Comparing future patterns of energy system change in 2 °C scenarios to expert projections

Integrated assessment models (IAMs) are computer-based instruments used to assess the implications of human activity on the human and earth system. They are simultaneously also used to explore possible response strategies to climate change. As IAMs operate simplified representations of real-world processes within their model structures, they have been frequently criticised to insufficiently represent the opportunities and challenges in future energy systems over time. To test whether projections by IAMs diverge in systematic ways from projections made by technology experts we elicited expert opinion on prospective change for two indicators and compared these with the outcomes of IAM studies. We specifically focused on five (energy) technology families (solar, wind, biomass, nuclear, and carbon capture and storage or CCS) and compared the considered implications of the presence or absence of climate policy on the growth and diffusion of these technologies over the short (2030) to medium (2050) term. IAMs and experts were found to be in relatively high agreement on system change in a business-as-usual scenario, albeit with significant differences in the estimated magnitude of technology deployment over time. Under stringent climate policy assumptions, such as the internationally agreed upon objective to limit global mean temperature increase to no more than 2 °C, we found that the differences in estimated magnitudes became smaller for some technologies and larger for others. Compared to experts, IAM simulations projected a greater reliance on nuclear power and CCS to meet a 2 °C climate target. In contrast, experts projected a stronger growth in renewable energy technologies, particularly solar power. We close by discussing several factors that are considered influential to the alignment of the IAM and expert perspectives in this study

Analysing interactions among Sustainable Development Goals with Integrated Assessment Models

To achieve all Sustainable Development Goals (SDGs) by 2030, it is necessary to understand how they interact with each other. Integrated Assessment Models (IAMs) represent many human–environment interactions and can inform policymakers about the synergies and trade-offs involved in meeting multiple goals simultaneously. We analyse how IAMs, originally developed to study interactions among energy, the economy, climate, and land, can contribute to a wider analysis of the SDGs in order to inform integrated policies. We compare the key interactions identified among the SDGs in an expert survey, with their current and planned representation in models as identified in a survey among modellers. We also use text mining to reveal past practices by extracting the themes discussed in the IAM literature, linking them to the SDGs, and identifying the interactions among them, thus corroborating our previous results. This combination of methods allowed us to discuss the role of modelling in informing policy coherence and stimulate discussions on future research. The analysis shows that IAMs cover the SDGs related to climate because of their design. It also shows that most IAMs cover several other areas that are related to resource use and the Earth system as well. Some other dimensions of the 2030 Agenda are also covered, but socio-political and equality goals, and others related to human development and governance, are not well represented. Some of these are difficult to capture in models. Therefore, it is necessary to facilitate a better representation of heterogeneity (greater geographical and sectoral detail) by using different types of models (e.g. national and global) and linking different disciplines (especially social sciences) together. Planned developments include increased coverage of human development goals and contribute to policy coherence

Data for long-term marginal abatement cost curves of non-CO2 greenhouse gases

The research leading to these results has received funding from the KR foundation (#G-1503-01733) and the Climate Works Foundation (IIA/17/1303).Peer reviewedPublisher PD

Analysing interactions among Sustainable Development Goals with Integrated Assessment Models

To achieve all Sustainable Development Goals (SDGs) by 2030, it is necessary to understand how they interact with each other. Integrated Assessment Models (IAMs) represent many human–environment interactions and can inform policymakers about the synergies and trade-offs involved in meeting multiple goals simultaneously. We analyse how IAMs, originally developed to study interactions among energy, the economy, climate, and land, can contribute to a wider analysis of the SDGs in order to inform integrated policies. We compare the key interactions identified among the SDGs in an expert survey, with their current and planned representation in models as identified in a survey among modellers. We also use text mining to reveal past practices by extracting the themes discussed in the IAM literature, linking them to the SDGs, and identifying the interactions among them, thus corroborating our previous results. This combination of methods allowed us to discuss the role of modelling in informing policy coherence and stimulate discussions on future research. The analysis shows that IAMs cover the SDGs related to climate because of their design. It also shows that most IAMs cover several other areas that are related to resource use and the Earth system as well. Some other dimensions of the 2030 Agenda are also covered, but socio-political and equality goals, and others related to human development and governance, are not well represented. Some of these are difficult to capture in models. Therefore, it is necessary to facilitate a better representation of heterogeneity (greater geographical and sectoral detail) by using different types of models (e.g. national and global) and linking different disciplines (especially social sciences) together. Planned developments include increased coverage of human development goals and contribute to policy coherence

Analysing interactions among Sustainable Development Goals with Integrated Assessment Models

To achieve all Sustainable Development Goals (SDGs) by 2030, it is necessary to understand how they interact with each other. Integrated Assessment Models (IAMs) represent many human–environment interactions and can inform policymakers about the synergies and trade-offs involved in meeting multiple goals simultaneously. We analyse how IAMs, originally developed to study interactions among energy, the economy, climate, and land, can contribute to a wider analysis of the SDGs in order to inform integrated policies. We compare the key interactions identified among the SDGs in an expert survey, with their current and planned representation in models as identified in a survey among modellers. We also use text mining to reveal past practices by extracting the themes discussed in the IAM literature, linking them to the SDGs, and identifying the interactions among them, thus corroborating our previous results. This combination of methods allowed us to discuss the role of modelling in informing policy coherence and stimulate discussions on future research. The analysis shows that IAMs cover the SDGs related to climate because of their design. It also shows that most IAMs cover several other areas that are related to resource use and the Earth system as well. Some other dimensions of the 2030 Agenda are also covered, but socio-political and equality goals, and others related to human development and governance, are not well represented. Some of these are difficult to capture in models. Therefore, it is necessary to facilitate a better representation of heterogeneity (greater geographical and sectoral detail) by using different types of models (e.g. national and global) and linking different disciplines (especially social sciences) together. Planned developments include increased coverage of human development goals and contribute to policy coherence

Early action on Paris Agreement allows for more time to change energy systems

The IMAGE integrated assessment model was used to develop a set of scenarios to evaluate the Nationally Determined Contributions (NDCs) submitted by Parties under the Paris Agreement. The scenarios project emissions and energy system changes under (i) current policies, (ii) implementation of the NDCs, and (iii) various trajectories to a radiative forcing level of 2.8 W/m2 in 2100, which gives a probability of about two thirds to limit warming to below 2 °C. The scenarios show that a cost-optimal pathway from 2020 onwards towards 2.8 W/m2 leads to a global greenhouse gas emission level of 38 gigatonne CO2 equivalent (GtCO2eq) by 2030, equal to a reduction of 20% compared to the 2010 level. The NDCs are projected to lead to 2030 emission levels of 50 GtCO2eq, which is still an increase compared to the 2010 level. A scenario that achieves the 2.8 W/m2 forcing level in 2100 from the 2030 NDC level requires more rapid transitions after 2030 to meet the forcing target. It shows an annual reduction rate in greenhouse gas emissions of 4.7% between 2030 and 2050, rapidly phasing out unabated coal-fired power plant capacity, more rapid scale-up of low-carbon energy, and higher mitigation costs. A bridge scenario shows that enhancing the ambition level of NDCs before 2030 allows for a smoother energy system transition, with average annual emission reduction rates of 4.5% between 2030 and 2050, and more time to phase out coal capacity

Early action on Paris Agreement allows for more time to change energy systems

The IMAGE integrated assessment model was used to develop a set of scenarios to evaluate the Nationally Determined Contributions (NDCs) submitted by Parties under the Paris Agreement. The scenarios project emissions and energy system changes under (i) current policies, (ii) implementation of the NDCs, and (iii) various trajectories to a radiative forcing level of 2.8 W/m2 in 2100, which gives a probability of about two thirds to limit warming to below 2 °C. The scenarios show that a cost-optimal pathway from 2020 onwards towards 2.8 W/m2 leads to a global greenhouse gas emission level of 38 gigatonne CO2 equivalent (GtCO2eq) by 2030, equal to a reduction of 20% compared to the 2010 level. The NDCs are projected to lead to 2030 emission levels of 50 GtCO2eq, which is still an increase compared to the 2010 level. A scenario that achieves the 2.8 W/m2 forcing level in 2100 from the 2030 NDC level requires more rapid transitions after 2030 to meet the forcing target. It shows an annual reduction rate in greenhouse gas emissions of 4.7% between 2030 and 2050, rapidly phasing out unabated coal-fired power plant capacity, more rapid scale-up of low-carbon energy, and higher mitigation costs. A bridge scenario shows that enhancing the ambition level of NDCs before 2030 allows for a smoother energy system transition, with average annual emission reduction rates of 4.5% between 2030 and 2050, and more time to phase out coal capacity

Energy, land-use and greenhouse gas emissions trajectories under a green growth paradigm

This paper describes the possible developments in global energy use and production, land use, emissions and climate changes following the SSP1 storyline, a development consistent with the green growth (or sustainable development) paradigm (a more inclusive development respecting environmental boundaries). The results are based on the implementation using the IMAGE 3.0 integrated assessment model and are compared with a) other IMAGE implementations of the SSPs (SSP2 and SSP3) and b) the SSP1 implementation of other integrated assessment models. The results show that a combination of resource efficiency, preferences for sustainable production methods and investment in human development could lead to a strong transition towards a more renewable energy supply, less land use and lower anthropogenic greenhouse gas emissions in 2100 than in 2010, even in the absence of explicit climate policies. At the same time, climate policy would still be needed to reduce emissions further, in order to reduce the projected increase of global mean temperature from 3 °C (SSP1 reference scenario) to 2 or 1.5 °C (in line with current policy targets). The SSP1 storyline could be a basis for further discussions on how climate policy can be combined with achieving other societal goals.ISSN:0959-3780ISSN:1872-949