Integrated Assessment Model Research Articles

The Role of Renewable-Derived Plastics in the Analysis of Waste Management Schemes: A Time-Dependent Carbon Cycle Assessment

Carbon capture and storage (CCS) is an essential greenhouse gas removal (GGR) technology used to achieve negative emissions in bioenergy plants using biomass feedstock (Bio-CCS). In this study, the climate mitigation potential of a novel GGR technology consisting in the production of renewable-derived plastics from municipal solid waste (MSW) refuse has been evaluated. This novel GGR technology allows for carbon storage, for variable periods, in stable materials (plastics), and thus overcomes the technical limitations of CCS. A time-dependent carbon cycle assessment has been conducted based on the Absolute Global surface Temperature change Potential (AGTP) metric. This new method to assess carbon emissions is presented against a traditional life cycle assessment (LCA). The production of renewable-derived plastics proves to be an effective GGR technology for both landfill- and incineration-dominant countries in Europe. The results obtained encourage the implementation of renewable-derived plastics in Integrated Assessment Models (IAMs) to assess their global potential in forecasting scenarios to achieve the ambitious climate change targets set in the European Union. Thanks to this study, a novel approach toward a green and sustainable economy has been established. This study will help to fill the gaps between bioenergy and renewable materials production.

Impact of the energy transition on long-term factor productivity

In this article, we propose to build a statistical model for factor productivity and illustrate our predictions on a common toy model : DICE. Data show that the variation of primary exergy, or simply called exergy is a good predictor of the TFP variation. That remark allows us to design new economic scenarios that respect the Paris Agreement. These scenarios are of particular interest for policy makers. Moreover, our model is capable to reconcile different projections by the introduction of environmental constraints. On one hand, if exergy increases, we have similar projections with standard economic models. On the other hand, if exergy decreases, we obtain projections closer to other Integrated Assessment Models, where economic output declines (Meadows et al., 2013; Capellán-Pérez et al., 2020).

Understanding expectations from and capabilities of climate-economy models for measuring the impact of crises on sustainability

The multi-faceted emergencies of our time (recession, pandemics, and international conflict) can disrupt progress towards sustainable development goals (SDGs). While climate-economy models can show pathways out of these disruptions, numerous stakeholder-informed enhancements are required to navigate through the interconnected SDG landscape. We introduce a novel Fuzzy Cognitive Maps (FCMs) approach that integrates Monte Carlo simulations, aiming to capture and understand the differences among modellers' and experts' perceptions of the impacts of such crises on broader sustainability, considering models’ existing/planned capacity and uncertainty over perceived magnitude and propagation of impacts across SDGs. Our application shows that expert stakeholders appeared more concerned over the implications of these crises for sustainable development than modellers, but expectations were considerably constrained by model capabilities. SDGs 8 (growth), 7 (energy-sector sustainability), and 13 (climate action) were robustly found as most prone to examined shocks. Our proposed Monte Carlo Fuzzy Cognitive Mapping (MCFCM) approach also highlighted potentially important propagation effects as well as gaps in integrated assessment model capabilities to holistically study the SDG spectrum.

Green investment and asset stranding under transition scenario uncertainty

Risks and opportunities related to environmental transition are usually evaluated through the use of scenarios, produced and maintained by international bodies such as the International Energy Agency. This approach assumes perfect knowledge of the scenario by the agent, but in reality, scenario uncertainty is an important obstacle for making optimal investment or divestment decisions. In this paper, we develop a real-options approach to evaluate assets and potential investment projects under dynamic climate transition scenario uncertainty. We use off-the-shelf Integrated Assessment Model (IAM) scenarios and assume that the economic agent acquires the information about the scenario progressively by observing a signal, such as the carbon price or the greenhouse gas emissions. The problem of valuing an investment is formulated as an American option pricing problem, where the optimal exercise time corresponds to the time of entering a potential investment project or the time of selling a potentially stranded asset. To illustrate our approach, we employ representative scenarios from the scenario database of the Network for Greening the Financial System in two energy-related examples: the divestment decision from a coal-fired power plant without Carbon Capture and Storage (CCS) technology and the potential investment into a green coal-fired power plant with CCS. In both cases, we find that the real option value is very sensitive to scenario uncertainty: the value of the coal-fired power plant is reduced by 25% and that of the green coal investment project is reduced by 7% when the agent deduces the scenario by observing carbon emissions, compared to the setting when the true scenario is known. We also find that scenario uncertainty can lead to considerable delays in the implementation of green investment projects, emphasizing the importance of timely and precise climate policy information.

Global residential scenarios towards low energy and material demands

Transition to low energy and material demand (LEMD) for buildings is key to reach climate change mitigation and sustainability targets but will require unprecedent technological and social transformations. Scenarios addressing LEMD transformations for the global building sector are still largely unexplored. In this study, we assess global residential energy and material demands until 2050 for three alternative sustainable development pathways (SDPs): Economy-driven innovation (EI), driven by technology and energy efficiency; Resilient communities (RC), a post-growth scenario centred around local communities and behavioural change; and Managing the global commons (MC), with strong global institutions and high electrification. We use the bottom-up framework MESSAGEix-Buildings, soft-linked to the integrated assessment model MESSAGEix-GLOBIOM, to model the three SDPs for the global residential sector. We show that the RC scenario entails the highest potential towards reducing energy and material demand driven by behavioural change. The EI and MC scenarios are characterized by relatively higher energy and material demand levels and might require additional efforts on the supply-side to reduce total building-related operational and construction greenhouse gases emissions. This study can support decision making on strategies towards sustainability and zero-energy and emission targets in the buildings sector.

Industry’s role in Japan’s energy transition: soft-linking GCAM and National IO table with extended electricity supply sectors

Japan’s energy transition towards carbon neutrality by 2050 will require a shift from fossil fuel energy on the energy supply side. The introduction of new power generation capacities and infrastructures will then lead to increasing demand for materials and industrial products. To capture such industrial energy service demand, we conducted a soft-linking between an integrated assessment model (GCAM) with an input–output framework (IONGES), considering both inter-model and inter-period iteration. The results show that: i) the industrial final energy under the carbon neutrality scenario would be 0.2-0.7EJ more after linking, which is almost the gap between the carbon neutrality and the reference scenario; ii) to achieve carbon neutrality by 2050, more power generation capacities would be introduced in the near-term periods (2020-2030), bringing additional growth afterward. Our soft-linking approach emphasized the role of industries in the energy transition and explored how industries can benefit from an increasingly low-carbon energy supply.

Temperature and GDP: A review of climate econometrics analysis

Climate econometric analysis of the relationship between temperature and gross domestic product (GDP) is increasingly being used to evaluate climate risks and understand economic impacts caused by climate change. We review the literature on growth and level effects (i.e., temperature rise respectively affects the growth and level of economic output), the setting of temperature variables’ forms and functional forms, and the inherent model specification of climate econometrics. Additionally, we introduce an approach for combining empirical findings with climate change integrated assessment models (IAMs) to improve damage modelling. Our findings show that estimates of damage through growth effects are generally much larger than those through level effects. Diverse impact mechanisms and adaptation effects can be revealed by changing the time resolution of temperature variables, introducing non-linearity into econometrics functions, and specifying temperature deviation. Combing the cross-sectional and panel model would enable us to examine the economic impacts at different future times.

Validity and Validation of Computer Simulations—A Methodological Inquiry with Application to Integrated Assessment Models

Our purpose is to advance a reasoned perspective on the scientific validity of computer simulation, using an example—integrated assessment modeling of climate change and its projected impacts—that is itself of great and urgent interest to policy in the real world. The spirited and continuing debate on the scientific status of integrated assessment models (IAMs) of global climate change has been conducted mostly among climate change modelers and users seeking guidance for climate policy. However, it raises a number and variety of issues that have been addressed, with various degrees of success, in other literature. The literature on methodology of simulation was mostly skeptical at the outset but has become more nuanced, casting light on some key issues relating to the validity and evidentiary standing of climate change IAMs (CC-IAMs). We argue that the goal of validation is credence, i.e., confidence or justified belief in model projections, and that validation is a matter of degree: (perfect) validity is best viewed as aspirational and, other things equal, it makes sense to seek more rather than less validation. We offer several conclusions. The literature on computer simulation has become less skeptical and more inclined to recognize that simulations are capable of providing evidence, albeit a different kind of evidence than, say, observation and experiments. CC-IAMs model an enormously complex system of systems and must respond to several challenges that include building more transparent models and addressing deep uncertainty credibly. Drawing on the contributions of philosophers of science and introspective practitioners, we offer guidance for enhancing the credibility of CC-IAMs and computer simulation more generally.

Auditing Public Debt Using Risk Management

The Audit Office of the Republic of Cyprus conducted the first-ever audit of the country’s public debt, seeking answers to two key questions. Is government debt sustainable, and is debt financing efficient and effective in securing the lowest cost with acceptable risks? The audit’s findings were discussed by the parliament and can have significant ramifications for public finance. However, public debt management is quite complex, and the International Organization of Supreme Audit Institutions suggests that sufficient technical knowledge is essential in undertaking an audit, including an understanding of the uncertain macroeconomy, financing conditions, and government fiscal stance. We use a risk management model based on scenario trees in conducting the audit. The model determines optimal debt financing strategies to benchmark the performance of the country’s Public Debt Management Office and answer the audit questions. We also incorporate an integrated assessment model to examine the risks from climate change. The auditor general presented the findings to the Parliamentary Audit Committee in the presence of the Minister of Finance, and his recommendations are expected to have a significant impact on the debt operations of the country. History: This paper was refereed. Funding: This work was supported by the Auditor General Office of the Republic of Cyprus. A. Consiglio was partially funded by NRRP-GRINS [Grant PE00000018].

Variable renewable energy deployment in low-emission scenarios: The role of technology cost and value

While rapid deployment of variable renewable energy (VRE) technologies, namely wind and solar PV, is often projected in 2C pathways generated by integrated assessment models, there is a wide range in projected VRE deployment by mid-century. Such differences could be the result of differences in assumptions about future technology costs and/or differences in model approaches for capturing other aspects of technology competitiveness. Here we introduce a consistent competitiveness metric, profitability-adjusted levelized cost of electricity (or PLCOE), to an integrated assessment model (EPPA) to evaluate the representation of technology competition, including VRE, in low-emission scenarios. We show that representing the value of technology (alongside cost) may significantly impact VRE deployment relative to scenarios without such an adjustment. In addition, we show that varying VRE costs by about 35% in 2050 results in differences in VRE deployment that span much of the range in outcomes (over the same period) observed in likely 2C scenarios assessed by the IPCC, suggesting that both cost and value are key drivers of VRE deployment in such scenarios. Given the central role that VRE technologies play in the electricity mix across most scenarios, we also find that alternative cost assumptions for VRE technologies can lead to changes in electricity prices, the associated demand for electricity, and total final and primary energy consumption. However, the demand for fuels other than electricity is relatively insensitive to VRE assumptions in the 2C scenarios considered here.

A multimodel analysis of post-Glasgow climate targets and feasibility challenges

The COP26 Glasgow process resulted in many countries strengthening their 2030 emissions reduction targets and announcing net-zero pledges for 2050–2070 but it is not clear how this would impact future warming. Here, we use four diverse integrated assessment models (IAMs) to assess CO2 emission trajectories in the near- and long-term on the basis of national policies and pledges, combined with a non-CO2 infilling model and a simple climate model to assess the temperature implications. We also consider the feasibility of national long-term pledges towards net-zero. While near-term pledges alone lead to warming above 2 °C, the addition of long-term pledges leads to emissions trajectories compatible with a future well below 2 °C, across all four IAMs. However, while IAM heterogeneity translates to diverse decarbonization pathways towards long-term targets, all modelled pathways indicate several feasibility concerns, relating to the cost of mitigation and the rates and scales of deployed technologies and measures. Although many countries have strengthened their emissions reduction pledges, their ability to limit the warming outcomes is still in question. A multimodel analysis demonstrates that these trajectories are in line with the 2 °C target but countries probably face feasibility challenges to achieve them.

Expanding the possible: exploring the role for heterodox economics in integrated climate-economy modeling

This paper explores the degree to which heterodox economics can contribute to the development and use of climate-economy integrated assessment models. To do so, it introduces the field of integrated assessment modeling, with a focus on the core economic methodology used by various types of models. It then summarizes some of the literature critiquing these models and how they inform policy. The paper then provides an extended classification of ways in which heterodox economics could be applied to climate-economy models and presents a number of storylines, or pathways, which could be created using insights and methods from heterodox schools. The paper concludes with an assessment of the scope for heterodox economics to answer the criticisms of climate-economy models, finding that despite not resolving all issues, the heterodoxy has a substantial role to play.

An Integrated Assessment Model for comparing electricity decarbonisation scenarios: The case for Spain

The decarbonisation of electricity supply poses a major milestone in the mitigation of climate change. Integrated Assessment Models (IAMs) provide a relevant instrument for the quantification and comparison of the economic and environmental impacts of various electricity decarbonisation scenarios, despite having rarely been applied to a national context. In this paper, an IAM able to calculate such impacts on the electricity sector in Spain is presented. Developed using the latest IAM modelling literature, the proposed model is able to estimate changes in temperature, climate-induced economic losses, and investment needs for climate mitigation corresponding to a range of electricity decarbonisation scenarios on a time horizon to 2050. The findings show that scenarios that undertake deeper and earlier cuts in CO2 emissions from electricity generation would achieve better welfare results, and that further reliance on fossil fuels would imply higher costs than the investment needed for renewable energy deployment in Spain. The findings constitute an insight towards the formulation of policies that address the decarbonisation of the Spanish electricity supply.

A quantitative risk assessment approach for developing contingency plans at a geologic carbon storage site

AbstractGeologic carbon storage (GCS) is an increasingly important technology for reducing carbon dioxide (CO2) emissions to the atmosphere. The leakage risks associated with GCS are an environmental and human health concern, however, and site operators must develop contingency plans that thoroughly consider leakage risks and identify potential mitigation strategies. Here, we use a GCS system model (the National Risk Assessment Partnership's Open‐Source Integrated Assessment Model, NRAP‐Open‐IAM) to evaluate different contingency plans for a hypothetical GCS site. In the scenario considered, an unplugged legacy well is discovered near the site after 5 years of CO2 injection. Our simulations show that the planned operation has a relatively high chance of causing brine leakage through the legacy well and into the two overlying aquifers, the shallower of which has potable water—an unacceptable outcome. To reduce this risk, we consider five remedial response scenarios that manipulate reservoir pressures through brine extraction, injection rate reduction, and early injection stopping. NRAP‐Open‐IAM is used to quantify the degree to which each scenario reduces the probability of brine leakage at the site amidst reservoir uncertainty. Evaluation of the different scenarios suggests that reduction of injection rates effectively reduces leakage risks while maintaining a substantial fraction of the initially intended cumulative CO2 storage. In the event of an emergency, the reservoir pressure management strategies considered here can provide operators more time while they pursue a more permanent solution. The analyses demonstrated here fit into a larger workflow we propose for evaluating the contingency plans of GCS sites. © 2023 Society of Chemical Industry and John Wiley & Sons, Ltd.

Climate change mitigation costs reduction caused by socioeconomic-technological transitions

Numerical scenarios generated by Integrated Assessment Models describing future energy and land-use systems that attain climate change mitigation goals have been considered important sources of guidance for climate policymaking. The climate change mitigation cost is one of the concerns in the emissions reduction efforts. However, how to moderate climate change mitigation costs is not well understood. Here, we describe the conditions needed for reducing or taking away climate change mitigation costs by implementing socioeconomic-technological transitions into numerical scenario assessment. The results indicate that integration of multiple socioeconomic-technological transitions would be effective, including lowering energy demand, shifting to an environmentally friendly food system, energy technology progress and the stimulus of capital formation that is additionally imposed to the normal carbon pricing mechanism. No single measure is sufficient to fully take away mitigation costs. These results indicate that cross-sectoral transformation is needed, as the realisation of all measures depends on effective government policies as well as uncertain social and technological changes.

The mutual benefits of comparing energy system models and integrated assessment models

Background: The transition to a carbon neutral society such as that envisaged in the European Union Green Deal requires careful and comprehensive planning. Integrated assessment models (IAMs) and energy system models (ESMs) are both commonly used for policy advice and in the process of policy design. In Europe, a vast landscape of these models has emerged and both kinds of models have been part of numerous model comparison and model linking exercises. However, IAMs and ESMs have rarely been compared or linked with one another. Methods: This study conducts an explorative comparison and identifies possible flows of information between 11 of the integrated assessment and energy system models in the European Climate and Energy Modelling Forum. The study identifies and compares regional aggregations and commonly reported variables We define harmonised regions and a subset of shared result variables that enable the comparison of results across the models. Results: The results highlight similarities and differences on final electricity demand, electricity supply and hydrogen across three levels of aggregation. However, the differences between the regional aggregation of the models limit detailed analysis. Conclusions: This first-of-its-kind comparison and analysis of modelling results across model type boundaries provides modellers and policymakers with a better understanding of how to interpret both IAM and ESM results. It also highlights the need for community standards for region definitions and information about reported variables to facilitate future comparisons of this kind.

Sustainable end-of-life value chain scenarios for wind turbine blades

This study presents a sustainable end-of-life (EoL) value chain scenario assessment framework for decommissioned wind turbine blades (WTBs) to address the challenge of increased volumes of WTBs reaching their EoL. Findings from the previous studies highlight that WTBs EoL scenarios and their upscaling are yet to be addressed environmentally and economically. The scenarios investigated herein are mechanical shredding, pyrolysis, and cement co-processing that can be industrially upscaled. Together with the industrial partners, end-of-life scenario value chains are identified, to assess their sustainability through material flow analysis (MFA), life cycle assessment (LCA), and techno-economic assessment (TEA). A prospective consequential LCA model is proposed for scenarios with different technology readiness levels (TRL) expected to be commercialized at different timeframes. IPCC’s Shared Socio-economic Pathways (SSPs) will be used to describe foreground and background systems in 2030, 2040, and 2050. More specifically, SSP1 (i.e., green road), SSP2 (i.e., middle road), and SSP5 (i.e., fossil-fueled development) will be employed and quantified based on integrated assessment models (IAM). Furthermore, environmental impacts, economic criteria, Social sustainability, and circularity cannot directly be compared to evaluate the scenarios. Thus, this research proposes multi-criteria decision-making (MCDM) method to evaluate the three end-of-life scenario value chains considering a prospective scheme and addressing the key challenges related to the assessment of emerging technologies. Furthermore, a full conceptual framework of the methodology is presented.

The Social Cost of Carbon When We Wish for Full-Path Robustness

We compute the social cost of carbon (SCC) when decision makers want robust estimates in the face of deep (or “Knightian”) uncertainty. We introduce the notion of full-path accumulated robust preferences from stochastic control theory to an integrated assessment model. Robust preferences are appropriate for analyzing climate-related problems because, given the large uncertainty in climate science, they enable decision makers to attain solutions that are robust to a wide range of climate change scenarios. We solve the resulting model, which includes uncertainty about climate change and the ensuing economic damage and show the existence of optimal solutions and time-consistent optimal deterministic Markov policies. Additionally, we also prove that the standard Hansen–Sargent recursive utility provides an upper bound of this full-path utility. In our baseline model specification, we find that the year 2020’s optimal SCC is US$162 per tCO2with an average annual growth rate of 2.5%, setting the world on a 1.37°C path, which requires full decarbonization by 2068. We introduce the notion of the SCC robustness premium, which we define as the additional SCC price tag for robustness. For a plausible range of preference parameters, the SCC robustness premium in 2020 is between US$1.41 and US$25.89 per tCO2with US$2.20 per tCO2in our baseline calibration. Over time, this premium grows significantly. The forecasts of our model facilitate managerial decision making during the world’s transition from a carbon- and emission-intensive economy to a regenerative economy. The high estimates for the SCC predict drastic rises in emission costs for high-emission industries.This paper was accepted by Elke Weber, Special Section of Management Science on Business and Climate Change.Funding: Y. Zhao and T. S. Lontzek acknowledge funding by the German Ministry of Research and Education (BMBF), Project CDR: “DAC-Tales”, under [Grant 01LS2196A].Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2023.4736 .

Prospective life cycle assessment of European cement production

Various measures can be employed to decarbonise cement production, including clinker substitution, alternative fuels, kiln improvements, and carbon capture and storage. In this study, we quantify the CO2-eq. emissions mitigation potentials of these measures on typical cement production in Europe until 2050 using prospective life cycle assessment, including the influence of possible futures of socioeconomic development. We combined environmental product declaration data for cement production with a modified life cycle inventory database (based on ecoinvent v.3.6) that incorporates scenarios developed using the IMAGE (Integrated Model to Assess the Global Environment) integrated assessment model (IAM). The IAM translates socio-economic factors into environmental data that follow Shared Socioeconomic Pathways (e.g., SSP2) to consistently describe possible futures of socio-economic development and environmental change beyond cement production, i.e., the ‘background effects’. The results show that in 2050, cement can be produced with significant CO2-eq. emissions reductions using clinker substitution (42%), alternative fuels (25%), or improved kiln efficiency (12%) relative to 2020. When combined, these measures could reduce CO2-eq. emissions of cement production by ∼58% (excluding carbon capture and storage) and ∼88% (including carbon capture and storage) by 2050 relative to year 2020, which could lower CO2-eq. emissions to as low as 0.09 kg per kg cement by 2050. The effect of using future decarbonisation scenarios for the electricity mix on the results is an additional ∼10% reduction in CO2 -eq. emissions by 2050. Multiple credible pathways exist for the cement sector to achieve and surpass CO2-eq. emissions reductions consistent with global climate targets.

Modern Methods of Prediction

Humans have always wanted to know what the future holds in store for them. In earlier centuries, people often sought clues to the future from sacred texts. Today, more secular approaches are increasingly used, although the older approaches to the future persist. Modern methods for prediction include trend extrapolation, the Delphi method, mathematical modeling, and scenario analysis, including backcasting. Extrapolation was only possible when reliable past data became available. The Delphi method relies on the judgement of experts in the subject matter. Mathematical modeling has been very successful in the physical sciences, and, in the form of integrated assessment models (IAMs), has been applied to problems such as assessing future energy use. Scenario analysis looks at a number of possible futures and develops internally consistent story lines around each. It is often used in conjunction with IAMs. Each of the four methods, including both their strengths and weaknesses, are discussed in turn. Finally, this entry looks at the future of prediction, and concludes that despite progress in each of the four approaches treated, predicting the future, never easy, is now harder than ever.