Abstract
In the last decade, instigated by the Paris agreement and United Nations Climate Change Conferences (COP22 and COP23), the efforts to limit temperature increase to 1.5 °C above pre-industrial levels are expanding. The required reductions in greenhouse gas emissions imply a massive decarbonization worldwide with much involvement of regions, cities, businesses, and individuals in addition to the commitments at the national levels. Improving end-use efficiency is emphasized in previous IPCC reports (IPCC 2014). Serving as the primary ‘agents of change’ in the transformative process towards green economies, households have a key role in global emission reduction. Individual actions, especially when amplified through social dynamics, shape green energy demand and affect investments in new energy technologies that collectively can curb regional and national emissions. However, most energy-economics models—usually based on equilibrium and optimization assumptions—have a very limited representation of household heterogeneity and treat households as purely rational economic actors. This paper illustrates how computational social science models can complement traditional models by addressing this limitation. We demonstrate the usefulness of behaviorally rich agent-based computational models by simulating various behavioral and climate scenarios for residential electricity demand and compare them with the business as usual (SSP2) scenario. Our results show that residential energy demand is strongly linked to personal and social norms. Empirical evidence from surveys reveals that social norms have an essential role in shaping personal norms. When assessing the cumulative impacts of these behavioral processes, we quantify individual and combined effects of social dynamics and of carbon pricing on individual energy efficiency and on the aggregated regional energy demand and emissions. The intensity of social interactions and learning plays an equally important role for the uptake of green technologies as economic considerations, and therefore in addition to carbon-price policies (top-down approach), implementing policies on education, social and cultural practices can significantly reduce residential carbon emissions.
Highlights
The efforts to limit temperature increase to 1.5 °C above pre-industrial levels are expanding in line with the ambitions laid down in the UNFCCC process1
We present the results of the Behavioral change in ENergy Consumption of Households (BENCH).v2 simulations by tracking individual and cumulative impacts of behavioral changes on carbon emissions among 1383 individual households in the Overijssel provinces over 14 years (2016–2030)
Our results indicate that such behavioral changes as investments in solar panels (A1)
Summary
The efforts to limit temperature increase to 1.5 °C above pre-industrial levels are expanding in line with the ambitions laid down in the UNFCCC process. In order to limit global warming to this critical level, they set an aim to achieve a balance between sources of anthropogenic emission and sinks of greenhouse gases in the second half of this century. Decarbonization of the economy will require massive worldwide efforts and strong involvement of regions, cities, businesses, and individuals in addition to the commitments at the national levels (Grubler et al 2018). Individual actions, especially when amplified through social dynamics, shape green energy demand and affect investments in new energy technologies that collectively can curb regional and national emissions. The importance of social influence, normative feedback, and information diffusion on pro-environmental behavior is rooted in different studies (Bass 1980; Festinger 1954; Rogers 1995; Schnelle et al 1980; Schultz 1998). There is a demand for tools that, next to economic considerations, can assess their cumulative emissions given the diversity of behavior and a variety of psychological and social factors influencing it
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