Integrated Assessment Models Scenarios Research Articles

A framework for high resolution coupled global electricity & hydrogen models based on integrated assessment model scenarios

Technology-rich Integrated Assessment Models (IAMs) offer the possibility to endogenously resolve hydrogen demand as a function of competition between technologies to meet energy service demands while considering wider interactions with climate and the economy. Such models are typically configured with relatively low spatial and temporal resolution thereby limiting their utility in studying future global hydrogen trade scenarios. This work presents a framework for the soft-linking of IAM scenarios to a higher spatial and temporal resolution global model. This framework provides an “engine” with which to generate future-looking coupled hydrogen & electricity models with the co-optimization of production capacity, storage, and transmission infrastructure that allow the user to vary key technoeconomic input parameters. The modelling framework is applied to an IAM scenario and validated against the parent IAM. The utility of the model when examining electricity & hydrogen commodity trade in future scenarios is then demonstrated.

Fire weather compromises forestation-reliant climate mitigation pathways

Abstract. Forestation can contribute to climate change mitigation. However, increasing frequency and intensity of climate extremes are posed to have profound impact on forests and consequently on the mitigation potential of forestation efforts. In this perspective, we critically assess forestation-reliant climate mitigation scenarios from five different integrated assessment models (IAMs) by showcasing the spatially explicit exposure of forests to fire weather and the simulated increase in global annual burned area. We provide a detailed description of the feedback from climate change to forest carbon uptake in IAMs. Few IAMs are currently accounting for feedback mechanisms like loss from fire disturbance. Consequently, many forestation areas proposed by IAM scenarios will be exposed to fire-promoting weather conditions and without costly prevention measures might be object to frequent burning. We conclude that the actual climate mitigation portfolio in IAM scenarios is subject to substantial uncertainty and that the risk of overly optimistic estimates of negative emission potential of forestation should be avoided. As a way forward we propose how to integrate more detailed climate information when modeling climate mitigation pathways heavily relying on forestation.

Decarbonizing the cement industry: Findings from coupling prospective life cycle assessment of clinker with integrated assessment model scenarios

In the race to achieve global climate neutrality, carbon intensive industries like the clinker and cement industry are required to decarbonize rapidly. The environmental impacts related to potential transition pathways to low-carbon systems can be evaluated using prospective life cycle assessment (pLCA). This study conducts a pLCA for future global clinker production, integrating long-term transition pathways from the IMAGE integrated assessment model (IAM) to maintain global consistency. It systematically modifies the ecoinvent v3.9.1 database using the Python library premise to create future database versions representing future clinker production embedded in a future economy according to a 3.5°C-baseline, a 2°C-compliant and a 1.5°C-compliant scenario. Our study indicates that climate change impacts of clinker production may decrease from about 1.03 kg CO2-eq/kg clinker in 2020 to 0.94 (3.5°C-baseline), 0.20 (2°C-compliant), and 0.16 (1.5°C-compliant) kg CO2-eq/kg clinker in 2060 for the global average. This corresponds to a 10% (3.5°C-baseline), 81% (2°C-compliant) and 84% (1.5°C-compliant) decrease by 2060 compared to 2020. Under these scenarios, global clinker production alone would require 5%–11% of the remaining end-of-century carbon budget for the 2 °C and 1.5 °C-target, respectively. While the climate change impacts are substantially reduced, our study also indicates that the transition pathways shift the burden towards other impact categories, such as ionizing radiation, ozone depletion, material resources and land use. Developing IAM-compatible scenarios for more product groups helps to increase the coherence of pLCA studies. As this study is based on an IAM heavily reliant on carbon capture and storage and bioenergy, future research should explore the effects of different technology pathways and alternative mitigation strategies.

Socio-technical modelling of UK energy transition under three global SSPs, with implications for IAM scenarios

The potential for using findings from socio-technical energy transition (STET) models in integrated assessment models (IAMs) has been proposed by several authors. A STET simulation model called TEMPEST, which includes the influence of societal and political factors in the UK’s energy transition, is used to model three of the global shared socioeconomic pathways (SSPs) at the national level. The SSP narratives are interpreted as inputs to TEMPEST, which drive scenario simulations to reflect varying societal preferences for mitigation measures, the level of political support for energy transition, and future economic and population trends. SSP1 and SSP2 come close to meeting UK net zero targets in 2050 but SSP5 does not reach net zero before 2080. An estimate of the total societal, political, and economic cost of scenarios indicates that while SSP1 achieves the best emissions reductions it also has the highest total cost, and SSP2 achieves the best ratio between rate of emissions reductions and total cost. Feasibility appears to be highest for SSP2 since it is the least different to historical precedent. Current UK government energy strategy is closer to the narrative in SSP5, however, which has the highest total cost and exceeds an estimated carbon budget by 32%. Three key TEMPEST findings are recommended for use in IAMs: (i) the uncertainty in emissions savings due to variability in political and societal support for energy transition, (ii) the influence of negative societal pushback to policies in achievement of expected policy outcomes, and (iii) the combined influence on energy service demand of disposable income, public willingness to participate, and user impacts from measures.

Emissions Lock-in, Capacity, and Public Opinion: How Insights From Political Science Can Inform Climate Modeling Efforts

The implementation of ambitious climate policies consistent with the goals of the Paris Agreement is fundamentally influenced by political dynamics. Yet, thus far, climate mitigation pathways developed by integrated assessment models (IAMs) have devoted limited attention to the political drivers of climate policymaking. Bringing together insights from the political science and socio-technical transitions literature, we summarize evidence on how emissions lock-in, capacity, and public opinion can shape climate policy ambition. We employ a set of indicators to describe how these three factors vary across countries and regions, highlighting context-specific challenges and enablers of climate policy ambition. We outline existing studies that incorporate political factors in IAMs and propose a framework to employ empirical data to build climate mitigation scenarios that incorporate political dynamics. Our findings show that there is substantial heterogeneity in key political drivers of climate policy ambition within IAM regions, calling for a more disaggregated regional grouping within models. Importantly, we highlight that the political challenges and enablers of climate policy ambition considerably vary across regions, suggesting that future modeling efforts incorporating political dynamics can significantly increase the realism of IAM scenarios.

Country-resolved combined emission and socio-economic pathways based on the Representative Concentration Pathway (RCP) and Shared Socio-Economic Pathway (SSP) scenarios

Abstract. Climate policy analysis needs reference scenarios to assess emission targets and current trends. When presenting their national climate policies, countries often showcase their target trajectories against fictitious so-called baselines. These counterfactual scenarios are meant to present future greenhouse gas (GHG) emissions in the absence of climate policy. These so-called baselines presented by countries are often of limited use, as they can be exaggerated and as the methodology used to derive them is usually not transparent. Scenarios created by independent modeling groups using integrated assessment models (IAMs) can provide different interpretations of several socio-economic storylines and can provide a more realistic backdrop against which the projected target emission trajectory can be assessed. However, the IAMs are limited in regional resolution. This resolution is further reduced in intercomparison studies, as data for a common set of regions are produced by aggregating the underlying smaller regions. Thus, the data are not readily available for country-specific policy analysis. This gap is closed by downscaling regional IAM scenarios to the country level. The last of such efforts has been performed for the SRES (“Special Report on Emissions Scenarios”) scenarios, which are over a decade old by now. CMIP6 (Coupled Model Intercomparison Project phase 6) scenarios have been downscaled to a grid; however they cover only a few combinations of forcing levels and SSP storylines with only a single model per combination. Here, we provide up-to-date country scenarios, downscaled from the full RCP (Representative Concentration Pathway) and SSP (Shared Socio-Economic Pathway) scenario databases, using results from the SSP GDP (gross domestic product) country model results as drivers for the downscaling process. The data are available at https://doi.org/10.5281/zenodo.3638137 (Gütschow et al., 2020).

Silicone v1.0.0: an open-source Python package for inferring missing emissions data for climate change research

Abstract. Integrated assessment models (IAMs) project future anthropogenic emissions which can be used as input for climate models. However, the full list of climate-relevant emissions is lengthy and most IAMs do not model all of them. Here we present Silicone, an open-source Python package which infers anthropogenic emissions of unmodelled species based on other reported emissions projections. For example, it can infer nitrous oxide emissions in one scenario based on carbon dioxide emissions from that scenario plus the relationship between nitrous oxide and carbon dioxide emissions found in other scenarios. Infilling broadens the range of IAMs available for exploring projections of future climate change, and hence Silicone forms part of the open-source pipeline for assessments of the climate implications of IAM scenarios, led by the Integrated Assessment Modelling Consortium (IAMC). This paper presents a variety of infilling options and outlines their suitability for different cases. We recommend certain infilling techniques as good defaults but emphasise that considering the specifics of the model being infilled will produce better results. We demonstrate the package's utility with three examples: infilling all required gases for a pathway with data for only one emission species, splitting up a Kyoto emissions total into separate gases, and complementing a set of idealised emissions curves to provide a complete, consistent emissions portfolio. The code and notebooks explaining details of the package and how to use it are available on GitHub (https://github.com/GranthamImperial/silicone, last access: 2 November 2020). The repository with this paper's examples and uses of the code to complement existing research is available at https://github.com/GranthamImperial/silicone_examples (last access: 2 November 2020).

From Zero to Hero?: Why Integrated Assessment Modeling of Negative Emissions Technologies Is Hard and How We Can Do Better

Climate change mitigation strategies informed by Integrated Assessment Models (IAMs) increasingly rely on major deployments of negative emissions technologies (NETs) to achieve global climate targets. Although NETs can strongly compliment emissions mitigation efforts, this dependence on the presumed future ability to deploy NETs at scale raises questions about the structural elements of IAMs that are influencing our understanding of their deployment. Model inter-comparison results underpinning the IPCC’s special report on Global Warming of 1.5oC were used to explore the role that current assumptions are having on projections and the way in which emerging technologies, economic factors, innovation, and tradeoffs between negative emissions objectives and UN Sustainable Development Goals might have on future deployment of NETs. Current generation IAM scenarios widely assume we are capable of scaling up NETs over the coming 30 years to achieve negative emissions of the same order of magnitude as current global emissions (tens of gigatons of CO2/year) predominantly relying on highly land intensive NETs. While the technological potential of some of these approaches (e.g., direct air capture) is much greater than for the land-based technologies, these are seldom included in the scenarios. Alternative NETs (e.g., accelerated weathering) are generally excluded because of connections with industrial sectors or earth system processes that are not yet included in many models. In all cases, modeling results suggest that significant NET activity will be conducted in developing regions, raising concerns about tradeoffs with UN Sustainable Development Goals. These findings provide insight into how to improve treatment of NETs in IAMs to better inform international climate policy discussions. We emphasize the need to better understand relative strength and weaknesses of full suite of NETs that can help inform the decision making for policy makers and stakeholders.

Preconditions for bioenergy with carbon capture and storage (BECCS) in sub-Saharan Africa: the case of Tanzania

Most mitigation scenarios compatible with a likely change of holding global warming well below 2 °C rely on negative emissions technologies (NETs). According to the integrated assessment models (IAMs) used to produce mitigation scenarios for the IPCC reports, the NET with the greatest potential to achieve negative emissions is bioenergy with carbon capture and storage (BECCS). Crucial questions arise about where the enormous quantities of biomass needed according to the IAM scenarios could feasibly be produced in a sustainable manner. Africa is attractive in the context of BECCS because of large areas that could contribute biomass energy and indications of substantial underground CO2 storage capacities. However, estimates of large biomass availability in Africa are usually based on highly aggregated datasets, and only a few studies explore future challenges or barriers for BECCS in any detail. Based on previous research and literature, this paper analyses the pre-conditions for BECCS in Tanzania by studying what we argue are the applications of BECCS, or the components of the BECCS chain, that are most feasible in the country, namely (1) as applied to domestic sugarcane-based energy production (bioethanol), and (2) with Tanzania in a producer and re-growth role in an international BECCS chain, supplying biomass or biofuels for export to developed countries. The review reveals that a prerequisite for both options is either the existence of a functional market for emissions trading and selling, making negative emissions a viable commercial investment, or sustained investment through aid programmes. Also, historically, an important barrier to the development of production capacity of liquid biofuels for export purposes has been given by ethical dilemmas following in the wake of demand for land to facilitate production of biomass, such as sugarcane and jatropha. In these cases, conflicts over access to land and mismanagement have been more of a rule than an exception. Increased production volumes of solid biomass for export to operations that demand bioenergy, be it with or without a CCS component, is likely to give rise to similar conflicts. While BECCS may well play an important role in reducing emissions in countries with high capacity to act combined with existing large point sources of biogenic CO2 emissions, it seems prudent to proceed with utmost caution when implicating BECCS deployment in least developed countries, like Tanzania.The paper argues that negative BECCS-related emissions from Tanzania should not be assumed in global climate mitigation scenarios.

When the Background Matters: Using Scenarios from Integrated Assessment Models in Prospective Life Cycle Assessment

SummaryProspective life cycle assessment (LCA) needs to deal with the large epistemological uncertainty about the future to support more robust future environmental impact assessments of technologies. This study proposes a novel approach that systematically changes the background processes in a prospective LCA based on scenarios of an integrated assessment model (IAM), the IMAGE model. Consistent worldwide scenarios from IMAGE are evaluated in the life cycle inventory using ecoinvent v3.3. To test the approach, only the electricity sector was changed in a prospective LCA of an internal combustion engine vehicle (ICEV) and an electric vehicle (EV) using six baseline and mitigation climate scenarios until 2050. This case study shows that changes in the electricity background can be very important for the environmental impacts of EV. Also, the approach demonstrates that the relative environmental performance of EV and ICEV over time is more complex and multifaceted than previously assumed. Uncertainty due to future developments manifests in different impacts depending on the product (EV or ICEV), the impact category, and the scenario and year considered. More robust prospective LCAs can be achieved, particularly for emerging technologies, by expanding this approach to other economic sectors beyond electricity background changes and mobility applications as well as by including uncertainty and changes in foreground parameters. A more systematic and structured composition of future inventory databases driven by IAM scenarios helps to acknowledge epistemological uncertainty and to increase the temporal consistency of foreground and background systems in LCAs of emerging technologies.

A Biophysical Perspective of IPCC Integrated Energy Modelling

The following article conducts an analysis of the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5), specifically in relation to Integrated Assessment Models (IAMs). We focus on the key drivers of economic growth, how these are derived and whether IAMs properly reflect the underlying biophysical systems. Since baseline IAM scenarios project a three- to eight-fold increase in gross domestic product (GDP)-per-capita by 2100, but with consumption losses of only between 3–11%, strong mitigation seems compatible with economic growth. However, since long-term productivity and economic growth are uncertain, they are included as exogenous parameters in IAM scenarios. The biophysical economics perspective is that GDP and productivity growth are in fact emergent parameters from the economic-biophysical system. If future energy systems were to possess worse biophysical performance characteristics, we would expect lower productivity and economic growth, and therefore, the price of reaching emission targets may be significantly costlier than projected. Here, we show that IAMs insufficiently describe the energy-economy nexus and propose that those key parameters are integrated as feedbacks with the use of environmentally-extended input-output analysis (EEIOA). Further work is required to build a framework that can supplement and support IAM analysis to improve biophysical rigour.

Climate extremes, land-climate feedbacks and land-use forcing at 1.5°C.

This article investigates projected changes in temperature and water cycle extremes at 1.5°C of global warming, and highlights the role of land processes and land-use changes (LUCs) for these projections. We provide new comparisons of changes in climate at 1.5°C versus 2°C based on empirical sampling analyses of transient simulations versus simulations from the ‘Half a degree Additional warming, Prognosis and Projected Impacts’ (HAPPI) multi-model experiment. The two approaches yield similar overall results regarding changes in climate extremes on land, and reveal a substantial difference in the occurrence of regional extremes at 1.5°C versus 2°C. Land processes mediated through soil moisture feedbacks and land-use forcing play a major role for projected changes in extremes at 1.5°C in most mid-latitude regions, including densely populated areas in North America, Europe and Asia. This has important implications for low-emissions scenarios derived from integrated assessment models (IAMs), which include major LUCs in ambitious mitigation pathways (e.g. associated with increased bioenergy use), but are also shown to differ in the simulated LUC patterns. Biogeophysical effects from LUCs are not considered in the development of IAM scenarios, but play an important role for projected regional changes in climate extremes, and are thus of high relevance for sustainable development pathways.This article is part of the theme issue ‘The Paris Agreement: understanding the physical and social challenges for a warming world of 1.5°C above pre-industrial levels'.

Expert assessment concludes negative emissions scenarios may not deliver

Many integrated assessment models (IAMs) rely on the availability and extensive use of biomass energy with carbon capture and storage (BECCS) to deliver emissions scenarios consistent with limiting climate change to below 2 °C average temperature rise. BECCS has the potential to remove carbon dioxide (CO2) from the atmosphere, delivering ‘negative emissions’. The deployment of BECCS at the scale assumed in IAM scenarios is highly uncertain: biomass energy is commonly used but not at such a scale, and CCS technologies have been demonstrated but not commercially established. Here we present the results of an expert elicitation process that explores the explicit and implicit assumptions underpinning the feasibility of BECCS in IAM scenarios. Our results show that the assumptions are considered realistic regarding technical aspects of CCS but unrealistic regarding the extent of bioenergy deployment, and development of adequate societal support and governance structures for BECCS. The results highlight concerns about the assumed magnitude of carbon dioxide removal achieved across a full BECCS supply chain, with the greatest uncertainty in bioenergy production. Unrealistically optimistic assumptions regarding the future availability of BECCS in IAM scenarios could lead to the overshoot of critical warming limits and have significant impacts on near-term mitigation options.