The environmental impact of the operation of an Australian University, i.e. the Queensland University of Technology (QUT), in 2022 has been assessed by applying the recently published life cycle assessment guidelines for Higher Education Institutions. Overall, 16 environmental impact categories were considered based on ISO 14072. QUT's energy supply was identified as the most substantial impact overall, accounting for over 48 % in each of eight impact categories. Airconditioning (with the use of the refrigerant R134a) has the highest impact on the ozone depletion category. Transport exhibits the second most significant impact in eight of the 16 impact categories, mostly due to international air travel by international students and staff. Infrastructure has the most significant impact in six categories but is probably underestimated due to lack of data. In addition, suggestions how to reduce QUT's environmental impact are discussed. Subsequently, recommendations to develop the LCA guidelines for HEIs further are presented.
{"title":"Life cycle assessment of an Australian higher education institution – The case study of the Queensland university of technology","authors":"Kristina Schmidt , Meret Jürgens , Hans-Josef Endres , Sebastian Spierling , Leonie Barner","doi":"10.1016/j.cesys.2025.100312","DOIUrl":"10.1016/j.cesys.2025.100312","url":null,"abstract":"<div><div>The environmental impact of the operation of an Australian University, i.e. the Queensland University of Technology (QUT), in 2022 has been assessed by applying the recently published life cycle assessment guidelines for Higher Education Institutions. Overall, 16 environmental impact categories were considered based on ISO 14072. QUT's energy supply was identified as the most substantial impact overall, accounting for over 48 % in each of eight impact categories. Airconditioning (with the use of the refrigerant R134a) has the highest impact on the <em>ozone depletion</em> category. Transport exhibits the second most significant impact in eight of the 16 impact categories, mostly due to international air travel by international students and staff. Infrastructure has the most significant impact in six categories but is probably underestimated due to lack of data. In addition, suggestions how to reduce QUT's environmental impact are discussed. Subsequently, recommendations to develop the LCA guidelines for HEIs further are presented.</div></div>","PeriodicalId":34616,"journal":{"name":"Cleaner Environmental Systems","volume":"18 ","pages":"Article 100312"},"PeriodicalIF":4.9,"publicationDate":"2025-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144867448","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-29DOI: 10.1016/j.cesys.2025.100306
Qingli Tan, Yihua Gan
Objective
To quantitatively analyze the innovation capability of China's new energy industry from the perspective of new-quality productive forces, explore issues related to innovation efficiency, and provide references for enhancing industrial innovation capability and developing new-quality productive forces.
Methods
Based on the data of 23 new energy A-share listed enterprises in China from 2020 to 2023, this study constructs an innovation efficiency evaluation index system under the context of new productive forces. It applies the CCR-DEA and BCC-DEA models to analyze the static efficiency in 2023, and combines the Malmquist-DEA index to examine the dynamic efficiency from 2020 to 2023. Additionally, projection analysis is employed to identify issues of input redundancy and output deficiency, while the stochastic frontier approach is utilized to supplement the DEA analysis.
Results
The overall innovation efficiency of China's new energy enterprises was approximately effective but varied significantly. More than 60 % of enterprises needed to optimize resource allocation efficiency. About half of the enterprises faced decreasing returns to scale, with prominent issues of output shortages such as patent quantity and R&D expenditure. From 2020 to 2023, total factor productivity showed a trend of first increasing and then decreasing, with technological regression being the main cause of declining innovation efficiency.
Conclusion
It is necessary to construct a resource utilization system, policy guidance mechanism, collaborative ecosystem, and talent supply system adapted to new-quality productive forces, so as to optimize the allocation of innovation resources, break through technological bottlenecks, and promote the high-quality development of the new energy industry.
{"title":"Innovation ability of China's new energy industry from the perspective of new quality productivity","authors":"Qingli Tan, Yihua Gan","doi":"10.1016/j.cesys.2025.100306","DOIUrl":"10.1016/j.cesys.2025.100306","url":null,"abstract":"<div><h3>Objective</h3><div>To quantitatively analyze the innovation capability of China's new energy industry from the perspective of new-quality productive forces, explore issues related to innovation efficiency, and provide references for enhancing industrial innovation capability and developing new-quality productive forces.</div></div><div><h3>Methods</h3><div>Based on the data of 23 new energy A-share listed enterprises in China from 2020 to 2023, this study constructs an innovation efficiency evaluation index system under the context of new productive forces. It applies the CCR-DEA and BCC-DEA models to analyze the static efficiency in 2023, and combines the Malmquist-DEA index to examine the dynamic efficiency from 2020 to 2023. Additionally, projection analysis is employed to identify issues of input redundancy and output deficiency, while the stochastic frontier approach is utilized to supplement the DEA analysis.</div></div><div><h3>Results</h3><div>The overall innovation efficiency of China's new energy enterprises was approximately effective but varied significantly. More than 60 % of enterprises needed to optimize resource allocation efficiency. About half of the enterprises faced decreasing returns to scale, with prominent issues of output shortages such as patent quantity and R&D expenditure. From 2020 to 2023, total factor productivity showed a trend of first increasing and then decreasing, with technological regression being the main cause of declining innovation efficiency.</div></div><div><h3>Conclusion</h3><div>It is necessary to construct a resource utilization system, policy guidance mechanism, collaborative ecosystem, and talent supply system adapted to new-quality productive forces, so as to optimize the allocation of innovation resources, break through technological bottlenecks, and promote the high-quality development of the new energy industry.</div></div>","PeriodicalId":34616,"journal":{"name":"Cleaner Environmental Systems","volume":"18 ","pages":"Article 100306"},"PeriodicalIF":4.9,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144757619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-28DOI: 10.1016/j.cesys.2025.100307
Monica C.M. Parlato , Francesca Valenti , Lorenzo Guerrini , Anna Perbellini , Andrea Pezzuolo
Around 1 billion tons of agricultural by-products (ABP) are generated globally each year, posing environmental challenges, particularly in rural areas. Efficient management can transform ABP into valuable resources for energy, construction, and food packaging, aligning with circular economy principles.
This research addresses a critical gap in current spatial modelling approaches for agricultural by-product (ABP) valorization by developing an integrated GIS-based framework that combines high-resolution spatial analysis with uncertainty quantification for sustainable construction material planning. A GIS-based model was applied to estimate and map the ABP in the Veneto region (Italy). Key crops—wheat, barley, sugar beet, grape, maize, and soy—were analyzed in terms of yield, spatial distribution, and biomass availability at regional, provincial, and municipal scales. Heatmaps were produced to highlight ABP hotspots and support the strategic placement of collection centers for effective by-product valorization. To estimate the potential output of ABP-based construction materials, a literature review was conducted, followed by a sensitivity analysis. Results indicate that production estimates are mainly affected by spatial and temporal variability, particularly annual yield averages per municipality and year-to-year fluctuations. The total amount of ABP estimated was around 550,000 tons per year. The annual potential production resulted in 45 million Composite Panels, and over 195 million adobe bricks. If fully utilized, ABP could satisfy 5.5 % of Veneto's adobe brick demand, contribute 14.6 % to national EPS panel production, and cover over 1 % of the green concrete region's yearly needs. These data serve as preliminary information for the sustainable placement of transformation centers and provide insights into the environmental impact of logistics and the supply phase.
{"title":"From agricultural by-products to building materials: A spatial modelling approach to foster green construction sector","authors":"Monica C.M. Parlato , Francesca Valenti , Lorenzo Guerrini , Anna Perbellini , Andrea Pezzuolo","doi":"10.1016/j.cesys.2025.100307","DOIUrl":"10.1016/j.cesys.2025.100307","url":null,"abstract":"<div><div>Around 1 billion tons of agricultural by-products (ABP) are generated globally each year, posing environmental challenges, particularly in rural areas. Efficient management can transform ABP into valuable resources for energy, construction, and food packaging, aligning with circular economy principles.</div><div>This research addresses a critical gap in current spatial modelling approaches for agricultural by-product (ABP) valorization by developing an integrated GIS-based framework that combines high-resolution spatial analysis with uncertainty quantification for sustainable construction material planning. A GIS-based model was applied to estimate and map the ABP in the Veneto region (Italy). Key crops—wheat, barley, sugar beet, grape, maize, and soy—were analyzed in terms of yield, spatial distribution, and biomass availability at regional, provincial, and municipal scales. Heatmaps were produced to highlight ABP hotspots and support the strategic placement of collection centers for effective by-product valorization. To estimate the potential output of ABP-based construction materials, a literature review was conducted, followed by a sensitivity analysis. Results indicate that production estimates are mainly affected by spatial and temporal variability, particularly annual yield averages per municipality and year-to-year fluctuations. The total amount of ABP estimated was around 550,000 tons per year. The annual potential production resulted in 45 million Composite Panels, and over 195 million adobe bricks. If fully utilized, ABP could satisfy 5.5 % of Veneto's adobe brick demand, contribute 14.6 % to national EPS panel production, and cover over 1 % of the green concrete region's yearly needs. These data serve as preliminary information for the sustainable placement of transformation centers and provide insights into the environmental impact of logistics and the supply phase.</div></div>","PeriodicalId":34616,"journal":{"name":"Cleaner Environmental Systems","volume":"18 ","pages":"Article 100307"},"PeriodicalIF":4.9,"publicationDate":"2025-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144757620","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-25DOI: 10.1016/j.cesys.2025.100303
Luis Armando Becerra-Pérez , Luis E. Rincón , Benjamín García-Páez , John A. Posada-Duque
This research estimates the number of agricultural residues burned in open field, their pollutant emissions and the energy lost in the 2,476 municipalities that make up Mexico. The emissions of Particulate Matter 10 (PM10) and 2.5 (PM2.5), Black Carbon (BC), Carbon Dioxide (CO2) and Methane Gas (CH4) at the municipal level were estimated. The bioenergy loss was also estimated, in terms of anhydrous ethanol. In addition, the economic value lost was estimated, as well as the amount of gasoline that could have been oxygenated at 6 % volume and the percentage of participation in the national gasoline demand. The results, aggregated at the national level, show that Mexico annually incinerates 4.1 million tons of corn stover which emits 13,662 tons of PM10, 11,178 tons of PM2.5, 787 tons of BC, 7.2 million tons of CO2 and 8,653 tons of CH4 to the atmosphere. If this amount of biomass were used to produce anhydrous ethanol, a volume of 1,106 million liters, worth US$840 million, could be produced, which might also be used to oxygenate 18,425 million liters of gasoline, covering approximately 100 % of the national demand for this biofuel. The results provide empirical evidence on open burning of agricultural residues in Mexico and can be used to design public policies to reduce the country's share of global pollutant emissions.
{"title":"Impacts assessment of open field burning of agricultural residues in Mexico","authors":"Luis Armando Becerra-Pérez , Luis E. Rincón , Benjamín García-Páez , John A. Posada-Duque","doi":"10.1016/j.cesys.2025.100303","DOIUrl":"10.1016/j.cesys.2025.100303","url":null,"abstract":"<div><div>This research estimates the number of agricultural residues burned in open field, their pollutant emissions and the energy lost in the 2,476 municipalities that make up Mexico. The emissions of Particulate Matter 10 (PM10) and 2.5 (PM2.5), Black Carbon (BC), Carbon Dioxide (CO2) and Methane Gas (CH4) at the municipal level were estimated. The bioenergy loss was also estimated, in terms of anhydrous ethanol. In addition, the economic value lost was estimated, as well as the amount of gasoline that could have been oxygenated at 6 % volume and the percentage of participation in the national gasoline demand. The results, aggregated at the national level, show that Mexico annually incinerates 4.1 million tons of corn stover which emits 13,662 tons of PM10, 11,178 tons of PM2.5, 787 tons of BC, 7.2 million tons of CO2 and 8,653 tons of CH4 to the atmosphere. If this amount of biomass were used to produce anhydrous ethanol, a volume of 1,106 million liters, worth US$840 million, could be produced, which might also be used to oxygenate 18,425 million liters of gasoline, covering approximately 100 % of the national demand for this biofuel. The results provide empirical evidence on open burning of agricultural residues in Mexico and can be used to design public policies to reduce the country's share of global pollutant emissions.</div></div>","PeriodicalId":34616,"journal":{"name":"Cleaner Environmental Systems","volume":"18 ","pages":"Article 100303"},"PeriodicalIF":4.9,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144750613","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-25DOI: 10.1016/j.cesys.2025.100304
Farzin Hosseinifard , Mohammad Ebadollahi , Majid Amidpour
Global warming has become one of the most pressing global challenges in recent years. In response, a range of technologies has been developed to mitigate its effects. One such approach involves burning biogas, which primarily produces carbon dioxide. The goal is to capture this CO2 to support a sustainable system. One such technology is carbon capture, particularly post-combustion carbon capture (PCC) at the industrial scale. However, conventional PCC configurations are associated with high energy consumption and inefficiencies, such as the lack of integration between the hot and cold sections. In this study, Aspen HYSYS V11 was employed to simulate and analyze three distinct PCC configurations: Lean Vapor Compression (LVC), Solvent Split Flow (SSF), and Rich Solvent Recycle (RSR). These configurations were rigorously evaluated for their energy efficiency and CO2 capture performance. Additionally, a comparative assessment was conducted between conventional PCC technologies and a bioremediation-based alternative: microalgae cultivation systems, in which CO2 is absorbed through photosynthetic microalgae growth. This comparative analysis was designed to benchmark the viability of biological carbon sequestration against solvent-driven PCC processes, providing insights into their respective technical and environmental tradeoffs. Furthermore, a comparative analysis based on energy, exergy, and economic performance was presented. In the PCC sector, the results showed that the RSR configuration could increase efficiency by approximately 3 % compared to the conventional configuration, while reducing the overall cost by about 1.30 $/h, bringing the total cost to around 23.28 $/h. When compared with the microalgae plant, the findings were even more significant. The microalgae system demonstrated a high exergy efficiency of about 72.64 % and a substantially lower total cost of approximately 7.17 $/h. These results indicate that the microalgae approach offers considerable advantages over even the optimized PCC configurations.
{"title":"Sustainable pathways for CO2 mitigation: A comparative energy, exergy, and economic analysis of optimized post-combustion capture and microalgae-based sequestration","authors":"Farzin Hosseinifard , Mohammad Ebadollahi , Majid Amidpour","doi":"10.1016/j.cesys.2025.100304","DOIUrl":"10.1016/j.cesys.2025.100304","url":null,"abstract":"<div><div>Global warming has become one of the most pressing global challenges in recent years. In response, a range of technologies has been developed to mitigate its effects. One such approach involves burning biogas, which primarily produces carbon dioxide. The goal is to capture this CO<sub>2</sub> to support a sustainable system. One such technology is carbon capture, particularly post-combustion carbon capture (PCC) at the industrial scale. However, conventional PCC configurations are associated with high energy consumption and inefficiencies, such as the lack of integration between the hot and cold sections. In this study, Aspen HYSYS V11 was employed to simulate and analyze three distinct PCC configurations: Lean Vapor Compression (LVC), Solvent Split Flow (SSF), and Rich Solvent Recycle (RSR). These configurations were rigorously evaluated for their energy efficiency and CO<sub>2</sub> capture performance. Additionally, a comparative assessment was conducted between conventional PCC technologies and a bioremediation-based alternative: microalgae cultivation systems, in which CO<sub>2</sub> is absorbed through photosynthetic microalgae growth. This comparative analysis was designed to benchmark the viability of biological carbon sequestration against solvent-driven PCC processes, providing insights into their respective technical and environmental tradeoffs. Furthermore, a comparative analysis based on energy, exergy, and economic performance was presented. In the PCC sector, the results showed that the RSR configuration could increase efficiency by approximately 3 % compared to the conventional configuration, while reducing the overall cost by about 1.30 $/h, bringing the total cost to around 23.28 $/h. When compared with the microalgae plant, the findings were even more significant. The microalgae system demonstrated a high exergy efficiency of about 72.64 % and a substantially lower total cost of approximately 7.17 $/h. These results indicate that the microalgae approach offers considerable advantages over even the optimized PCC configurations.</div></div>","PeriodicalId":34616,"journal":{"name":"Cleaner Environmental Systems","volume":"18 ","pages":"Article 100304"},"PeriodicalIF":4.9,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144723533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-23DOI: 10.1016/j.cesys.2025.100305
T.D. Gates , M. Hannouf , D. Gebremedhin , T.D. Beyene , G. Assefa , I.D. Gates
Energy poverty (EP) and energy security (ES) are complex, multi-dimensional challenges with profound environmental, economic, and social implications that persist in both developed and developing nations. Addressing EP requires a holistic, life-cycle perspective to prevent unintended consequences, consider problem-shifting and sub-optimization, while managing trade-offs for sustainable ES. However, despite numerous proposed solutions, a comprehensive triple-bottom-line framework that integrates a life-cycle perspective remains absent in EP decision-making. Life cycle sustainability assessment (LCSA) offers a powerful methodology for addressing EP by encompassing all sustainability dimensions needed to eradicate it. This study conducts a comprehensive review of EP determinants and establishes a novel mapping between LCSA impact categories and EP drivers. Findings reveal that affordability, accessibility, and emissions are fundamental to EP/ES, with demographics and regional disparities influencing vulnerability. The mapping highlights primary determinants of EP/ES, including fair salary, poverty alleviation, public commitment to sustainability issues, climate change, and land use. To enhance the applicability of the LCSA framework to EP/ES, new categories related to energy and consumption are introduced, such as ‘education provided online’, ‘policy development and implementation’, and ‘subsidization’, which capture critical nuances of EP solutions. Additionally, identified gaps in LCSA methodology offer new insights for mitigating EP, strengthening ES, and refining LCSA itself for broader sustainability applications.
{"title":"Energy poverty from a life cycle sustainability assessment perspective","authors":"T.D. Gates , M. Hannouf , D. Gebremedhin , T.D. Beyene , G. Assefa , I.D. Gates","doi":"10.1016/j.cesys.2025.100305","DOIUrl":"10.1016/j.cesys.2025.100305","url":null,"abstract":"<div><div>Energy poverty (EP) and energy security (ES) are complex, multi-dimensional challenges with profound environmental, economic, and social implications that persist in both developed and developing nations. Addressing EP requires a holistic, life-cycle perspective to prevent unintended consequences, consider problem-shifting and sub-optimization, while managing trade-offs for sustainable ES. However, despite numerous proposed solutions, a comprehensive triple-bottom-line framework that integrates a life-cycle perspective remains absent in EP decision-making. Life cycle sustainability assessment (LCSA) offers a powerful methodology for addressing EP by encompassing all sustainability dimensions needed to eradicate it. This study conducts a comprehensive review of EP determinants and establishes a novel mapping between LCSA impact categories and EP drivers. Findings reveal that affordability, accessibility, and emissions are fundamental to EP/ES, with demographics and regional disparities influencing vulnerability. The mapping highlights primary determinants of EP/ES, including fair salary, poverty alleviation, public commitment to sustainability issues, climate change, and land use. To enhance the applicability of the LCSA framework to EP/ES, new categories related to energy and consumption are introduced, such as ‘education provided online’, ‘policy development and implementation’, and ‘subsidization’, which capture critical nuances of EP solutions. Additionally, identified gaps in LCSA methodology offer new insights for mitigating EP, strengthening ES, and refining LCSA itself for broader sustainability applications.</div></div>","PeriodicalId":34616,"journal":{"name":"Cleaner Environmental Systems","volume":"18 ","pages":"Article 100305"},"PeriodicalIF":4.9,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144750612","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study addresses a key research gap by developing a machine learning-driven open innovation framework for prioritizing Circular Economy as a Service (CEaaS) measures in the food service sector. Conventional sustainability strategies often fail to integrate dynamic customer preferences with scalable circular economy practices. To bridge this gap, this research employs Random Forest classification and feature selection to assess the impact of sixteen CEaaS measures on customer satisfaction across Indonesian and Hungarian food service markets. The framework is grounded in PRISMA-guided literature review, customer surveys, and machine learning-based decision analytics. Sustainable sourcing, reusable packaging systems, and circular loyalty programs emerge as the most critical CEaaS measures, reflecting global consumer priorities for ethical procurement, waste minimization, and behavior-based engagement. Notably, surplus food redistribution and food waste upcycling services rank consistently high, underscoring growing expectations for visible circularity and social value. The cross-country model validation confirms the framework's robustness and generalizability. By integrating circular economy principles, customer insights, and machine learning, the study advances open innovation theory and provides actionable guidance for sustainable transformation in the food service sector. The findings support Sustainable Development Goals related to responsible consumption, climate action, industry innovation, and global partnerships.
{"title":"Customer-centric circular economy as-a-service decision-making: Machine learning-driven open innovation in food service","authors":"Tutur Wicaksono , Marhadi Marhadi , Agustinus Fritz Wijaya , Velly Anatasia , Krisztina Taralik","doi":"10.1016/j.cesys.2025.100302","DOIUrl":"10.1016/j.cesys.2025.100302","url":null,"abstract":"<div><div>This study addresses a key research gap by developing a machine learning-driven open innovation framework for prioritizing Circular Economy as a Service (CEaaS) measures in the food service sector. Conventional sustainability strategies often fail to integrate dynamic customer preferences with scalable circular economy practices. To bridge this gap, this research employs Random Forest classification and feature selection to assess the impact of sixteen CEaaS measures on customer satisfaction across Indonesian and Hungarian food service markets. The framework is grounded in PRISMA-guided literature review, customer surveys, and machine learning-based decision analytics. Sustainable sourcing, reusable packaging systems, and circular loyalty programs emerge as the most critical CEaaS measures, reflecting global consumer priorities for ethical procurement, waste minimization, and behavior-based engagement. Notably, surplus food redistribution and food waste upcycling services rank consistently high, underscoring growing expectations for visible circularity and social value. The cross-country model validation confirms the framework's robustness and generalizability. By integrating circular economy principles, customer insights, and machine learning, the study advances open innovation theory and provides actionable guidance for sustainable transformation in the food service sector. The findings support Sustainable Development Goals related to responsible consumption, climate action, industry innovation, and global partnerships.</div></div>","PeriodicalId":34616,"journal":{"name":"Cleaner Environmental Systems","volume":"18 ","pages":"Article 100302"},"PeriodicalIF":4.9,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144757617","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-20DOI: 10.1016/j.cesys.2025.100301
Tian Xia , Xudong Chen
In the context of accelerating digital transformation and increasing environmental pressures, this study investigates how enterprise digitalization influences green dual innovation—comprising green exploratory innovation (EI) and green developmental innovation (DI)—within Chinese A-share listed firms from 2016 to 2023. Drawing upon fixed-effects and triple difference models, we empirically examine the mechanisms through which digital transformation (DCG) enhances green innovation and assess the mediating role of R&D investment and the moderating effect of government subsidies (GS). Results reveal that digital transformation significantly promotes both EI and DI, with a stronger effect on EI. R&D investment fully mediates this relationship, indicating that digital capabilities boost green innovation primarily through enhanced research capacity. Government subsidies exhibit a dual effect: they positively moderate the impact of digital transformation on EI, while dampening its influence on DI, possibly due to over-reliance on external funding. Heterogeneity analysis through triple difference methods uncovers substantial regional and industry-level variation—particularly among high-tech and heavily polluting firms in Eastern China—where digital transformation's green effects are constrained by strategic short-termism or technological limitations. These findings offer theoretical insights and practical implications for firms and policymakers aiming to align digital strategy with green transformation objectives under sustainability mandates.
{"title":"Unlocking sustainable production pathways: Digital transformation driving green dual innovation in Chinese enterprises","authors":"Tian Xia , Xudong Chen","doi":"10.1016/j.cesys.2025.100301","DOIUrl":"10.1016/j.cesys.2025.100301","url":null,"abstract":"<div><div>In the context of accelerating digital transformation and increasing environmental pressures, this study investigates how enterprise digitalization influences green dual innovation—comprising green exploratory innovation (EI) and green developmental innovation (DI)—within Chinese A-share listed firms from 2016 to 2023. Drawing upon fixed-effects and triple difference models, we empirically examine the mechanisms through which digital transformation (DCG) enhances green innovation and assess the mediating role of R&D investment and the moderating effect of government subsidies (GS). Results reveal that digital transformation significantly promotes both EI and DI, with a stronger effect on EI. R&D investment fully mediates this relationship, indicating that digital capabilities boost green innovation primarily through enhanced research capacity. Government subsidies exhibit a dual effect: they positively moderate the impact of digital transformation on EI, while dampening its influence on DI, possibly due to over-reliance on external funding. Heterogeneity analysis through triple difference methods uncovers substantial regional and industry-level variation—particularly among high-tech and heavily polluting firms in Eastern China—where digital transformation's green effects are constrained by strategic short-termism or technological limitations. These findings offer theoretical insights and practical implications for firms and policymakers aiming to align digital strategy with green transformation objectives under sustainability mandates.</div></div>","PeriodicalId":34616,"journal":{"name":"Cleaner Environmental Systems","volume":"19 ","pages":"Article 100301"},"PeriodicalIF":4.9,"publicationDate":"2025-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145107621","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-13DOI: 10.1016/j.cesys.2025.100297
Yu Lei , Jorn de Vos, Huub Rijnaarts, Wei-Shan Chen
The occurrence of micropollutants in the aquatic environment shows potential adverse effects towards ecosystems, such as estrogenic effects on the sexual development of fish and the resistance of microorganisms to antibiotics. Constructed wetlands (CWs) can be used as a post-treatment technology to remove micropollutants from the effluent of conventional wastewater treatment plants. Life Cycle Assessment was performed to assess the environmental and economic impacts of two constructed wetlands (i.e. sand-based CW and bark and biochar-based CW), and compared these impacts with other selected wastewater treatment technologies (i.e. ozone and activated carbon-based technologies). Regarding the removal efficiency of MPs, the bark and biochar-based CW showed a higher removal range than other technologies, though a fluctuation of removals exists due to the effect of seasonality. The CW scenarios require larger land to obtain the desired MP removal efficiencies than other technologies. Despite this, using bark and biochar as support matrices can reduce the land use of the CW system (0.51 m2/m3) compared with sand (0.58 m2/m3). The Global Warming Potential and overall treatment costs of the CW scenarios (i.e. the bark and biochar-based CW with 148 g CO2 equivalent/m3 and 0.14 €/m3; the sand-based CW with 108 g CO2 equivalent/m3 and 0.12 €/m3) rank in the middle among the studied technologies. The findings of this research provide valuable support for the decision-making process in selecting a nature-based technology working as a post-treatment of WWTPs for MP removal.
微污染物在水生环境中的出现显示了对生态系统的潜在不利影响，例如对鱼类性发育的雌激素影响和微生物对抗生素的抗性。人工湿地（CWs）可作为一种后处理技术，用于去除常规污水处理厂出水中的微污染物。采用生命周期评估方法，对两种人工湿地（砂基连续湿地、树皮和生物炭基连续湿地）的环境和经济影响进行了评估，并将这些影响与其他选定的废水处理技术（臭氧和活性炭基技术）进行了比较。在MPs的去除率方面，树皮和生物炭基CW的去除率高于其他技术，但由于季节的影响，去除率存在波动。与其他技术相比，连续油管方案需要更大的土地来获得所需的MP去除效率。尽管如此，与沙子（0.58 m2/m3）相比，使用树皮和生物炭作为支撑基质可以减少CW系统的土地利用（0.51 m2/m3）。连续水处理方案的全球变暖潜势和总体处理成本(即树皮基和生物炭基连续水处理分别为148 g CO2当量/m3和0.14欧元/m3；砂基连续油管技术（CO2当量为108 g /m3， CO2当量为0.12€/m3）在研究的技术中排名居中。本研究的发现为选择基于自然的技术作为污水处理厂去除MP的后处理的决策过程提供了有价值的支持。
{"title":"Quantifying global warming potential, land use and financial cost of constructed wetland as a post-treatment technology for removing micropollutants from municipal wastewater","authors":"Yu Lei , Jorn de Vos, Huub Rijnaarts, Wei-Shan Chen","doi":"10.1016/j.cesys.2025.100297","DOIUrl":"10.1016/j.cesys.2025.100297","url":null,"abstract":"<div><div>The occurrence of micropollutants in the aquatic environment shows potential adverse effects towards ecosystems, such as estrogenic effects on the sexual development of fish and the resistance of microorganisms to antibiotics. Constructed wetlands (CWs) can be used as a post-treatment technology to remove micropollutants from the effluent of conventional wastewater treatment plants. Life Cycle Assessment was performed to assess the environmental and economic impacts of two constructed wetlands (i.e. sand-based CW and bark and biochar-based CW), and compared these impacts with other selected wastewater treatment technologies (i.e. ozone and activated carbon-based technologies). Regarding the removal efficiency of MPs, the bark and biochar-based CW showed a higher removal range than other technologies, though a fluctuation of removals exists due to the effect of seasonality. The CW scenarios require larger land to obtain the desired MP removal efficiencies than other technologies. Despite this, using bark and biochar as support matrices can reduce the land use of the CW system (0.51 m<sup>2</sup>/m<sup>3</sup>) compared with sand (0.58 m<sup>2</sup>/m<sup>3</sup>). The Global Warming Potential and overall treatment costs of the CW scenarios (i.e. the bark and biochar-based CW with 148 g CO<sub>2</sub> equivalent/m<sup>3</sup> and 0.14 €/m<sup>3</sup>; the sand-based CW with 108 g CO<sub>2</sub> equivalent/m<sup>3</sup> and 0.12 €/m<sup>3</sup>) rank in the middle among the studied technologies. The findings of this research provide valuable support for the decision-making process in selecting a nature-based technology working as a post-treatment of WWTPs for MP removal.</div></div>","PeriodicalId":34616,"journal":{"name":"Cleaner Environmental Systems","volume":"18 ","pages":"Article 100297"},"PeriodicalIF":6.1,"publicationDate":"2025-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144671015","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-12DOI: 10.1016/j.cesys.2025.100300
Alexandros Maziotis , Ramón Sala-Garrido , Manuel Mocholi-Arce , Maria Molinos-Senante
Within the water-energy-carbon nexus, understanding the trade-offs among resource use, drinking water delivery, and greenhouse gas emissions is essential for ensuring the sustainable provision of drinking water. Addressing this challenge, this study estimates four performance indices—technical efficiency, ecological efficiency, process environmental quality efficiency, and overall efficiency —using a unified framework based on Data Envelopment Analysis. The analysis was conducted under two scenarios, reflecting water companies’ prioritization of production and environmental dimensions. The empirical application, performed on a sample of English and Welsh water companies, revealed that water companies focused on technical efficiency, achieving average scores of 0.648 and 0.798 under environmental and production prioritization scenarios, respectively. In contrast, process environmental quality and ecological efficiency metrics were considerably lower, with average values of 0.179 and 0.129 for the environmental scenario and 0.153 and 0.131 for the production scenario. The temporal evolution of these performance indices highlights a trade-off between technical efficiency and performance indices integrating carbon emissions under the environmental prioritization scenario.
{"title":"Trade-offs in technical and environmental performance of water utilities: Insights focused on water-energy-carbon nexus","authors":"Alexandros Maziotis , Ramón Sala-Garrido , Manuel Mocholi-Arce , Maria Molinos-Senante","doi":"10.1016/j.cesys.2025.100300","DOIUrl":"10.1016/j.cesys.2025.100300","url":null,"abstract":"<div><div>Within the water-energy-carbon nexus, understanding the trade-offs among resource use, drinking water delivery, and greenhouse gas emissions is essential for ensuring the sustainable provision of drinking water. Addressing this challenge, this study estimates four performance indices—technical efficiency, ecological efficiency, process environmental quality efficiency, and overall efficiency —using a unified framework based on Data Envelopment Analysis. The analysis was conducted under two scenarios, reflecting water companies’ prioritization of production and environmental dimensions. The empirical application, performed on a sample of English and Welsh water companies, revealed that water companies focused on technical efficiency, achieving average scores of 0.648 and 0.798 under environmental and production prioritization scenarios, respectively. In contrast, process environmental quality and ecological efficiency metrics were considerably lower, with average values of 0.179 and 0.129 for the environmental scenario and 0.153 and 0.131 for the production scenario. The temporal evolution of these performance indices highlights a trade-off between technical efficiency and performance indices integrating carbon emissions under the environmental prioritization scenario.</div></div>","PeriodicalId":34616,"journal":{"name":"Cleaner Environmental Systems","volume":"18 ","pages":"Article 100300"},"PeriodicalIF":6.1,"publicationDate":"2025-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144623357","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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