Ecolabels play a crucial role in achieving responsible production and consumption. Current LCA-based food ecolabels suffer from inconsistent methodologies, leading to significant variability in the estimated sustainability performance for the same product. To address the methodological challenges, we investigated 31 food ecolabels based on LCA from the EU countries, Norway, the UK, and Switzerland. Data were collected through questionnaires and systematically analysed. The analysis revealed significant heterogeneity in the methodologies behind the different food ecolabels, with variations in functional units, system boundaries, impact categories assessed, etc. Ecolabels exhibited a wide range of label formats regarding gradation type, score/value type, and impact category aggregation type, showcasing diverse approaches to communicating sustainability performance. The Product Environmental Footprint (PEF) and some PEF Category Rules (PEFCRs) are available for the LCA methodology used for the calculation, even though they need to be further tailored. However, no standards or guidelines are available for guiding the communication of LCA results with consumers in term of label formats at the EU level. Finally, the identified methodological challenges were discussed, emphasising the need for regulatory standards to address the diversity in ecolabeling practices and to guide the development of a more uniform and transparent framework for food ecolabels.
{"title":"Status of European food ecolabels based on life cycle assessment: methodological challenges toward convergence","authors":"Huayang Zhen , Bjørn Aamand Andersen , Vincent Colomb , Koen Boone , Lisbeth Mogensen , Fatemeh Hashemi , Marie Trydeman Knudsen","doi":"10.1016/j.spc.2025.10.012","DOIUrl":"10.1016/j.spc.2025.10.012","url":null,"abstract":"<div><div>Ecolabels play a crucial role in achieving responsible production and consumption. Current LCA-based food ecolabels suffer from inconsistent methodologies, leading to significant variability in the estimated sustainability performance for the same product. To address the methodological challenges, we investigated 31 food ecolabels based on LCA from the EU countries, Norway, the UK, and Switzerland. Data were collected through questionnaires and systematically analysed. The analysis revealed significant heterogeneity in the methodologies behind the different food ecolabels, with variations in functional units, system boundaries, impact categories assessed, etc. Ecolabels exhibited a wide range of label formats regarding gradation type, score/value type, and impact category aggregation type, showcasing diverse approaches to communicating sustainability performance. The Product Environmental Footprint (PEF) and some PEF Category Rules (PEFCRs) are available for the LCA methodology used for the calculation, even though they need to be further tailored. However, no standards or guidelines are available for guiding the communication of LCA results with consumers in term of label formats at the EU level. Finally, the identified methodological challenges were discussed, emphasising the need for regulatory standards to address the diversity in ecolabeling practices and to guide the development of a more uniform and transparent framework for food ecolabels.</div></div>","PeriodicalId":48619,"journal":{"name":"Sustainable Production and Consumption","volume":"61 ","pages":"Pages 94-105"},"PeriodicalIF":9.6,"publicationDate":"2025-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145425604","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-22DOI: 10.1016/j.spc.2025.10.008
Lorenzo Giacomella , Erika De Keyser , Erik Mathijs , Liesbet Vranken
Food packaging is often criticised for its environmental impact. However, it can play a crucial role in reducing avoidable waste generated during the consumption of food products. Relying on a lifecycle analysis, this study explores the trade-off between the environmental impacts of packaging and its potential to prevent food waste. In particular, commodity-specific waste scenarios are compared for packaged and unpackaged options across different household sizes, as household composition influences consumption rates and the likelihood of food spoilage. Results show that, when food waste rates are equal, packaged options generally have higher environmental impacts due to added processing and packaging materials. However, packaged alternatives may offer a preferable option when avoidable food waste is reduced below threshold levels that are commodity and household-size-specific. In particular, single-person households, currently over one-third of European households, are most at risk of exceeding these thresholds, implying that right-sized, convenience-oriented packaging could deliver net benefits if it effectively cuts waste. Conversely, larger households generally minimise impacts by choosing unpackaged produce. The findings underline three priorities: (i) incorporate commodity- and household-level waste heterogeneity into lifecycle assessment (LCA) and policy analyses; (ii) tailor packaging design to smaller households to realise waste-reduction potential; and (iii) refine food-waste statistics to support evidence-based decisions.
{"title":"Avoidable food waste and household size: A life cycle comparison of packaged and unpackaged fruits and vegetables","authors":"Lorenzo Giacomella , Erika De Keyser , Erik Mathijs , Liesbet Vranken","doi":"10.1016/j.spc.2025.10.008","DOIUrl":"10.1016/j.spc.2025.10.008","url":null,"abstract":"<div><div>Food packaging is often criticised for its environmental impact. However, it can play a crucial role in reducing avoidable waste generated during the consumption of food products. Relying on a lifecycle analysis, this study explores the trade-off between the environmental impacts of packaging and its potential to prevent food waste. In particular, commodity-specific waste scenarios are compared for packaged and unpackaged options across different household sizes, as household composition influences consumption rates and the likelihood of food spoilage. Results show that, when food waste rates are equal, packaged options generally have higher environmental impacts due to added processing and packaging materials. However, packaged alternatives may offer a preferable option when avoidable food waste is reduced below threshold levels that are commodity and household-size-specific. In particular, single-person households, currently over one-third of European households, are most at risk of exceeding these thresholds, implying that right-sized, convenience-oriented packaging could deliver net benefits if it effectively cuts waste. Conversely, larger households generally minimise impacts by choosing unpackaged produce. The findings underline three priorities: (i) incorporate commodity- and household-level waste heterogeneity into lifecycle assessment (LCA) and policy analyses; (ii) tailor packaging design to smaller households to realise waste-reduction potential; and (iii) refine food-waste statistics to support evidence-based decisions.</div></div>","PeriodicalId":48619,"journal":{"name":"Sustainable Production and Consumption","volume":"61 ","pages":"Pages 1-14"},"PeriodicalIF":9.6,"publicationDate":"2025-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145366163","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-21DOI: 10.1016/j.spc.2025.10.006
Yiwei Wang , Yuping Bai , Xiangzheng Deng , Gaurav Sikka , Yecui Hu , Yangfan Chen , Guofeng Wang
The challenge of reversing the vicious cycle between climate change and food systems is attracting considerable attention. However, building a sustainable dietary system in line with China's national conditions remains a challenging endeavor. By developing a multi-regional input-output model at high sector resolution for China encompassing 31 provinces and 163 sectors, we investigate five diet-related environmental footprint indicators, assess the environmental impacts of dietary consumption and design five possible future dietary strategies to explore their potential environmental mitigation effects in China. Our findings revealed significant spatial heterogeneity in the environmental footprints of food consumption adopting different dietary strategies. The comprehensive dietary strategy could reduce environmental pressure by 3 %–15 %. The most significant effect would be a reduction by 146.82 Mt CO2eq in greenhouse gas (GHG) footprint and 33.71bcm in water use footprint relative to the business-as-usual scenario, equivalent to about 10 % of current agricultural GHG emissions and water use. This environmental benefit is largely due to reduced cereals and red meat consumption. Achieving a sustainable dietary shift would require the concerted efforts of diverse stakeholders.
{"title":"Exploring dietary transition and its environmental mitigation effects in China","authors":"Yiwei Wang , Yuping Bai , Xiangzheng Deng , Gaurav Sikka , Yecui Hu , Yangfan Chen , Guofeng Wang","doi":"10.1016/j.spc.2025.10.006","DOIUrl":"10.1016/j.spc.2025.10.006","url":null,"abstract":"<div><div>The challenge of reversing the vicious cycle between climate change and food systems is attracting considerable attention. However, building a sustainable dietary system in line with China's national conditions remains a challenging endeavor. By developing a multi-regional input-output model at high sector resolution for China encompassing 31 provinces and 163 sectors, we investigate five diet-related environmental footprint indicators, assess the environmental impacts of dietary consumption and design five possible future dietary strategies to explore their potential environmental mitigation effects in China. Our findings revealed significant spatial heterogeneity in the environmental footprints of food consumption adopting different dietary strategies. The comprehensive dietary strategy could reduce environmental pressure by 3 %–15 %. The most significant effect would be a reduction by 146.82 Mt CO<sub>2</sub>eq in greenhouse gas (GHG) footprint and 33.71bcm in water use footprint relative to the business-as-usual scenario, equivalent to about 10 % of current agricultural GHG emissions and water use. This environmental benefit is largely due to reduced cereals and red meat consumption. Achieving a sustainable dietary shift would require the concerted efforts of diverse stakeholders.</div></div>","PeriodicalId":48619,"journal":{"name":"Sustainable Production and Consumption","volume":"61 ","pages":"Pages 37-47"},"PeriodicalIF":9.6,"publicationDate":"2025-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145425603","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study examines Northern Italian farmers' intentions to adopt biochar by applying the Technology Acceptance Model and an extended specification tailored to sustainability contexts. A cross-sectional telephone survey of farmers (n = 131) was analysed using partial least squares structural equation modelling. We estimate a baseline model that includes perceived usefulness, perceived ease of use, subjective norm, image, job relevance, output quality, and result demonstrability, as well as an extended model that adds climate-change awareness, perceived economic value (price–value), and perceived external control/support.
Across specifications, intention to adopt is positively related to perceived usefulness and perceived ease of use. In the extended model, the economic value proposition emerges as the most salient antecedent of perceived usefulness, with additional contributions from output quality, result demonstrability, and awareness of climate change. By contrast, social-influence pathways (subjective norm, image) are weak or inconsistent.
The exploratory findings suggest that, in a voluntary setting with generally low prior knowledge, farmers' intentions are most consistent with instrumental, value-for-money judgments and the perceived simplicity of implementation, rather than social endorsement. Interpretations are correlational and are bound to a sample of Northern Italian farmers. Practical implications include demonstrating credible agronomic and economic benefits, reducing perceived complexity, and ensuring visible support for early adopters. Future research should validate these patterns longitudinally and in other countries and awareness stages.
{"title":"Exploring behavioural intentions behind biochar technology adoption in agriculture","authors":"Mariavittoria Perrone , Giordano Ruggeri , Alberto Tosca , Edoardo Verga , Chiara Mazzocchi","doi":"10.1016/j.spc.2025.10.009","DOIUrl":"10.1016/j.spc.2025.10.009","url":null,"abstract":"<div><div>This study examines Northern Italian farmers' intentions to adopt biochar by applying the Technology Acceptance Model and an extended specification tailored to sustainability contexts. A cross-sectional telephone survey of farmers (<em>n</em> = 131) was analysed using partial least squares structural equation modelling. We estimate a baseline model that includes perceived usefulness, perceived ease of use, subjective norm, image, job relevance, output quality, and result demonstrability, as well as an extended model that adds climate-change awareness, perceived economic value (price–value), and perceived external control/support.</div><div>Across specifications, intention to adopt is positively related to perceived usefulness and perceived ease of use. In the extended model, the economic value proposition emerges as the most salient antecedent of perceived usefulness, with additional contributions from output quality, result demonstrability, and awareness of climate change. By contrast, social-influence pathways (subjective norm, image) are weak or inconsistent.</div><div>The exploratory findings suggest that, in a voluntary setting with generally low prior knowledge, farmers' intentions are most consistent with instrumental, value-for-money judgments and the perceived simplicity of implementation, rather than social endorsement. Interpretations are correlational and are bound to a sample of Northern Italian farmers. Practical implications include demonstrating credible agronomic and economic benefits, reducing perceived complexity, and ensuring visible support for early adopters. Future research should validate these patterns longitudinally and in other countries and awareness stages.</div></div>","PeriodicalId":48619,"journal":{"name":"Sustainable Production and Consumption","volume":"61 ","pages":"Pages 66-81"},"PeriodicalIF":9.6,"publicationDate":"2025-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145425607","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-21DOI: 10.1016/j.spc.2025.10.007
Sofia Bahmutsky , Ian Turner , Vivek Arulnathan , Nathan Pelletier
A well-executed life cycle assessment requires thorough data collection across all relevant processes, combined with advanced data analysis. Common data-related issues in life cycle assessment research include the absence of necessary data, low data quality, inconsistencies, uncertainty, and failure to account for variations over time and location. In this context, data science, the discipline of extracting meaningful insights from data, has the potential to address these challenges. While the integration of data science with life cycle assessment holds significant potential, best use cases depend on the goal of the study, as well as the data type and volume required, underscoring the necessity of reviewing the intersection of data science and life cycle assessment. This study used the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) method to identify literature addressing the use of data science elements to support life cycle assessment. It evaluated which data science techniques are appropriate for specific life cycle assessment stages or problem areas and the strengths and weaknesses of current data science applications in life cycle assessment. Key opportunities identified revolve around solutions for dealing with missing or poor-quality data, expensive/prohibitive data collection, and improving the accuracy of life cycle assessment results. The currently most feasible pathways appear to involve use of machine learning techniques, as these types of studies were the most conducted and generated tangible results. Extreme gradient boosting, random forest, and artificial neural networks were particularly prominent algorithm choices. Data collection and transferability using ontologies and semantic tools were also highlighted as important strategies for improving data flow in life cycle assessment, including the integration of a wide variety of databases and non-life cycle assessment data.
{"title":"Advancing life cycle assessment through data science: A critical review of algorithms, tools, and data challenges","authors":"Sofia Bahmutsky , Ian Turner , Vivek Arulnathan , Nathan Pelletier","doi":"10.1016/j.spc.2025.10.007","DOIUrl":"10.1016/j.spc.2025.10.007","url":null,"abstract":"<div><div>A well-executed life cycle assessment requires thorough data collection across all relevant processes, combined with advanced data analysis. Common data-related issues in life cycle assessment research include the absence of necessary data, low data quality, inconsistencies, uncertainty, and failure to account for variations over time and location. In this context, data science, the discipline of extracting meaningful insights from data, has the potential to address these challenges. While the integration of data science with life cycle assessment holds significant potential, best use cases depend on the goal of the study, as well as the data type and volume required, underscoring the necessity of reviewing the intersection of data science and life cycle assessment. This study used the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) method to identify literature addressing the use of data science elements to support life cycle assessment. It evaluated which data science techniques are appropriate for specific life cycle assessment stages or problem areas and the strengths and weaknesses of current data science applications in life cycle assessment. Key opportunities identified revolve around solutions for dealing with missing or poor-quality data, expensive/prohibitive data collection, and improving the accuracy of life cycle assessment results. The currently most feasible pathways appear to involve use of machine learning techniques, as these types of studies were the most conducted and generated tangible results. Extreme gradient boosting, random forest, and artificial neural networks were particularly prominent algorithm choices. Data collection and transferability using ontologies and semantic tools were also highlighted as important strategies for improving data flow in life cycle assessment, including the integration of a wide variety of databases and non-life cycle assessment data.</div></div>","PeriodicalId":48619,"journal":{"name":"Sustainable Production and Consumption","volume":"61 ","pages":"Pages 25-36"},"PeriodicalIF":9.6,"publicationDate":"2025-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145425662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-21DOI: 10.1016/j.spc.2025.10.010
Hafiz Usman Ghani , Anniina Lehtilä , Anna Forssén , Xing Liu , Ilkka Leinonen
The European forests are essential in achieving the land use and land-use change (LULUC) related CO2 removal targets. Adoption of various harvesting practices significantly influences the overall LULUC emissions and removals of forests. In this study, we used the life cycle assessment (LCA) approach to systematically evaluate the land use and land use change-related emissions and removals (GWPLULUC) of harvested wood raw material. We applied different case study scenarios with different forest management practices in Finland in comparison to the business as usual scenario (one pre-commercial thinning and two commercial thinnings): i) a scenario with no pre-commercial thinning, ii) a scenario with reduced thinning with longer rotation cycle, and iii) a scenario with collection of logging residues. We also explored the effect of management on land occupation. We modeled various scenarios using the MOTTI stand simulation for birch, spruce, and pine, encompassing different vegetation types across various regions of Finland. This was followed by soil carbon modelling using the Yasso07 model to assess the effect of residue collection for spruce. Our analysis indicated that the management effects on GWPLULUC emissions and removals vary across regions, vegetation types, and management practices. Especially, reduced thinning with longer rotation cycles results in significant carbon removals and lowest land occupation due to the longest rotation cycle (except for birch). The collection of residues leads to small losses of soil organic carbon, but the effect was a negligible factor in the overall GWP of wood raw material. These findings underscore the intricate interplay between regional, species-specific, and management-related factors in shaping the GWPLULUC of forest-based products.
{"title":"Evaluating the global warming potential of harvested wood due to the carbon stock changes under different forest management practices","authors":"Hafiz Usman Ghani , Anniina Lehtilä , Anna Forssén , Xing Liu , Ilkka Leinonen","doi":"10.1016/j.spc.2025.10.010","DOIUrl":"10.1016/j.spc.2025.10.010","url":null,"abstract":"<div><div>The European forests are essential in achieving the land use and land-use change (LULUC) related CO<sub>2</sub> removal targets. Adoption of various harvesting practices significantly influences the overall LULUC emissions and removals of forests. In this study, we used the life cycle assessment (LCA) approach to systematically evaluate the land use and land use change-related emissions and removals (GWP<sub>LULUC</sub>) of harvested wood raw material. We applied different case study scenarios with different forest management practices in Finland in comparison to the business as usual scenario (one pre-commercial thinning and two commercial thinnings): i) a scenario with no pre-commercial thinning, ii) a scenario with reduced thinning with longer rotation cycle, and iii) a scenario with collection of logging residues. We also explored the effect of management on land occupation. We modeled various scenarios using the MOTTI stand simulation for birch, spruce, and pine, encompassing different vegetation types across various regions of Finland. This was followed by soil carbon modelling using the Yasso07 model to assess the effect of residue collection for spruce. Our analysis indicated that the management effects on GWP<sub>LULUC</sub> emissions and removals vary across regions, vegetation types, and management practices. Especially, reduced thinning with longer rotation cycles results in significant carbon removals and lowest land occupation due to the longest rotation cycle (except for birch). The collection of residues leads to small losses of soil organic carbon, but the effect was a negligible factor in the overall GWP of wood raw material. These findings underscore the intricate interplay between regional, species-specific, and management-related factors in shaping the GWP<sub>LULUC</sub> of forest-based products.</div></div>","PeriodicalId":48619,"journal":{"name":"Sustainable Production and Consumption","volume":"61 ","pages":"Pages 15-24"},"PeriodicalIF":9.6,"publicationDate":"2025-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145425663","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-19DOI: 10.1016/j.spc.2025.10.005
Yuning Zhang , Yanhua Wang , Yunsong Liang , Ke Wang , Hongxia Zhang
Demand-side strategies are vital for mitigating supply bottlenecks of critical materials in clean energy deployment. However, their potential remains unclear primarily due to the “black box” limitation of conventional material flow analysis (MFA) methods. This study develops a dynamic integrated assessment framework combining a hybrid input-output analysis, an optimized Markov model, a dynamic MFA approach, and Monte Carlo simulation. This framework is applied to quantify the anthropogenic metabolism of eight critical materials in China's solar power system toward 2060 and to assess the material-saving effects of five demand-side strategies, such as grid integration enhancement. Results show that cumulative demand for Tellurium, Selenium, Indium, and Germanium may exceed China's 2022 reserves by 2060 in baseline case. Fortunately, implementing demand-side strategies can reduce primary material inputs by 32.8–36.7 %, with maximum material-saving contributions of 3.5 Mt for Silicon, 10.6 kt for Germanium, 4.8 kt for Copper, 4.4 kt for Indium, 1.1 kt for Gallium, 11.2 kt for Selenium, 3.8 kt for Cadmium, and 4.3 kt for Tellurium. Furthermore, these strategies outperform recycling alone and resolve Selenium and Indium constraints, making CIGS the only materially sustainable thin-film technology in SSP2-CD and SSP5-CD scenarios. The proposed framework provides a systematic basis for China's demand-side policymaking to mitigate critical material supply bottlenecks in solar system, while offering scalable solutions to harmonize sustainable material consumption with low-carbon energy transitions in emerging economies.
{"title":"Demand-side strategies can mitigate critical material supply bottlenecks in China's solar photovoltaic deployment: A dynamic integrated assessment framework","authors":"Yuning Zhang , Yanhua Wang , Yunsong Liang , Ke Wang , Hongxia Zhang","doi":"10.1016/j.spc.2025.10.005","DOIUrl":"10.1016/j.spc.2025.10.005","url":null,"abstract":"<div><div>Demand-side strategies are vital for mitigating supply bottlenecks of critical materials in clean energy deployment. However, their potential remains unclear primarily due to the “black box” limitation of conventional material flow analysis (MFA) methods. This study develops a dynamic integrated assessment framework combining a hybrid input-output analysis, an optimized Markov model, a dynamic MFA approach, and Monte Carlo simulation. This framework is applied to quantify the anthropogenic metabolism of eight critical materials in China's solar power system toward 2060 and to assess the material-saving effects of five demand-side strategies, such as grid integration enhancement. Results show that cumulative demand for Tellurium, Selenium, Indium, and Germanium may exceed China's 2022 reserves by 2060 in baseline case. Fortunately, implementing demand-side strategies can reduce primary material inputs by 32.8–36.7 %, with maximum material-saving contributions of 3.5 Mt for Silicon, 10.6 kt for Germanium, 4.8 kt for Copper, 4.4 kt for Indium, 1.1 kt for Gallium, 11.2 kt for Selenium, 3.8 kt for Cadmium, and 4.3 kt for Tellurium. Furthermore, these strategies outperform recycling alone and resolve Selenium and Indium constraints, making CIGS the only materially sustainable thin-film technology in SSP2-CD and SSP5-CD scenarios. The proposed framework provides a systematic basis for China's demand-side policymaking to mitigate critical material supply bottlenecks in solar system, while offering scalable solutions to harmonize sustainable material consumption with low-carbon energy transitions in emerging economies.</div></div>","PeriodicalId":48619,"journal":{"name":"Sustainable Production and Consumption","volume":"61 ","pages":"Pages 48-65"},"PeriodicalIF":9.6,"publicationDate":"2025-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145425605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-17DOI: 10.1016/j.spc.2025.10.004
Sara Rashidian , SK Tahsin Hossain , Kirsty Volz , Melissa Teo
<div><div>Integrating Construction 4.0 technologies—the construction-specific application of Industry 4.0—with circular economy (CE) principles presents a transformative opportunity for the construction sector to enhance sustainability, improve resource efficiency, and build long-term resilience. Construction 4.0 refers to the digitalisation and automation of processes through technologies such as Building Information Modelling (BIM), the Internet of Things (IoT), blockchain, digital twins, robotics, and artificial intelligence (AI). Given the construction industry's significant environmental footprint and contribution to global waste, aligning Construction 4.0 with CE principles is essential for shifting from traditional linear practices towards regenerative, closed-loop systems. While sectors such as transport and manufacturing have already demonstrated the benefits of Industry 4.0 technologies in reducing waste and optimising resources, construction has been comparatively slow to embed these innovations across buildings and infrastructure. In addition, despite growing scholarly and industry interest, there remains no comprehensive framework that systematically integrates Construction 4.0 technologies with CE principles across all stages of the construction lifecycle.</div><div>This study addresses this gap through a systematic literature review of 58 peer-reviewed articles published between 2015 and 2024, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The review focused on English-language publications directly examining the intersection of Construction 4.0 and CE in the construction sector, while excluding non-peer-reviewed studies from unrelated industries. Thematic and co-occurrence analyses were applied to map the alignment of CE principles with Construction 4.0 technologies across seven phases of construction: Planning, Design, Tendering, Manufacturing, Construction, Operation, and End-of-Life. The study contributes a conceptual framework that visualises these alignments and highlights key opportunities and barriers for advancing circularity through digital transformation within the construction industry.</div><div>The findings highlight that BIM and IoT play pivotal roles in lifecycle planning, operational efficiency, and resource optimisation, while AI and digital twins support predictive maintenance, material recovery, and closed-loop optimisation. In contrast, robotics and blockchain remain underutilised in manufacturing and deconstruction, representing significant untapped potential to advance circularity. Persistent challenges, including fragmented stakeholder collaboration, siloed practices, and slow technological adoption, continue to impede the sector's ability to fully realise CE ambitions.</div><div>Future research should focus on fostering early stakeholder engagement and promoting cross-phase integration of Construction 4.0 technologies to enhance circular outcomes. Furth
{"title":"Enabling circularity in construction: A technology-phase alignment of construction 4.0 and circular economy principles","authors":"Sara Rashidian , SK Tahsin Hossain , Kirsty Volz , Melissa Teo","doi":"10.1016/j.spc.2025.10.004","DOIUrl":"10.1016/j.spc.2025.10.004","url":null,"abstract":"<div><div>Integrating Construction 4.0 technologies—the construction-specific application of Industry 4.0—with circular economy (CE) principles presents a transformative opportunity for the construction sector to enhance sustainability, improve resource efficiency, and build long-term resilience. Construction 4.0 refers to the digitalisation and automation of processes through technologies such as Building Information Modelling (BIM), the Internet of Things (IoT), blockchain, digital twins, robotics, and artificial intelligence (AI). Given the construction industry's significant environmental footprint and contribution to global waste, aligning Construction 4.0 with CE principles is essential for shifting from traditional linear practices towards regenerative, closed-loop systems. While sectors such as transport and manufacturing have already demonstrated the benefits of Industry 4.0 technologies in reducing waste and optimising resources, construction has been comparatively slow to embed these innovations across buildings and infrastructure. In addition, despite growing scholarly and industry interest, there remains no comprehensive framework that systematically integrates Construction 4.0 technologies with CE principles across all stages of the construction lifecycle.</div><div>This study addresses this gap through a systematic literature review of 58 peer-reviewed articles published between 2015 and 2024, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The review focused on English-language publications directly examining the intersection of Construction 4.0 and CE in the construction sector, while excluding non-peer-reviewed studies from unrelated industries. Thematic and co-occurrence analyses were applied to map the alignment of CE principles with Construction 4.0 technologies across seven phases of construction: Planning, Design, Tendering, Manufacturing, Construction, Operation, and End-of-Life. The study contributes a conceptual framework that visualises these alignments and highlights key opportunities and barriers for advancing circularity through digital transformation within the construction industry.</div><div>The findings highlight that BIM and IoT play pivotal roles in lifecycle planning, operational efficiency, and resource optimisation, while AI and digital twins support predictive maintenance, material recovery, and closed-loop optimisation. In contrast, robotics and blockchain remain underutilised in manufacturing and deconstruction, representing significant untapped potential to advance circularity. Persistent challenges, including fragmented stakeholder collaboration, siloed practices, and slow technological adoption, continue to impede the sector's ability to fully realise CE ambitions.</div><div>Future research should focus on fostering early stakeholder engagement and promoting cross-phase integration of Construction 4.0 technologies to enhance circular outcomes. Furth","PeriodicalId":48619,"journal":{"name":"Sustainable Production and Consumption","volume":"60 ","pages":"Pages 245-259"},"PeriodicalIF":9.6,"publicationDate":"2025-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145325693","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-11DOI: 10.1016/j.spc.2025.10.001
Lu Chen , Chenyang Shuai , Xi Chen , Bu Zhao
Effective monitoring of the Sustainable Development Goals (SDGs) is crucial for advancing global sustainable development. However, widespread data gaps continue to hinder the accurate assessment of SDG performance across countries and goals. To address this challenge, this study develops a data-driven integrated assessment framework combining dimensionality reduction and machine learning-based imputation techniques, based on 380 SDG indicators from the World Bank database covering the period 2000–2020. Principal indicators were selected using a combination of Principal Component Analysis (PCA) and multiple regression, and missing data were imputed using the random forest (RF)-based missForest algorithm. Based on the completed dataset, the SDG index and performance of 17 individual SDGs were assessed for 215 countries and regions worldwide from 2000 to 2020. The results show that: (1) identification of 218 principal indicators covering over 90 % of the information in the initial set; (2) robust imputation of missing values with a Normalized Root Mean Squared Error (NRMSE) of approximately 0.2 and a Proportion of Falsely Classified (PFC) around 0.08; (3) a steady global improvement in SDG performance with significant regional disparities—Europe leading, Africa lagging, and Asia progressing most rapidly; and (4) uneven development across different goals, with some facing considerable challenges. This study enhances the completeness and applicability of global SDG performance assessment and provides empirical evidence to support more targeted sustainable development policymaking.
{"title":"A data-driven framework for assessing global progress towards sustainable development goals","authors":"Lu Chen , Chenyang Shuai , Xi Chen , Bu Zhao","doi":"10.1016/j.spc.2025.10.001","DOIUrl":"10.1016/j.spc.2025.10.001","url":null,"abstract":"<div><div>Effective monitoring of the Sustainable Development Goals (SDGs) is crucial for advancing global sustainable development. However, widespread data gaps continue to hinder the accurate assessment of SDG performance across countries and goals. To address this challenge, this study develops a data-driven integrated assessment framework combining dimensionality reduction and machine learning-based imputation techniques, based on 380 SDG indicators from the World Bank database covering the period 2000–2020. Principal indicators were selected using a combination of Principal Component Analysis (PCA) and multiple regression, and missing data were imputed using the random forest (RF)-based missForest algorithm. Based on the completed dataset, the SDG index and performance of 17 individual SDGs were assessed for 215 countries and regions worldwide from 2000 to 2020. The results show that: (1) identification of 218 principal indicators covering over 90 % of the information in the initial set; (2) robust imputation of missing values with a Normalized Root Mean Squared Error (NRMSE) of approximately 0.2 and a Proportion of Falsely Classified (PFC) around 0.08; (3) a steady global improvement in SDG performance with significant regional disparities—Europe leading, Africa lagging, and Asia progressing most rapidly; and (4) uneven development across different goals, with some facing considerable challenges. This study enhances the completeness and applicability of global SDG performance assessment and provides empirical evidence to support more targeted sustainable development policymaking.</div></div>","PeriodicalId":48619,"journal":{"name":"Sustainable Production and Consumption","volume":"60 ","pages":"Pages 217-228"},"PeriodicalIF":9.6,"publicationDate":"2025-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145325692","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-09DOI: 10.1016/j.spc.2025.10.002
Qingjuan Chen , Chengzhen Xu , Qunwei Wang
Unequal exchanges of energy consumption and economic benefits among provinces hinder sustainable development, underscoring the need to evaluate trade-induced disparities. Using the latest multiregional input–output tables, we examine the transfers of energy consumption and value-added embodied in China's interregional trade. We then develop a mutual EEI index and an extended EEI index to quantify bilateral and aggregate energy–economic inequality (EEI). Finally, we employ energy-related Gini coefficients to evaluate overall inequality and identify its drivers. The results reveal that: (1) in 2017, 41.12 % of energy consumption and 32.29 % of value-added were transferred across provinces, with the north, northeast, and northwest being major net exporters of energy consumption, while the southwest and northwest were net importers of value-added; (2) the highest EEI mainly occurs between developed and less developed regions, where trade benefits concentrate in more developed regions but diminish over time, whereas disadvantaged provinces are often located in the northwest; and (3) overall EEI has widened, with heavy industry and construction as the primary contributors on the production and consumption sides, respectively, and significant influences from between-group effects and coal consumption. These findings provide insights for allocating energy-saving responsibilities and distributing economic benefits more equitably, ultimately supporting sustainable trade patterns.
{"title":"Revealing energy-economic inequality in China: A quantification and decomposition analysis","authors":"Qingjuan Chen , Chengzhen Xu , Qunwei Wang","doi":"10.1016/j.spc.2025.10.002","DOIUrl":"10.1016/j.spc.2025.10.002","url":null,"abstract":"<div><div>Unequal exchanges of energy consumption and economic benefits among provinces hinder sustainable development, underscoring the need to evaluate trade-induced disparities. Using the latest multiregional input–output tables, we examine the transfers of energy consumption and value-added embodied in China's interregional trade. We then develop a mutual EEI index and an extended EEI index to quantify bilateral and aggregate energy–economic inequality (EEI). Finally, we employ energy-related Gini coefficients to evaluate overall inequality and identify its drivers. The results reveal that: (1) in 2017, 41.12 % of energy consumption and 32.29 % of value-added were transferred across provinces, with the north, northeast, and northwest being major net exporters of energy consumption, while the southwest and northwest were net importers of value-added; (2) the highest EEI mainly occurs between developed and less developed regions, where trade benefits concentrate in more developed regions but diminish over time, whereas disadvantaged provinces are often located in the northwest; and (3) overall EEI has widened, with heavy industry and construction as the primary contributors on the production and consumption sides, respectively, and significant influences from between-group effects and coal consumption. These findings provide insights for allocating energy-saving responsibilities and distributing economic benefits more equitably, ultimately supporting sustainable trade patterns.</div></div>","PeriodicalId":48619,"journal":{"name":"Sustainable Production and Consumption","volume":"60 ","pages":"Pages 200-216"},"PeriodicalIF":9.6,"publicationDate":"2025-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145269706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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