Integrated Assessment Model Research Articles

Towards a green recovery in the EU: Aligning further emissions reductions with short- and long-term energy-sector employment gains

To tackle the negative socioeconomic implications of the COVID-19 pandemic, the European Union (EU) introduced the Recovery and Resilience Facility, a financial instrument to help Member States recover, on the basis that minimum 37% of the recovery funds flow towards the green transition. This study contributes to the emerging modelling literature on assessing COVID-19 vis-à-vis decarbonisation efforts, with a particular focus on employment, by optimally allocating the green part of the EU recovery stimulus in selected low-carbon technologies and quantifying the trade-offs between resulting emissions reductions and employment gains in the energy sector. We couple an integrated assessment model with a multi-objective linear-programming model and an uncertainty analysis framework aiming to identify robust portfolio mixes. We find that it is possible to allocate recovery packages to align mitigation goals with both short- and long-term energy-sector employment, although over-emphasising the longer-term sustainability of new energy-sector jobs may be costlier and more vulnerable to uncertainties compared to prioritising environmental and near-term employment gains. Robust portfolios with balanced performance across objectives consistently feature small shares of offshore wind and nuclear investments, while the largest chunks are dominated by onshore wind and biofuels, two technologies with opposite impacts on near- and long-term employment gains.

Determinants of the distribution of utility-scale photovoltaic power facilities across the globe

Photovoltaic power (PV) is the fastest-growing source of renewable electricity. Making reliable scenarios of PV deployment requires information on what drives the spatial distribution of PV facilities. Here we empirically derive the determinants of the distribution of utility-scale PV facilities across six continents, using a mixed effects logistic regression modelling approach relating the occurrence of over 10 000 PV facilities to a set of potential determinants as well as accounting for country and spatially correlated random effects. Our regression models explain the distribution of PV facilities with high accuracy, with travel times to settlements and irradiation as the main determinants. In contrast, our results suggest that land cover types are not strong determinants of the PV distribution, except for Asia and Africa where the PV distribution is related to the presence of agriculture, short natural vegetation and bare land. For Europe and Asia a considerable part of the variance in PV distribution is explained by inter-country differences in factors not included in our fixed determinants. Relevant determinants identified in our study are in line with the main assumptions made in cost of electricity (COE) maps used in the IMAGE integrated assessment model (IAM). However, we found correlations (Spearman ρ) of −0.18–0.54 between our PV probability maps and IMAGE’s COE maps. These may partly be explained by conceptual differences between our empirically-derived probability maps and the COE maps, but we also recommend using higher-resolution maps of PV potential and COE computations such as used in IAMs.

Social cost of carbon: A revisit from a systems analysis perspective

The social cost of carbon (SCC) is estimated by integrated assessment models (IAMs) and is widely used by government agencies to value climate policy impacts. Although there is an ongoing debate about obtained numerical estimates and related uncertainties, little attention has been paid so far to the SCC calculation method itself. This work attempts to fill the gap by providing the theoretical background and economic interpretation of the SCC calculation approach implemented in the DICE (Dynamic Integrated Climate-Economy) IAM. Our analysis indicates that the present calculation method is unable to reflect the linkages between two key IAM components—complex interconnected systems—climate and economy, both influenced by emission abatement policies. Within the modeling framework of DICE, the presently estimated SCC valuates emissions, which are beyond policy control, against consumption of products, which cannot be produced by the economy. This makes the SCC irrelevant for application in climate-economic policies and, therefore, calls for a replacement by a more appropriate indicator. An apparent SCC alternative, which can be considered for policy formulation, is the direct output of the DICE model, the socially optimal marginal abatement cost (SMAC), which corresponds to technological possibilities at the optimal level of carbon emissions abatement. In policymaking, because of the revealed SCC deficiency, great attention needs to be paid to the use of estimates obtained earlier.

Estimating the Likelihood of GHG Concentration Scenarios From Probabilistic Integrated Assessment Model Simulations

AbstractThe climate scenarios that form the basis for current climate risk assessments have no assigned probabilities, and this impedes the analysis of future climate risks. This paper proposes an approach to estimate the probability of carbon dioxide (CO2) concentration scenarios used in key climate change modeling experiments. It computes the CO2 emissions compatible with the concentrations prescribed by Coupled Model Intercomparison Project Phase 5 (CMIP5) and CMIP6 experiments. The distribution of these compatible cumulative emissions is interpreted as the likelihood of future emissions given a concentration pathway. Using Bayesian analysis, the probability of each pathway can be estimated from a probabilistic sample of future emissions. The approach is demonstrated with five probabilistic CO2 emission simulation ensembles from four Integrated Assessment Models (IAM), leading to independent estimates of the likelihood of the CO2 concentration of Representative Concentration Pathways (RCP) and Shared Socioeconomic Pathways (SSP). Results suggest that SSP5‐8.5 is unlikely for the second half of the 21st century, but offer no clear consensus on which of the remaining scenarios is most likely. Estimates of likelihoods of CO2 concentrations associated with RCP and SSP scenarios are affected by sampling errors, differences in emission sources simulated by the IAMs, and a lack of a common experimental framework for IAM simulations. These shortcomings, along with a small IAM ensemble size, limit the applicability of the results presented here. Novel joint IAM and the Earth System Model experiments are needed to deliver actionable probabilistic climate risk assessments.

Optimal climate policies under fairness preferences

Integrated assessment models are tools largely used to investigate the benefit of reducing polluting emissions and limiting the anthropogenic mean temperature rise. However, they have been often criticized for their underlying assumptions, often leading to low levels of abatement. Countries and regions that are generally the actors in these models are usually depicted as having standard concave utility functions in consumption. This, however, disregards a potentially important aspect of environmental negotiations, namely its distributive implications. The present paper tries to fill this gap assuming that countries/regions have Fehr and Schmidt (The Quarterly Journal of Economics 114(3):817–868, 1999) (F&S) utility functions, specifically tailored for including inequality aversion. By adopting the RICE model, we compare its standard results with the ones obtained introducing F&S utility functions, showing that, under optimal cooperation, the level of temperature rise is lower in the last scenario. In particular, the peak temperature, reached in 2155 under standard assumptions and one or two decades later under F&S preferences with, respectively, heterogeneous and homogeneous F&S inequality aversion parameters (α and β), is of 2.86 ∘C in the former scenario and of 2.65 ∘C and 2.67 ∘C in the latter two. Furthermore, it is shown that potentially stable coalitions are easier to be achieved when F&S preferences are assumed. However, potentially stable coalitions are far from reaching environmental targets close to limiting the mean temperature rise below 2 ∘C despite the adoption of F&S utility functions. The 2 ∘C target is almost achieved in all scenarios when the payoffs in the F&S utility function are given by the per-capita consumption rather than utility of consumption, with F&S preferences and heterogeneous F&S inequality aversion parameters leading to a peak temperature rise of 2.04 ∘C.

Enhancing the realism of decarbonisation scenarios with practicable regional constraints on CO2 storage capacity

• Integrated assessment model scenarios substantially overestimate CO 2 storage potential. • A new storage potential estimate, the investable potential, is introduced. • Reduced CO 2 storage requires faster mitigation and greater use of renewable energy. • Scenarios prioritise very different CCS applications depending on storage availability. • The impact of cross-border trade in CO 2 and low discount rates are also explored. Most low-carbon scenarios produced by integrated assessment models deploy substantial amounts of carbon capture and storage (CCS). These models generally assume that CO 2 storage is a low-cost and globally ubiquitous resource. Here we challenge this assumption, introducing a CO 2 storage potential which accounts for the financial, contractual, and institutional barriers to CO 2 storage, which we term the investable potential. We provide a first estimate of this investable potential and utilise a global energy system model to explore the implications for global and regional mitigation pathways. Our results suggest that low-carbon scenarios which assume abundant CO 2 storage may substantially overestimate the role of CCS in deep decarbonisation, particularly in key regions such as China and India. Limited CO 2 storage leads to mitigation pathways with faster emission reductions and greater reliance on renewable energy for decarbonisation. We demonstrate that the optimal use of CCS depends heavily on the availability of CO 2 storage, with different use-cases prioritised at different scales of storage availability. Finally, we present exploratory analysis on the potential for cross-border trade in captured CO 2 to match sources and sinks. The results of this analysis can help calibrate expectations and inform policy decisions around the role of CCS in addressing climate change.

Limited impact of COVID-19 recovery packages on near-term CO2 emissions pathways

Part of the economic recovery plans implemented by governments following COVID-19 is directed towards the energy transition. To understand the potential effects of these post-COVID green recovery packages on reductions of global greenhouse gas emissions until 2030, we investigated three different approaches. First, we analyzed simulation results of Integrated Assessment Models (IAMs) to infer the change in CO2 intensity of GDP that could result from post-COVID low-carbon investment plans. Second, we investigated the scenarios the International Energy Agency (IEA) provided based on a bottom-up energy system model. Combining the two approaches, we found that green recovery packages implemented and planned globally can lead to an emissions reduction of merely 1%–6% from the 2030 baseline levels at most. Third, we looked into the results of the Adaptative Regional Input-Output model, which simulates the dynamic effects of economic crisis and fiscal stimuli through supply chains following labor shortage. The third approach shows that the increase of activity driven by fiscal stimuli leads to a rebound of CO2 emissions even if they do not target carbon-intensive sectors. We conclude that green recovery packages targeting low-carbon technologies have a limited impact on near-term CO2 emissions and that demand-side incentives, as well as other policy efforts to disincentivize the use of fossil fuels, are also crucial for scaling up climate mitigation.

Synergies of carbon neutrality, air pollution control, and health improvement — a case study of China energy interconnection scenario

Climate change and air pollution are primarily caused by the combustion and utilization of fossil fuels. Both climate change and air pollution cause health problems. Based on the development of China, it is extremely important to explore the synergies of the energy transition, CO2 reduction, air pollution control, and health improvement under the target of carbon peaking before 2030 and carbon neutrality before 2060. This study introduces the policy evolution and research progress related to energy, climate change, and the environment in China and proposes a complete energy-climate-air- health mechanism framework. Based on the MESSAGE-GLOBIOM integrated assessment model, emission inventory and chemical transport model, and exposure-response function, a comprehensive assessment method of energy-climate-air- health synergies was established and applied to quantify the impacts of Chinese Energy Interconnection Carbon Neutrality (CEICN) scenario. The results demonstrate that, by 2060, the SO2, NOx and PM2.5 emissions are estimated to be reduced by 91 %, 85 %, and 90 % respectively compared to the business-as-usual (BAU) scenario. The direct health impacts brought by achieving the goal of carbon neutrality will drive the proactive implementation of more emission reduction measures and bring greater benefits to human health.

Are there synergies in the decarbonization of aviation and shipping? An integrated perspective for the case of Brazil

SummaryAviation and shipping account for 22% of total transport-related CO2 emissions. Low-carbon fuels (such as biofuels and e-fuels) are the most promising alternatives to deeply decarbonize air and maritime transport. A number of technological routes focused on the production of renewable jet fuel can coproduce marine fuels, emulating the economies of scope of crude oil refineries. This work aims to investigate possible synergies in the decarbonization of aviation and shipping in Brazil, selected as an interesting case study. An Integrated Assessment Model (IAM) of national scope is used to explore different combinations of sectoral and national climate targets. This IAM represents not only the energy supply and transport systems but also the agricultural and land-use systems. In the absence of a deep mitigation policy for Brazil, results indicate synergies related to oilseed- and lignocellulosic-based biofuels production routes. Imposing a strict carbon budget to the Brazilian economy compatible with a world well below 2°C, the portfolio of aviation and shipping fuels changes significantly with the need for carbon dioxide removal strategies based on bioenergy. In such a scenario, synergies between the two sectors still exist, but most renewable marine energy supply is a by-product of synthetic diesel produced for road transport, revealing a synergy different from the one originally investigated by this work.

Study of climate change impact on hydro-climatic extremes in the Hanjiang River basin, China, using CORDEX-EAS data

An integrated assessment modelling framework is introduced to comprehensively evaluate the climate change impact on hydro-climatic extremes over the Hanjiang River basin, China. The framework consists of climate model scenarios, bias correction method, hydrological model, and extreme climate and streamflow indices. The outputs from five CORDEX-EAS regional climate models (RCMs) under RCP 2.6 and 8.5 were firstly bias-corrected for two future windows, i.e. near future (2021-2050) and far future (2051-2080), and then used to drive a hydrological model to estimate the changes of extreme climate and streamflow, which were described by 19 standard hydro-climatic indices. The hydrological model was calibrated using a new software developed based on generalized likelihood uncertainty estimation (GLUE) algorithm under parallel computing environment. From the ensemble median of RCMs, it was found that the study basin is expected to be slightly wetter and significantly hotter in the future, with more intense and frequent precipitation and higher temperature extremes. Particularly, the extreme annual maximum 1-day streamflow index would have an overall increase across the basin, with the most significant increase in the south-western part of the basin. The extreme annual minimum 7-day streamflow index is projected to have a significant increase in the northern, south-western and south-eastern parts of the basin in the near future, while it would show a basin-wide decrease in the far future under RCP 8.5. Our findings helped gain an in-depth insight into the responses of hydro-climatic extremes to climate changes for a large-scale watershed and offer valuable guidance to decision makers who are responsible in designing adaptation strategies to mitigate the risks from extreme water-related disasters in the future.

Energy Transition Scenarios for Fossil Fuel Rich Developing Countries under Constraints on Oil Availability: The Case of Ecuador

The aim of this paper is to analyze energy pathways for a fossil fuel rich developing country towards an energy transition considering national and international oil availability using Ecuador as a reference. An integrated assessment model has been developed to simulate energy transition scenarios considering constraints on oil availability at the national and global level. Results show that if current trends in energy demand and supply persist, energy scarcity would start around 2040 due to depletion of national oil reserves and restricted access to foreign oil. This would trigger a degrowth in economic activity in sectors with high dependency on petroleum products. Scenarios with conservative efforts might partially revert the increasing use of fossil fuels supported by policies for energy efficiency and substitution of liquid fuels with electricity mainly from renewables. However, energy shortages would still be foreseeable as well as a decay of the economy. Under a maximum efforts scenario with an optimistic availability of national oil, a moderate-sustained economic growth could be feasible. This shows that oil would still play a key role during the transition. Furthermore, ambitious policies must be implemented in the short term to smooth the effects of displacing oil as energy and income source.

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.

Exploring Global Climate Policy Futures and Their Representation in Integrated Assessment Models

The Paris Agreement, adopted in 2015, paved the way for a new hybrid global climate governance architecture with both bottom-up and top-down elements. While governments can choose individual climate goals and actions, a global stocktake and a ratcheting-up mechanism have been put in place with the overall aim to ensure that collective efforts will prevent increasing adverse impacts of climate change. Integrated assessment models show that current combined climate commitments and policies of national governments fall short of keeping global warming to 1.5 °C or 2 °C above preindustrial levels. Although major greenhouse gas emitters, such as China, the European Union, India, the United States under the Biden administration, and several other countries, have made new pledges to take more ambitious climate action, it is highly uncertain where global climate policy is heading. Scenarios in line with long-term temperature targets typically assume a simplistic and hardly realistic level of harmonization of climate policies across countries. Against this backdrop, this article develops four archetypes for the further evolution of the global climate governance architecture and matches them with existing sets of scenarios developed by integrated assessment models. By these means, the article identifies knowledge gaps in the current scenario literature and discusses possible research avenues to explore the pre-conditions for successful coordination of national policies towards achieving the long-term target stipulated in the Paris Agreement.

Why Ambitious and Just Climate Mitigation Needs Political Science

A large-scale transformation of the energy system, which climate mitigation entails, is a global and highly politicized problem. This thematic issue brings together scholars who work with Integrated Assessment Models (IAMs)—which are used for Intergovernmental Panel on Climate Change (IPCC) reports and other key analyses of future climate trajectories—and social scientists working on climate and energy issues to highlight how the two strands of research could benefit from combining insights across different disciplines and methods. One of the key messages across almost all contributions is that the more technical perspectives could benefit from adjusting their assumptions to reflect the patterns observed in quantitative and qualitative social science. Combining different disciplines is methodologically challenging but promising to ensure that the mitigation strategies developed are considered technically and politically feasible, as well as just.

MUSE: An open-source agent-based integrated assessment modelling framework

Integrated assessment models (IAMs) are a cornerstone of an effective approach to climate change mitigation. Despite the variety of methodologies for characterising the energy system, land use change, economics, and climate response, the modelling community has an open and urgent request for tools capable of more realistic interpretation of the energy transition, capturing human behaviour, and embodying the principles of transparency, reproducibility, and flexibility of use.This paper presents an open-source modelling framework designed to fill that gap. Named MUSE (ModUlar energy systems Simulation Environment), this new agent-based model supports flexible characterisation of agent decision-making, including individual goals, bounded-rationality, imperfect foresight, and limited knowledge during the decision process. MUSE integrates this agent-based approach in a partial-equilibrium framework and enables a technology-rich description of the energy systems with an unprecedented degree of flexibility for including technological, temporal, and geographical granularity. The structure of MUSE creates the ability to produce climate change mitigation assessments that are more grounded, and more tangible model outputs for conceiving effective approaches to mitigation. MUSE is available open source under a GNU General Public License v3.0 on GitHub at this link https://github.com/SGIModel/MUSE_OS.

AIRCC-Clim: A user-friendly tool for generating regional probabilistic climate change scenarios and risk measures

Complex physical models are the most advanced tools available for producing realistic simulations of the climate system. However, such levels of realism imply high computational cost and restrictions on their use for policymaking and risk assessment. Two central characteristics of climate change are uncertainty and that it is a dynamic problem in which international actions can significantly alter climate projections and information needs, including partial and full compliance of global climate goals. Here we present AIRCC-Clim, a simple climate model emulator that produces regional probabilistic climate change projections of monthly and annual temperature and precipitation, as well as risk measures, based both on standard and user-defined emissions scenarios for six greenhouse gases. AIRCC-Clim emulates 37 atm-ocean coupled general circulation models with low computational and technical requirements for the user. This standalone, user-friendly software is designed for a variety of applications including impact assessments, climate policy evaluation and integrated assessment modelling.

Health impact assessment of climate change mitigation and adaptation policies

BACKGROUND AND AIM: Current climate policy focuses on two key aspects: the relevance and extent of mitigation measures to avoid crossing the point of no return; and the necessity for adaptation measures considering socio-economic state and dynamics across the globe. Assessing properly the health benefits of policy measures geared towards adapting to climate change is a key requirement for accurate impact assessment of climate action. METHODS: The climate exposome is the exposome of human population considering the climate change aspects relevant to the life course. The methodological framework for unravelling the climate exposome is presented and examples demonstrating its applicability and usefulness in climate policy are given. The new generation of integrated assessment models entail a model scheme based on enhanced data fusion and on the concept of ensemble modelling, supported by big data analytics for filling data gaps. RESULTS: Drivers pertaining to direct impacts on climate are increased temperatures; precipitation extremes; extreme weather events; and sea level rise. To better understand the impacts of climate change, the environmental and institutional context is accounted for including land use change; ecosystem change; condition of the infrastructure; geography; agricultural production and livestock use. The social and behavioural context including age and gender; race and ethnicity; poverty; housing and infrastructure; education; discrimination; access to shared and community health infrastructure is a significant modifier of the impacts associated with climate change. CONCLUSIONS: The climate exposome addresses interactions among activity sectors and the changing environment; exposure and effects of chemical, physical and biological stressors and waste; interactions among these stressors. Refined tools for understanding the impacts using high dimension biology techniques are crucial. The interplay between vulnerabilities and socio-economic factors affecting exposure profiles and individual susceptibility to these complex exposures determine the ultimate relationship between climate change and health. KEYWORDS: climate change, health, exposome

Projecting the impact of air pollution on child stunting in India—synergies and trade-offs between climate change mitigation, ambient air quality control, and clean cooking access

Many children in India face the double burden of high exposure to ambient (AAP) and household air pollution, both of which can affect their linear growth. Although climate change mitigation is expected to decrease AAP, climate policies could increase the cost of clean cooking fuels. Here, we develop a static microsimulation model to project the air pollution-related burden of child stunting in India up to 2050 under four scenarios combining climate change mitigation (2 °C target) with national policies for AAP control and subsidised access to clean cooking. We link data from a nationally representative household survey, satellite-based estimates of fine particulate matter (PM2.5), a multi-dimensional demographic projection and PM2.5 and clean cooking access projections from an integrated assessment model. We find that the positive effects on child linear growth from reductions in AAP under the 2 °C Paris Agreement target could be fully offset by the negative effects of climate change mitigation through reduced clean cooking access. Targeted AAP control or subsidised access to clean cooking could shift this trade-off to result in net benefits of 2.8 (95% uncertainty interval [UI]: 1.4, 4.2) or 6.5 (UI: 6.3, 6.9) million cumulative prevented cases of child stunting between 2020–50 compared to business-as-usual. Implementation of integrated climate, air quality, and energy access interventions has a synergistic impact, reducing cumulative number of stunted children by 12.1 (UI: 10.7, 13.7) million compared to business-as-usual, with the largest health benefits experienced by the most disadvantaged children and geographic regions. Findings underscore the importance of complementing climate change mitigation efforts with targeted air quality and energy access policies to concurrently deliver on carbon mitigation, health and air pollution and energy poverty reduction goals in India.

Research trends and areas of focus on water rights: a bibliometric analysis 1971-2020.

This study investigated the research trends, key areas, and directions of water rights (WRs) using bibliometric data based on the Science Citation Index Expanded (SCI-E) and Social Sciences Citation Index (SSCI). This paper presents a comprehensive review of annual output, research fields, cooperative networks, published journals, and hot spot evolution from 1971 to 2020. The results show that the number of published papers on WRs has an exponential upward trend. This research mainly focuses on water resources, environmental sciences, environmental studies, law, agronomy, and political science. Rutgerd Boelens and Barbara Van Koppen are authors of the most widely published and influential factors in the field. Leo Heller, Priscila Neves-Silva, and Jeroen Vos have been the most recently active authors. University of New Mexico and the United States Department of Agriculture are the organizations with the most publications and total citations, respectively. The USA, China, Australia, the UK, The Netherlands, and Spain are among the most productive countries for WR research. Keyword analysis showed that the study of WRs has gone through three stages: the exploration of laws and regulations, comprehensive management, and technology development and application. Literature citation cluster analysis shows that a highly central article provides a strong link between internal research on WRs. Western USA, trading WRs, and constitutional reform were hot spots before 2010, while economic anthropology, combined effect, public attitude, and integrated assessment modeling have become popular recently. The study results can help experts understand the research progress in WRs.

Poverty and inequality implications of carbon pricing under the long-term climate target

Many countries have taken stringent climate policies to minimize the risks by climate change. But these policies could burden households and the poor with the extra costs and threaten their wellbeing. However, the consequences of climate policies on poverty and welfare loss are seldom presented in stringent long-term climate change mitigation projections. Carbon pricing is a cost-effective approach; how it affects households varies among countries. This study investigated the distributional effects and poverty implications of carbon pricing in China during the transition towards carbon neutrality and the Paris Agreement’s long-term goals. We assessed multiple poverty and equity standards in future scenarios with a newly developed integrated assessment model. It was found that climate change mitigation efforts would not greatly hinder poverty alleviation in China, with the poverty headcount under the $3.2/cap/day-threshold being less than 0.3 million people in 2050 in most scenarios. A carbon tax became a regressive factor mainly due to price increases in food and energy goods. This indicates that the distributional effects on carbon pricing should be considered. For example, supplementary policies that compensate for price changes, such as subsidies and early mitigation actions, that lead to modest price increases in the long term are worthy of consideration as valid instruments for the just transition towards the 2 °C or even 1.5 °C pathway.