglu--2020|Biresselioglu et al. 2020]] ; [[#van%20Sluisveld--2020|van Sluisveld et al. 2020]] ). These types of barriers to technology diffusion are currently not explicitly detailed in most of the climate-energy-economy models. Rather, they are accounted for in models through scenario narratives, such as the ones in the ''Shared Socioeconomic Pathways'' ( [[#Riahi--2017|Riahi et al. 2017]] ), in which assumptions about technology adoption are spanned over a plausible range of values. Complementary methods are increasingly used to explore their importance in future scenarios ( [[#Turnheim--2015|Turnheim et al. 2015]] ; [[#Geels--2016|Geels et al. 2016]] ; [[#Doukas--2018|Doukas et al. 2018]] ; [[#Gambhir--2019|Gambhir et al. 2019]] ; [[#Trutnevyte--2019|Trutnevyte et al. 2019]] ). It takes a very complex modelling framework to include all aspects affecting technology cost reductions and technology diffusion, such as heterogeneous agents ( [[#Lamperti--2020|Lamperti et al. 2020]] ), regional labour costs ( [[#Skelton--2020|Skelton et al. 2020]] ), materials cost and trade and perfect foresight multi-objective optimisation (Aleluia Reis et al. 2021). So far, no model can account for all these interactions simultaneously.

Another key aspect of decarbonisation regards issues of acceptability and social inclusion in decision-making. Participatory processes involving stakeholders can be implemented using several methods to incorporate qualitative elements in model-based scenarios on future change ( [[#van%20Vliet--2010|van Vliet et al. 2010]] ; [[#Nikas--2017|Nikas et al. 2017]] , 2018; [[#Doukas--2020|Doukas and Nikas 2020]] ; [[#van%20der%20Voorn--2020|van der Voorn et al. 2020]] ).

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