• Energy Research

International shipping accounts for around 2 % of global CO2 emissions. The International Maritime Organization (IMO) has set the ambition to halve shipping GHG emissions by 2050 to help mitigate climate change. As shipping connects countries and sectors, its future development is highly dependent on regional and sectoral trends. So far, the literature on the decarbonization of shipping has focused on sectoral analyses while integrated assessment models (IAMs) have paid little attention to this matter. In this study, the IMAGE model is used to assess different futures of energy, agricultural and industry impacting the effort required to meet IMO's target for 2050. To that end, long-term seaborne trade projections are created from outputs of the IMAGE model. The results show that varying pathways of socio-economic development strongly affect the size of the sector. The mass shipped globally ranges from 17 to 35 Gt/yr in 2050. This corresponds to an energy demand between 9 and 25 EJ in the same year, which would require significant amounts of low-carbon fuels. Interestingly, in a climate policy scenario, the avoided trade of fossil energy, although partially compensated by an increase of biofuel trade, lowers the international shipping mitigation effort.

International shipping accounts for around 2 % of global CO2 emissions. The International Maritime Organization (IMO) has set the ambition to halve shipping GHG emissions by 2050 to help mitigate climate change. As shipping connects countries and sectors, its future development is highly dependent on regional and sectoral trends. So far, the literature on the decarbonization of shipping has focused on sectoral analyses while integrated assessment models (IAMs) have paid little attention to this matter. In this study, the IMAGE model is used to assess different futures of energy, agricultural and industry impacting the effort required to meet IMO's target for 2050. To that end, long-term seaborne trade projections are created from outputs of the IMAGE model. The results show that varying pathways of socio-economic development strongly affect the size of the sector. The mass shipped globally ranges from 17 to 35 Gt/yr in 2050. This corresponds to an energy demand between 9 and 25 EJ in the same year, which would require significant amounts of low-carbon fuels. Interestingly, in a climate policy scenario, the avoided trade of fossil energy, although partially compensated by an increase of biofuel trade, lowers the international shipping mitigation effort.

Adoption of dynamic energy tariffs by households is crucial for the transition to carbon-neutral energy systems. Influencing the adoption patterns of these tariffs necessitates an examination of the drivers, decision components, and contextual factors influencing household decisions. Few computational models address this comprehensively, often omitting non-financial decision variables. Moreover, methodologically robust integrative reviews on this topic are scarce. To address this gap, this paper develops a concept-centered integrative review methodology aimed at deriving computer models for socio-techno-economic simulations of household adoption of sustainable technologies. The methodology encompasses five sequential phases: Setup, Literature Search, Analysis, Synthesis and Conceptual Model, and Discussion. To illustrate the methodology, it is applied to the case of household adoption of dynamic energy tariffs, resulting in an abstract conceptual model adaptable to local contexts. The review reveals a lack of consensus on modeled tariffs but highlights the significance of tariff complexity, relative advantage, household heterogeneity, and various agent properties. It also identifies potential improvements in model fundamentals, particularly spatial modeling. The developed process model focuses on the stages ‘knowledge’, ‘decision’, and ‘reevaluation’. The article contributes by presenting a comprehensive review scheme and delivering a concept-centered integrative review along with an explicit conceptual model derived from it.

Adoption of dynamic energy tariffs by households is crucial for the transition to carbon-neutral energy systems. Influencing the adoption patterns of these tariffs necessitates an examination of the drivers, decision components, and contextual factors influencing household decisions. Few computational models address this comprehensively, often omitting non-financial decision variables. Moreover, methodologically robust integrative reviews on this topic are scarce. To address this gap, this paper develops a concept-centered integrative review methodology aimed at deriving computer models for socio-techno-economic simulations of household adoption of sustainable technologies. The methodology encompasses five sequential phases: Setup, Literature Search, Analysis, Synthesis and Conceptual Model, and Discussion. To illustrate the methodology, it is applied to the case of household adoption of dynamic energy tariffs, resulting in an abstract conceptual model adaptable to local contexts. The review reveals a lack of consensus on modeled tariffs but highlights the significance of tariff complexity, relative advantage, household heterogeneity, and various agent properties. It also identifies potential improvements in model fundamentals, particularly spatial modeling. The developed process model focuses on the stages ‘knowledge’, ‘decision’, and ‘reevaluation’. The article contributes by presenting a comprehensive review scheme and delivering a concept-centered integrative review along with an explicit conceptual model derived from it.

Research on climate change mitigation tends to focus on supply-side technology solutions. A better understanding of demand-side solutions is missing. We propose a transdisciplinary approach to identify demand-side climate solutions, investigate their mitigation potential, detail policy measures and assess their implications for well-being.

Research on climate change mitigation tends to focus on supply-side technology solutions. A better understanding of demand-side solutions is missing. We propose a transdisciplinary approach to identify demand-side climate solutions, investigate their mitigation potential, detail policy measures and assess their implications for well-being.