Journal Description
Sustainability
Sustainability
is an international, peer-reviewed, open-access journal on environmental, cultural, economic, and social sustainability of human beings, published semimonthly online by MDPI. The Canadian Urban Transit Research & Innovation Consortium (CUTRIC), International Council for Research and Innovation in Building and Construction (CIB) and Urban Land Institute (ULI) are affiliated with Sustainability and their members receive discounts on the article processing charges.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SCIE and SSCI (Web of Science), GEOBASE, GeoRef, Inspec, AGRIS, RePEc, CAPlus / SciFinder, and other databases.
- Journal Rank: JCR - Q2 (Environmental Studies) / CiteScore - Q1 (Geography, Planning and Development)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 18.8 days after submission; acceptance to publication is undertaken in 3.6 days (median values for papers published in this journal in the second half of 2023).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
- Testimonials: See what our editors and authors say about Sustainability.
- Companion journals for Sustainability include: World, Sustainable Chemistry, Conservation, Future Transportation, Architecture, Standards, Merits and Wind.
Impact Factor:
3.9 (2022);
5-Year Impact Factor:
4.0 (2022)
Latest Articles
Urban Heat Island Assessment in the Northeastern State Capitals in Brazil Using Sentinel-3 SLSTR Satellite Data
Sustainability 2024, 16(11), 4764; https://doi.org/10.3390/su16114764 (registering DOI) - 3 Jun 2024
Abstract
The lack of a solid methodology defining urban and non-urban areas has hindered accurately estimating the Surface Urban Heat Island (SUHI). This study addresses this issue by using the official national urban areas limit together with a surrounding areas classification to define three
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The lack of a solid methodology defining urban and non-urban areas has hindered accurately estimating the Surface Urban Heat Island (SUHI). This study addresses this issue by using the official national urban areas limit together with a surrounding areas classification to define three different reference classes: the urban adjacent (Ua), the future urban adjacent (FUa), and the peri-urban (PUa), consequently providing a more accurate SUHI estimation on the nine northeastern Brazilian capitals. The land surface temperature was obtained in this study using the Sentinel-3 satellite data for 2019 and 2020. Subsequently, the maximum and average SUHI and the complementary indexes, specifically the Urban Thermal Field Variation Index (UTFVI) and the Thermal Discomfort Index (TDI), were calculated. The UTFVI expresses how harmful the eco-environmental spaces are, with a very strong SUHI for three capitals. In addition, the TDI, with values between 24.6–28.8 °C, expresses the population’s thermal comfort, with six capitals showing a very hot TDI. These findings highlight the need for strategies to mitigate the effects of the SUHI and ensure the population’s thermal comfort. Therefore, this study provides a better SUHI understanding and comparison for the Brazilian northeastern region, which has diverse areas, populations, and demographic variations.
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(This article belongs to the Section Air, Climate Change and Sustainability)
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Open AccessArticle
Research on Autonomous Vehicle Obstacle Avoidance Path Planning with Consideration of Social Ethics
by
Lanwen Wang, Hui Jing, Guoan Zhong, Jiachen Wang and Tao Wang
Sustainability 2024, 16(11), 4763; https://doi.org/10.3390/su16114763 (registering DOI) - 3 Jun 2024
Abstract
Self-driving car research can effectively reduce the occurrence of traffic accidents, but when encountering sudden people or obstacles cutting into the lane, how to reduce the damage hazard to traffic participants and make ethical decisions is the key point that the development of
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Self-driving car research can effectively reduce the occurrence of traffic accidents, but when encountering sudden people or obstacles cutting into the lane, how to reduce the damage hazard to traffic participants and make ethical decisions is the key point that the development of self-driving technology must break through. When faced with sudden traffic participants, self-driving vehicles need to make ethical decisions between ramming into the traffic participants or other obstacles. Therefore, in this paper, we propose a model decision planning method based on multi-objective evaluation function path evaluation of local path planning. This method addresses the ethical model disagreement problem of self-driving vehicles encountering traffic participants and other obstacles. The aim is to ensure the safety of the lives of the traffic participants and achieve the vehicle’s reasonable ethical decision planning. Firstly, when anticipating traffic participants and other obstacles, the vehicle’s planning intention decisions are obtained through fuzzy algorithms. Different sets of curves for various positions are generated based on dynamic programming algorithms. These curves are then fitted using B-spline curves, incorporating obstacle collision costs, and classifying obstacles into different types with varying cost weights. Secondly, factors such as path length and average path curvature are considered for path total cost calculations. Finally, a local path that avoids traffic participants is obtained. This path is then tracked using a pure pursuit algorithm. The proposed algorithm’s effectiveness is verified through simulation experiments and comparative analyses conducted on the MATLAB platform. In conclusion, this research promotes a safer and more sustainable transport system in line with the principles of sustainable development by addressing the challenges associated with safety and ethical decision making in self-driving cars.
Full article
(This article belongs to the Collection Accident Prevention and Risk Management for Safe and Sustainable Transportation)
Open AccessArticle
Multilevel Change of Urban Green Space and Spatiotemporal Heterogeneity Analysis of Driving Factors
by
Huimin Wang, Canrui Lin, Sihua Ou, Qianying Feng, Kui Guo, Xiaojian Wei and Jiazhou Xie
Sustainability 2024, 16(11), 4762; https://doi.org/10.3390/su16114762 (registering DOI) - 3 Jun 2024
Abstract
Analyzing the change trend of urban green space (UGS) and exploring related driving forces can provide scientific reference for sustainable development in rapidly urbanizing areas. However, the spatial and temporal driving mechanisms of the drivers on UGS patterns at different scales are still
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Analyzing the change trend of urban green space (UGS) and exploring related driving forces can provide scientific reference for sustainable development in rapidly urbanizing areas. However, the spatial and temporal driving mechanisms of the drivers on UGS patterns at different scales are still not deeply understood. Based on the GlobeLand30 land cover data, nighttime lighting data and spatial statistics from 2000 to 2020, this study analyzed the size, shape and diversity of UGS in Guangzhou at the urban level, gradient level and township level with multiple landscape indices. Diversity means the richness of UGS patch types. The selected indices include percent of landscape (PLAND), largest path index (LPI), landscape shape index (LSI), aggregation index (AI) and Shannon’s diversity index (SHDI). The spatiotemporal heterogeneity of the drivers was then explored using the spatiotemporal weighted regression (GTWR) method. Results showed the following: (1) During 2000−2020, the total amount of UGS in Guangzhou increased slightly and then decreased gradually. UGS was mainly transferred into artificial surfaces (lands modified by human activities). (2) The UGS landscape showed a non-linear trend along the urban–rural gradient and fluctuated more in the interval of 20–60% urbanization level. PLAND, LPI and AI decreased significantly in areas with higher levels of urbanization. LSI increased and SHDI decreased significantly in areas with lower levels of urbanization. At township level, the landscape indices showed significant spatial autocorrelation. They transformed from discrete changes at the edge and at the junction of the administrative district to large-scale aggregated change, especially in northern areas. (3) The size of UGSs was mainly influenced by natural factors and population density, but their shape and diversity were mainly influenced by socio-economic factors. More regular shapes of green patches were expected in higher urbanization areas. Population agglomeration positively influenced green space patterns in the northeastern and southern regions (Zengcheng, Conghua and Nansha). Meanwhile the negative influence of urban expansion on the green space pattern in the central and southern regions decreased over time. This study contributes to an in-depth understanding of how the key factors affect the different changes of UGS with time and space and provides methodological support for the long-term zoning planning and management of UGS.
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(This article belongs to the Section Sustainable Urban and Rural Development)
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Open AccessArticle
How to Enhance Consumer’s Engagement with Returnable Cup Services? A Study of a Strategic Approach to Achieve Environmental Sustainability
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Derrick Jessey Yang, Tseng-Ping Chiu and Min-Yuan Ma
Sustainability 2024, 16(11), 4761; https://doi.org/10.3390/su16114761 (registering DOI) - 3 Jun 2024
Abstract
The issue of sustainability has once again received attention and promotion in the post-COVID-19 pandemic era. Countries worldwide have launched returnable cup services for beverages, such as Taiwan, which is a highly developed market for hand-shaken drinks, and various beverage and convenience stores
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The issue of sustainability has once again received attention and promotion in the post-COVID-19 pandemic era. Countries worldwide have launched returnable cup services for beverages, such as Taiwan, which is a highly developed market for hand-shaken drinks, and various beverage and convenience stores have been gradually launching this service. However, reasonable usage rates have yet to be achieved. This study aimed to explore the psychological cognition of using a returnable cups service by understanding the motivation affecting the behavior intention through external and internal influencing and categorizing realistic cognition, which observes the motivating factors from three perspectives: passively acquired awareness, autonomous consciousness, and perception in real life for further achieving environmental sustainability. Research found that when consumers’ environmental awareness is insufficient to sacrifice convenience, it is necessary to employ a service strategy design for passive influence. The focal point for influencing consumer attitudes lies in the backend of services, particularly in cup return, which is the chain-closing juncture. The result can provide the beverage industry and governments with a reference to promote returnable cups and contribute to plastic reduction in sustainable development.
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(This article belongs to the Special Issue Relation and Development between Circular Economy, Economic Growth and Environmental Sustainability)
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Open AccessArticle
Secondary Succession in Fallow Agroforestry Systems Managed in Tropical Dry Forest in Western Mexico
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Alana Pacheco-Flores, Alejandro Casas, Ana I. Moreno-Calles, Roberto Lindig-Cisneros, Francisco Javier Rendón-Sandoval, Francisco Mora-Ardila, Fernando Estañol-Tecuatl, Gonzalo D. Álvarez-Ríos and Rubén Ortega-Álvarez
Sustainability 2024, 16(11), 4760; https://doi.org/10.3390/su16114760 (registering DOI) - 3 Jun 2024
Abstract
Tropical dry forests (TDFs) are ecosystems of high biocultural value, in which agroforestry systems (AFSs) have been essential in their management and conservation. We aimed to characterize agroforestry practices and analyze their capacity to conserve perennial plant diversity. In addition, we sought to
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Tropical dry forests (TDFs) are ecosystems of high biocultural value, in which agroforestry systems (AFSs) have been essential in their management and conservation. We aimed to characterize agroforestry practices and analyze their capacity to conserve perennial plant diversity. In addition, we sought to evaluate how the management of TDFs as AFSs, together with their regeneration, influences species diversity and vegetation structure in a landscape with AFSs and TDFs in different conservation states. We compared the species diversity and basal area (BA) of plants in active and fallow AFSs at different regeneration stages in Zacualpan, Colima, Mexico. We found that AFSs harbored 71% of species richness (0D), forming a mosaic that contributed to the gamma diversity (124 species) of TDFs in the area. AFSs supported 23 endemic and 12 protected species. TDFs, active and advanced regeneration AFSs, had the highest number of useful species and diversity. Species richness (0D) in management categories increased as succession progressed, but not the BA, possibly due to frequent browsing and wood and firewood extraction. However, BA may be related to the management of useful trees maintained through agroforestry practices. We suggest increasing the matrix quality through a mosaic of active and fallow AFSs to promote ecological connectivity and biodiversity conservation.
Full article
(This article belongs to the Section Sustainability, Biodiversity and Conservation)
Open AccessArticle
Improved YOLO v7 for Sustainable Agriculture Significantly Improves Precision Rate for Chinese Cabbage (Brassica pekinensis Rupr.) Seedling Belt (CCSB) Detection
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Xiaomei Gao, Gang Wang, Jiangtao Qi, Qingxia (Jenny) Wang, Meiqi Xiang, Kexin Song and Zihao Zhou
Sustainability 2024, 16(11), 4759; https://doi.org/10.3390/su16114759 (registering DOI) - 3 Jun 2024
Abstract
Precise navigation in agricultural applications necessitates accurate guidance from the seedling belt, which the Global Positioning System (GPS) alone cannot provide. The overlapping leaves of Chinese cabbage (Brassica pekinensis Rupr.) present significant challenges for seedling belt fitting due to difficulties in plant
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Precise navigation in agricultural applications necessitates accurate guidance from the seedling belt, which the Global Positioning System (GPS) alone cannot provide. The overlapping leaves of Chinese cabbage (Brassica pekinensis Rupr.) present significant challenges for seedling belt fitting due to difficulties in plant identification. This study aims to address these challenges by improving the You Only Look Once (YOLO) v7 model with a novel approach that decouples its network head deriving from the Faster-Regions with Convolutional Neural Network (Faster R-CNN) architecture. Additionally, this study introduced a BiFormer attention mechanism to accurately identify the centers of overlapping Chinese cabbages. Using these identified centers and pixel distance verification, this study achieved precise fitting of the Chinese cabbage seedling belt (CCSB). Our experimental results demonstrated a significant improvement in performance metrics, with our improved model achieving a 2.5% increase in mean average precision compared to the original YOLO v7. Furthermore, our approach attained a 94.2% accuracy in CCSB fitting and a 91.3% Chinese cabbage identification rate. Compared to traditional methods such as the Hough transform and linear regression, our method showed an 18.6% increase in the CCSB identification rate and a 17.6% improvement in angle accuracy. The novelty of this study lies in the innovative combination of the YOLO v7 model with a decoupled head and the BiFormer attention mechanism, which together advance the identification and fitting of overlapping leafy vegetables. This advancement supports intelligent weeding, reduces the reliance on chemical herbicides, and promotes safer, more sustainable agricultural practices. Our research not only improves the accuracy of overlapping vegetable identification, but also provides a robust framework for enhancing precision agriculture.
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(This article belongs to the Section Sustainable Agriculture)
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Open AccessArticle
Economic and Environmental Benefit Analysis between Crumb Rubber Concrete and Ordinary Portland Cement Concrete
by
Guanghong Xiong, Safat Al-Deen, Xiao Guan, Qing Qin and Chenghua Zhang
Sustainability 2024, 16(11), 4758; https://doi.org/10.3390/su16114758 (registering DOI) - 3 Jun 2024
Abstract
Although manifold empirical studies have identified the mechanical properties of crumb rubber concrete (CRC), a comparative analysis of economic and environmental benefits between CRC and ordinary Portland cement concrete (OPCC) is not explored. In this paper, a quantitative meta-analysis between CRC and OPCC
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Although manifold empirical studies have identified the mechanical properties of crumb rubber concrete (CRC), a comparative analysis of economic and environmental benefits between CRC and ordinary Portland cement concrete (OPCC) is not explored. In this paper, a quantitative meta-analysis between CRC and OPCC is conducted to explore optimized design strength, and a comparative analysis of the economic and environmental benefits of the two materials is undertaken. Considering cost price as the economic index and CO2 emissions per cubic meter of concrete as the environmental index in the materialization stage, CRC and OPCC were compared with different mix designs to achieve grades of similar strengths. Upon replacing less than 20% of natural fine aggregates in concrete with crumb rubber, while retaining the cement content, an increase of 6% in the cost price was achieved for CRC with 30–40 MPa strength grade. Apart from the aspect of mining and transportation of natural aggregates, the reduction of CO2 emissions by means of CRC adoption was verified in the treatment process of waste tire incineration. The results show that CO2 emissions from CRC decreased by 15–17% when compared with OPCC for 30~40 MPa grade concrete. The research conclusion can serve as a theoretical basis for the engineering application of CRC with the same strength, and make certain contributions to the industrial application of crumb rubber aggregates and the sustainable treatment of waste tires.
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Open AccessEditorial
Advancing Sustainability in Geotechnical Engineering
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Shuren Wang, Chen Cao and Hongwei Yang
Sustainability 2024, 16(11), 4757; https://doi.org/10.3390/su16114757 (registering DOI) - 3 Jun 2024
Abstract
Geotechnical engineering is a key element for all engineering construction that establishes contact with the earth, including foundation engineering, slope engineering, tunnel engineering, mining engineering, etc [...]
Full article
(This article belongs to the Special Issue Advancing Sustainability in Geotechnical Engineering)
Open AccessArticle
Energy-Efficient Secure Routing for a Sustainable Heterogeneous IoT Network Management
by
Ashok Thangavelu and Prabakaran Rajendran
Sustainability 2024, 16(11), 4756; https://doi.org/10.3390/su16114756 (registering DOI) - 3 Jun 2024
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The Heterogeneous Internet of Things (H-IoT) is considered as the upcoming industrial and academic revolution in the technological world, having billions of things and devices connected to the Internet. This H-IoT has a major issue of energy consumption during data transmission which leads
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The Heterogeneous Internet of Things (H-IoT) is considered as the upcoming industrial and academic revolution in the technological world, having billions of things and devices connected to the Internet. This H-IoT has a major issue of energy consumption during data transmission which leads to low scalability. Additionally, anomalies in the data create a serious threat to energy in H-IoT. To overcome these issues, a novel approach has been proposed in this study termed as the Energy-Efficient Memetic Clustering Method (EEMCM), which combines the Parallelized Memetic Algorithm (PMA) with the AlexNet architecture to improve anomaly detection efficiency in IoT WSNs. Initially, cluster formation and CH selection are carried out using PMA. This is followed by routing path generation, and the data are prepared for high-level feature extraction. The extracted features are classified to identify anomalies. For anomaly detection, high-level features were collected that contain data relevant to the model given as input into the AlexNet architecture, which detects anomalies and identifies normal or potential attacks within the IoT WSNs. The proposed EEMCM model has been implemented in the MATLAB platform and obtained an accuracy of 99.11%. As a result, the overall performance of the network is improved.
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Open AccessArticle
Optimizing Lithium-Ion Battery Performance: Integrating Machine Learning and Explainable AI for Enhanced Energy Management
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Saadin Oyucu, Betül Ersöz, Şeref Sağıroğlu, Ahmet Aksöz and Emre Biçer
Sustainability 2024, 16(11), 4755; https://doi.org/10.3390/su16114755 (registering DOI) - 3 Jun 2024
Abstract
Managing the capacity of lithium-ion batteries (LiBs) accurately, particularly in large-scale applications, enhances the cost-effectiveness of energy storage systems. Less frequent replacement or maintenance of LiBs results in cost savings in the long term. Therefore, in this study, AdaBoost, gradient boosting, XGBoost, LightGBM,
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Managing the capacity of lithium-ion batteries (LiBs) accurately, particularly in large-scale applications, enhances the cost-effectiveness of energy storage systems. Less frequent replacement or maintenance of LiBs results in cost savings in the long term. Therefore, in this study, AdaBoost, gradient boosting, XGBoost, LightGBM, CatBoost, and ensemble learning models were employed to predict the discharge capacity of LiBs. The prediction performances of each model were compared based on mean absolute error (MAE), mean squared error (MSE), and R-squared values. The research findings reveal that the LightGBM model exhibited the lowest MAE (0.103) and MSE (0.019) values and the highest R-squared (0.887) value, thus demonstrating the strongest correlation in predictions. Gradient boosting and XGBoost models showed similar performance levels but ranked just below LightGBM. The competitive performance of the ensemble model indicates that combining multiple models could lead to an overall performance improvement. Furthermore, the study incorporates an analysis of key features affecting model predictions using SHAP (Shapley additive explanations) values within the framework of explainable artificial intelligence (XAI). This analysis evaluates the impact of features such as temperature, cycle index, voltage, and current on predictions, revealing a significant effect of temperature on discharge capacity. The results of this study emphasize the potential of machine learning models in LiB management within the XAI framework and demonstrate how these technologies could play a strategic role in optimizing energy storage systems.
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(This article belongs to the Special Issue Interpretable and Explainable AI Applications)
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Estimating the Energy Demand and Carbon Emission Reduction Potential of Singapore’s Future Road Transport Sector
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Shiddalingeshwar Channabasappa Devihosur, Anurag Chidire, Tobias Massier and Thomas Hamacher
Sustainability 2024, 16(11), 4754; https://doi.org/10.3390/su16114754 (registering DOI) - 3 Jun 2024
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About 20% of the world’s CO2 emissions originate from transport. Many countries are committed to decarbonizing their transport sector. Singapore pledged to electrify a whole host of its land transportation fleet, which includes private cars, public buses, ride-hail vehicles, and motorcycles. This
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About 20% of the world’s CO2 emissions originate from transport. Many countries are committed to decarbonizing their transport sector. Singapore pledged to electrify a whole host of its land transportation fleet, which includes private cars, public buses, ride-hail vehicles, and motorcycles. This paper proposes a simple empirical framework to estimate the future energy demand after 100% electrification has been realized for nine selected road transport vehicle sub-classes and to calculate the carbon emission reduction potential based on various scenarios. The present energy demand for each vehicle sub-class is first calculated based on parameters like petrol and diesel consumption, heat value and density of petrol and diesel, population of vehicle type, and average mileage per vehicle sub-class. Several scenarios are presented, and an analysis is carried out to derive a range of emission factors which are used to estimate the carbon emission reduction potential. Relative to the present day, the future energy demand estimates reveal an overall reduction of 73.60%. Full electrification and a “clean” power generation mix could lead to an emission reduction as high as 93.64% across all vehicles sub-classes, with private cars having the highest reduction potential.
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Open AccessArticle
Greening Emerging Economies: Enhancing Environmental, Social, and Governance Performance through Environmental Management Accounting and Green Financing
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Tianyao Zhen and Md. Mominur Rahman
Sustainability 2024, 16(11), 4753; https://doi.org/10.3390/su16114753 (registering DOI) - 3 Jun 2024
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Given the rising interest in sustainability globally, this paper investigates whether the environmental management accounting (EMA) and green financing of a firm are associated with superior environmental, social, and governance (ESG) performance, considering manufacturing firms from emerging economies like Bangladesh to address a
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Given the rising interest in sustainability globally, this paper investigates whether the environmental management accounting (EMA) and green financing of a firm are associated with superior environmental, social, and governance (ESG) performance, considering manufacturing firms from emerging economies like Bangladesh to address a gap in relevant research. Drawing on the perspective of contingency theory, this study is one of the first to analyze how EMA and green financing enable sustainable production to enhance ESG performance, as well as the mediation that sustainable production exerts on this relationship. This study entails an analysis of ESG performance in sensitive industries, i.e., those that are more likely to cause social and environmental damage. To test our hypotheses, we applied partial least squares path modeling to analyze data from 467 responses. Further, we used fuzzy set qualitative comparative analysis (fsQCA) to check the robustness. The results suggest that sensitive industries present superior ESG performance through integrating EMA and green financing. Further, empirical evidence demonstrates that sustainable production fully mediates the relationship between EMA and ESG performance. Meanwhile, sustainable production does not moderate green financing and ESG performance. For managers, this study demonstrates how embedding green financing and EMA into the organizational process for transitioning to a sustainable production model can present superior ESG performance. Our study contributes to research on both the impact of EMA and green financing on ESG performance, mediation effects of sustainable production, and integrated analysis using PLS-SEM and fsQCA, and the practice of sustainability management in firms in developing countries.
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Open AccessArticle
Performance Analysis and Optimization of Solar-Coupled Mine Water-Source Heat Pump Combined Heating and Cooling System
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Chang Zhao, Jianhui Zhao and Mei Wang
Sustainability 2024, 16(11), 4752; https://doi.org/10.3390/su16114752 (registering DOI) - 3 Jun 2024
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To address the energy consumption issue in mining area buildings, this paper proposed a solar-coupled mine water-source heat pump combined heating and cooling (SMWHP-CHC) system, taking the employee dormitory building group of a coal mining enterprise in Tongchuan City, China, as a case
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To address the energy consumption issue in mining area buildings, this paper proposed a solar-coupled mine water-source heat pump combined heating and cooling (SMWHP-CHC) system, taking the employee dormitory building group of a coal mining enterprise in Tongchuan City, China, as a case study. The system utilizes renewable solar energy and waste heat recovered from mine water as composite heat sources, and utilizes the cold energy in mine water as a cooling source to meet the demands for space heating, space cooling, and annual domestic hot water of the building in a sustainable manner. The simulation model of the system was established by TRNSYS to analyze the system’s annual operational performance. The results indicated that the system exhibited a positive energy efficiency and environmental performance under different operating conditions. The heating coefficients of the performance of the system (COPsys) during the space heating season and transition season were 3.54 and 18.6, and the cooling energy efficiency ratio of the system (EERsys) was 3.79. In addition, aiming to minimize the annual cost of the system, multiple crucial device parameters were synchronously optimized employing the PSO-HJ hybrid optimization algorithm through the GenOpt 2 software. The annual cost of the optimized system was reduced by 8.82%, and the investment cost was significantly reduced, while the performance was also improved. This study can provide theoretical support for the sustainable engineering application of the SMWHP-CHC system in mining area buildings.
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Open AccessArticle
The Effects of Fossil Fuel Consumption-Related CO2 on Health Outcomes in South Africa
by
Akinola Gbenga Wilfred and Abieyuwa Ohonba
Sustainability 2024, 16(11), 4751; https://doi.org/10.3390/su16114751 (registering DOI) - 3 Jun 2024
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The consumption of fossil fuel significantly contributes to the growth of South Africa’s economy but produces carbon dioxide (CO2), which is detrimental to environmental sustainability with overall effects on health outcomes. This study sought to (i) examine the impacts of fossil
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The consumption of fossil fuel significantly contributes to the growth of South Africa’s economy but produces carbon dioxide (CO2), which is detrimental to environmental sustainability with overall effects on health outcomes. This study sought to (i) examine the impacts of fossil energy consumption-related CO2 emissions on the under-five mortality and infant mortality rates in South Africa and (ii) analyse the causal relationship between fossil energy consumption, CO2 emissions, and mortality rates in South Africa. Linear and nonlinear ARDL bounds and the Toda–Yamamoto causality test were used to establish the equilibrium property in the long run and the causal effects of the models’ variables. Health outcome data include the under-five mortality rate (MTR1) and infant mortality rate (MTR2). Other explanatory variables include fossil energy consumption (FOC), inflation (Inf), carbon dioxide emissions (CO2), and government expenditure (GEH). It is evident from the results of linear ARDL that the first lag of the under-five mortality rate in the short run has a positive and significant impact on the under-five mortality rate in South Africa. Holding the other variables constant, the under-five mortality rate in South Africa would increase by 0.630% for every 1% increase in its lagged values. Fossil energy consumption has a positive and significant effect on the under-five mortality rate in South Africa. This significant relationship implies that a 1% increase in fossil energy consumption increases the under-five mortality rate per 1000 persons per year in South Africa by 0.418% in the short run, all things being equal. The results from the Toda–Yamamoto causality test revealed that there is no causality between the under-five mortality rate and both the consumption of fossil fuel and CO2 emissions in South Africa. The results from nonlinear ARDL presented four separate scenarios. In the short run, during increasing levels of CO2 in the initial period (lag of CO2), a 1% increase in CO2 would decrease the under-five mortality rate by 1.15%. During periods of decreasing levels of CO2 in the short run, a 1% increase in CO2 would increase the infant mortality rate by 0.66%. Again, during previous and current periods of decreasing levels of FEC, a 1% increase in FEC would increase the infant mortality rate by 0.45% and 0.32%, respectively. In the long run, during periods of increasing levels of CO2, a 1% increase in CO2 would decrease the infant mortality rate by 4.62% whereas during decreasing levels of CO2, a 1% increase in CO2 would increase the infant mortality rate by 2.3%. The risk posed by CO2 emissions and their effects on humans can then be minimised through a government expansionary policy within health programmes.
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Open AccessArticle
Conception of Improved Blackgram (Vigna mungo L.) Production Technology and its Propagation among Farmers for the Development of a Sustainable Seeds Production Strategy
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S. Marimuthu, C. Vanitha, U. Surendran, Salah El-Hendawy and Mohamed A. Mattar
Sustainability 2024, 16(11), 4750; https://doi.org/10.3390/su16114750 (registering DOI) - 3 Jun 2024
Abstract
Having a strong seed system that could spur agricultural expansion would be the first and most important step toward achieving food security in the nation of India. The main objective of this study was to investigate the impact of Improved Production Technology (IPT)
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Having a strong seed system that could spur agricultural expansion would be the first and most important step toward achieving food security in the nation of India. The main objective of this study was to investigate the impact of Improved Production Technology (IPT) on the production of high-quality seeds of blackgram (Vigna mungo L.) cultivar VBN 6 in a farmer-participatory mode in Tamil Nadu, India’s Ponnanaiyar subbasin during kharif and rabi 2017–18. In total, 985 farmers from 235 places throughout chosen Pudukkottai and Tiruchirappalli districts received frontline IPT demonstrations and IPT was applied in their agronomic practices afterwards. Compared to traditional approaches, our study demonstrated that IPT not only facilitated the production of high-quality seeds, but also a 25.14% higher seed yield of blackgram. Furthermore, the average water productivity was improved from 0.116 kg ha−1 m−3 to 0.154 kg ha−1 m−3. This study indicated IPT was effective in guaranteeing a system of sustainable seed production and thus was of great value in raising the farmers’ net incomes, profitability, and cost-benefit ratios. There is little well-documented data on how the farmer-participatory approach improves seed production technology in a sustainable way in the case of pulses when adopting improved production technologies in arable crop farming. Our creative method of having farmers participate in the demonstrations allowed us to evaluate how these extension programs affected the technology utilized to produce high-quality seeds. This study indicated IPT was effective in guaranteeing a system of sustainable seed production and thus was of great value in raising the farmers’ net incomes, profitability, and cost–benefit ratios.
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(This article belongs to the Section Sustainable Agriculture)
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Urban Vulnerability under the Extreme High Temperatures in the Chengdu-Chongqing Area, Western China
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Zhaoqi Yin, Weipeng Li, Zhongsheng Chen, Li Zhu and Panheng Shui
Sustainability 2024, 16(11), 4749; https://doi.org/10.3390/su16114749 (registering DOI) - 3 Jun 2024
Abstract
The frequent occurrence of extreme high-temperature events in the summer under global climate change poses a serious threat to Chinese society. An urban vulnerability evaluation system for counties in the Chengdu-Chongqing Area was constructed to calculate the urban vulnerability and distribution characteristics of
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The frequent occurrence of extreme high-temperature events in the summer under global climate change poses a serious threat to Chinese society. An urban vulnerability evaluation system for counties in the Chengdu-Chongqing Area was constructed to calculate the urban vulnerability and distribution characteristics of each district. In this study, a vulnerability-contribution model was used to analyze the types of urban vulnerability in the Chengdu-Chongqing Area. Additionally, combined with the optimal parameter geographic detector (OPGD) model, the main influencing factors and interactions of urban vulnerability were explored. The results show that: ① The urban vulnerability of the Chengdu-Chongqing Area is high in the east and low in the west, with vulnerability degree mostly below the medium degree. ② Exposure contributes more than 50% to severe and general urban vulnerability in the region, while adaptability contributes the highest proportion to mild urban vulnerability, reaching 47.53%. ③ From the factor perspective, the impact ratio of high-temperature days on urban vulnerability is 39.1%, and the interaction between various meteorological factors and social factors produces an enhancement effect, with the highest interaction q-value reaching 0.7863.
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(This article belongs to the Topic Climate Change Impacts and Adaptation: Interdisciplinary Perspectives)
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Does Tax Sharing Matter for Export Quality Upgrading? Evidence from China
by
Kunpeng Zhang, Yibei Guo and Xiaotian Hu
Sustainability 2024, 16(11), 4748; https://doi.org/10.3390/su16114748 (registering DOI) - 3 Jun 2024
Abstract
Tax policy is critical for business operations and export decisions. However, the relationship between tax sharing and export has been less frequently discussed. This paper explicitly examines the underexplored tax-sharing system’s effect on manufacturing exporters’ export quality and develops four hypotheses. We use
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Tax policy is critical for business operations and export decisions. However, the relationship between tax sharing and export has been less frequently discussed. This paper explicitly examines the underexplored tax-sharing system’s effect on manufacturing exporters’ export quality and develops four hypotheses. We use data on Chinese manufacturing exporters and prefecture-level tax-sharing from 2008 to 2013 and employ an instrumental variable approach to alleviate the endogeneity problem. The empirical evidence supports our hypotheses. We find that an increase in the prefecture-level government tax-sharing ratio significantly reduces export product quality of firms. This quality effect can occur through channels, including tax burden effect, production scale effect, and innovation effect. Moreover, more productive firms and those operated in cities with stronger intellectual property protection can face a smaller quality-reducing effect. Our findings offer policy implications for improving China’s modernized tax system and trade upgrading. Policymakers should recalibrate the tax-sharing system to reduce the tax burden on manufacturing exporters, particularly for innovative and high-productivity firms, and bolster intellectual property rights to enhance export quality and support China’s trade and economic modernization.
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(This article belongs to the Special Issue Advanced Technologies in Smart Manufacturing and Product Innovation)
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The Role of Smart Human Resource Management in the Relationship between Technology Application and Innovation Performance
by
Elham Hmoud Al-Faouri, Yazan Abu Huson, Nader Mohammad Aljawarneh and Thikra jamil Alqmool
Sustainability 2024, 16(11), 4747; https://doi.org/10.3390/su16114747 (registering DOI) - 2 Jun 2024
Abstract
This study investigates the intricate relationships between technology application, smart human resource management (SHRM), and innovation performance within the Jordanian telecom industry. Employing a quantitative research methodology, data were collected from employees of telecommunications firms in Jordan. The results illuminate significant positive associations
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This study investigates the intricate relationships between technology application, smart human resource management (SHRM), and innovation performance within the Jordanian telecom industry. Employing a quantitative research methodology, data were collected from employees of telecommunications firms in Jordan. The results illuminate significant positive associations between technology application, SHRM, and innovation performance, elucidating the pivotal roles of technology and HRM strategies in fostering innovation and bolstering organizational success. Practical implications of the findings advocate for substantial investments in cutting-edge technologies, the integration of intelligent HRM practices, and the prioritization of continuous learning and development initiatives to nurture an innovative workforce. This research contributes to a deeper comprehension of innovation dynamics within the telecommunications sector and furnishes valuable insights for practitioners striving to elevate innovation capabilities within their respective organizations.
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(This article belongs to the Section Economic and Business Aspects of Sustainability)
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Tourist Values and Well-Being in Rural Tourism: Insights from Biodiversity Protection and Rational Automobile Use in Al-Ahsa Oasis, Saudi Arabia
by
Abdulrahman Mubarark AlAli, Thowayeb H. Hassan and Mostafa A. Abdelmoaty
Sustainability 2024, 16(11), 4746; https://doi.org/10.3390/su16114746 (registering DOI) - 2 Jun 2024
Abstract
In response to the escalating significance of sustainable tourism and the growing global concern for environmental conservation, the current study sought to investigate the intricate dynamics of two pro-environmental behaviors (biodiversity protection and rational car use), personal values (altruistic, biospheric, and egoistic), farm
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In response to the escalating significance of sustainable tourism and the growing global concern for environmental conservation, the current study sought to investigate the intricate dynamics of two pro-environmental behaviors (biodiversity protection and rational car use), personal values (altruistic, biospheric, and egoistic), farm tourists’ well-being, and environmental and activity attachment among farm tourists in the Al-Ahsa region of Saudi Arabia. Employing an online survey, our methodology involved partial least structural equation modeling to unravel the complex relationships among these variables. Based on responses retrieved from 309 farm tourists, results revealed that biodiversity protection significantly influenced altruistic values and the well-being of farm tourists. Additionally, rational automobile use exerted positive impacts on both altruistic and biospheric values. These results underscore the intricate dynamics shaping tourists’ attitudes and experiences in the Al-Ahsa region. The study contributes to the broader understanding of sustainable tourism practices, emphasizing the need for tailored interventions. The positive associations identified highlight the potential for farm tourism experiences to enhance both pro-environmental values and the well-being of tourists, thus offering valuable insights for future research and sustainable tourism initiatives.
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(This article belongs to the Special Issue Enhancing Sustainable Rural Development through Tourism Strategies)
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Challenges and Remediation Strategies for Per- and Polyfluoroalkyl Substances (PFAS) Contamination in Composting
by
Sali Khair Biek, Leadin S. Khudur and Andrew S. Ball
Sustainability 2024, 16(11), 4745; https://doi.org/10.3390/su16114745 (registering DOI) - 2 Jun 2024
Abstract
Abstract: Municipal solid waste (MSW) is projected to rise to 3.4 billion tonnes by 2050, with only 33% undergoing environmentally friendly management practices. Achieving a circular economy involves sustainable approaches, among which diverting waste from landfills to composting plays a crucial role.
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Abstract: Municipal solid waste (MSW) is projected to rise to 3.4 billion tonnes by 2050, with only 33% undergoing environmentally friendly management practices. Achieving a circular economy involves sustainable approaches, among which diverting waste from landfills to composting plays a crucial role. However, many of the products society uses and discards in MSW daily contain per- and polyfluoroalkyl substances (PFAS), raising concerns that composts may inadvertently introduce PFAS into the environment, posing a significant challenge to waste management and environmental sustainability. PFAS have been detected in compost at concentrations ranging between 1.26–11.84 µg/kg. Composts are therefore a source of PFAS contamination, posing risks to human and ecosystem health. Impactful technologies are therefore required for PFAS remediation during the composting process. This review examines the composting process as a sustainable organic waste management technology, examining the various systems employed, compost quality, and uses, particularly emphasising the challenge posed by PFAS contamination. The review provides novel insights into possible PFAS remediation technologies. A comprehensive understanding of PFAS origin, fate, and transformation during the composting process is lacking, creating substantial knowledge gaps regarding the inputs processes contributing most to PFAS accumulation in the final product. Addressing these gaps in future studies is crucial for minimising PFAS discharge into the environment and developing an effective remediation approach. This review highlights the urgent need for innovative solutions to mitigate PFAS contamination in compost and the importance of advancing research and technology to achieve sustainable waste management objectives.
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(This article belongs to the Section Waste and Recycling)
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