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Laser-induced photo-detachment diagnostic for interrogating pulsed ECR-driven plasmas: Application to 𝐇 -and 𝐃 -negative ions

Introduction

The study of H -and D -negative ions relevant to the accelerator and fusion applications, may be supported by considering transient kinetics within the corresponding plasmas. This concept is here tested by: (i) generating electron cyclotron resonance (ECR) H2 and D2 plasmas, sustained by 2.45 GHz microwave bursts; and (ii) interrogating them by means of time-resolved photo-detachment (PD) and electrostatic probe (EP) techniques.

Experimental setup and method

H2 and D2 plasmas are produced in the ECRdriven SCHEME-II+ reactor, which is designed to study volume-produced H -and D -negative ions with respect to surface-enhanced production of rovibrationally excited molecules [1]. Microwave power (150 W) is delivered from a solid-state 2.45 GHz generator and chopped to form bursts (repetition rate 2 kHz; pulse width 150 μs). Laser-induced photo-detachment [2] (50 Hz) and electrostatic probe acquisition are both synchronized with the microwave bursts as explained in Fig. 1.

Measurements are carried out at 1.6 Pa and 75 mm downstream of the midplane of the ECR zone. Data are averaged over 100 and 1000 periods of the bursts for the EP and the PD experiments, respectively.

Results and Conclusion

Fig. 2 demonstrates indicative results from the D2 plasma, i.e., the signal of the electrons photodetached from the D -negative ions. The above results stress the enhanced negative ion yield in the post-discharge phase (>150 μs). This may be attributed to the rapid decay of energetic electrons, atomic population, and positive ions involved in destruction reactions, along with the formation of vibrationally excited molecules of long lifetime [3] involved in the main volume production reaction of the H -and D -ions, i.e., dissociative attachment.

  Laser-induced photo-detachment diagnostic for interrogating pulsed ECR-driven plasmas: Application to H --and D --negative ions M Mitrou, S Béchu, P Svarnas To cite this version: M Mitrou, S Béchu, P Svarnas. Laser-induced photo-detachment diagnostic for interrogating pulsed ECR-driven plasmas: Application to H --and D --negative ions. International Conference on Phenomena in Ionized Gases (XXXV ICPIG), Jul 2023, Egmond aan Zee, Netherlands. hal-04285360

Figure 1 .

 1 Figure 1. Generation of ECR-plasma bursts and scheduling for time-resolved PD and EP measurements.

Figure 2 .

 2 Figure 2. Representative time-resolved photo-detachment signals. Insets: corresponding time points of the acquisition and absolute D -ion densities. The latter are calculated after factoring in the corresponding time-specific electron densities from the time-resolved probe I-V curves.

  Photodetached electron current (A)

High Voltage Lab., Electrical & Computer Eng. Dept., University of Patras, Rion-Patras

26504, Greece 2 Université Grenoble Alpes, CNRS, Grenoble INP (Institute of Engineering), LPSC-IN2P3, 38000 Grenoble, FranceThe present work is devoted to an experimental setup tailored to study time-resolved processes relative to negative ion formation in ECR-driven plasmas. It refers to a laser-induced electron photo-detachment system synchronized with H2 and D2 ECR-plasmas being sustained by 2.45 GHz bursts in the kHz range. The system is combined with electrostatic probe time-resolved measurements and information is obtained both on the formation path and the yield enhancement of H -and D -negative ions.


CIRED Julien Lefèvre

Agroparistech

Integrated Assessment Models and Input-Output Analysis : bridging fields for advancing sustainability scenarios research

Keywords: Integrated Assessment Models, Input-Output Analysis, model linking, sustainability, climate mitigation scenarios

Technology-rich Integrated assessment models (IAMs) and Environmentally-Extended Input-Output Analysis (EEIOA) are widely employed for sustainability analysis, each offering unique strengths.

IAMs focus on forward-looking scenarios, exploring technological shifts and climate change mitigation costs. EEIOA provides more comprehensive but static assessments of environmental and socioeconomic impacts throughout supply chains, adopting a lifecycle perspective. I conduct a literature review to assess the current state of IAM-IO integration, paving the way for future research opportunities with advanced models. Existing studies have loosely linked IAM and IO models to improve one field or the other. This perspective highlights the potential for more advanced IAM-IO model linking and identifies three domains within sustainability scenarios research where IAM-IO integration could play a crucial role : the energy-industry nexus in decarbonization pathways, multi-dimensional sustainability impact assessment and demand-side solutions and post-growth climate mitigation scenarios. The expected research insights may be pivotal to design effective sustainable policies.

Introduction

Urgent global sustainability issues, such as climate change and the Sustainable Development Goals (SDGs), require immediate attention and viable solutions. Technology-rich Integrated Assessment Models (IAMs) serve as central tools for exploring available options and understanding the consequences of various strategies to mitigate climate change and address other policy goals [START_REF] Keppo | Exploring the possibility space: Taking stock of the diverse capabilities and gaps in integrated assessment models[END_REF]. IAMs simulate interactions within and between critical systems in future scenarios, including energy, economic, and land use systems. These models rely on narratives about future technological and socio-economic trends, such as the Shared Socio-economic Pathways (SSPs) [START_REF] Riahi | The shared socioeconomic pathways and their energy, land use, and greenhouse gas emissions implications: an overview[END_REF] and quantify transformation pathways and cost-effective technological developments to achieve climate targets. A strong research community has built around IAMs, with formal organization (e.g. with the IAM Consortiumhttps://www.iamconsortium.org/) and fostering collaborative efforts through Model Intercomparison Projects and collective work across various international projects (e.g. EU ADVANCE and NAVIGATE projects). The IAM community also plays a key role in the assessments conducted by the Intergovernmental Panel on Climate Change (IPCC). The usefulness of IAM analysis is widely recognized in both scientific and policy arenas, as it has greatly influenced the framing of mitigation issues and the formulation of solutions to address climate change and broader sustainable development issues.

The field of Input-Output Analysis (IOA) predates that of IAMs and is more comprehensive in its approach. IOA was pioneered by Leontief [START_REF] Leontief | Interrelation of prices, output, savings, and investment[END_REF], who introduced a multi-sectoral perspective to macroeconomics, effectively capturing inter-industry linkages. IOA focuses on assessing impacts across entire supply chains, considering the perspective of consumption.

Environmentally-Extended Input-Output Analysis (EEIOA) [START_REF] Miller | Input-output analysis: foundations and extensions[END_REF], [START_REF] Ewing | Integrating ecological and water footprint accounting in a multi-regional input-output framework[END_REF][START_REF] Kitzes | An introduction to environmentally-extended input-output analysis[END_REF] expands the application of IOA to the environmental and material aspects of supply chains, facilitating the assessment of various environmental issues like climate change, water scarcity, and natural resource depletion. EEIOA has become a crucial tool in Industrial Ecology (IE) research, which aims to analyze the intricate biophysical linkages within society [START_REF] Pauliuk | Industrial ecology in integrated assessment models[END_REF]. More recently, the development of global Multi-Regional Input-Output (MRIO) databases with comprehensive environmental and social accounts [START_REF] Stadler | EXIOBASE 3: Developing a time series of detailed environmentally extended multi-regional input-output tables[END_REF] [START_REF] Lenzen | Building Eora: a global multi-region inputoutput database at high country and sector resolution[END_REF] [START_REF] Timmer | The world input-output database (WIOD): contents, sources and methods[END_REF], has supported extensive analysis of the environmental and socio-economic footprints of nations [START_REF] Hertwich | Carbon footprint of nations: a global, trade-linked analysis[END_REF]) [START_REF] Simas | Labor embodied in trade: The role of labor and energy productivity and implications for greenhouse gas emissions[END_REF] [START_REF] Tukker | Environmental and resource footprints in a global context: Europe's structural deficit in resource endowments[END_REF] [START_REF] Giljum | Identifying priority areas for European resource policies: a MRIO-based material footprint assessment[END_REF] [START_REF] Wiedmann | Environmental and social footprints of international trade[END_REF].

These studies have brought attention to the unsustainability of present economies (from both environmental and social viewpoints) [START_REF] Fanning | The social shortfall and ecological overshoot of nations[END_REF] [START_REF] Wiedmann | Scientists' warning on affluence[END_REF] (Hickel et al., 2022), revealing the profound impact of current consumption and production patterns on the planet and society at large. IAMs and IOA offer complementary strengths for sustainability analysis. While IAMs provide a forward-looking perspective on transformative technological change, they lack coherence in describing the lifecycle impacts of technologies and usually fail to consider supply chains beyond the energy system [START_REF] Pauliuk | Industrial ecology in integrated assessment models[END_REF]. Conversely, EEIOA comprehensively captures the environmental and economic dimensions of global supply chains, but falls short in providing only static assessments, ignores technical change and lacks technology detail. Apart from a few IAMs that originate from macroeconomic modeling and incorporate an IO economic accounting, IAM and IO fields have mostly developed independently. Nevertheless, recent endeavors to integrate IAM and IO methods hold great promise for future research. In this perspective paper, I conduct a literature review to assess the current state of IAM-IO integration and provide an outlook on the future research opportunities with advanced IAM-IO models. I find that most existing studies rely on loose model linking to improve assessment of one field based on the other. Then I identify opportunities for more advanced IAM-IO model linking and three domains within sustainability scenarios research where IAM-IO integration could play a pivotal role : the energy-industry nexus in decarbonization pathways, multi-dimensional sustainability impact assessment and demand-side solutions and post-growth climate mitigation scenarios.

Two complementary fields for sustainability analysis

IAM refers to a variety of models with alternative scope, granularity, and intended purposes [START_REF] Krey | Looking under the hood: a comparison of techno-economic assumptions across national and global integrated assessment models[END_REF]. Process-based IAMs delve into technology and process dynamics and can be distinguished from cost-benefit IAMs that consolidate these processes into simplified relationships between abatement costs and climate change damage [START_REF] Weyant | Some contributions of integrated assessment models of global climate change[END_REF]. This paper focuses on process-based technology-rich IAMs -hereafter IAMs. IAMs cover the main sources of GHG emissions and model integrated energy, land-use and economic systems with a focus on technology and process dynamics to achieve climate and other policy goals. In doing so IAMs highlight feedbacks and trade-offs between choices about the energy system, economy and the environment. Although having been criticized along different lines, IAM have demonstrated valuable in exploring key topics such as technology dynamics, investment needs for decarbonization, energy-economy feedbacks and policy scenarios [START_REF] Keppo | Exploring the possibility space: Taking stock of the diverse capabilities and gaps in integrated assessment models[END_REF].

Energy System Modelling (ESM) is the core of most IAMs [START_REF] Wilson | Evaluating process-based integrated assessment models of climate change mitigation[END_REF] and in this case the energy system is linked to the broader economy through different ways : partial equilibrium (PE) IAMs include GDP as a main exogenous driver for energy demand but disregard the feedbacks of the energy system on the economy, contrary to general equilibrium (GE) IAMs. IAMs also vary in the way the model is solved over the time horizon : some models optimize intertemporal welfare or minimize costs with perfect knowledge of future conditions whereas others adopt a recursive dynamic approach based on myopic expectations.

In addition, typical IAMs based on ESMs reflect a 'linear' representation of energy flows and energy-economy relationships (see Fig. 1). GDP drives demand for energy services (in industry, transport and buildings sectors), which drive demand for final energy through end-use technologies (industrial processes, transport vehicles, heating systems, etc.). Final energy is supplied by the energy system after conversion of primary sources (fossil fuels, renewable sources, biomass, etc.) into final carriers (electricity, final solid, liquid and gas fuels) based on different technologies (e.g. gas-fired, solar or wind power). GE-IAMs also include aggregated feedbacks between the energy system and the overall economy : energy system costs must be covered by GDP and energy services are input to macroeconomic production. In the context of sustainability analysis, IAMs have been criticized for their weak coverage of the linkages within and between biophysical and economic systems. [START_REF] Pauliuk | Industrial ecology in integrated assessment models[END_REF] highlight the main limitations of IAMs from an industrial ecology perspective. First, IAMs incoherently describe the lifecycle impacts of technologies, i.e. the environmental and economic impacts of technologies across their entire lifespan, from their creation and use to their disposal (extraction of resources, manufacturing and production, use phase, end-of-life, etc.). In particular, the linear linkages between energy supply, energy demand and economic production can not properly describe the indirect environmental and economic impacts of energy conversion and end-use assets, especially related to the build-up of these assets (e.g. emissions linked to producing the materials for given asset). At best, in GE-IAMs, the macroeconomic feedback of energy system costs on economic output allows capturing the global supply chains of total capital investment in the energy system in a highly aggregated form (one single macroeconomic production). Second, standard IAMs focus on energy flows and ignore other physical balances (e.g. material cycles). Likewise, IAMs capture the direct GHG impacts of processes but generally ignore broader environmental impacts across supply chains. Eventually, the aggregate production perspective of the economy does not allow for consumption-based analysis of upstream and downstream industrial impacts and exploration of inter-sectoral linkages.

These weaknesses of IAMs are basically the strengths of EEIO analysis. IO and supply-anduse tables (SUTs) capture the detailed interlinkages between economic sectors (intermediary consumption) and final demand [START_REF] Miller | Input-output analysis: foundations and extensions[END_REF]. As illustrated in Fig. 2, IO analysis is based on an interlinked representation of economic flows including those associated to the energy system as part of the broader economy, as opposed to the linear IAM approach centered on the energy system. The IO framework enables to estimate direct and indirect economy-wide impacts across supply chains from a consumption-based viewpoint. Environmentally-Extended Input-Output tables include satellite accounts of physical flows (e.g. materials) and environmental stressors attached to main production matrix -describing resource requirement or environmental impacts per unit of output for individual sectors -for environmental analysis across supply chains (e.g. consumption-based assessments of various environmental impacts such as climate change, land use and biodiversity). IO linkages can also be downscaled to technology levels and hybridized with lifecyle inventories (LCI) through so-called hybrid LCA (lifecycle assessment)-IO approach [START_REF] Suh | System boundary selection in life-cycle inventories using hybrid approaches[END_REF]. In this case, the detailed bottom-up data from LCIs describing the inputs and outputs in physical units for individual processes and technologies are introduced within a broader top-down IO framework in monetary units (outside environmental extensions). This approach allows capturing the lifecycle impacts of individual technologies. Multi-Regional IO (MRIO) models represent the bilateral trade linkages between countries and give a complete picture of the global production network and supply chains. MRIO models thus generally offer a higher sectoral and regional resolution than IAMs. There has been growing interests in global value chain environmental and socioeconomic footprint analysis supported by the recent development of global Environmentally-Extended MRIO database (GTAP [START_REF] Aguiar | The GTAP data base: version 10[END_REF], EXIOBASE [START_REF] Stadler | EXIOBASE 3: Developing a time series of detailed environmentally extended multi-regional input-output tables[END_REF], EORA [START_REF] Lenzen | Building Eora: a global multi-region inputoutput database at high country and sector resolution[END_REF], WIOD (Timmer et al., 2012), etc.). A range of studies has provided key insights on the environmental footprints of nations including carbon footprints [START_REF] Hertwich | Carbon footprint of nations: a global, trade-linked analysis[END_REF] [START_REF] Wiebe | Carbon and materials embodied in the international trade of emerging economies: A multiregional input-output assessment of trends between 1995 and 2005[END_REF], material and other resource footprints [START_REF] Wiebe | Carbon and materials embodied in the international trade of emerging economies: A multiregional input-output assessment of trends between 1995 and 2005[END_REF] [START_REF] Tukker | Environmental and resource footprints in a global context: Europe's structural deficit in resource endowments[END_REF] [START_REF] Wiedmann | The material footprint of nations[END_REF] [START_REF] Giljum | Identifying priority areas for European resource policies: a MRIO-based material footprint assessment[END_REF] and broader environmental and socio-economic footprints [START_REF] Simas | Labor embodied in trade: The role of labor and energy productivity and implications for greenhouse gas emissions[END_REF] [START_REF] Ivanova | Environmental impact assessment of household consumption[END_REF] [START_REF] Malik | Advancements in input-output models and indicators for consumption-based accounting[END_REF] [START_REF] Wiedmann | Environmental and social footprints of international trade[END_REF]. It has paved the way for enhanced sustainability assessments, offering complementary perspectives on, for instance, the industrial ecology of linked material and carbon footprints [START_REF] Hertwich | Increased carbon footprint of materials production driven by rise in investments[END_REF] [START_REF] Rasul | Decomposition Analysis of the Carbon Footprint of Primary Metals[END_REF] [START_REF] Lenzen | Implementing the material footprint to measure progress towards Sustainable Development Goals 8 and 12[END_REF], the quantification of ecological thresholds and overshoot of nations [START_REF] Hickel | National responsibility for ecological breakdown: A fair-shares assessment of resource use, 1970-2017[END_REF] [START_REF] Fanning | The social shortfall and ecological overshoot of nations[END_REF], global carbon inequality both between and within countries [START_REF] Chancel | Global carbon inequality over 1990-2019[END_REF] [START_REF] Zheng | Rising carbon inequality and its driving factors from 2005 to 2015[END_REF] and progress towards the SDGs (Gómez-Paredes and [START_REF] Gómez-Paredes | Tracking the Sustainable Development Goals with Input-Output Analysis: A commentary and example[END_REF]. Despite the richness of EE-MRIO methods and their potential for robust multi-dimensional sustainability analysis, the standard EEIO approach has intrinsic limitations. While it proves useful for disentangling key relationships in retrospective assessments based on past data, it falls short in exploring the implications of forward-looking scenarios. One of the primary reasons for this limitation is the static nature of the IO framework. It focuses on assessing consumption-based impacts of past trends or future exogenous changes in final demand while assuming fixed technical coefficients for intermediary consumption and environmental stressors, as well as fixed trade coefficients. Consequently, it does not account for technical improvements, input substitutions, and changes in trade relationships that are likely to occur in future scenarios. Furthermore, the EEIO approach does not capture intertemporal effects such as linked to capital formation and in-use stocks. While recent IO models endogenize capital [START_REF] Södersten | Endogenizing Capital in MRIO Models: The Implications for Consumption-Based Accounting[END_REF], they rely on data for a specific year and do not account for the technical changes occuring between the year of capital formation and the subsequent periods of capital utilization. This has implications for footprint estimates, particularly concerning long-lived assets. Additionally, it overlooks economic behaviors and price-induced mechanisms on both the supply and demand sides of the economy. As a result, the standard IO approach is inherently limited in its ability to explore transformation pathways and future scenarios. Furthermore, being a top-down approach based on macro accounting data, it tends to lack granularity in technological details.

Current state of IAM-IO integration

IAM and IO methods have been recently combined to address novel challenges in forwardlooking scenarios. To evaluate the current state of integration between IAM and IO, I conducted a literature review within this emerging field. The review followed a staged approach. Initially, I conducted a search on Google Scholar using relevant keywords 1 and screened abstracts to select an initial set of papers. Additionally, I identified supplementary relevant papers by scrutinizing the reference lists of these initial papers. At the abstract screening stage, the inclusion criterion was that the paper should introduce a linking of methods within the domains of IAM (inclusive of energy system modeling and energy transition scenarios) and IOA (including EE-IO, MRIO, and hybrid LCA-IO 2 ). Subsequently, during the in-depth reading stage, I focused on assessing the nature of the linking approaches employed (distinguishing between soft and hard linking and directionality) and the research questions studied. Based on these evaluations, I categorized and summarized the principal approaches employed for integrating IAM and IO methods, as presented in Table 2.

1 Including integrated assessment model, energy model, scenarios, input-output, lifecycle assessment 2 For constructing the core literature review which is focused on IO, I have only retained hybrid LCA-IO studies that include an explicit IO component. However, I have also considered some other papers more focused on LCA approaches to put IO approaches in perspective and to highlight the specific strengths of LCA methods compared to IO. Table 2 : Summary of the current state of IAM-IO integration 3.1. Soft-linking approaches

IAM to IO linking

The first main approach consists in soft-linking IAM and IO methods in a single direction by using information from one field to improve assessment based on the other. In the first direction, assumptions and results from IAMs and ESMs have been incorporated in IO models to perform different types of scenarios analysis.

A first type of scenario analysis explores the lifecycle environmental impacts of energy technology developments based on the implementation of exogenous energy technology scenarios in a hybrid LCA-IO model. For instance (Arvesen and[START_REF] Arvesen | Environmental implications of large-scale adoption of wind power: a scenario-based life cycle assessment[END_REF](Wolfram et al., 2016) implement power technology scenarios in two-region LCA-IO models (through exogenous shares of technologies in the IO matrix) to assess environmental impacts of large scale adoption of wind power in Europe for the former and the renewable electricity transition in Australia for the latter. [START_REF] Hertwich | Integrated life-cycle assessment of electricity-supply scenarios confirms global environmental benefit of low-carbon technologies[END_REF] and [START_REF] Gibon | Life cycle assessment demonstrates environmental cobenefits and trade-offs of low-carbon electricity supply options[END_REF] [START_REF] Knobloch | Net emission reductions from electric cars and heat pumps in 59 world regions over time[END_REF] and heating systems [START_REF] Cox | Life cycle environmental and cost comparison of current and future passenger cars under different energy scenarios[END_REF] and developed advanced methods for adjusting entire clusters of industrial activities, beyond the primary sector of interest, in the pLCI database [START_REF] Sacchi | PRospective EnvironMental Impact asSEment (premise): A streamlined approach to producing databases for prospective life cycle assessment using integrated assessment models[END_REF].

A second type of analysis explores economy-wide climate transition scenarios and assess their implications for future environmental footprints of regions and sectors across global supply chains and trade. For instance [START_REF] Wiebe | Implementing exogenous scenarios in a global MRIO model for the estimation of future environmental footprints[END_REF] , 2016). A growing body of studies have been using this approach to explore the environmental efficacy of consumer-oriented policy measures and sufficiency lifestyles [START_REF] Vita | The environmental impact of green consumption and sufficiency lifestyles scenarios in Europe: connecting local sustainability visions to global consequences[END_REF] [START_REF] Wood | Prioritizing consumption-based carbon policy based on the evaluation of mitigation potential using input-output methods[END_REF] [START_REF] Moran | Quantifying the potential for consumer-oriented policy to reduce European and foreign carbon emissions[END_REF] building on the detailed final consumption structure of MRIO databases.

A third type of analysis directly feeds IO models with PE ESM outputs to evaluate the carbon and socio-economic impacts across economic sectors of energy system transition scenarios. In practice, the ESM provides information on the future changes in the energy system which are translated into changes of input requirements and final demand (fuel consumption, demand for capital goods, labour requirement, etc.) in the IO model. Existing studies use this method to assess the direct and indirect job and output impacts across economic sectors of various energy transition scenarios [START_REF] Siala | Towards a sustainable European energy system: Linking optimization models with multi-regional input-output analysis[END_REF]) [START_REF] Oei | Coal phase-out in Germany-Implications and policies for affected regions[END_REF]) [START_REF] Ju | Job creation in response to Japan's energy transition towards deep mitigation: an extension of partial equilibrium integrated assessment models[END_REF].

IO to IAM linking

To a lesser extent, IAM-IO soft-linking has been performed the other way around using IO results to improve IAM and ESM assessments. This approach has been used to compute optimal energy system decarbonization pathways taking into account the indirect lifecycle emissions of technologies embodied in capital goods [START_REF] Daly | Indirect CO2 emission implications of energy system pathways: linking IO and TIMES models for the UK[END_REF] [START_REF] Lefèvre | Global socioeconomic and climate change mitigation scenarios through the lens of structural change[END_REF]. Some of these models emphasize energy-economic linkages and price effects (e.g. IMACLIM [START_REF] Sassi | IMACLIM-R: a modelling framework to simulate sustainable development pathways[END_REF] or GEM-E3 [START_REF] Capros | GEM-E3 model documentation[END_REF]) ; for instance the impacts of energy prices variations due to technological changes in energy supply, on industries competitiveness and final consumption.

Others models provide more detailed descriptions of trade mechanisms [START_REF] Duchin | Combining multiregional input-output analysis with a world trade model for evaluating scenarios for sustainable use of global resources, part II: Implementation[END_REF]) [START_REF] Distelkamp | Pathways to a resource-efficient and low-carbon Europe[END_REF]. IO-based IAMs do not contain full-resolution GMRIO datasets in general but usually include most of the information that is necessary to estimate a full GMRIO system (e.g. E3ME [START_REF] Mercure | Environmental impact assessment for climate change policy with the simulation-based integrated assessment model E3ME-FTT-GENIE[END_REF]) and perform consumption-based assessments across global supply chains.

The review of the literature reveals that IAM-IO integration is still at a nascent stage.

Methodologically, the majority of existing studies adopt a soft-linking approach wherein IAM or ESM and IO models are integrated in a unidirectional manner to enhance the analysis in one field based on insights from the other. While a few rare instances of two-way soft-linking between ESM and IO models have been explored [START_REF] Heinrichs | Integrated assessment of a phase-out of coal-fired power plants in Germany[END_REF] this special issue includes several papers that offer a glimpse into the potential for more advanced IAM-IO model integration [START_REF] Ju | Industry's role in Japan's energy transition: soft-linking GCAM and National IO table with extended electricity supply sectors[END_REF]) [START_REF] Budzinski | Coupling energy system models with multi-regional input-output models based on the make and use framework-insights from MESSAGEix and EXIOBASE[END_REF]. These and other methodological advancements hold the promise of unlocking new perspectives for advancing sustainability scenarios research in various directions. Notably, they could facilitate a deeper exploration of the energy-industry nexus in decarbonization pathways, enable more comprehensive and robust multi-dimensional sustainability impact assessments, and enhance the accuracy of modeling demand-side solutions and post-growth climate mitigation scenarios.

Advancing IAM-IO integration and sustainability scenarios research

Advanced model integration

As outlined in the previous section, the current IAM-IO model integration is based on two main approaches : one involving loosely soft-linking independent models and data, and the other entailing the development of built-in approaches and strong model integration. We can expect these two tracks to evolve as complementary paths, facilitating the advancement of more sophisticated sustainability analyses.

Currently, soft-linking of IAM or ESM and IO models has primarily been developed for specific studies. We first propose fostering a more structured community interaction centered around a multi-model ecology, encouraging the co-evolution and interaction of various models, including IAMs, ESMs, MRIOs, and LCA-IOs [START_REF] Pauliuk | Industrial ecology in integrated assessment models[END_REF]. Standardizing model linking practices and scenario assessments would be essential in this endeavor. For instance, MRIO models could enhance the quantification of SSP scenarios in dimensions that IAMs often inadequately cover, such as demand-side transformations and structural changes in industry sectors. Conversely, EE-MRIO and LCA-IO models could be leveraged to post-process IAM results, enabling more standardized and accurate assessment of SDG impacts through multidimensional environmental and socio-economic footprint estimates. IAM-IO soft-linking could also be expanded at the level of each modeling team through the development of complementary modules such as e.g. the IO-scenario builder of the MESSAGE model team [START_REF] Qiyu | Coupling an Integrated Assessment Models with an Input-Output database[END_REF]. Overall, this process would both improve IAM-based scenarios and widen the scope of MRIO modelers in a way that is consistent with established forward-looking scenario modeling. Limited interaction between researchers from the two fields is sufficient for this approach, but it would greatly improve with the establishment of shared standards for open data and model interfaces. Collaborating on open source softwares would promote higher transparency and work quality, aligning for instance with the established practices within the IE research community [START_REF] Pauliuk | Lifting industrial ecology modeling to a new level of quality and transparency: a call for more transparent publications and a collaborative open source software framework[END_REF] [START_REF] Stadler | Pymrio-A Python based multi-regional input-output analysis toolbox[END_REF]. However, IAM-IO soft-linking does not address the deeper disparities regarding the incorporation of specific system linkages.

Therefore, it is also highly relevant to advance built-in IAM-IO integration, tailoring different modeling techniques to address specific questions. A first promising direction is the development of more sophisticated ESM-IO linking, moving beyond simple one-way data exchange. Recent examples of this approach include [START_REF] Ju | Industry's role in Japan's energy transition: soft-linking GCAM and National IO table with extended electricity supply sectors[END_REF] and [START_REF] Budzinski | Coupling energy system models with multi-regional input-output models based on the make and use framework-insights from MESSAGEix and EXIOBASE[END_REF] in this special issue. [START_REF] Ju | Industry's role in Japan's energy transition: soft-linking GCAM and National IO table with extended electricity supply sectors[END_REF]) linked the GCAM model with a national IO model for Japan through an iterative approach. This iterative process involves exchanging data between the ESM and IO model at each time step to achieve convergence on common measuring points, i.e investment in power capacities and energy demand. This ensures an advanced integration of system linkages embedded in one model but weakly or not covered by the other. For example, it captures power generation dynamic investment choices from the ESM and feedback from power investment on industrial sectors and energy demand from the IO model. In contrast, [START_REF] Budzinski | Coupling energy system models with multi-regional input-output models based on the make and use framework-insights from MESSAGEix and EXIOBASE[END_REF] achieved full integration of ESM and MRIO data for a benchmark year within a common accounting system based on the Make and Use framework. This integration involved rearranging ESM energy flows data (primary, secondary, final, imports, exports, etc.) in the make and use logic, converting it into monetary units, and reconciling it with the broader economic Make and Use tables of the MRIO model. Expanding this approach to forward-looking scenarios would enable the generation of fully integrated ESM-IO projections without double accounting or overlapping of linkages representation.

A second general approach involves enhancing existing IO-based macroeconomic IAMs or develop new IAMs with a core IO framework. Current IO-based IAMs already encompass the essential system linkages of a standard IO framework, including demand-supply interdependence and supply chain connections across economic sectors and regions. Moreover, they offer additional descriptions of endogenous input substitution, economic behaviors, and feedback mechanisms, such as price and income effects, including rebound effects. However, their application has been limited in exploring inter-sectoral dynamics in future scenarios, e.g. in relation to structural change effects [START_REF] Lefèvre | Global socioeconomic and climate change mitigation scenarios through the lens of structural change[END_REF]. Strengthening the core IO framework of these models could significantly improve the representation of economic and biophysical linkages. Presently, while some hybridization of energy-economic IO data exists, energy flows are still primarily accounted for in money-based units within their macroeconomic core. To foster a more consistent integration of physical-macroeconomic dimensions, direct accounting of energy flows in hybrid units should be more systematically implemented. This would enable incorporating information on energy substitutability or energy efficiency potentials and constraints directly based on engineering expertise. Hybridization of IO data could also be expanded to encompass other physical flows, such as materialss and accounts of broader environmental stressors beyond GHG emissions should be more systematically incorporated (Econometrics, n.d.). Improving the supply chain linkages of fixed capital and investment is another area of opportunity. Expanding the typical representation of an average investment vector to a matrix format would enable capturing the specific content of fixed capital formation in a given sector concerning investment goods. At a technology level, this investment matrix approach could better account for the lifecycle impacts of technologies and the energy system, such as net energy assessments (e.g., Energy return on investment -EROI [START_REF] Brand-Correa | Developing an input-output based method to estimate a national-level energy return on investment (EROI)[END_REF]) or labour impacts [START_REF] Dai | Green growth: The economic impacts of large-scale renewable energy development in China[END_REF].

Furthermore, the development of new IAMs based on the IO framework offers a promising avenue. Most existing IO-based macroeconomic IAMs are CGE models that adhere to a neoclassical oriented approach, emphasizing equilibrium, perfect markets, and high input substitutability with limited representation of finance. Beyond existing exceptions that challenge the standard CGE paradigm within IAMs (e.g. imperfect markets and limited substitutability [START_REF] Sassi | IMACLIM-R: a modelling framework to simulate sustainable development pathways[END_REF] or macroeconometric demand-led approaches [START_REF] Mercure | Environmental impact assessment for climate change policy with the simulation-based integrated assessment model E3ME-FTT-GENIE[END_REF]), some scholars call for a new economic approach of energy transition models that embraces the features of modern economies encompassing complexity, non-equilibrium and uncertainty [START_REF] Hafner | Emergence of new economics energy transition models: A review[END_REF]. To achieve this goal, the emerging field of ecological macroeconomics proposes a diverse set of relevant modeling approaches, combining post-Keynesian and ecological economics [START_REF] Hardt | Ecological macroeconomic models: assessing current developments[END_REF]. Notably, the integration of IO with stock-flow consistent (SFC) models, which incorporate finance through consistent accounting of all monetary stocks and flows, as well as financial assets and liabilities [START_REF] Lavoie | Kaleckian models of growth in a coherent stock-flow monetary framework: a Kaldorian view[END_REF], shows promise in assessing integrated concerns about ecological impacts, financial stability, and social progress [START_REF] Hardt | Ecological macroeconomic models: assessing current developments[END_REF]. Additionally, IO can be effectively combined with broader system dynamics approaches, incorporating the representation of stocks, flows, and feedbacks across complex systems [START_REF] Radzicki | System dynamics and its contribution to economics and economic modeling[END_REF]. This integration allows for an improved representation of the dynamics of economic and biophysical linkages, by better capturing, for instance, the limitations to input substitutability through dynamic IO coefficients or the physical constraints linked to energy and resource availability [START_REF] Nieto | Macroeconomic modelling under energy constraints: Global low carbon transition scenarios[END_REF].

Advancing sustainability scenarios research

Overall, I see three important domains within sustainability scenarios research where advanced IAM-IO model integration could play a critical role.

Energy -Industry nexus

First of all, it could help to advance our understanding of the role of the industry sector in decarbonization pathways and to explore the energy-industry systems nexus beyond usual lifecycle analysis. While IAM-based scenarios often focus on the decarbonization of industrial processes (e.g., steel, cement, chemicals) based on assumptions about industrial demand trends, the industry sector is significantly influenced by various factors, including the lifecycle impacts of energy conversion and demand assets (such as power systems, transport equipment, buildings, etc.) through upstream and downstream supply chains involving intermediary consumption and investment. Particularly, manufacturing and construction of these assets have crucial supply chain linkages that feedback into industrial production and demand, with materials playing a significant role. Although existing linked IAM-IO studies already capture these linkages to a considerable extent [START_REF] Hertwich | Integrated life-cycle assessment of electricity-supply scenarios confirms global environmental benefit of low-carbon technologies[END_REF]) [START_REF] Wiebe | Implementing exogenous scenarios in a global MRIO model for the estimation of future environmental footprints[END_REF], they often do not thoroughly disentangle the detailed indirect impacts of energy technology development on industrial sectors and induced energy demand, mainly focusing on reporting carbon footprints. Hence, there is a need to comprehensively explore these feedbacks to better assess the role of the industry sector in decarbonization pathways, considering structural change perspectives and the broader socio-economic implications. The advanced IAM-IO modeling methods described in previous section can be utilized to address complementary aspects of this question. For instance, to explore the indirect and dynamically-consistent impacts of technology development on future material production and energy demand, an approach incorporating technology-specific vintage stock modeling and IO data would be favorable, for instance IAM hybrid LCA-MRIO soft-linking [START_REF] Hertwich | Integrated life-cycle assessment of electricity-supply scenarios confirms global environmental benefit of low-carbon technologies[END_REF] or advanced ESM-MRIO linking [START_REF] Ju | Industry's role in Japan's energy transition: soft-linking GCAM and National IO table with extended electricity supply sectors[END_REF] [START_REF] Budzinski | Coupling energy system models with multi-regional input-output models based on the make and use framework-insights from MESSAGEix and EXIOBASE[END_REF]. Vintage stock modeling is important for accurately assessing the material and energy impacts at the year of capital formation. On the other hand, a more top-down approach based on MRIO (without LCA data) or IO-based IAMs could be sufficient to capture the primary long-run energy-industry lifecycle linkages in economy-wide scenarios, including aspects such as the future EROI of the energy system, without requiring full lifecycle resolution or dynamic effects of specific technologies. Moreover, the socioeconomic implications for industrial sectors, including aspects like employment, value-added, and competitiveness, could be better evaluated using MRIO and IO-based IAMs, as these models focus on economic data and linkages.

Multi-dimensional sustainability impact assessment

A second research domain with significant potential for IAM-IO integration lies in the assessment of broader environmental interventions, extending beyond climate change, and achieving a more consistent and comprehensive evaluation of Sustainable Development Goals and pathways. Presently, IAM-based scenarios primarily focus on energy and climate policy, with efforts to assess the implications of mitigation pathways for SDGs [START_REF] Sörgel | A sustainable development pathway for climate action within the UN 2030 Agenda[END_REF].

However, these scenarios do not fully incorporate analysis of other environmental interventions beyond climate change on the one hand, and still perform incomplete assessment of SDGs by relying on indirect proxies or limiting assessments to impacts related solely to the energy system, on the other [START_REF] Rauner | Air quality co-benefits of ratcheting up the NDCs[END_REF].

The IO framework, by capturing industrial supply chains beyond the energy system, first enables investigation into additional environmental interventions. One such area is the circular economy, a crucial sustainability policy field that complements climate policy by aiming at greater circularity and resource efficiency in industrial processes (e.g., recycling, material efficiency, reuse) [START_REF] Yang | Circular economy strategies for combating climate change and other environmental issues[END_REF][START_REF] Gallego-Schmid | Links between circular economy and climate change mitigation in the built environment[END_REF]. Recently, EE-MRIO approaches have been utilized to evaluate global circular economy scenarios [START_REF] Wiebe | Global circular economy scenario in a multiregional input-output framework[END_REF], and IAM-EEMRIO linking could facilitate the exploration of integrated circular and mitigation scenarios, addressing both climate and resource-saving objectives. This integration is particularly relevant, considering that circular economy policies may also offer significant decarbonization potential [START_REF] Serrano | Contribution of circular economy strategies to climate change mitigation: Generic assessment methodology with focus on developing countries[END_REF]) [START_REF] Cooper | Thermodynamic insights and assessment of the 'circular economy[END_REF]. While a fully integrated circular and climate policy IO-based IAM is an option [START_REF] Econometrics | Study on modelling of the economic and environmental impacts of raw material consumption[END_REF], softlinking IAM-EEMRIO approaches may be more suitable for disentangling the different effects captured by complementary models. One challenge in gaining deeper insights into the circular economy is the explicit modeling of stock formation, which is usually not done with EE-MRIO models. The potentials for material efficiency and reusing or the availability of secondary materials are indeed highly contingent upon the dynamics of in-use stocks.

Moreover, IAM-IO integration provides a foundation for a more consistent and comprehensive assessment of SDGs and quantification of Sustainable Development Pathways (SDPs) across environmental, social, and economic dimensions. The EEMRIO framework can serve as an integrative platform for various scenario information, enabling the derivation of environmental and socio-economic footprint indicators across global supply chains that can be further related to SDGs. To translate footprints (i.e., pressures) into impacts and damages and ultimately SDG indicators (e.g., water scarcity, ecosystem damage, human health, resource depletion), dedicated add-on models (e.g. health impacts [START_REF] Zhang | Transboundary health impacts of transported global air pollution and international trade[END_REF]) [START_REF] Wiedmann | Environmental and social footprints of international trade[END_REF]) could be utilized. Similar approaches have been employed by different EEMRIO models to track current progress towards SDGs (Malik et al., 2019) (Gómez-Paredes and[START_REF] Gómez-Paredes | Tracking the Sustainable Development Goals with Input-Output Analysis: A commentary and example[END_REF].

For instance, material footprint estimates have been used to quantify SDGs 8 and 12 [START_REF] Lenzen | Implementing the material footprint to measure progress towards Sustainable Development Goals 8 and 12[END_REF], water footprinting for SDG6 [START_REF] Vanham | Physical water scarcity metrics for monitoring progress towards SDG target 6.4: An evaluation of indicator 6.4. 2 "Level of water stress[END_REF], social footprint for SDGs 3,5,6 and 16 [START_REF] Xiao | How social footprints of nations can assist in achieving the sustainable development goals[END_REF] including employment impacts [START_REF] Montt | Does climate action destroy jobs? An assessment of the employment implications of the 2-degree goal[END_REF], etc. Through IAM-EEMRIO integration, a similar approach could be applied in forward-looking scenarios, offering the advantage of consistent SDG assessment throughout global supply chains within the EEMRIO framework, including region-specific impacts. Here again, a soft-linking between IAM and MRIO might be the more relevant approach, mitigating the complexity of multidimensional analysis with a standalone IO-based IAM.

In addition, IAM-MRIO integration holds potential for advancing analysis in the field of inequality and equity. Recent studies have evaluated current global carbon inequality, examining the heterogeneity of carbon footprints across regions and individuals by combining EEMRIO data with household surveys [START_REF] Zheng | Rising carbon inequality and its driving factors from 2005 to 2015[END_REF] [START_REF] Chancel | Global carbon inequality over 1990-2019[END_REF]. These approaches can serve as a basis for evaluating the evolution of carbon inequality in transition scenarios, addressing equity issues related to the fair sharing of mitigation efforts across and within regions. To achieve this, IAM-EEMRIO linking can be combined with income inequality scenarios [START_REF] Rao | Income inequality projections for the shared socioeconomic pathways (SSPs)[END_REF] and estimates of income elasticities of carbon footprints to project carbon inequality within regions in addition to average regional carbon footprints. Moreover, the MRIO framework can be utilized to project income inequality within regions by examining changes in the sectoral composition of economies in relation to income distribution factors, such as labor and capital ratios and skill structures of sectors. Some IO-based macroeconomic and ecological macroeconomic IAMs already incorporate endogenous income distribution by describing heterogeneous households and worker groups distinguished by skills, occupational status, income sources, and taxation (Fragkos andFragkiadakis, 2022) (D'Alessandro et al., 2020).

Demand-side mitigation and post-growth scenarios

Eventually, we envision IAM-IO integration as a pivotal methodological approach for exploring demand-side transformations, demand-side solutions for mitigation (including sufficiency lifestyles), and post-growth climate mitigation scenarios. Despite recent efforts, demand-side transformations continue to be a major blind spot in IAMs, often represented only by the energy consumption of a few end-use sectors (such as industry, buildings, and transportation) as shown in Fig. 1. Energy projections in IAMs commonly rely on aggregated relationships between energy use and income per capita [START_REF] Bauer | Shared socio-economic pathways of the energy sector-quantifying the narratives[END_REF]. On the contrary, MRIO models offer a detailed description of final demand beyond energy and provide the opportunity to project demand-driven structural change scenarios, even at the macroeconomic level, based on alternative assumptions of final demand levels and structure [START_REF] Wiebe | Implementing exogenous scenarios in a global MRIO model for the estimation of future environmental footprints[END_REF]. Therefore, using MRIO frameworks can significantly expand the quantification of demand-side drivers in baseline scenarios like the SSPs. To achieve supply-demand integrated pathways, ESMs can be enriched with energy demand data derived from MRIO models.

Additionally, built-in demand-side drivers of structural change can be effectively captured using standalone IO-based macroeconomic IAMs [START_REF] Lefèvre | Global socioeconomic and climate change mitigation scenarios through the lens of structural change[END_REF].

In addition, while IAMs have explored demand-side mitigation measures towards reducing energy demand [START_REF] Grubler | A low energy demand scenario for meeting the 1.5 C target and sustainable development goals without negative emission technologies[END_REF][START_REF] Van Vuuren | Alternative pathways to the 1.5 C target reduce the need for negative emission technologies[END_REF], these measures have often been quantified outside the models and do not encompass the full scope of consumer-oriented solutions beyond the energy and food sectors [START_REF] Creutzig | Towards demand-side solutions for mitigating climate change[END_REF]. In contrast, the MRIO approach provides a consistent framework for more accurate and comprehensive exploration of consumer-oriented measures from an economy-wide perspective [START_REF] Wood | Prioritizing consumption-based carbon policy based on the evaluation of mitigation potential using input-output methods[END_REF]. Within IAM-IO integration holds particular potential to explore sufficiency lifestyles. Sufficiency lifestyles are broadly defined as those that seek to minimize material and energy consumption, reducing environmental pressures while satisfying human needs and prioritizing well-being and quality of life [START_REF] Jackson | Live better by consuming less?: is there a "double dividend" in sustainable consumption?[END_REF] [START_REF] Vita | The environmental impact of green consumption and sufficiency lifestyles scenarios in Europe: connecting local sustainability visions to global consequences[END_REF] [START_REF] Samadi | Sufficiency in energy scenario studies: Taking the potential benefits of lifestyle changes into account[END_REF]. In practice, transitioning from unsustainable consumption to sufficiency involves directly reducing resource-intensive consumption (e.g., buying fewer clothes, minimizing long-distance leisure travels, reducing living space and indoor temperature) or indirectly through sharing and repairing practices, and adopting more sustainable consumption modes (e.g., shifting transportation from cars to bikes or embracing less meat-intensive diets) through individual and collective actions. While a few IAM studies have integrated some sufficiency measures into alternative scenarios (e.g., adopting less meat-intensive diets, implementing transport modal shifts, lowering indoor temperatures), emphasizing their benefits in mitigation pathways, including reduced reliance on uncertain technologies, positive impacts on other sustainability goals, and alignment with well-being considerations [START_REF] Grubler | A low energy demand scenario for meeting the 1.5 C target and sustainable development goals without negative emission technologies[END_REF][START_REF] Van Vuuren | Alternative pathways to the 1.5 C target reduce the need for negative emission technologies[END_REF] [START_REF] Creutzig | Demand-side solutions to climate change mitigation consistent with high levels of well-being[END_REF], the MRIO approach offers a more comprehensive representation of sufficiency lifestyles [START_REF] Vita | The environmental impact of green consumption and sufficiency lifestyles scenarios in Europe: connecting local sustainability visions to global consequences[END_REF]. It allows for a wide range of sufficiency scenarios, encompassing direct end-use energy sufficiency for transportation and housing, as well as a more granular differentiation between high versus low resource-intensive or luxury versus essential goods and services.

Moreover, MRIO modeling can reflect various scenarios concerning changing preferences, beyond the scope of utility maximization, and quantify service provision and related consumption systems' implications on well-being. Here again, the advantages of MRIO can be harnessed through IAM-MRIO linking. Furthermore, IO-based macroeconomic IAMs, while representing sufficiency measures in less detail, can capture specific economic and behavioral feedback linked to sufficiency policies. For instance, they can account for potential unintended rebound effects that might lead to lower environmental benefits than initially anticipated [START_REF] Sorrell | The limits of energy sufficiency: A review of the evidence for rebound effects and negative spillovers from behavioural change[END_REF]) [START_REF] Figge | Sufficiency or efficiency to achieve lower resource consumption and emissions? The role of the rebound effect[END_REF].

In addition, sufficiency lifestyles align with the concept of a post-growth economy, which represents a broader shift in the economic paradigm towards a prosperous system that does not rely on continuous economic growth [START_REF] Kallis | The economics of degrowth[END_REF]. Instead, the focus lies on principles of equity, sufficiency, and service provision to achieve strong social outcomes while minimizing environmental footprints. In post-growth climate mitigation scenarios for highincome countries, the emphasis is on scaling down energy use and material throughput through sufficiency-oriented consumption and production patterns. It aims to enhance social well-being by reducing inequality, ensuring full employment, and guaranteeing access to public services [START_REF] Hickel | Urgent need for post-growth climate mitigation scenarios[END_REF]. The primary goal of post-growth policies is not to stabilize or decline aggregated GDP, but given the historical coupling between material throughput and GDP, it is a likely consequence that need to be dealt with [START_REF] Hardt | Ecological macroeconomic models: assessing current developments[END_REF]. Post-growth scenarios build on the advantages of sufficiency lifestyles but also encompass a wider transformation of the economic paradigm, deliberately avoiding rebound effects and relying on uncertain decoupling between economic growth and energy use. Despite the appealing features, IAMs have not much explored post-growth mitigation scenarios so far [START_REF] Hickel | Urgent need for post-growth climate mitigation scenarios[END_REF] and virtually all existing scenarios assume continuous economic growth in all countries from the outset [START_REF] Dellink | Long-term economic growth projections in the Shared Socioeconomic Pathways[END_REF]. Only a limited number of integrated modeling studies have approached post-growth mitigation, often based on alternative assumptions of lower GDP and aggregated consumption [START_REF] D'alessandro | Feasible alternatives to green growth[END_REF] or homogeneous downscaling of useful energy demand across economic sectors [START_REF] Li | Integrated assessment modelling of degrowth scenarios for Australia[END_REF]. While such studies allow exploration of uncharted areas in the existing scenario space such as the SSPs [START_REF] Dellink | Long-term economic growth projections in the Shared Socioeconomic Pathways[END_REF], providing insights into the benefits and risks of lower growth and consumption (faster decarbonization, lower need for low carbon technologies, but possible macroeconomic and social risks, etc.) (D'Alessandro et al., 2020) [START_REF] Li | Integrated assessment modelling of degrowth scenarios for Australia[END_REF], they do not provide insights on the structural transformations induced by post-growth strategies : what is consumed and produced in the economy ? How is the provisioning system organized ? Where do people get income from ? etc. Yet, a post-growth economy fundamentally involves differentiated downscaling of production and consumption [START_REF] Fitzpatrick | Exploring degrowth policy proposals: A systematic mapping with thematic synthesis[END_REF]. The IO framework, though not extensively used in this context thus far, could play a crucial role in describing the structural changes associated with a post-growth economy [START_REF] Hardt | What structural change is needed for a postgrowth economy: A framework of analysis and empirical evidence[END_REF] by integrating both consumption and production aspects. On the consumption side, IO mapping enables a clear understanding of shifts towards sufficiency lifestyles, minimizing energy and material throughput while meeting essential needs. On the production side, it can describe changes in production structures, promoting labor-intensive sectors and meaningful employment, such as in health, culture, education, and other service sectors [START_REF] Hardt | What structural change is needed for a postgrowth economy: A framework of analysis and empirical evidence[END_REF]. Table 3 : Summary of research topics (rows) and corresponding modeling approaches (columns). For each column, 'XX', 'X' and '--' indicate that the modeling approach is respectively best adapted, adapted or not adapted to address each research topic in collumn.

Table 3 provides an overview of the outlook for advanced IAM-IO integration and its relevance to sustainability scenarios research, as explored in this paper. Specifically, the table highlights the modeling approaches that are best suited to address each specific research topic, as discussed in more detail in the main text. It can be seen as a reference to select the most suitable approaches for tackling future research issues with advanced IAM-IO models.

Conclusion

The further integration of IAM and IO modeling approaches holds tremendous promise for enhancing our understanding of the intricate biophysical and economic linkages that underpin human societies. By combining the strengths of IAMs in representing transformative processes with the comprehensive supply chain linkages and interdependencies of IO frameworks, advanced IAM-IO integration opens up new avenues for multi-dimensional analysis of forwardlooking transition scenarios. Beyond technology-driven energy transition and decarbonization, this integration offers the potential to address a broader range of pressing sustainability challenges. In this paper, we have identified three main research domains needing urgent policy responses where IAM-IO integration can play a pivotal role : the energy-industry nexus, multidimensional sustainability assessment, and demand-side solutions, including post-growth climate mitigation scenarios. However, this list is not exhaustive, and other critical topics could be incorporated (e.g. climate change impacts across supply chains [START_REF] Okuyama | Disaster impact and input-output analysis[END_REF]). Moving forward, IAM-IO interaction and integration should be nurtured as a dynamic ecosystem of models and model linking methods, empowering researchers and practitioners to choose the most appropriate approach for addressing specific prospective questions across a wide spectrum of sustainability topics. This evolution will be bolstered by advanced community integration, fostering the sharing of data, model interfaces, and best practices. By cultivating such collaborations, policymakers and the general public would benefit from more advanced and transparent research, supporting collective decision-making for sustainable development strategies.

Figure 1 :

 1 Figure 1 : Linear representation of energy -economic systems in typical IAMs (based on ESMs)

Figure 2 :

 2 Figure 2 : Interdependence of economic sectors in IOA

From

  VA, output, jobs, etc.) impact assessment across economic sectors of energy system transition scenarios[START_REF] Siala | Towards a sustainable European energy system: Linking optimization models with multi-regional input-output analysis[END_REF] [START_REF] Ju | Job creation in response to Japan's energy transition towards deep mitigation: an extension of partial equilibrium integrated assessment models[END_REF] [START_REF] Oei | Coal phase-out in Germany-Implications and policies for affected regions[END_REF])[START_REF] Rady | Soft-linking Bottom-up energy models with Top-down Input-Output models to assess the environmental impact of future energy scenarios[END_REF]

  implement exogenous energy-economy scenarios, including technological and structural changes, in a global MRIO model. Exogenous scenarios information cover the level and structure of expenditure from households and capital formation (including investment for energy technologies) on the demand side and the input structure of energy supply and intermediary energy consumption -reflecting technical and technological improvements and substitutions -on the production side. Such a framework allows for exploring the implications of technology and production-oriented versus demandside consumption-oriented scenarios (De Koning et al.

  this framework, three main options for consumption-based solutions can be tested : (1) changing detailed consumption patterns, including reducing overall consumption (i.e., altering consumption of individual products and services, including energy); (2) modifying the inputs required for production in industries (e.g., optimizing production recipes for improved efficiency); and (3) reducing direct emissions and environmental impacts. Therefore, detailed consumption-based measures in transition scenarios could be captured through IAM-MRIO linking, for comprehensively representing supply-demand transformations based on consistent supply chain linkages. For instance, IAM-MRIO linking would allow for the examination of structural transformations in industry sectors triggered by changes in consumption patterns, and the subsequent implications for energy demand and carbon emissions.

  Furthermore, by distinguishing between private and public consumption, the IO framework can shed light on changes in provisioning systems, moving from markets to government with sectoral differentiation. It can also analyze changes in 'welfare purchasing power' of income. In this context, aggregated consumption and economic output become a consequence of changes in consumption and production patterns, rather than an assumption from the beginning. The IAM-MRIO linking approach thus offers an integrated vision of the detailed structural changes associated with post-growth scenarios and their implications for energy demand and decarbonization pathways. The sectoral effects also offer insights for deriving economic and social implications, such as economic output, employment, and income inequality. IO-based macroeconomic IAMs can also contribute to describing structural change effects in post-growth scenarios, although with less granularity, while providing macroeconomic feedback and consistency related to the impact of changes in production levels and structure on income and final demand. Beyond structural change, post-growth raises important questions about macroeconomic and financial stability, work patterns, and redistributive fiscal policies. IObased ecological macroeconomic IAMs are valuable tools to assess these issues and the macroeconomic transitions towards a post-growth economy[START_REF] D'alessandro | Feasible alternatives to green growth[END_REF]. In summary, the combination of IAM and MRIO modeling offers a comprehensive framework to explore post-growth scenarios, incorporating detailed structural changes, and understanding their wide-ranging implications on energy demand, decarbonization, economic stability,

Table 1

 1

	summarizes the main comparative advantages of IAM and EEIOA highlighting their
	complementary strengths for sustainability analysis.
		IAM	EEIOA
		 System dynamics	 System interdependence
		 Forward-looking scenarios	 Lifecycle impacts of
	Comparative	 Technical change	technology
	advantages	 Dynamic economic	 Multiple environmental impacts
		behaviours	across supply chains
		 High technology detail	 Consumption-based analysis
		 Price effects

 Intersectoral economic linkages

Table 1 : comparative advantages of IAM and EEIOA for sustainability analysis

  develop a global hybrid LCA-MRIO model to assess the multi-dimensional environmental impacts of exogenous scenarios of large scale adoption of low carbon power technologies at global scale. Future technological change is captured with high detail through the hybrid approach combining lifecyle inventories and MRIO data. A vintage stock model is also used to account for the

changes in the energy mix for manufacturing the future power plants. Incorporating detailed technical changes for upstream processes (e.g. manufacturing) in addition to that of the technology itself, becomes crucial when the objective is to quantify the lifecyle impacts of a specific technology in the future. This more precise aim is at the heart of prospective lifecycle assessment (pLCA) which involves modifying LCI data based on specific scenarios or IAM projections

[START_REF] Van Der Giesen | A critical view on the current application of LCA for new technologies and recommendations for improved practice[END_REF]

. Recent pLCA studies have expanded the scope of LCAs to future passengers vehicles

  as certain scenario data from the IAM, in addition to external sources, is utilized in the pLCA model to derive the EEU coefficients. However, improvements are still needed to enhance harmonization of scenario data across the LCA and IAM. the indirect emissions linked to consumption of intermediate goods and services[START_REF] He | Energy-economic recovery resilience with Input-Output linear programming models[END_REF] and capital formation (through the endogenization of capital goods for electricity technologies)[START_REF] Kang | Optimizing the Chinese electricity mix for co2 emission reduction: an input-output linear programming model with endogenous capital[END_REF].

	Eventually, although the majority of IAMs are based on ESM, a subset of models under the
	IAM umbrella (e.g. 4 out of 20 global IAMs referenced in Annex 3 of IPCC AR6 WGIII report :
	https://www.ipcc.ch/report/ar6/wg3/) originate from multi-sectoral macroeconomic modeling
	with IO economic accounting at their core -hereafter IO-based macroeconomic IAMs. These
	models employ a hard-linking approach, integrating bottom-up technical modules for key
	sectors (such as energy extraction, power generation, transportation, buildings, industry, and
	land-use) with dynamic multi-regional multi-sectoral computable general equilibrium (CGE)
	models or macroeconomic demand-led IO models. IO-based macroeconomic IAMs are
	designed to assess integrated technical and macroeconomic transformation pathways,
	considering structural change effects and supply chain linkages across production,
	consumption, economic sectors, and trade
	3.2. Hard-linking approaches
	Beyond soft-linking existing IAM and IO information or models, a few studies have sought to
	develop hard-linked IAM-IO or ESM-IO approaches. For instance, (He et al., 2017) and (Kang

[START_REF] Mcdowall | Is the optimal decarbonization pathway influenced by indirect emissions? Incorporating indirect life-cycle carbon dioxide emissions into a European TIMES model[END_REF]

. To do so, indirect emission factors (IEF) are estimated for the different technologies based on a hybrid LCA-IO model and further used in the optimization program of the ESM. This especially raises issues with sector to technology mapping and double counting. In

[START_REF] Mcdowall | Is the optimal decarbonization pathway influenced by indirect emissions? Incorporating indirect life-cycle carbon dioxide emissions into a European TIMES model[END_REF]

some evolution of IEFs is taken into account which follows the average decarbonization rate of the ESM industry sector. Alternatively, similar studies use a bottom-up LCA database instead of top-down IO models to evaluate a range of lifecycle environmental stressors per technology that are further applied to IAMs for environmental impact assessment

[START_REF] Arvesen | Deriving life cycle assessment coefficients for application in integrated assessment modelling[END_REF]

)

[START_REF] Rauner | Holistic energy system modeling combining multi-objective optimization and life cycle assessment[END_REF]

. For intance,

[START_REF] Pehl | Understanding future emissions from low-carbon power systems by integration of life-cycle assessment and integrated energy modelling[END_REF]

use coefficients for embodied energy use (EEU) and IEFs derived from a prospective LCA model within the IAM REMIND to evaluate optimal future energy systems accounting for indirect energy use and emissions. Also, as for

[START_REF] Mcdowall | Is the optimal decarbonization pathway influenced by indirect emissions? Incorporating indirect life-cycle carbon dioxide emissions into a European TIMES model[END_REF]

, in this case the linkage to the IAM can be considered bidirectional, et al., 2019) develop input-output linear programming (IO-LP) models at country level based on energy system cost minimization under I-O balance constraint. This method enables to compute in a standalone model optimal energy and power system decarbonization while taking into account