Eco Efficiency Research Articles

Evaluating the mechanical and environmental impact of PEF plastic waste incorporated with graphene nano-platelets in concrete

There has been a significant surge in the yearly use of plastics, leading to a notable rise in plastic waste generation. Consequently, the recycling of plastic garbage has emerged as a prominent concern around the world. This research explores the feasibility of using polyethylene furanoate (PEF) plastic waste as a substitute for coarse aggregate (CA) in concrete. Graphene nano-platelets (GNPs) were added to the concrete mix in different quantities to improve its structural reliability. The research study used an experimental research design in conducting its investigation. PEF waste plastic was added in concrete in varying proportions of 0%, 5%, 15%, 20%, and 25% as a supplementary material to gravel, and GNPs were added in different percentages of 0%, 0.03%, 0.05%, 0.08%, and 0.1% by weight of cement. Mechanical tests were conducted, which includes compressive strength (CS), split tensile strength (STS), flexural strength (FS), modulus of elasticity (MoE), and ultrasonic pulse velocity (UPV), and the environmental assessment of concrete was done by assessing carbon in concrete and concrete’s eco efficiency (ESE). It was found that 5% addition of PEF as the substitute to CA and 0.1% of GNPs gives the optimum strength, enhancing CS, STS, and FS by 9.10%, 18.18%, and 4.45%, respectively. Response surface technique (RSM) models were created to provide mathematical equations for predicting the predicted outcomes. All models were optimized using a multi-objective optimization approach and then validated.

Urban eco-efficiency of China: Spatial evolution, network characteristics, and influencing factors

Urban eco-efficiency (EE) refers to the ability of a city to balance economic growth with environmental protection through the optimal use of resources and environmental management, reflecting the city’s performance in sustainable development. Quantitative EE analysis is a crucial evaluation criterion for measuring the process of sustainable development (SD). To assess the current state of sustainable development in China, this study employs the slacks-based super efficiency model (Super-SBM) to measure the the urban eco-efficiency in China (CUEE) of 284 cities. The study utilizes Kernel Density Estimation (KDE) and Spatial Autocorrelation Analysis (SAA) to investigate the fundamental patterns of CUEE in terms of inter-city differences and relationships. Complex Network Analysis (CNA) and Link Prediction methods are applied to examine the characteristics and future trends of the CUEE network. Additionally, Geodetector and Geographically Weighted Regression (GWR) are used to analyze the influencing factors of CUEE. The findings are as follows: Overall CUEE is relatively low but shows a steady increase. The spatial association network of CUEE is becoming more complex, with increasing association strengths. The Chengdu-Chongqing Economic Circle (CCEC) is expected to further enhance its spatial association strength and may emerge as a new core area. The effectiveness of the interactions among selected factors is greater than that of individual factors. Degree centrality (X1) is identified as a core explanatory factor influencing CUEE, showing a positive correlation with CUEE. Scientific expenditure (X5) is also positively correlated with CUEE. Local fiscal budget expenditure (X3), industrial output value of foreign-invested enterprises (X7), and total cargo transportation volume (X9) are negatively correlated with CUEE. The analytical framework and research conclusions of this study offer valuable insights into the development of urban ecological efficiency in China and provide constructive recommendations for promoting sustainable urban development.

The coordinated relationship and interactive response between urban quality of life and eco-efficiency in China

It is crucial to clarify the interaction mechanism between quality of life (QOL) and eco-efficiency (EE) to achieve high-quality urban development. This study investigated the complex and dynamic interaction and coupling process between QOL and EE. By constructing two evaluation index systems, this study obtained the values of QOL and EE levels in 282 cities from 2008 to 2020. Then, the interactive relationship between QOL and EE was investigated from two perspectives: static coupling and dynamic coupling. The different development types were classified according to the regional differences between them. The results show that: (1) From 2008 to 2020, the value of QOL gradually increased, while the EE exhibited a “V-shaped” change. Medium to high levels of QOL were located in cities in the eastern coastal area, while low levels were distributed in the western, central and northeastern regions. Furthermore, medium to high levels of EE were distributed in cities in the eastern coastal and southwestern regions, whereas low levels were found in the central and northwestern regions; (2) Overall, the coupled coordination of QOL and EE got better from 2008 to 2020, showing that the relationship between them was close and that the coordination gradually got better. Consequently, the spatial change of the coupled coordination was more pronounced, the number of mildly uncoordinated cities was gradually decreasing, urban development was shifting from uncoordinated to coordinated, and the clustering characteristics of the coupled coordination degree were consistent with the spatial change characteristics; (3) Moreover, there was a Granger causality relationship between QOL and EE. This means that the degree of their mutual influence increased over time, while their development became less dependent on inertia, with obvious interaction characteristics; and (4) The values of integrated QOL and EE were separately clustered and combined with the type of coupled and coordinated urban development based on their development stage. Therefore, the research area was divided into three types: “optimization and upgrading,” “continuous improvement,” and “cultivating development.”

Stakeholder Insights: A Socio-Agronomic Study on Varietal Innovation Adoption, Preferences, and Sustainability in the Arracacha Crop (Arracacia xanthorrhiza B.)

Arracacha, a root crop indigenous to the Andean region of South America, holds significant agronomic and socio-economic importance in Colombia. The study aims to evaluate the impacts of adopting the ‘Agrosavia La 22’ variety on agricultural sustainability and productivity, encompassing economic, environmental, and social dimensions. Additionally, it analyzes the preferences of farmers and other stakeholders regarding the sustainability of the introduced technological innovations. Conducted over three years (2021–2023), the study offers comprehensive insights into adoption trends and stakeholder perceptions. Utilizing the Ambitec-Agro methodology, the research assesses the environmental, social, and economic impacts of ‘Agrosavia La 22’. Data collection involved field observations and interviews with farmers and key actors in the arracacha supply chain. Results indicate a substantial increase in the cultivated area from 1500 hectares in 2021 to 2650 hectares in 2023, with the proportion of total cultivated area rising from 47.6% to 84.1%. Economically, ‘Agrosavia La 22’ demonstrated significant input cost savings, reducing costs by USD 347 per hectare by 2023 and enhancing producer surplus from USD 30.95 to USD 651.16 per hectare. Yield comparisons show higher median yields for ‘Agrosavia La 22’ (20 t ha−1 in 2023) compared to traditional varieties (12.5 t ha−1). Socially, there was a marked improvement in farmers’ income perceptions, and environmentally, there was a reduction in greenhouse gas emissions (324.05 kg CO2-eq ha−1) due to optimized fertilizer and pesticide applications. Eco-efficiency (EE) analysis shows that ‘Agrosavia La 22’ consistently demonstrated positive EE values, indicating economic viability alongside lower GHG emissions. In 2021, its EE stood at 2.2 USD/kg CO2-eq, increasing to 27.75 USD/kg CO2-eq by 2023, reflecting substantial economic gains relative to environmental impact. Conversely, the traditional variety initially exhibited lower EE due to high GHG emissions. Challenges such as soil quality decline and market price volatility were noted. Overall, the findings underscore the economic, social, and environmental benefits of ‘Agrosavia La 22’. Furthermore, the methodology used in this study can be applied to the evaluation of other varietal innovations in developing countries with limited resources for assessing agricultural technology impacts.

The Effect of Eco-Efficiency and Eco-Innovation Disclosure on Firm Value: Does Profitability Matter?

This research aims to test whether profitability strengthens the influence of eco innovation and eco efficiency disclosures on the value of mining sector companies listed on the Indonesia Stock Exchange. Research data was obtained from annual reports and sustainability reports from the Indonesian Stock Exchange website and company websites. The sample used was 39 companies that met the criteria and were listed on the Indonesia Stock Exchange in 2018 – 2021. The sample data calculation technique used the cross sectional method via the eviews application. Hypothesis testing in this research uses multiple linear regression analysis methods. The results of this research show that eco innovation and eco efficiency have a positive effect on firm value, and profitability has an effect as a moderating predictor variable in the relationship between eco innovation and eco efficiency on firm value. This study differentiates samples based on more diverse dependent variables and involves moderating variables as amplifiers. Previous research did not use the two dependent variables, namely eco innovation and eco efficiency simultaneously so that the value of the company could not be determined as a whole whether the implementation of both had an effect on the value of the company. Then the researchers found that investors considered the application of eco innovation and eco efficiency to the value of mining sector companies.

Can green finance improve eco-efficiency? New Insights from China.

Achieving economic development and ecological protection simultaneously is an inevitable selection for sustainable development in today's world, so it is crucial to improve eco-efficiency (EE). According to Chinese panel data at the provincial level between 2010 and 2020, this research explores the nexus between green finance (GF) and EE. The results denote that GF can significantly improve EE, and the higher the level of EE, the stronger the effect of improvement. The upgrading of industrial structure, optimization of energy structure, enterprises' concern for environmental protection and the public's attention to the environment are all favorable factors that can enhance the promotion effect of GF on EE. Additionally, this facilitation can only be played under a good external environment and mature internal conditions. Our findings can provide new insights for improving EE by developing GF.

A conceptual model for evaluating eco-efficiency of thermal spraying processes

Thermal spraying (TS) is one of the main processes for obtaining surfaces with the desired protective properties in various industrial applications. TS is an energy-intensive treatment required to heat the application material and consumes different resources. To assess the environmental impact of TS, it becomes necessary to integrate an approach that jointly analyses and evaluates the economic and environmental variables influencing the system. The concept of eco-efficiency (EE) added to the TS process allows for assessing the environmental and economic condition through the survey and application of eco-indicators. The lack of an EE evaluation model for TS processes was identified based on literature searches. Thus, the overall objective of this work is to propose a conceptual model to evaluate the EE of TS treatment, selecting environmental and economic indicators considered more impactful in the process. The model developed consists of three main steps: (i) the input and output indicators (environmental and economic) are identified by applying the Analytic Hierarchy Process (AHP) method; (ii) the structure to be employed in the model is defined; and (iii) the Data Envelopment Analysis (DEA) model is applied to define the EE evaluation form. The proposed model consists of clear and easy-to-follow steps for evaluating the EE of spraying processes, filling the gap found in the literature. The use of DEA allowed the integration of the environmental and economic indicators obtained from the TS processes to generate important insights for evaluating EE. The results prove the model's effectiveness in identifying the EE results for each analysed unit of the TS process. The model has provided an evaluation consistent with the existing studies, and the EE scores were assessed according to twenty-one decision-making units (DMUs) allowing the identification of the most eco-efficient DMUs concerning TS processes.

BIM- and GIS-Based Life-Cycle-Assessment Framework for Enhancing Eco Efficiency and Sustainability in the Construction Sector

The world is progressing towards sustainable, eco-friendly, recyclable materials to enhance the circular economy and mitigate the issues of carbon footprint, overburdened landfills, and waste of natural resources. As increasing greenhouse gas (GHG) emissions are a major contributor towards climate change and given that the construction industry is one of the major producers of GHG emissions, it is crucial to meticulously quantify and lower its emissions, especially in the context of developing countries. This research presents a novel framework by combining advanced tools i.e., building information modeling (BIM), life-cycle assessment (LCA), geographic information systems (GISs), and quantification of embodied emissions to optimize construction’s design, material-selection, operations, maintenance, and waste-management processes. The effectiveness of the proposed approach has been demonstrated with the help of a real-world case study in Islamabad, Pakistan. A building model has been generated using BIM, and a comprehensive LCA has been conducted. Additionally, GIS tools have been utilized to identify the locations and accessibility of available-waste-management facilities. Based on this data, embodied emissions related to handling and transportation of waste material to disposal facilities have been computed using mathematical analyses. Furthermore, targeted mitigation strategies have been proposed and an optimized route has been designed using GIS-based route-optimization tools along the suggested facility centers in the Islamabad region. The case study has been reassessed with alleviation strategies, and the results show that 29.35% of the materialization stage, 16.04% of the operational stage, and 21.14% of the end-of-life-phase GHG emissions can be effectively reduced. Hence, pre-evaluating the environmental degradation caused by construction projects throughout their life cycle might offer an opportunity to comprehend and reduce prospective environmental impacts.

The Effect of Eco Efficiency, Number of Audit Committees and Sustainability Report on Going Concern Audit Opinion

Going concern for business is always a major issue that is considered by the management. The going concern audit opinion is one of the elements that displays the findings of the business continuity assessment. It can provide credibility that will affect investors' confidence in investing, and provide guarantees for companies that have potential issues related to their going concern. The goal of this study was to investigate how going concern audit opinion was impacted by eco-efficiency, the number of audit committees, and sustainability reports. Based on mining companies listed between 2020 and 2022 on the Indonesia Stock Exchange (IDX), the research was conducted. This study makes use of secondary data in the form of financial statements. Structural Equation Modeling - Partial Least Square (SEM-PLS) is the data analysis method used. The findings demonstrated that going concern audit opinions are significantly impacted by eco efficiency, the number of audit committees, and sustainability reports.

Using eco‐efficiency and eco‐wellbeing performance as indicators for urban sustainable development: A two‐stage network analysis

AbstractSustainable development is one of the most significant issues of concern around the world today. Sustainable development goals cover natural resources, the environment, and human well‐being. It follows that eco‐efficiency (EE) and eco‐well‐being performance (EWP) are valid tools for measuring the level of different stages of sustainable development. This study uses a two‐stage super‐SBM model to gauge the EE and EWP of 281 cities in China from 2011 to 2019. The results show the following: (1) The national EE average is low, with M‐shaped “rising‐declining‐rising‐declining” fluctuation. The national EWP average is low, but there is a clear upward trend. (2) From a regional perspective, the best EE is in the eastern region, followed by the central and western regions, and the worst is in the northeastern region. The best EWP is in the western region, followed by the eastern and northeastern regions, and the worst is in the central region. (3) Among the 281 sample cities, approximately 12.8% are in the high EE‐high EWP development mode, 25.6% are in the high EE‐low EWP development mode, 18.2% are in the low EE‐high EWP development mode, and 43.4% are in the low EE‐low EWP development mode. Collectively, the three cities with the strongest sustainability are Shenzhen, Beijing, and Haikou, and the three weakest are Baise, Jinchang, and Baiyin. In addition, cities with larger populations tend to exhibit greater sustainability. These results provide the necessary reference for Chinese cities and cities worldwide in similar situations to formulate policies to improve sustainability.

Principal component analysis of containership traffic in the Black Sea

A novel quantitative analysis employing the Principal Component Analysis (PCA) of containership traffic in the Black Sea from 2018 to 2021 is performed. The study uses a matrix covering five ship size classes from A to E for four years of operation, from 2018 to 2021, accounting for ship traffic, CO2, fuel consumption (FC), shipping intensity, and eco and traffic efficiency. Only the first two principal factors are analysed because of their total variation weight. Shipping intensity, FC intensity, and CO2 intensity plays a significant role in the first factor, while Eco efficiency, FC efficiency, and Traffic efficiency are considered for the second factor. Notably, the set of parameters pertains to time and is strongly associated with DWT. Two principal components were identified, F1 and F2, where F1 integrates efficiency and intensity. At the same time, F2 separates the intensity from the efficiency conditional on the ship size and the year of operations. In the principal component F1 the activities of ships A and C differ from B, D and E, separating more efficiently from less efficiently used ships, and in F2, the activities of class sizes of ships C and D and E contrast A and B ships, distinguishing the big-size class ships from small ones. It was concluded that the most intensively used ships are the ship size classes C and D, and the most efficient are ship size classes A and B. The most intensive use of the ships was in 2020, followed by 2021, and the most efficient were in 2018, 2019. Based on the ship activities and using the Within-class variance, ships are grouped into two clusters of similar activities, where the first one, with lower variance and more homogeneous, includes only the ship size class A. The second one with a relatively large variance consists of the rest size of the ships. Linear relationships considering the intensity and efficiency are derived as a function of the main variables, where the factor loading represents the variable’s coefficient, given as a relative weight to any factor.

Eco Efficiency Optimization of Municipal Solid Waste Management

Abstract: Municipal solid wastes, commonly referred to as trash or garbage, are the solid wastes generated from human activities. A number of these wastes are extremely toxic and infectious. The uncontrolled and unscientific way of dumping such wastes have raised the number of incidents of hazards to human health. One among the important aspects which gains more impact on sustainability of the environment is management of municipal solid waste. A case study of Juhu (MCGM) has been selected for effective and efficient management of municipal solid waste. The main objective of the research is to seek out an optimal route for transporting the rubbish from dumper bins and from temporary transfer stations to the ultimate dumping yard. The research work has been administered in two stages, namely data collection within the first stage and data analysis for optimization within the second stage. For locating the optimal transportation route, VRPTW model is employed in the GIS and GA environments. The proposed study is concentrated on finding the optimal route in transporting the MSW from dumper bins and temporary transfer stations to the dump-yard. MCGM must operate 90 such vehicles in 6 trips. . When time window is employed for vehicle routing, resources like labours and vehicles can be effectively managed and utilized. Due to the time window, it is easier for the highest-level officials to manage both labour and transportation vehicles.

Eco-Efficiency of the Urban Agglomerations: Spatiotemporal Characteristics and Determinations

Attaining optimal eco-efficiency is of paramount importance in promoting the sustainable and harmonious development of the economy and environment within urban agglomerations. Firstly, this paper utilizes the Super-SBM model with undesirable output to measure the eco-efficiency (EE) of 64 cities in the Beijing–Tianjin–Hebei metropolitan region (BTHMR), the Yangtze River Delta (YRD), the Pearl River Delta (PRD), and the Chengdu–Chongqing Economic Zone (CCEZ) from 2006 to 2019. Secondly, this study puts forth a novel and comprehensive index system aimed at evaluating the urbanization efficiency and sheds light on the spatiotemporal changes in EE and urbanization efficiency. Finally, the STIRPAT model is used to examine the influencing factors of EE and to investigate the correlation between EE and urbanization efficiency. The study found that the overall EE of the four typical urban agglomerations is high, but the trend varies with a decrease of about 12.9% from 2006 to 2019. The mean EE is in the order of CCEZ > PRD > BTHMR > YRD, with mean values of 0.941, 0.909, 0.842, and 0.732, respectively. The level of science and technology and the urbanization efficiency have a significant positive impact on EE, while population, industrial structure, FDI, and greening level have an inhibitory effect on urban eco-efficiency. Based on the results, policy suggestions such as paying attention to regional heterogeneity and giving full play to the government’s macro-regulatory role in shaping the economic and industrial structure are proposed to serve as a guide for the coordinated development of urban agglomerations under the Dual Carbon Target.

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.

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.

Exploring the Impacts of Urbanization on Eco-Efficiency in China

It is of significant importance to conduct research on the relationship between urbanization and eco-efficiency (EE), for it can aid policy making for urban and regional sustainable development. This paper studied the effects of urbanization on the EE in 30 provinces of China from 2008 to 2019. Using the epsilon-based measure (EBM) model with undesirable outputs, this study measured the EE of China’s provinces before empirically analyzing the effects of urbanization on EE. Conclusions could be drawn: the annual mean EE of the eastern region was the highest (0.837), followed by those of the central region (0.653) and western region (0.570), and that of the northeast region remained the lowest (0.438). Zooming into the provinces and cities, the EEs of Beijing, Shanghai, and Fujian were at the production frontier surface, with a high level of EE during the study period, while those of Gansu, Ningxia, and Xinjiang were generally at a lower level. Empirical analysis showed that the effects of urbanization on EE in China presented a U-shaped relationship, having a negative correlation first and then reversing to a positive one. At present, China is in the early negative stage, and the turning point has yet to come. Considering the control variables, the economic development level, technological progress, and foreign direct investment have positively influenced eco-efficiency. Overall, the paper may shed light on related studies and provide relevant policy suggestions to promote EE through a new urbanization strategy.

The Impact and Mechanism of the Increased Integration of Urban Agglomerations on the Eco-Efficiency of Cities in the Region—Taking the Chengdu–Chongqing Urban Agglomeration in China as an Example

China is attaching increasing importance to the creation of regional integration, high-quality economic development and ecological civilization. An accurate grasp of the traction effect of the increased level of integration of urban agglomerations on the eco-efficiency (EE) of cities in the region will help to promote the steady improvement of urban economic development and the ecological environment. This paper constructs an index system to measure the level of integration of the Chengdu–Chongqing urban agglomeration (CCUA) and the EE of each city within it from 2011 to 2020 and explores the impact of regional integration on urban EE and its mechanism of action. The study presents the follow findings: (1) The level of integration of the CCUA increased nearly 10 times from 2011 to 2020, with the government playing a significant leading role. (2) The positive and negative effects of the level of integration of the CCUA on urban EE depend on factors such as the level of economic development, the stage of development and the location. There are several relationships between the level of intra-regional integration and urban EE: first, a nearly linear increase, as in Chongqing and Chengdu; second, an increase in fluctuation, as in Dazhou, Guang’an and Leshan; and third, a fluctuation, decrease, flat or even no real increase, as in Luzhou, Ya’an and Zigong. (3) Based on this, this paper considers the mechanism of the level of integration within the region on urban EE in terms of both economic and eco-environmental effects, with a view to exploring the future green development path of the CCUA.

Coordination of industrial structure and eco-efficiency in ecologically fragile areas: A case study of the Loess Plateau, China

The relationship between industrial structure (IS) and eco-efficiency (EE) is intricate with mutual influence and constraint. Exploring the coordinated relationship between IS and EE is beneficial to the sustainable development of ecologically fragile areas. This paper estimates and analyses the levels of EE and IS in 39 prefecture-level cities of the Loess Plateau, discussing the comprehensive and coordinated development levels between industrial structure rationalization (ISR) and EE, industrial structure advancement (ISA) and EE based on the coupling coordination degree model (CCDM). The results showed that the comprehensive development of the Loess Plateau has rough and imbalanced issues. The EE and IS are developing at a relatively low level, and the spatial distribution shows the development trend of high in the east and down in the west. The CCD of ISA and EE performs better than that of ISR and EE, but neither has reached the collaborative coupling state. The poor CCD score in the Loess Plateau is primarily attributable to its relatively backward degree of integrated EE and IS. The results are expected to provide decision-making support for EE improvement and industrial restructuring in the Loess Plateau and other ecologically fragile areas.

Peningkatan Earning Before Interest and Tax (EBIT) melalui Penerapan Green Accounting

This study aims to analyze the increase in eco efficiency with the application of green accounting. Data collection techniques using literature study, observation, interviews and documentation. Checking the validity of the data through extension of participation, persistence of observation, and triangulation of data. The results showed that Lumintu farm’s had implemented green accounting through the stages of identifying costs for handling the impact of negative externalities on production, the recognition stage, the measurement stage, the presentation stage through the income statement and the stage of disclosing the costs or costs incurred by the company for environmental management. The good environmental performance of the entity also has an impact on the positive response of consumers so that it can increase profits or EBIT..

Carbon Emission Disclosure and Firm Value: Does Eco-Efficiency Moderate this Relationship?

The purpose of this research is to analyze the effect of Carbon Emission Disclosure and Firm Value on moderate of Eco efficiency relationship. Carbon Emission Disclosure as an independent variable is measured by dummy. Firm value as dependent variable is measured by Tobins’Q. This research using Leverage, Firm Size, profitability as control variable. The research uses 495 samples, comprising the data of 99 manufacturing companies listed on the Indonesia Stock Exchange over five years, from 2017 to 2021. The sampling method in this research is purposive sampling. The analysis technique in this study using multiple linear regression analysis. The results show that Carbon Emission Disclosure has a significant positive influence on the Firm Value, while Eco-Efficiency has a significant negative influence. The implications of this research it is hoped that investors will be increasingly concerned about the environment by considering the environmental impacts produced by companies as a consideration for determining investment decisions because investors are one of the parties that can pressure companies to implement environmental policies.