Looking under the hood: A comparison of techno-economic assumptions across national and global integrated assessment models

Krey, Volker; Guo, Fei; Kolp, Peter; Zhou, Weisheng; Schaeffer, Roberto; Awasthy, Aayushi; Bertram, Christoph; Boer, Harmen Sytze de; Fragkos, Panagiotis; Fujimori, Shinichiro; He, Chenmin; Iyer, Gokul; Keramidas, Kimon; Köberle, Alexandre C.; Oshiro, Ken; Reis, Lara Aleluia; Shoai-Tehrani, Bianka; Vishwanathan, Saritha Sudharmma; Capros, Pantélis; Drouet, Laurent; Edmonds, James E.; Garg, Amit; Gernaat, David; Jiang, Kejun; Kannavou, Maria; Kitous, Alban; Kriegler, Elmar; Luderer, Gunnar; Mathur, Ritu; Muratori, Matteo; Sano, Fuminori; Vuuren, Detlef P. van

doi:10.1016/j.energy.2018.12.131

Cited by 131 publications

(96 citation statements)

References 17 publications

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“…Integrated assessment models (IAMs) represent human interactions with the natural systems through mathematical formulations based on insights from physics, chemistry, biology, economics, sociology, and transition theory [23,24]. They are useful tools to project the evolution of human activity and its environmental impacts into the future by either optimizing or simulating the evolution of these systems subject to exogenous constraints and assumptions [6].…”

Section: Iams and Beccsmentioning

confidence: 99%

The Value of BECCS in IAMs: a Review

Köberle

2019

Curr Sustainable Renewable Energy Rep

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Purpose of Review Integrated assessment model (IAM) scenarios consistent with Paris Agreement targets involve large negative emission technologies (NETs), mostly bioenergy with carbon capture and storage (BECCS). Such reliance on BECCS implies IAMs assign it a high value. Past analyses on the value of BECCS in IAMs have not explicitly addressed the role of model structure and assumptions as value drivers. This paper examines the extent to which the value of BECCS in IAMs is enhanced by model structure constraints and assumptions. Recent Findings Predominant use of high discount rates (3.5-5%) means models opt for delayed-action strategies for emissions mitigation that lead to high levels of cumulative net-negative emissions, while lower discount rates lead to reduce reliance on NETs. Until recently in the literature, most models limited NET options to only BECCS and afforestation, but introduction of other CDR options can reduce BECCS deployment. Constraints on grid penetration of variable renewable energy (VRE) is a determining factor on the level of BECCS deployment across models, and more constrained grid penetration of VREs leads to more BECCS in electricity generation. Summary This paper concludes BECCS derives significant value not only from the existing structure of IAMs but also from what is not represented in models and by predominant use of high discount rates. Omissions include NETs other than BECCS and deforestation, low-carbon innovation in end-use technologies, grid resilience to intermittent sources, and energy use in agriculture production. As IAMs increasingly endogenize such constraints, the value of BECCS in resulting scenarios is likely to be dampened.

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Section: Iams and Beccsmentioning

confidence: 99%

The Value of BECCS in IAMs: a Review

Köberle

2019

Curr Sustainable Renewable Energy Rep

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“…In addition, the response points to the considerable documentation of the models used, as well as details of input assumptions [31]. Furthermore, a recent paper includes specific details of some of the power sector technology costs included in the models, along with comparisons to cost projections from organisations such as the International Energy Agency [33].…”

Section: Lack Of Transparency Around What Drives Model Resultsmentioning

confidence: 99%

“…For example, less developed countries may face low levels of energy access, a reliance on traditional fuels and informal economies, and poorly functioning markets such as power markets [58][59][60]. These challenges could mean developing regions experience higher costs of mitigation (owing to lower availability of mitigation technologies, or higher implementation costs of those technologies) than specified in some IAMs, where these countries' energy technology costs can often be assumed to be lower than for developed countries (see e.g., [33]). This can also mean they may be simulated to mitigate much more in "cost-optimal" scenarios than they realistically can do, or than any equity or burden-sharing approach might imply (see e.g., [61]).…”

Section: Lack Of Representation Of Reality Of Behavioural and Economimentioning

confidence: 99%

A Review of Criticisms of Integrated Assessment Models and Proposed Approaches to Address These, through the Lens of BECCS

et al. 2019

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This paper reviews the many criticisms that Integrated Assessment Models (IAMs)—the bedrock of mitigation analysis—have received in recent years. Critics have asserted that there is a lack of transparency around model structures and input assumptions, a lack of credibility in those input assumptions that are made visible, an over-reliance on particular technologies and an inadequate representation of real-world policies and processes such as innovation and behaviour change. The paper then reviews the proposals and actions that follow from these criticisms, which fall into three broad categories: scrap the models and use other techniques to set out low-carbon futures; transform them by improving their representation of real-world processes and their transparency; and supplement them with other models and approaches. The article considers the implications of each proposal, through the particular lens of how it would explore the role of a key low-carbon technology—bioenergy with carbon capture and storage (BECCS), to produce net negative emissions. The paper concludes that IAMs remain critically important in mitigation pathways analysis, because they can encompass a large number of technologies and policies in a consistent framework, but that they should increasingly be supplemented with other models and analytical approaches.

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“…(Jiang et al 1998) 2005-2050 Yes No from statistical data. As different models have different inputs on the operating hours and technical lifetime, we made two major assumptions to improve the comparability: the full load hour (FLH) is assumed to be 4400 h, which was roughly the average level in 2015 (Yan and Yuan 2016); the technical lifetime is assumed to be 40 years, according to a former IAMs study (Krey et al 2019). The main idea is to calculate the demand of operating plants from IAM coal power generation projection, to calculate the actual capacity from the statistics and the assumed lifetime.…”

Section: Methodsologymentioning

confidence: 99%

“…With a long technical lifetime, newly-built coal-based power plants are expected to be operational until midcentury, leading to a significant carbon lock-in risk. Krey et al found that the technical lifetime of coalbased power plants ranges from 30-60 years in IAMs (Krey et al 2019).…”

Section: Stranded Risk Of Investment In Coal-based Powermentioning

confidence: 99%

Early transformation of the Chinese power sector to avoid additional coal lock-in

Wang

Chen

Bertram

et al. 2020

Environ. Res. Lett.

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Emission reduction from the coal-dominated power sector is vital for achieving China's carbon mitigation targets. Although the coal expansion has been slowed down due to the cancellation of and delay in new construction, coal-based power was responsible for over one third of China's energyrelated CO 2 emissions by 2018. Moreover, with a technical lifetime of over 30 years, current investment in coal-based power could hinder CO 2 mitigation until 2050. Therefore, it is important to examine whether the current coal-based power planning aligns with the long-term climate targets. This paper introduces China's Nationally Determined Contribution (NDC) goals and an ambitious carbon budget along with global pathways well-below 2 degrees that are divided into five integrated assessment models, which are two national and three global models. We compare the models' results with bottom-up data on current capacity additions and expansion plans to examine if the NDC targets are in line with 2-degree pathways. The key findings are: 1. NDC goals alone are unlikely to lead to significant reductions in coal-based power generation. On the contrary, more plants may be built before 2030; 2. this would require an average of 187-261 TWh of annual coal-based power capacity reduction between 2030 and 2050 to achieve a 2°C compatible trajectory, which would lead to the stranding of large-scale coal-based power plants; 3. if the reduction in coal power can be brought forward to 2020, the average annual coal-based power reduction required would be 104-155 TWh from 2020 to 2050 and the emissions could peak earlier; 4. early regulations in coal-based power would require accelerated promotion of alternatives between 2020 and 2030, with nuclear, wind and solar power expected to be the most promising alternatives. By presenting the stranding risk and viability of alternatives, we suggest that both the government and enterprises should remain cautious about making new investment in coal-based power sector.

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Looking under the hood: A comparison of techno-economic assumptions across national and global integrated assessment models

Cited by 131 publications

References 17 publications

The Value of BECCS in IAMs: a Review

The Value of BECCS in IAMs: a Review

A Review of Criticisms of Integrated Assessment Models and Proposed Approaches to Address These, through the Lens of BECCS

Early transformation of the Chinese power sector to avoid additional coal lock-in

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