Eco-efficiency Improvements Research Articles

Enhancing eco-efficiency in hemp-based construction boards: environmental and economic strategies for sustainability

ABSTRACT Hemp-based construction materials have increasingly captured attention in recent years as viable alternatives to carbon-intensive materials. A benefit of using hemp (Cannabis sativa L) in construction is its ability to sequester carbon dioxide during plant growth, thereby providing the potential to create carbon-negative materials. However, hemp production can contribute to other environmental impacts such as acidification and eutrophication. Additionally, hemp-based materials usually involve higher costs compared to traditional materials. This study presented an application of an eco-efficiency framework to explore options for improving the environmental and economic performance of non-load-bearing hemp-based construction boards at the production stage in Australia. The study integrated environmental life cycle assessment, multi-criteria analysis, environmental mitigation strategies, life cycle costing and eco-efficiency portfolio analysis in order to identify eco-efficiency improvement opportunities for non-structural hemp-based construction boards and to compare them with conventional alternatives. The analysis showed that the use of solar electricity during the post-farm stage of hemp-based board production can reduce their environmental impact by 26 per cent and production costs by 0.4 per cent. The proposed framework can assist hemp growers and hemp-based composite manufacturers in Australia in developing cost-effective environmental mitigation strategies to assist sustainability in the construction sector.

Mechanisms and Impact Effects of Digital Agriculture Development on Agricultural Eco-Efficiency in China

The green development of agriculture is an essential way to achieve high-quality agricultural development, and the development of digitalization has given new momentum to the green development of agriculture. In this study, based on the panel data of 30 provinces in China from 2011 to 2022, we measure the agricultural eco-efficiency and the level of digital agriculture development in China using the Super-SBM model with global reference and the entropy value method, respectively. The impact of the level of digital agriculture development on agricultural eco-efficiency is explored with the help of a regression model, and the mediating role of pesticide and fertilizer inputs in this impact pathway is explored using a mediating effects model. The study found that: (1) the level of digital agriculture development positively and significantly affects agricultural eco-efficiency to a relatively large extent; (2) the effect of digital agriculture development on the improvement of agriculture eco-efficiency is significantly heterogeneous in different regions; (3) pesticide and fertilizer inputs have a mediating role in this impact pathway. Therefore, the application and promotion of digital agriculture technology should be strengthened to build a green agricultural production and management system, so as to promote high-quality and sustainable development of Chinese agriculture.

How to improve fishery eco-efficiency by building marine ranch in China

Based on the panel data of the province and municipality in 2010–2021, this paper measures the fishery eco-efficiency by using the SBM-DEA model and empirically analyses how China’s marine ranch construction improves the fishery eco-efficiency by using the double-difference fixed-effect model. The results show that, firstly, China’s marine ranch construction can improve the fishery eco-efficiency. Secondly, China’s marine ranch construction promotes fisheries eco-efficiency by improving the input efficiency of labor, fish species, fishing vessel, fishery technology extension, aquaculture area and by reducing pollutant outputs. Thirdly, the fishery eco-efficiency of the marine ranch construction region has increased annually since 2015, and technological changes, scale efficiency changes and technical efficiency changes can all contribute to the fishery eco-efficiency improvement, and increase in order. Based on the results of the empirical analyses, this paper proposes policy recommendations to improve the fishery eco-efficiency in the conjunction with the construction of marine ranch in China.

Green innovation and eco-efficiency: Interaction between society and environment of sustainable development demonstration belt in China

China has achieved remarkable results in sustainable development, particularly in integrating green innovation to enhance eco-efficiency. But why choose green innovation as the driver for urban eco-efficiency? How did it do? Based on ecological civilization demonstration zone in China (Yangtze River Economic Belt) city data from 2006 to 2019. This research developed comprehensive evaluation systems to measure both urban green innovation and ecoefficiency, making use of the SBM model with undesired output to gauge ecological efficiency of urban areas. On this basis, we extended analysis by applying a baseline regression model and a Spatial Durbin model to delve into the mechanisms of green innovation affects eco-efficiency. The results are as follows. (1) green innovation and urban eco-efficiency showed fluctuating upward trends but that regional heterogeneity existed among the three regions. Specifically, the lower reaches outperform in green innovation, closely followed by the middle and upper reaches. Concurrently, the eco-efficiency levels of the middle reaches surpass those of the lower and upper reaches. (2) Our findings confirmed that green innovation promotes eco-efficiency by pursuing economic growth while reducing externalities. Furthermore, green innovation and eco-efficiency exhibit a positive spatial correlation and benefits neighboring city’s’ eco-efficiency, revealing spatial spillover effect. (3) Technological progress and industrial restructuring, driven by green innovation practices, emerge as pivotal drivers for the improvement in eco-efficiency. The study's insights provide valuable guidance to policymakers and stakeholders seeking to leverage green innovation practices to promote long-term and healthy urban development.

Spatial-temporal differentiation of urban eco-efficiency and its driving factors: A comparison of five major urban agglomerations in China.

This paper utilizes an improved undesirable output DEA model to measure the eco-efficiency of cities in five major urban agglomerations in China during 2006-2020. It employs the Theil Index and Geodetector to investigate the spatial-temporal distribution differentiation characteristics and driving factors of urban eco-efficiency. The main findings are as follows. Firstly, the eco-efficiency of all urban agglomerations showed a fluctuating upward trend, but the eco-efficiency performance of different urban agglomerations in China shows a stratification characteristic. Specifically, the Pearl River Delta urban agglomeration consistently ranks first in China, while the mean values of the Yangtze River Delta urban agglomeration, Beijing-Tianjin-Hebei urban agglomeration, and Chengdu-Chongqing urban agglomeration are lower than the national average. Secondly, the overall differences in the urban eco-efficiency of all sample cities show a consistently fluctuating downward trend. The factor that affects the level differences of eco-efficiency in different cities is the intra-regional differences. Last but not least, the top three factors affecting the spatial distribution difference of urban eco-efficiency in the whole sample are environmental pollution control investments, innovation level, and environmental infrastructure investments. In the end, this paper proposes that reducing the intra-regional differences is the primary task to achieve the coordinated improvement of urban eco-efficiency in urban agglomerations, and then puts forward some policy suggestions to improve eco-efficiency for the five major urban agglomerations.

Eco-efficiency and economic assessment of gypsum-based precast with polymeric waste: A case study

The adoption of sustainable building policies and the society’s increasing emphasis on sustainability underscore the urgent need to evaluate the environmental and economic impact of construction materials. This study examines the effects of incorporating polyurethane foam waste into gypsum-based ceiling tiles. It compares its economic performance and eco-efficiency with conventional alternatives. Methodologically, Life Cycle Cost Analysis (LCCA) quantifies total life cycle costs, followed by Eco-Efficiency Assessment (EE), considering results from both Life Cycle Assessment (LCA) and LCCA. Our findings reveal a compelling 5.91% cost advantage for the novel precast, driven by enhanced production capacity resulting from shorter drying times. The economic benefits of this approach are underscored by a detailed breakdown of cost savings in production phases. Furthermore, the EE remarks a substantial 7.5% boost, emphasizing the positive environmental impact achieved through reduced resource consumption and lower emissions combined with lower life-cycle costs. These results highlight the economic viability and eco-efficiency of polymeric waste-integrated gypsum ceiling tiles for environmental sustainability. The specific percentage improvements in cost and eco-efficiency provide a quantitative basis for understanding the advantages of adopting these innovative materials.

Precision co-composting of multi-source organic solid wastes provide a sustainable waste management strategy with high eco-efficiency: a life cycle assessment.

With the increase of organic solid wastes (OSWs), current waste management practices, such as landfill, incineration, and windrow composting, have shown weaknesses in both resource recycling and environmental protection. Co-composting has been used to achieve nutrient and carbon recycling but is accused of high ammonia emission and low degradation efficiency. Therefore, this study developed a precision co-composting strategy (S3, which adds functional bacteria generated from food processing waste to a co-composting system) and compared it with the current OSW treatment strategy (S1) and traditional co-composting strategy (S2) from a life cycle assessment (LCA) perspective. The results showed that compared with S1, the eco-efficiency increased by 31.3% due to the higher economic profit of S2 but did not directly reduce the environmental cost. The addition of bacterial agents reduced ammonia emissions and shortened composting time, so compared with S1 and S2, the environmental cost of S3 was reduced by 37.9 and 43.6%, while the economic profit increased by 79.8 and 24.4%, respectively. The changes in environmental costs and economic benefits resulted in a huge improvement of S3's eco-efficiency, which was 189.6 and 121.7% higher than S1 and S2. Meanwhile, the adoption of S3 at a national scale in China could reduce the emission of 1,4-dichlorobenzene by 99.9% compared with S1 and increase profits by 6.58 billion USD per year. This study proposes a novel approach that exhibits high eco-efficiency in the treatment of OSWs.

Life Cycle Engineering as a Pathway to Achieving Net-zero Targets

Life cycle engineering (LCE) was introduced in the early 1990s with a focus on eco-efficiency, hence designing products to reduce the environmental impact over their life cycle while maintaining or increasing the value created. In the meantime, the world has seen the emergence of a climate crisis and a biodiversity crisis despite significant eco-efficiency improvements of individual products and services over the years, highlighting the gap between bottom-up LCE activities and top-down sustainability concepts such as planetary boundaries and net-zero targets for climate change.This paper presents a structured LCE approach for practitioners, supporting life cycle engineering of product life cycles with an absolute sustainability perspective towards achieving net-zero targets. An industrial case is provided to demonstrate the applicability of the methodology.

Government intervention, industrial structure, and energy eco-efficiency: an empirical research on new energy demonstration in cities

This study investigates the relationships among government intervention, industrial structure, and energy eco-efficiency (EE). Energy eco-efficiency was measured based on a non-radial directional distance function for 236 cities in China from 2005 to 2019. Additionally, the difference-in-difference model (DID) method and spatial econometric models were used to analyse the impact of government intervention and industrial structure on energy eco-efficiency and their spatial spill-over effects. Government intervention includes fiscal expenditures and policy orientation for new energy demonstration construction. Our results indicate that: China’s EE has a fluctuating upward trend and increased 17.85% in the period, and its spatial distribution imbalance gradually developed into a regional distribution balance. Moreover, government intervention and adjustment of the industrial structure improved urban energy eco-efficiency by 7.43% and 0.92%, respectively, which also has spatial spill-over effects in neighbouring regions. Furthermore, economic development, technological innovation, and foreign direct investment enable EE. However, urbanisation hinders the improvement of energy eco-efficiency. Finally, heterogeneity analysis showed that the policy of the new energy demonstration city has better effects on eastern and western cities in promoting EE.

Spatial–Temporal Characteristics and Influencing Factors of Marine Fishery Eco-Efficiency in China: Evidence from Coastal Regions

Marine fishery is an important part of China’s maritime power strategy. Improving the ecological efficiency of marine fishery is the inevitable way to achieve the sustainable development of fishery. Based on the perspective of industrial sustainable development, this study used the Super-SBM model to evaluate the ecological efficiency of marine fishery in 11 coastal provinces of China from 2011 to 2020. Combined with Malmquist index, Moran index and other methods, the spatial and temporal evolution characteristics were analyzed. On this basis, the Tobit panel model was used to explore the influencing factors of marine fishery eco-efficiency. The results show that: (1) From 2011 to 2020, the marine fishery eco-efficiency in the 10 coastal provinces and cities of China shows a clear trend of improvement, and the efficiency values in high-efficiency areas remain basically stable. The relative gap between efficient and inefficient regions remains significant. (2) From the perspective of spatial distribution characteristics, the ecological efficiency of marine fishery in coastal provinces and cities in China had no obvious spatial correlation, and showed a trend of cross-distribution between high-efficiency regions and low-efficiency regions. (3) The change of marine fishery eco-efficiency is the result of a variety of influencing factors. Fishery industrial structure, scientific and technological support levels and environmental regulation play a role in promoting the improvement of marine fishery eco-efficiency. Therefore, optimizing the structure of the fishery industry, improving environmental regulation and increasing investment in science and technology are all effective measures for local governments to improve the eco-efficiency of marine fisheries.

Exploring the Role of Foreign Direct Investment and Environmental Regulation in Regional Ecological Efficiency in the Context of Sustainable Development

Eco-efficiency (EE) is an important indicator of regional sustainable development, which reflects the efficiency of regional economic development in using resources effectively to reduce environmental pressures, and foreign direct investment and environmental regulation are very important in promoting regional economic growth and enhancing eco-efficiency. In this paper, we chose China’s panel data from 2009 to 2021, measured China’s regional eco-efficiency using the super-efficient SBM model, and explored environmental regulation and the impact of FDI on EE in different regions using the Tobit model, with conclusions as follows: (1) The average value of national EE in China during 2009–2021 was about 0.631, which was at a low level, and there were significant differences between regions, with the highest EE in the eastern region, and the central and western regions being lower than the national average. (2) FDI at the national level had a significant promoting effect on regional EE, with an elasticity coefficient of 0.0213, which verifies that the “pollution paradise” effect does not exist at national level. FDI promoted EE in the eastern region, while not being significant in the other two regions. The impact of the environmental regulation act on EE at the national level did not pass the significance test, but the impact passed the significance test with positive coefficients for both the eastern and central regions, while in the western region it was not significant. (3) Financial investment in science and technology promoted EE in the national, east, and central regions significantly, while not being significant in the western region. The economic development level of all regions was positively correlated with EE; the impact of urbanization on EE was significantly positive in national, central, and western regions, but was not significant in the eastern region. The industrial structure of all regions was not conducive to the improvement of EE, with the western region having the most negative impact on EE. The study in this paper represents an important addition and refinement to research in related fields.

How to incentivize bank credit development in blue carbon projects? A study of refinancing mechanisms with evolutionary game

The improvement of eco-efficiency is strongly supported through blue carbon projects. However, the absence of incentive mechanisms makes risk aversion more alluring to commercial banks than profits, making project funding challenging. In this study, a “refinance for blue” mechanism is developed, and the evolutionary game model integrating the prospect theory (PT) is constructed. We are devoted to elucidating the impact of the perceived utility on player behaviors and confirming the efficacy of this incentive mechanism. Results indicate that: (1) Without any incentive mechanism, blue carbon projects are difficult to develop. (2) By modifying the perceived utility of both maritime enterprises and commercial banks, the “refinance for blue” mechanism helps marine enterprises to escape the financing limitation. (3) Commercial banks are more motivated by refinancing interest rates than by green credit interest rates. Finally, this research provides insightful information for commercial banks with the different perceived utility to assess the financial benefit of financing blue carbon projects and choose the most appropriate option in an unpredictable context.

Digital finance promotes sustainable total factor eco-efficiency: evidence from China

ABSTRACT A super-efficient SBM model was constructed using Chinese provincial panel data from 2011 to 2018 to explore the impact of digital finance on sustainable total factor eco-efficiency (STFEcE) and its mechanisms of action. The results show that digital finance can promote the improvement of STFEcE, and this promotion is heterogeneous. Western regions with more backward financial development, ecologically inefficient regions, and financially weakly regulated regions have more significant eco-efficiency improvements from digital financial services. Digital finance influences STFEcE by expanding the scale of green credit and enhancing the level of green and digital technology innovation. Therefore, the government should support the efficient integration of digital technology and financial services in macro policies, accelerate the infrastructure construction of digital finance, eliminate the digital divide, and create a favourable financial environment for improving STFEcE.

Analysis on Evaluation and Spatial-Temporal Evolution of Port Cluster Eco-Efficiency: Case Study from the Yangtze River Delta in China

The improvement of port cluster eco-efficiency is of great significance to constructing a world-class shipping hub and the high-quality development of regional economy. This study adopts the Super-EBM (Super-efficiency Epsilon-Based Measure) model to evaluate the eco-efficiency of the Yangtze River Delta port cluster in China, and the GML (Global Malmquist-Luenberger) index, spatial hot spot analysis, gravity center migration model, and the Theil index are combined to reveal the spatial-temporal evolution. The results show that the average eco-efficiency of the Yangtze River Delta port cluster is 0.686, with 55.6% of the ports being below the average, which is directly related to the low scale efficiency. Mainly driven by technical efficiency improvement, the overall eco-efficiency has a growth rate of 8.7% from 2010 to 2019. Moreover, considerable spatial divergence has formed in the port cluster, and the eco-efficiency gravity center has always been in the south of Jiangsu. The overall eco-efficiency gap has widened by 19.92%, and the gap within the region, particularly within Zhejiang, is the major source. To improve the overall eco-efficiency of the port cluster, policymakers should strengthen the technological spillover of ecologically efficient ports in clean production and mechanism reform, while optimizing the resource consolidation system of ports with relatively low eco-efficiency.

Profit, productivity, and eco-efficiency of using Caucasian clover/ grass pastures in hill country farms

The following study was conducted to establish whether significant amounts of Caucasian clover-based pastures in hill country farms can increase eco-efficiency and profitability. Published data were used to predict the production of Caucasian clover-based pastures, based on weather data and soil moisture deficit prediction, for four sheep and beef farms with low rainfall in the South Island. Scenarios with 10, 20 or 30% of the flat and rolling areas improved with Caucasian clover/grass pastures were compared to current systems based on resident white clover-based pastures. A staged approach, to utilise the extra high-quality feed produced, used a sequentially process to improve productivity by increasing lamb finishing, higher hogget liveweight, better ewe nutrition or more beef finishing, depending on initial efficiency metrics. Timeto maximum production using an annual establishment programme of 5% of the target areas in Caucasian clover/grass mixtures took 4 to 6.5 years (10% and 30% respectively). Adding Caucasian clover/grass increased pasture production by 5.5% while product/kg DM consumed increased by 12.8% and profitability by 22% when either sheep or beef production were used to capture the extra amount and quality of pasture. Greenhouse gas (GHG) emissions were increased by only 6.3%, resulting in more efficient meat production.

Assessing the network characteristics and structural effects of eco-efficiency: A case study in the urban agglomerations in the middle reaches of Yangtze River, China

Crude economic development models create severe environmental pressures. Eco-efficiency (EE) is an important basis for evaluating ecological civilization in China. Under the national strategy of ecological priority and green development in China's Yangtze River Economic Belt, the urban agglomerations in the middle reaches of Yangtze River (UAMRYR) was considered as a case study and an evaluation index system of county EE was constructed based on multi-source remote sensing data, the EE values from 2009 to 2018 were measured by a super slack-based measure (Super-SBM) model, the spatial correlations of EE were revealed by an improved gravity model, the spatial network characteristics of EE were portrayed by social network analysis, and the nature of network effects were further explored by multiple linear regression models. Findings of the study included EE has been shown to be indeed spatially correlated.The EE of the nodes, the differences increased, the transmission pattern was relatively stable, and the association was characterized by bidirectional inequity. The spatial network of EE was characterized by small groups, whose tightness was small and increasingly loose overall, and the overall network operation efficiency is low. In terms of the spatial structure of individual network, the Degree Centrality (DC) showed the circle structure, the Closeness Centrality (CC) demonstrated ‘central collapse’, and the Betweenness Centrality (BC) evolved into five ‘core-periphery’ sub-groups from the ‘circle distribution’. Regarding the structural effects, in terms of EE improvement, the UAMRYR nodes were mainly through the agglomeration effect as well as dissemination channels and spillover paths, the core nodes were self-sufficient, and the edge nodes mainly relied on, the radiation role of core nodes, the transmission role of intermediary nodes, and their own active integration and connection roles. This study provides a new perspective for understanding EE and these findings are important for promoting the synergistic improvement of green development in China and other countries.

New Digital Infrastructure's Impact on Agricultural Eco-Efficiency Improvement: Influence Mechanism and Empirical Test-Evidence from China.

This paper attempts to explore the overall impact of its rural digitization process on agricultural carbon emissions and non-point source pollution in the context of China. By doing so, we analyze whether digitization has an impact on agricultural pollution reduction, analyze its conductive mechanism, and draw its policy implications. To this end, the paper innovatively incorporates new digital infrastructure and urbanization level into of the concept of agricultural eco-efficiency (AEE) and adopts the SBM-DEA model, entropy weighting method, and mixed regression to analyze, based on the sample data of the 30 provinces of China from 2011 to 2020. The results indicate that: (1) new digital infrastructure has a significant contribution to the improvement of AEE of China; (2) both information infrastructure and integration infrastructure have a significant positive effect on AEE, and the effect of information infrastructure is more effective, but there is an inverted "U"-shaped relationship between innovation infrastructure and AEE level; (3) the moderating effect mechanism suggests that the level of urbanization reinforces the contribution of new digital infrastructure to AEE; and (4) the heterogeneity test shows that the effect of new digital infrastructure on AEE is more significant in regions with well-developed traditional transportation facilities and in periods when the government pays more attention to agricultural ecological issues. The above results also provide rich insights for China and other similar developing countries on how to balance the agriculture digitization and AEE.

Examining energy eco-efficiency in China's logistics industry

Carbon dioxide (CO2) emission significantly affects sustainability efforts, calling for improvements in energy eco-efficiency (EEE). In this study, we use three methods—input–output indicators, projection pursuit regressions, and neural networks—to investigate the CO2 emission characteristics of the logistics industry in China and its provinces from 2010 to 2019. We find influential factors of carbon emissions and their corresponding efficiencies in various provinces of China. Our results reveal excess inputs and deficient outputs and the relationship between economic development levels and the environmental quality. Based on the results, we provide technical measures and managerial implications for effectively reducing CO2 emissions and improving EEE.

The impact and transmission mechanisms of financial agglomeration on eco-efficiency: Evidence from the organization for economic co-operation and development economies

Whether financial agglomeration is conducive to eco-efficiency is of great importance for countries to better pursue cleaner production, low carbon emission reduction, and sustainable development paths. This paper focuses on 38 Organization for Economic Co-operation and Development (OECD) members. Based on the scientific accounting of green eco-efficiency by the super-efficiency slack-based measure (SBM) model, the relationship between financial agglomeration and eco-efficiency is thoroughly investigated by combining the spatial Durbin model (SDM), the mediating effects model, and the panel threshold regression (PTR) model, bridging the knowledge gap. Empirical results reveal that (1) Financial agglomeration has strong positive externalities for eco-efficiency in the home country and its neighbors, with the trickle-down effect playing a key role. (2) Financial agglomeration can indirectly promote cleaner production and eco-efficiency by strengthening technological innovation and upgrading industrial structure, with the latter being more strongly mediated. (3) The effect of financial agglomeration in enhancing eco-efficiency has clear stage differences. The low-level financial agglomeration will impede the improvement of green eco-efficiency while the high-level will support it, which is in line with the Environmental Kuznets Curve theory and the law of economic development. The research broadens the theoretical underpinnings of financial agglomeration and eco-efficiency and provides guidance and implications for OECD members and other emerging economies on how to optimize the spatial allocation of financial resources, promote eco-efficiency, and advance green sustainable development.

Analysis of the Spatial Differentiation and Promotion Potential for Agricultural Eco-Efficiency-Evidence of Pollution's Strong Disposability.

Agricultural eco-efficiency is an important indicator used to measure agriculture's high-quality and sustainable development. Therefore, this paper uses the EBM-Super-ML method with strong disposability of undesired output to calculate Chinese agricultural eco-efficiency and uses a geographical detector to measure the driving force of the factor. The research conclusions are mainly reflected in three aspects. Firstly, from the perspective of eco-efficiency changes, the overall mean value of agricultural eco-efficiency increased by 3.5%, and the regional heterogeneity is significant, with the fastest growth in the eastern region. Secondly, the results of driving force analysis show that the main driving factors of agricultural eco-efficiency divergence are capital inputs, total carbon emissions, labor inputs, agricultural film residues, fertilizer use, and pesticide residues, with driving forces of 0.43, 0.37, 0.34, 0.31, 0.28, and 0.20, respectively. Finally, from the perspective of eco-efficiency improvement potential, the mean value of output improvement potential is 5%, and the input factor is 7%. Among the non-desired outputs, the reduction rate of agricultural films can reach 40%. Among the input factors, labor input has the highest potential for intensive use, while agricultural machinery has a negative effect. Therefore, strengthening the development of the agricultural service industry is of great significance to improve the utilization rate of mechanical equipment and reduce the undesired output of agriculture.