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

Comparing future patterns of energy system change in 2°C scenarios with historically observed rates of change

This paper systematically compares modeled rates of change provided by global integrated assessment models aiming for the 2 °C objective to historically observed rates of change. Such a comparison can provide insights into the difficulty of achieving such stringent climate stabilization scenarios. The analysis focuses specifically on the rates of change for technology expansion and diffusion, emissions and energy supply investments. The associated indicators vary in terms of system focus (technology-specific or energy system wide), temporal scale (timescale or lifetime), spatial scale (regional or global) and normalization (accounting for entire system growth or not). Although none of the indicators provide conclusive insights as to the achievability of scenarios, this study finds that indicators that look into absolute change remain within the range of historical growth frontiers for the next decade, but increase to unprecedented levels before mid-century. Indicators that take into account or normalize for overall system growth find future change to be broadly within historical ranges. This is particularly the case for monetary-based normalization metrics like GDP compared to energy-based normalization metrics like primary energy. By applying a diverse set of indicators alternative, complementary insights into how scenarios compare with historical observations are acquired but they do not provide further insights on the possibility of achieving rates of change that are beyond current day practice

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

The impact of copper scarcity on the efficiency of 2050 global renewable energy scenarios

In the coming decades, copper scarcity is likely to result in deteriorating ore quality, which in turn will lead to a higher GER (gross energy requirement) for copper production. In this study, this increasing GER and the effect it has on the EROI (energy return on investment) of wind turbine technologies have been analysed. The GER of copper in a 2050 100% renewable energy system will be a factor 2–7 larger than it is today, depending on technological progress, the recycling rate and the future electricity demand. Because of an increasing in-use stock of copper, recycling will play a relatively small role even when the recycling rate is high. The future EROI of wind turbines is approximately 15% less than is currently often taken into account, mainly due to network losses. The GER of increasingly scarce materials can potentially be used as a more meaningful indicator for abiotic depletion in LCA studies than the current mineral reserve based practice

Long-term marginal abatement cost curves of non-CO2 greenhouse gases

This study presents a new comprehensive set of long-term Marginal Abatement Cost (MAC) curves of all major non-CO2 greenhouse gas emission sources. The work builds on existing short-term MAC curve datasets and recent literature on individual mitigation measures. The new MAC curves include current technology and costs information as well as estimates of technology development and removal of implementation barriers to capture long-term dynamics. Compared to earlier work, we find a higher projected maximum reduction potential (MRP) of nitrous oxide (N2O) and a lower MRP of methane (CH4). The combined MRP for all non-CO2 gases is similar but has been extended to also capture mitigation measures that can be realized at higher implementation costs. When applying the new MAC curves in a cost-optimal, integrated assessment model-based 2.6 W/m2 scenario, the total non-CO2 mitigation is projected to be 10.9 Mt CO2 equivalents in 2050 (i.e. 58% reduction compared to baseline emissions) and 15.6 Mt CO2equivalents in 2100 (i.e. a 71% reduction). In applying the new MAC curves, we account for inertia in thline implementation speed of mitigation measures. Although this does not strongly impact results in an optimal strategy, it means that the contribution of non-CO2 mitigation could be more limited if ambitious climate policy is delayed

Long-term marginal abatement cost curves of non-CO2 greenhouse gases

This study presents a new comprehensive set of long-term Marginal Abatement Cost (MAC) curves of all major non-CO2 greenhouse gas emission sources. The work builds on existing short-term MAC curve datasets and recent literature on individual mitigation measures. The new MAC curves include current technology and costs information as well as estimates of technology development and removal of implementation barriers to capture long-term dynamics. Compared to earlier work, we find a higher projected maximum reduction potential (MRP) of nitrous oxide (N2O) and a lower MRP of methane (CH4). The combined MRP for all non-CO2 gases is similar but has been extended to also capture mitigation measures that can be realized at higher implementation costs. When applying the new MAC curves in a cost-optimal, integrated assessment model-based 2.6 W/m2 scenario, the total non-CO2 mitigation is projected to be 10.9 Mt CO2 equivalents in 2050 (i.e. 58% reduction compared to baseline emissions) and 15.6 Mt CO2equivalents in 2100 (i.e. a 71% reduction). In applying the new MAC curves, we account for inertia in thline implementation speed of mitigation measures. Although this does not strongly impact results in an optimal strategy, it means that the contribution of non-CO2 mitigation could be more limited if ambitious climate policy is delayed