The first major theme in the collection concerns the design and modification of asphalt binders and mixtures using functional and composite additives to survive increasingly hostile environments. One study by Huang and colleagues tackled the brutal combination of heat and humidity that afflicts coastal regions, demonstrating that synergistic modification, in which multiple additives are engineered to work together rather than in isolation, can improve both moisture stability and high-temperature performance. Crucially, the researchers backed their macroscopic observations with molecular-scale adhesion analysis, clarifying the mechanism by which the modified binder resists water-driven erosion at the interface between aggregate and asphalt. That kind of mechanistic explanation matters, because a modification that works without being understood is a fragile engineering solution, while one with a verified mechanism can be optimized, standardized, and transferred to new climates.

Nanomaterials and recycled modifiers are another frontier highlighted in the topic. A study by Wang and colleagues explored combinations of nanoscale additives with recycled components, showing improvements in physical properties, rheological behavior, and anti-aging performance. Rheology, the study of how materials deform and flow, is the key language here: pavements must resist rutting at summer temperatures yet remain flexible enough to avoid brittle cracking in winter, and a binder’s viscoelastic fingerprint determines how it walks that tightrope over decades of traffic. Meanwhile, Tao and colleagues showed that hybrid modification can balance high-temperature stability and water resistance with acceptable low-temperature performance. The practical significance is considerable, because balanced hybrid systems can reduce reliance on conventional petroleum asphalt, steering the industry toward modified and partially recycled binders without sacrificing the performance envelope that keeps roads safe.

The second theme cuts to the heart of modern materials science: the relationship between microstructure and macroscopic behavior. The editors deliberately encouraged multi-scale thinking, and several papers responded by linking material composition, internal structure, and engineering performance in explicit chains of evidence. A representative study by Hu and colleagues integrated conventional physical tests, rheological evaluation, infrared spectroscopy, and grey correlation analysis to show how waste-derived mineral additions alter chemical indices and viscoelastic behavior. Infrared spectroscopy reveals which chemical bonds and functional groups are present, while grey correlation analysis quantifies which of those chemical signatures most strongly predict the mechanical outcomes. The result is a pathway toward resource reutilization that is not guesswork but performance tailoring, in which an industrial by-product is transformed into an engineered ingredient whose effects can be tuned and predicted.

This approach carries a message the editors underline: sustainable pavement materials should not be viewed merely as cheap substitutes for virgin resources, but as engineered systems whose functionality emerges from controllable interactions across scales. A waste powder dumped into a mix is substitution; a waste powder whose chemistry, moisture sensitivity, and stiffening effect have been characterized and correlated with pavement response is design. That conceptual shift is what separates genuine circular-economy engineering from greenwashing, and it is becoming visible in the literature as cross-scale methods combining microstructural observation, rheological characterization, mechanistic modeling, and field validation become the norm rather than the exception.

Beyond asphalt, the topic extends into cementitious and composite materials that support transport infrastructure more broadly. Jiang and colleagues examined how stone powder content affects workability, strength development, and hydration behavior in concrete systems, providing practical guidance for using manufactured sand by-products more rationally. Manufactured sand, crushed rock produced as aggregates are quarried, arrives with variable fines content that can either improve packing and cohesion or cripple water demand and setting; quantifying that balance gives producers a rational basis for utilization rather than disposal. In a complementary study, Han and colleagues explicitly connected material design with environmental outcomes, showing that suitable composite admixtures can improve early-age performance while reducing carbon emissions across the material’s life stages. Together, these papers reinforce an essential message: sustainable pavement engineering increasingly depends on integrating mechanical performance objectives with circular resource use and measurable environmental benefit, not one at the expense of the other.

A third cluster of papers confronts the unforgiving reality that a superior material in the laboratory means little unless it produces a more resilient structure in service. Pavements operate under wildly variable traffic and environmental actions, so the editors emphasize the need to verify that improved materials translate into system-level performance. Huang and colleagues contributed valuable field evidence by combining in-situ bridge measurements with simulation, clarifying how axle load and vehicle speed influence the dynamic response of steel bridge deck pavement systems. Steel orthotropic bridge decks are among the most demanding pavement service environments anywhere, subject to intense local flexure and thermal extremes, and field-instrumented studies like this help close the gap between laboratory material innovation and full-scale engineering verification.

The digital dimension of the field is expanding just as fast. In a more data-driven direction, work illustrated in the topic shows how advanced numerical simulation and machine learning can be deployed together to improve structural evaluation under measurement uncertainty, pointing toward future digital-twin-based pavement management. A digital twin, in this context, would be a continuously updated computational replica of a pavement asset, fed by sensor data and calibrated models, capable of forecasting deterioration and optimizing maintenance before failures surface. Related contributions push the same frontier from other angles: studies modeling static and dynamic tire-pavement contact with an emphasis on three-dimensional surface texture, analyses of how different asphalt pavement structures respond under realistic tire loading, and characterization of concealed pavement distresses using ground-penetrating radar in integrated experimental and numerical studies. Sustainable pavement engineering, in other words, is not limited to creating better materials; it demands better characterization of texture, load transfer, hidden damage, and service-state evolution.

Taken together, the collected papers reveal three broader trends that the editors distill from the body of work. First, functional modification is moving toward synergistic and composite systems in which multiple additives are selected not to improve isolated properties but to achieve balanced performance under coupled thermal, moisture, traffic, and chemical actions. Second, the field increasingly relies on cross-scale methods that combine microstructural observation, rheological characterization, mechanistic modeling, and field validation to explain why materials perform as they do, replacing empirical trial and error with mechanistic understanding. Third, and perhaps most consequentially, sustainability is becoming quantifiable: many studies now connect material innovation with recyclability, resource efficiency, durability extension, or carbon reduction, moving the conversation from qualitative claims to engineering evidence that can be audited, compared, and codified into standards.

The editorial does not present the field as finished. The editors identify clear directions for future work, including long-term field validation of functional materials under climate change, standardization of multi-scale testing and performance indicators, tighter coupling of mechanistic and data-driven models, and life-cycle frameworks that simultaneously weigh performance, maintenance, emissions, and cost. They also call for deeper collaboration across materials science, transportation engineering, structural mechanics, sensing technology, and environmental assessment, disciplines that have historically published in parallel rather than in concert. The aspiration is pavements that are not only stronger and longer lasting, but smarter, more adaptive, and more sustainable, roads engineered as multi-scale systems from molecular adhesion to axle loads. As the editors conclude, the collected studies help define that pathway, and they hope the topic will serve as a useful reference for researchers and practitioners building the next generation of pavement materials and systems.

Subject of Research: Functional and sustainable materials for multi-scale pavement engineering design and environmental integration

Article Title: Editorial: Functional materials for sustainable pavement engineering: multi-scale design and environmental integration

Article References: Dai, J., Sangiorgi, C., Yang, X., Zhao, Z., & Li, C. (2026). Editorial: Functional materials for sustainable pavement engineering: multi-scale design and environmental integration. Frontiers in Materials, 13, Article 1931574. https://doi.org/10.3389/fmats.2026.1931574

Image Credits: AI Generated

DOI: 10.3389/fmats.2026.1931574

Keywords: sustainable pavements, asphalt modification, nanomaterials, rheology, multi-scale characterization, recycled materials, ground-penetrating radar, digital twin, life-cycle assessment, carbon reduction, tire-pavement contact, smart infrastructure

At its core, the book explores the integration of high-performance computing and artificial intelligence as complementary engines of sustainable digital transformation. High-performance computing, or HPC, refers to the aggregation of computing power across thousands of processors working in parallel, enabling scientists and engineers to tackle problems far beyond the reach of ordinary desktop machines. These systems simulate climate dynamics, model molecular interactions for drug discovery, optimize energy networks and process enormous datasets generated by satellites and sensors. Artificial intelligence, meanwhile, supplies the analytical layer that can extract patterns and actionable insights from the flood of data such simulations and sensors produce. The volume argues that when these two domains are deliberately combined with cloud computing platforms, organizations can scale their computational capacity up or down as needed, avoiding the waste associated with permanently provisioned hardware that sits idle much of the time.

The energy dimension of this convergence is among the most pressing themes the editors address. Large-scale computing facilities consume substantial electricity, both to power their processors and to cool the heat they generate. As artificial intelligence models grow larger and training runs stretch across weeks on vast GPU clusters, the carbon footprint of the digital economy has come under increasing scrutiny. The book positions HPC and AI not merely as sources of this footprint but as instruments for reducing it. Computational models can identify inefficiencies in manufacturing processes, optimize logistics routes to cut fuel consumption, and accelerate the design of new materials for batteries, solar cells and carbon capture technologies. In this framing, every kilowatt-hour spent on intelligent computation is an investment that can yield disproportionate savings in energy, emissions and materials elsewhere in the economy.

One of the most concrete application areas the volume examines is agriculture. AI- and AIoT-enabled sustainable agriculture, sometimes called smart farming, combines internet-connected sensors deployed across fields with machine learning systems that interpret the resulting data streams. Soil moisture probes, weather stations, drone-mounted cameras and satellite imagery together generate a continuous picture of crop health that no human observer could assemble manually. Machine learning models trained on this data can recommend precise irrigation schedules, detect pest infestations before they spread, and predict yields with enough accuracy to guide planting and harvesting decisions. The result, as the book describes it, is a form of farming that uses less water, applies fewer chemicals and produces less waste, all while maintaining or improving output. For a world facing both population growth and climate volatility, such precision techniques represent one of the most tangible ways computational technology contributes to sustainability.

The protection of critical cyber-physical infrastructure receives equally detailed treatment. Smart power grids exemplify the category: electricity networks that use digital sensors, automated controls and two-way communication to balance supply and demand in real time, particularly as intermittent renewable sources such as wind and solar are added to the generation mix. These systems are extraordinarily valuable and, by the same token, extraordinarily attractive targets. A successful cyberattack on a national grid could disrupt hospitals, water treatment plants, transportation and communications simultaneously. The book surveys cybersecurity solutions designed for such environments, including frameworks for risk assessment, continuous monitoring and the auditing of systems where a single vulnerability can cascade into physical consequences. Artificial intelligence plays a defensive role here as well, with anomaly detection models trained to recognize the subtle signatures of intrusions in network traffic before human operators could possibly respond.

Cloud security and data protection form a third pillar of the volume’s coverage. As organizations migrate workloads and sensitive data to cloud platforms, the traditional perimeter-based model of security dissolves. Data now crosses organizational, national and jurisdictional boundaries as a matter of routine, raising questions about who is responsible for protecting it and under which legal regime. The book addresses strategies for cloud security, risk assessment and auditing, alongside the governance frameworks needed to keep data handling accountable. These concerns are not abstract. Breaches of cloud-hosted databases have exposed the personal information of hundreds of millions of people, and regulators worldwide have responded with increasingly strict data protection requirements. The volume’s treatment of these topics reflects a growing consensus that security and sustainability are intertwined: infrastructure that cannot be trusted cannot be relied upon to deliver long-term environmental or economic benefits.

Beyond the technical chapters, the editors devote significant attention to the ethical, governance and policy considerations surrounding AI-driven computing. Intelligent systems increasingly make or inform decisions with real consequences for people, from credit assessments to medical diagnoses to the operation of autonomous machinery. Questions of algorithmic bias, transparency, accountability and the concentration of computational power in a small number of corporations are now inseparable from questions of system design. The book engages with these issues as part of a holistic view of sustainable computing, arguing that a digital infrastructure is only genuinely resilient if the societies that depend on it trust its operation and its oversight. Policy frameworks, the volume suggests, must evolve as quickly as the underlying technology if the benefits of AI and HPC are to be distributed broadly rather than captured narrowly.

The readership the editors envision is correspondingly broad. Researchers, graduate students, computer scientists and professionals working in artificial intelligence, high-performance computing, cloud computing, cybersecurity and sustainable computing are all named as the intended audience. This interdisciplinary reach reflects the nature of the challenge itself. No single discipline can deliver sustainable digital infrastructure: it requires computer architects who understand energy-efficient hardware, data scientists who can build trustworthy models, security specialists who can defend distributed systems, and domain experts in agriculture, energy and public policy who know where computational tools can do the most good. By gathering these perspectives in a single reference, the book functions as a bridge between communities that have often worked in parallel rather than in concert.

The volume is edited by Jagdish Chandra Patni and Nilesh Bhaskarrao Bahadure, who bring together research and professional perspectives on emerging computational technologies, artificial intelligence, cybersecurity and sustainable digital systems. Their editorial approach emphasizes the convergence of previously separate fields, treating sustainability not as an afterthought to computing but as a design objective that shapes architecture, software, security and governance alike. In an era when the digital sector’s share of global electricity consumption continues to climb even as the world races to decarbonize, that reframing carries real weight. The book’s central message is that the tools of computation and the goals of sustainability are not adversaries to be balanced but allies to be integrated, provided the engineering, security and ethical foundations are laid deliberately. For researchers and practitioners navigating that integration, the volume arrives as a timely and comprehensive map of the terrain.

Subject of Research: Convergence of high-performance computing, artificial intelligence and cloud technologies for sustainable and secure digital infrastructure

Article Title: High performance computing and sustainability through artificial intelligence

Article References: High performance computing and sustainability through artificial intelligence. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: high-performance computing, artificial intelligence, cloud computing, sustainability, cybersecurity, smart agriculture, AIoT, smart grids, data protection, carbon reduction, digital infrastructure, AI governance

The idea behind recycled-component concrete is deceptively simple. Instead of crushing waste concrete down into small recycled aggregates, or even into mid-sized concrete lumps of 60 to 300 millimeters, the new approach salvages entire concrete members, such as columns recovered through selective dismantling, and gives them only minimal processing: stripping off the rendering layer, cutting to length, and roughening the surfaces. These chunky recycled components are then placed directly inside the formwork of a new member, and fresh self-compacting concrete is cast around them. The result is a hybrid column in which nearly half the cross-section is made of old, already-cured concrete, complete with its original reinforcing bars and stirrups still intact inside.

The advantages over conventional recycling are substantial. Crushing waste into recycled aggregates still demands all the cement of ordinary concrete, so the carbon penalty of clinker production remains untouched. Recycled lump concrete improves on that by replacing some of the new mix, but casting quality limits lump replacement to about 35 percent, and the crushing process generates fine powder that is difficult to use. Recycled-component concrete, by contrast, can replace more than 50 percent of the new concrete, produces far less waste powder, and preserves the old reinforcement in usable condition, potentially trimming the amount of new steel required. Earlier studies in Europe had reused cut concrete slabs directly in new buildings, with one prototype floor system showing embodied carbon 80 to 94 percent lower than conventional concrete floors. But direct reuse runs into a stubborn problem: salvaged members rarely match the dimensions or strength grades their new positions demand. Casting new concrete around a recycled component elegantly dissolves that mismatch, because the surrounding mix absorbs any dimensional discrepancy and a stronger new mix can compensate for weaker old concrete.

What had never been tested, until now, was whether this hybrid configuration could survive the two brutal trials that matter most for columns: crushing axial compression and repeated cyclic earthquake loading. The concern was real. In a recycled-component concrete column, the old concrete sits as a concentrated block in the center of the section, surrounded by new concrete, creating a large, regularly shaped interface between the two generations of material. If that interface were to delaminate or slip under load, the whole concept would collapse, figuratively and literally. There was also a puzzle for the engineers’ calculators: the column contains two overlapping systems of stirrups, the new outer hoops and the old hoops locked inside the recycled component, and existing strength-prediction models, built for a single confinement system, simply did not apply.

To find out, the team fabricated nine square column specimens, 400 millimeters on a side and 1200 millimeters tall, for axial compression testing, seven of them recycled-component columns with a replacement ratio of 46 percent and two conventional references. Each recycled component was a 270 by 270 millimeter column, cut and roughened from a prefabricated 300 by 300 millimeter old column, its eight 12-millimeter longitudinal bars and 6-millimeter stirrups retained. The specimens were squeezed in a 15,000-kilonewton machine under displacement control, with strain gauges glued to both old and new stirrups to reveal how the two confinement systems shared the work. Seven more specimens, cantilever columns with a shear-span ratio of 3.375, were subjected to low-cycle reversed lateral loading under a constant axial load ratio of 0.4, mimicking the demands of a major earthquake.

The axial results were encouraging. During testing, no large-area delamination or spalling of new concrete from the recycled components occurred, confirming that the bond between old and new material held firm all the way to failure. The recycled-component columns carried somewhat lower peak loads than the references, from 7571 to 8339 kilonewtons against 8445 to 8648 kilonewtons, but the shortfall traced cleanly to the weaker old concrete, not to any interfacial weakness. Crucially, when the team raised the strength of the new concrete, specimen CR6 reached 8339 kilonewtons, nearly matching the 8445-kilonewton conventional reference, proving that a stronger surrounding mix can compensate for weaker salvaged material. Inclined-crossed stirrups, arranged in an X-pattern instead of conventional rectangular hoops, slightly increased capacity at the same steel quantity, and strain measurements showed they mobilized their confinement more effectively.

The seismic tests delivered the headline finding. Under reversed cyclic loading, the recycled-component columns and the conventional reference failed in the same characteristic way, with flexural cracks forming at the base, evolving into diagonal flexural-shear cracks, and culminating in concrete crushing within the plastic hinge region. Their hysteretic loops were similarly full, indicating strong energy dissipation, and their skeleton curves were nearly indistinguishable. Ductility coefficients ranged from 3.43 to 3.80, comfortably above the minimum of 3 required for reinforced concrete columns, and all but one specimen exceeded the 2 percent ultimate drift ratio demanded by Chinese seismic design codes. Remarkably, the recycled-component columns actually developed higher peak lateral loads than the conventional reference, reaching up to 370.2 kilonewtons against 343.9 kilonewtons, thanks to the stronger old concrete and the higher yield strength of the retained reinforcement. Incorporating a recycled component while slimming the new longitudinal bars from 18 and 16 millimeters down to 12 millimeters cost only 4 percent of ductility.

The experiments also delivered practical verdicts on construction details. Drilling post-installed rebars into the recycled components proved counterproductive under axial load, reducing peak capacity by 4.2 percent, apparently because the drilling introduced internal defects, and offering no seismic benefit either. Welded connectors between new and old stirrups improved ductility by only 4.7 percent, a gain judged too small to justify the cumbersome installation. The team’s recommendation is refreshingly economical: skip both. On the other hand, widening the spacing of the new stirrups cut the equivalent viscous damping coefficient by 17.6 percent and dropped one specimen below the drift-ratio requirement, so the confinement steel in the plastic hinge zone must not be skimped. Inclined-crossed stirrups emerged as the preferred arrangement, boosting energy dissipation by up to 8.6 percent, and their orientation relative to the loading direction made virtually no difference, freeing contractors from fussy placement.

Finally, the researchers closed the analytical gap. They divided the hybrid cross-section into three regions: unconfined cover concrete, concrete confined by the new stirrups alone, and the central old concrete squeezed simultaneously by both stirrup systems, then summed the regional contributions along with the old and new longitudinal steel. The resulting formula predicted the measured axial capacities of all nine specimens with a maximum error of just 8 percent, and only 5 percent for the conventional columns, showing that the dual-confinement model works across the spectrum. Taken together, the study offers the first technical foundation for columns that swallow nearly half their volume in salvaged concrete and part of their steel in salvaged reinforcement, while standing up to earthquakes as reliably as their all-new counterparts. In a construction industry desperate to cut its carbon ledger, that is a result worth building on.

Subject of Research: Axial compressive and seismic performance of recycled-component concrete columns made from reused waste concrete members

Article Title: Axial compressive behavior and seismic performance of recycled-component concrete columns

Article References: Li, Y., Wu, B., Zhang, H., & Wang, F. (2026). Axial compressive behavior and seismic performance of recycled-component concrete columns. Case Studies in Construction Materials, 25, Article e06453. https://doi.org/10.1016/j.cscm.2026.e06453

Image Credits: AI Generated

DOI: 10.1016/j.cscm.2026.e06453

Keywords: recycled-component concrete, recycled concrete, construction and demolition waste, seismic performance, axial compression, confinement, stirrups, carbon reduction, sustainable construction, cyclic loading, structural engineering, circular economy

The study, published in the Journal of Industrial Ecology, introduces a multi-objective, multi-level cleaner production evaluation framework that does something traditional scorecards have long failed to do: it treats carbon reduction as a first-class criterion rather than an afterthought. Grounded in the principles of industrial ecology, the framework combines a full life-cycle perspective with a dedicated carbon dimension, forcing evaluators to look beyond the smokestack and consider impacts from raw material extraction all the way through to the final steel product.

Cleaner production, a concept that has guided industrial environmental policy for decades, traditionally emphasizes reducing pollution and conserving resources within factory boundaries. But as climate change has moved to the center of global concern, that narrow focus has become inadequate. The Fudan team, led by Shoubing Wang together with Yuxuan Zhang, Qi Wei and Jingru Hu, argued that evaluation systems built before the carbon era simply cannot capture the full environmental profile of a modern steel enterprise, which must now answer for greenhouse gas emissions across its entire value chain.

To construct the framework, the researchers wove together three complementary methods. A systematic policy review of China’s cleaner production regulations for the steel sector revealed how policy priorities have evolved through three distinct stages, from an initialization phase, through rapid development, and into the current era of innovation and carbon focus. A life-cycle inventory analysis then defined the system boundary and screened which indicators genuinely matter across the steel production chain. Finally, expert consultation refined and validated the resulting indicator set, ensuring the framework reflected both scientific rigor and practical industrial realities.

Scoring within the framework relies on two well-established analytical techniques. An improved analytic hierarchy process, a structured method for deriving weights from pairwise comparisons, determines how much each indicator contributes to the overall score. Fuzzy comprehensive evaluation then converts indicator data into performance grades, an approach well suited to environmental assessment where many measures are inherently imprecise or qualitative. The combination allows the framework to aggregate dozens of indicators spanning resource consumption, energy use, pollution, product management and carbon reduction into a single interpretable score.

The real test came at Baosteel, one of China’s flagship steel producers and a subsidiary of the Baowu Group, the world’s largest steelmaker. Applying the framework to real operational data, the researchers found that Baosteel’s cleaner production score climbed from 62.68 in 2014, a rating classified as Domestic Poor, to 86.39 in 2021, achieving the Domestic Advanced category. That leap of nearly 24 points over seven years represents a striking transformation, but the story behind the numbers proved even more valuable than the headline result.

The evaluation did more than certify improvement; it pinpointed precisely where the company still fell short. Two critical weaknesses emerged: carbon reduction and product life-cycle management. Even as Baosteel advanced on conventional pollution and resource metrics, the dedicated carbon dimension exposed gaps that a traditional assessment would likely have missed or underweighted. This diagnostic capability is arguably the framework’s most important contribution, because it transforms evaluation from a passive grading exercise into an actionable roadmap, generating specific recommendations for where investment and management attention should flow next.

The timing of this work could hardly be more significant. China’s steel industry, the world’s largest producer, has been formally incorporated into the national carbon emissions trading market, and the sector faces intense pressure under the country’s carbon neutrality pledges. For an industry responsible for a substantial share of global carbon dioxide emissions, the difference between a scorecard that treats carbon as peripheral and one that places it at the core could shape investment decisions worth billions. A framework that quantifies carbon performance alongside energy efficiency and pollution control gives regulators, investors and company managers a common language for assessing progress.

The researchers are careful about the limits of their findings. The full case study rests on a single Chinese enterprise, and they emphasize that the results require cautious interpretation until the framework is validated across broader industrial and geographical contexts. The framework is presented as a proof of concept, a preliminary tool that could, with further contextualization and testing, help steel companies navigate sustainable production under tightening carbon constraints. Data limitations also reflect commercial realities: the raw Baosteel data was provided under license by Baosteel Engineering & Technology Group Co., Ltd. and cannot be made public due to confidentiality agreements, although the team notes supporting data are available upon reasonable request.

Nevertheless, the implications reach well beyond one company or one country. As carbon border adjustments, emissions trading schemes and net-zero commitments spread across the global economy, heavy industries everywhere will need credible, standardized ways to measure and compare environmental performance. A life-cycle based evaluation framework with a dedicated carbon dimension offers a template that could be adapted to cement, aluminum, chemicals and other hard-to-abate sectors. If cleaner production evaluation once measured how little smoke a factory emitted, the next generation of scorecards will measure how deeply a company has rewired its entire metabolism for a carbon-constrained world, and China’s steel industry, the study suggests, has shown just how far that rewiring can go in a single decade.

Subject of Research: A life cycle based cleaner production evaluation framework with an integrated carbon dimension, applied to China's steel industry

Article Title: A life cycle based cleaner production evaluation framework integrating a dedicated carbon dimension: a case study of China’s steel industry

Article References: Wang, S., Zhang, Y., Wei, Q., & Hu, J. (2026). A life cycle based cleaner production evaluation framework integrating a dedicated carbon dimension: a case study of China’s steel industry. Journal of Industrial Ecology, 30(5), 2295-2316. https://doi.org/10.1007/s44498-026-00155-4

Image Credits: AI Generated

DOI: 10.1007/s44498-026-00155-4

Keywords: steel industry, cleaner production, carbon reduction, life cycle assessment, industrial ecology, China, Baosteel, evaluation framework, carbon neutrality, multi-criteria decision analysis, fuzzy comprehensive evaluation, sustainable production