The selection process is deliberately structured to balance technical excellence with accessibility. Papers are nominated by members of the journal’s Editorial Board or its Prize Committee, and each candidate is evaluated against three criteria: professional merit, contribution to the field, and presentation quality. The adjudication committee publishes its rules on the journal’s website, and past award announcements, stretching back to the first winners introduced in 2015, provide a record of how the discipline’s methodological frontier has shifted over the past decade, from early material flow accounting toward machine learning, Bayesian statistics, and high-resolution global spatial modeling.

Nine papers were nominated for the 2025 cycle, and their collective breadth offers a snapshot of where industrial ecology is heading. Four were research articles. Aleksandra Kim, Christopher Mutel, and Stefanie Hellweg applied machine learning to conduct a global sensitivity analysis of correlated uncertainties in life cycle assessment, addressing one of the most persistent statistical problems in environmental footprinting. Jasmine Chea and colleagues automated the mapping of chemicals through their conditions of use, a step toward faster and more scalable life cycle chemical assessment. Two further nominated papers involved high-resolution mapping of materials in building stocks: a comprehensive global analysis of material stocks in buildings by Helmut Haberl and colleagues, and a dynamic assessment of building stock turnover across Japan by Satoshi Nagata and colleagues, which traced material and flow patterns nationwide from 2003 to 2020.

The remaining five nominated papers were methods articles, reflecting the field’s intense current interest in better analytical machinery. Philipp Grimmel and colleagues demonstrated how decision-support algorithms and databases of existing material exchanges can identify optimal opportunities for industrial symbiosis in regional economies, essentially building a recommendation platform that learns from historical exchange patterns to connect urban factories. Karin Krych, Daniel Müller, and Johan Pettersen cleverly incorporated what they describe as the nature and nurture of product lifetimes into a hazard function for dynamic stock modeling, separating intrinsic durability from contextual factors that shorten or extend product use. Jing Liao and colleagues took a technically sophisticated Bayesian approach to managing uncertainty in material flow networks, using model selection to discriminate between competing network structures and to support risk-informed decisions.

Rounding out the methods nominees, Miguel Sierra-Montoya and colleagues presented WindTrace, an open-source parametric model for generating life cycle inventories of wind turbines and wind parks, allowing environmental impacts of alternative wind energy designs to be assessed before hardware is ever built. Hanspeter Wieland, Dominik Wiedenhofer, Nina Eisenmenger, Takuma Watari, and Stefan Giljum used a global physical input-output model to assess the footprint of global iron ore mining on ecosystems, linking the steel consumed in one part of the world to the land disturbed in another. Together, the nominated set demonstrates a discipline that is simultaneously becoming more computational, more spatially explicit, and more directly connected to decision-making in energy and materials policy.

The 2025 Junior Best Paper Prize was awarded to Aleksandra Kim, Christopher Mutel, and Stefanie Hellweg for their publication on global sensitivity analysis of correlated uncertainties in life cycle assessment. Kim and Mutel are affiliated with the Laboratory for Energy Systems Analysis at the Paul Scherrer Institute in Villigen, Switzerland, while Kim also works with Hellweg in the Department of Civil, Environmental and Geomatic Engineering at ETH Zurich. The paper confronts a subtle but consequential problem: life cycle assessment databases are riddled with data whose uncertainties are correlated, because the same background processes, emission factors, and measurement methods feed into many different inventory entries. Classical sensitivity analysis techniques assume independence among inputs, and when that assumption fails, they can wildly misidentify which parameters actually drive the variability in a result.

The prize committee judged the Kim paper to be highly novel, providing new insight into how correlations between data can be handled when performing a global sensitivity analysis in life cycle assessment. The committee emphasized that the work is of high scientific quality and important for the field precisely because the approach can be applied to any life cycle assessment dataset, helping analysts address the credibility and robustness of their results. In practical terms, this matters for anyone who has ever questioned whether an environmental footprint number can be trusted: the method gives analysts a principled way to rank the true sources of uncertainty even when inputs are statistically entangled. The committee also praised the paper’s organization and readability, noting that complex techniques were explained clearly and supported by effective diagrams, a reminder that even the most mathematically demanding work in this field is judged partly on how well it communicates.

The junior prize competition was described as particularly close this year, and the committee gave special mention to two runner-up papers. The first was the Bayesian model selection work by Liao and colleagues, which brings formal probabilistic reasoning to the problem of choosing among competing material flow network structures. The second was the product lifetime paper by Krych and colleagues, whose nature-and-nurture framing of survival analysis offers dynamic stock modelers a more realistic treatment of why some products endure and others fail prematurely. That two of the three most celebrated junior-authored papers are methods innovations underscores how methodological development currently defines the field’s intellectual edge.

The 2025 Senior Best Paper Prize went to Hanspeter Wieland, Dominik Wiedenhofer, Nina Eisenmenger, Takuma Watari, and Stefan Giljum for their study assessing mining-related land footprints of global steel use with a global physical input-output model. Wieland, Wiedenhofer, and Eisenmenger are based at the Institute of Social Ecology at the University of Natural Resources and Life Sciences in Vienna, Austria. Watari works in the Material Cycles Division of the National Institute for Environmental Studies in Tsukuba, Japan, and Giljum is at the Institute for Ecological Economics at the Vienna University of Economics and Business. The paper builds on the authors’ previous global input-output model for iron and steel, but adds a decisive new layer of ecological granularity by disaggregating material flows into the specific biomes where mining takes place and by modeling both embodied land footprints and the human appropriation of net primary production.

The committee recognized many novel features in the winning senior paper. While iron ore mining is globally dominated by China, Australia, and Brazil, the authors showed that Europe holds the largest share of ecologically vulnerable tropical biomes in its embodied iron ore imports, a finding that reframes the geography of responsibility for mining-driven ecosystem damage. Rather than measuring trade in tonnes alone, the model traces exactly which ecosystems are disturbed to supply which consuming economies, connecting consumption patterns in wealthy regions to habitat loss and productivity appropriation in biodiversity-rich mining frontiers. The committee noted that the text was well written, aside from a high use of acronyms, and supported by vibrant diagrams, again rewarding technical rigor delivered with clarity.

Taken together, the 2025 Graedel Prizes highlight a discipline in methodological ascent. The winning junior paper makes uncertainty quantification in life cycle assessment more trustworthy; the winning senior paper makes the ecological consequences of the global steel economy visible at the biome scale. Around them, the nominated field is building recommendation engines for industrial symbiosis, parametric inventories for wind energy, Bayesian tools for flow networks, and continent-scale maps of the materials locked in buildings. For a field founded on the idea that human industry should be understood as an integrated system within the biosphere, the current generation of prize-recognized work shows that vision becoming operational: quantified, spatialized, and increasingly ready to inform real environmental decisions.

Subject of Research: The 2025 Graedel Prizes recognizing the best junior and senior first-authored papers in the Journal of Industrial Ecology.

Article Title: Winners of the 2025 Graedel Prizes: The Journal of Industrial Ecology Best Paper Prizes

Article References: Winners of the 2025 Graedel Prizes: The Journal of Industrial Ecology Best Paper Prizes. (n.d.). https://doi.org/10.1007/s44498-026-00165-2

Image Credits: AI Generated

DOI: 10.1007/s44498-026-00165-2

Keywords: Graedel Prizes, industrial ecology, life cycle assessment, sensitivity analysis, material flow analysis, steel land footprint, input-output model, industrial symbiosis, product lifetimes, building material stocks, wind energy, Journal of Industrial Ecology

The study’s authors, led by Lorenzo Rinaldi of the Department of Energy at Politecnico di Milano, built what they call a hybrid life-cycle assessment framework, embedding a detailed process-based model of the crystalline-silicon photovoltaic supply chain into the multi-regional input–output structure of the EXIOBASE database. The distinction matters because the two dominant tools for assessing the environmental footprint of technologies each fail in opposite ways. Process-based life-cycle assessment captures the fine technical detail of manufacturing but truncates the wider economy-wide ripples of production decisions. Top-down input–output models, by contrast, capture the whole economy but are too aggregated to distinguish polysilicon refining from wafer slicing or cell fabrication. The hybrid approach stitches the two together, resolving 18 new photovoltaic activities and 16 new commodities within a model spanning 22 regions, 205 activities and 220 commodities.

The supply chain the researchers resolved is one of the most geographically concentrated in the world. China accounts for more than 80 percent of global cell and module manufacturing capacity and more than 95 percent of the capacity for polysilicon, ingots and wafers, the electricity-hungry upstream stages where raw silicon is purified and sliced into the building blocks of solar cells. The model represents the full chain for monocrystalline silicon technology, which made up more than 98 percent of global production in 2024, from metallurgical-grade silicon through solar-grade silicon, ingots, wafers, cells and modules, along with balance-of-system components, installation and end-of-life treatment. Each stage is parameterised with bottom-up life-cycle inventory data drawn primarily from the IEA PVPS Task 12 database, complemented by NREL inventories and IRENA cost data, and harmonised to a functional unit of one square metre of module with a representative efficiency of 19.5 percent.

Before applying the model to policy, the team verified it against the literature. The carbon footprints of solar electricity produced by the hybrid model fall between 22 and 65 grams of CO2-equivalent per kilowatt-hour across regions, squarely within the ranges reported by harmonised life-cycle assessments and recent assessments by the IPCC, IRENA and NREL. The conventional top-down representation, by contrast, produced irregular and dispersed regional patterns, and in some cases implausible results, because without explicit manufacturing stages it assigned embodied emissions to generic domestic sectors such as electricity generation and construction. The hybrid model also reproduced producer prices of solar electricity more consistently against IRENA levelized-cost benchmarks. A key methodological finding is that conventional input–output models systematically underestimate the footprint of capital-intensive technologies like photovoltaics because the embodied impacts of productive capital, including the modules themselves, do not propagate into per-unit footprints unless capital is explicitly endogenised.

The decomposition of the footprint reveals where the carbon actually lives in a solar panel’s life. Electricity is the single largest contributor, reflecting the carbon-intensive grids powering upstream stages such as polysilicon, ingot and wafer production. Coal-fired power alone accounts for roughly 38 percent of the EU’s photovoltaic electricity footprint, rising to nearly 45 percent when coal extraction is included, and about 58 percent of the EU footprint originates in China. Each stage of the chain inherits most of its footprint from the stage immediately upstream — between 60 and 95 percent in both the EU and China — so delivered solar electricity is dominated by inherited manufacturing impacts: about 74 percent of the 51 grams per kilowatt-hour in the EU27 and 62 percent of the 65 grams in China. This cascading structure is precisely why relocating downstream assembly changes so little of the total footprint as long as upstream stages stay abroad.

When the researchers ran the Net Zero Industry Act scenario, comparing a 2030 baseline against a 2030 configuration in which 40 percent of module and upstream demand is met domestically, the reconfiguration proved strikingly uneven. EU module output rises from below 1 percent to about 10 percent of global production, but the EU share of cells, wafers, ingots and polysilicon remains at only a few per cent or less. European module factories would continue to rely heavily on imported intermediate inputs from Asia–Pacific regions, and the share of the EU’s photovoltaic electricity footprint originating within the EU climbs only from about 16 percent to 22 percent — meaning nearly 80 percent of embodied emissions remain tied to imported upstream stages even under the policy.

The economic picture is similarly asymmetric. EU value added increases by approximately €4 billion, with roughly half arriving as employee compensation, indicating that expanded module manufacturing, installation and downstream activities are relatively labour-intensive. China experiences the largest absolute loss, about €3.5 billion or 0.06 percent of its GDP, while South Korea, India and other suppliers of intermediate components benefit indirectly. Employment tells a similar story with a sharp asymmetry: the EU gains about 65,000 jobs while China loses about 229,000, a gap reflecting the fact that the Chinese industry spans an integrated set of upstream and downstream stages whereas the reshoring scenario expands mainly downstream activities in Europe. A substantial share of the additional European activity still leaks abroad through continued imports of cells, wafers, polysilicon and key materials such as glass, aluminium and precious metals.

The sensitivity analysis tested whether these findings were artefacts of scenario design. Sweeping the EU domestic share of upstream photovoltaic stages from 0 to 100 percent showed both the footprint and the recovered value responding smoothly, with no threshold at which leakage stops. Even full upstream reshoring would lower the EU footprint only from 42.8 to 39.9 grams of CO2-equivalent per kilowatt-hour, and the 40 percent target captures about €2 billion of the roughly €7 billion of value added recoverable under complete upstream reshoring. Physical parameters mattered too: for the EU, module efficiency is the dominant uncertainty, cutting the footprint by up to 14 percent at 24 percent efficiency, while for China the capacity factor dominates, with a 19 percent swing reflecting divergent yield estimates for Chinese sites.

The authors conclude that the Net Zero Industry Act should be understood primarily as an industrial capacity and supply-chain resilience policy rather than a climate instrument or a macroeconomic stimulus. The roughly 0.6 megatonnes of CO2-equivalent saved — about 5 percent of EU photovoltaic-related emissions and 0.02 percent of total EU greenhouse-gas emissions — largely reflect a geographic redistribution of manufacturing emissions rather than net global abatement, especially since photovoltaic electricity is already low-carbon and the environmental advantage of European manufacturing is likely to narrow as China’s grid decarbonises. If domestic value creation is the goal, the researchers argue, policy support should extend selectively to the electricity-intensive polysilicon, ingot and wafer stages that currently remain offshore, and the industrial strategy should be aligned with climate instruments such as the EU Emissions Trading System and the Carbon Border Adjustment Mechanism.

Beyond the specific policy verdict, the study carries a broader methodological message for anyone assessing clean-energy industrial strategy. Reshoring’s downstream concentration, persistent upstream import dependence, and the redistribution of emissions and value added across regions would be poorly captured by conventional models in which photovoltaic electricity generation is decoupled from its manufacturing chain. By resolving every stage from sand to silicon to module, the hybrid framework traces policy shocks along the global chain and exposes spillovers, bottlenecks and trade dependencies that aggregated models miss entirely. As the United States and India pursue parallel re-regionalisation of clean-energy supply chains, the finding that resilience comes at the price of modest climate and economic returns is likely to resonate far beyond Brussels.

Subject of Research: Environmental and socio-economic assessment of solar photovoltaic manufacturing reshoring in the EU under the Net Zero Industry Act using a hybrid input–output life-cycle model.

Article Title: Environmental and socio-economic implications of solar photovoltaic reshoring under the EU Net Zero Industry Act: a hybrid input–output assessment

Article References: Rinaldi, L., Merletti, R., Citterio, C., Golinucci, N., & Rocco, M. V. (2026). Environmental and socio-economic implications of solar photovoltaic reshoring under the EU Net Zero Industry Act: a hybrid input–output assessment. Journal of Industrial Ecology. https://doi.org/10.1007/s44498-026-00175-0

Image Credits: AI Generated

DOI: 10.1007/s44498-026-00175-0

Keywords: solar photovoltaics, Net Zero Industry Act, reshoring, hybrid life-cycle assessment, EXIOBASE, input–output model, carbon footprint, supply chain, value added, employment, EU industrial policy, photovoltaic manufacturing