Sustainability

21 pages, 1907 KB

Open AccessArticle

Promoting Sustainable Manufacturing Growth Through Foreign Direct Investment and Foreign Trade: Evidence from China’s 28 Sub-Industries

by Xiaomei Li and Radziah Adam

Sustainability 2025, 17(20), 9059; https://doi.org/10.3390/su17209059 (registering DOI) - 13 Oct 2025

Abstract

This paper systematically explores the dynamic effects of foreign direct investment (FDI), foreign trade, technological innovation, and human capital across China’s 28 sub-industries. The results show that FDI and foreign trade significantly promote manufacturing output growth, while technological innovation and human capital have [...] Read more.

This paper systematically explores the dynamic effects of foreign direct investment (FDI), foreign trade, technological innovation, and human capital across China’s 28 sub-industries. The results show that FDI and foreign trade significantly promote manufacturing output growth, while technological innovation and human capital have a more sensitive response to growth fluctuations in the short term. The Granger causality test shows that FDI, technological innovation, and human capital all have strong predictive power and can effectively predict the future trend of manufacturing output. The impulse response function and variance decomposition analysis further reveal the key role of these factors in promoting the manufacturing industry’s long-term sustainable development. Based on the above findings, this paper suggests that local government should continue to optimize the structure and quality of attracting foreign capital, increase the support for technology research and development and intelligent manufacturing, enhance the added value of export products, and strengthen human capital investment so as to promote China’s manufacturing industry’s high-quality and sustainable development and provide reference for other developing countries’ manufacturing development. Full article

(This article belongs to the Special Issue Sustainable Management: Economic and Business Development)

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29 pages, 2152 KB

Open AccessArticle

Mitigating Transport-Based CO₂ Emissions in Landlocked Countries: The Role of Economic Growth, Trade Openness, Freight Transportation and Renewable Energy Consumption

by Oumayma Messaoudi, Fedy Ouni and Kaies Samet

Sustainability 2025, 17(20), 9058; https://doi.org/10.3390/su17209058 (registering DOI) - 13 Oct 2025

Abstract

The transportation sector plays a pivotal role in economic development but is also a major contributor to environmental degradation due to its reliance on fossil fuels. This study explores the relationship between transport-related CO₂ emissions, economic growth, road and rail freight transport, [...] Read more.

The transportation sector plays a pivotal role in economic development but is also a major contributor to environmental degradation due to its reliance on fossil fuels. This study explores the relationship between transport-related CO₂ emissions, economic growth, road and rail freight transport, industry, trade openness, fossil fuel consumption, financial development, and renewable energy in ten landlocked countries from 1990 to 2022. Using panel cointegration tests and PMG-ARDL techniques, the findings reveal a bidirectional causality between CO₂ emissions, road freight, financial development, and industry. Road freight transport significantly boosts economic growth but also intensifies emissions, while renewable energy effectively mitigates transport-related CO₂. The results emphasize the need for policymakers to balance economic advancement with sustainable energy and emission reduction strategies. Achieving economic-energy sustainability is essential for fostering a green and clean environment without compromising growth. Full article

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22 pages, 1786 KB

Open AccessArticle

University Students’ Perceptions on Climate Change Awareness and Sustainable Environments Through an Unsupervised Clustering Approach

by Deniz Karaelmas, Mükerrem Bahar Başkır, Kübra Tekdamar, Canan Cengiz and Bülent Cengiz

Sustainability 2025, 17(20), 9057; https://doi.org/10.3390/su17209057 (registering DOI) - 13 Oct 2025

Abstract

The main objective of this study is to determine the knowledge and awareness levels of climate change among preparatory class students at Zonguldak Bülent Ecevit University in the Western Black Sea Region of Türkiye using an unsupervised clustering approach. Within this scope, a [...] Read more.

The main objective of this study is to determine the knowledge and awareness levels of climate change among preparatory class students at Zonguldak Bülent Ecevit University in the Western Black Sea Region of Türkiye using an unsupervised clustering approach. Within this scope, a survey was administered to university students (n = 280). Participant scores for the survey sections containing five-point Likert-type questions on climate change awareness were calculated using min–max normalization. The normalized data was then processed using the k-means algorithm, a well-known technique in unsupervised machine learning. This resulted in a classification (clustering) related to climate change awareness. The number of clusters was determined using the Silhouette index. Three clusters identified using k-means and Silhouette index (

S \approx 0.55)

revealed the knowledge and application levels of student groups regarding climate change awareness. As a result of clustering, it was determined that Cluster-3 students (n = 134, 47.9%), defined as having a high level of knowledge and application, had a higher impact value in their overall assessments of green space-focused issues related to climate change awareness compared to the overall assessments of students in other clusters. Some notable findings concerning the attitudes of Cluster-3 students highlight climate change awareness-related practices. These include minimizing water consumption to levels necessary for ecosystem water management (mean = 95.7, std. deviation = 10.9) and exercising controlled, sustainable daily energy use to alleviate pressure on green spaces (mean = 94.4, std. deviation = 12.5). This study offers practical insights for policymakers, educators, and institutions, emphasizing the need to enhance climate education and to promote the active involvement of younger generations in shaping sustainable environments. Full article

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24 pages, 6483 KB

Open AccessArticle

Evaluating Eutrophication and Water Clarity on Lake Victoria’s Ugandan Coast Using Landsat Data

by Moses Kiwanuka, Randy Leslie, Anthony Gidudu, John Peter Obubu, Assefa Melesse and Maruthi Sridhar Balaji Bhaskar

Sustainability 2025, 17(20), 9056; https://doi.org/10.3390/su17209056 (registering DOI) - 13 Oct 2025

Abstract

Satellite remote sensing has emerged as a reliable and cost-effective approach for monitoring inland water quality, offering spatial and temporal advantages over traditional in situ methods. Lake Victoria, the largest tropical lake and a critical freshwater resource for East Africa, faces increasing eutrophication [...] Read more.

Satellite remote sensing has emerged as a reliable and cost-effective approach for monitoring inland water quality, offering spatial and temporal advantages over traditional in situ methods. Lake Victoria, the largest tropical lake and a critical freshwater resource for East Africa, faces increasing eutrophication driven by nutrient inflows from agriculture, urbanization, and industrial activities. This study assessed the spatiotemporal dynamics of water quality along Uganda’s Lake Victoria coast by integrating field measurements (2014–2024) with Landsat 8/9 imagery. Chlorophyll-a, a proxy for algal blooms, and Secchi disk depth, an indicator of water clarity, were selected as key parameters. Cloud-free satellite images were processed using the Dark Object Subtraction method, and spectral reflectance values were correlated with field data. Linear regression models from single bands and band ratios showed strong performance, with adjusted R² values of up to 0.88. When tested on unseen data, the models achieved R² values above 0.70, confirming robust predictive ability. Results revealed high algal concentrations for nearshore and clearer offshore waters. These models provide an efficient framework for monitoring eutrophication, guiding restoration priorities, and supporting sustainable water management in Lake Victoria. Full article

(This article belongs to the Special Issue Sustainable Future of Ecohydrology: Climate Change and Land Use)

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25 pages, 920 KB

Open AccessArticle

Non-Food Geographical Indications in the European Union: Comparative Indicators, Cluster Typologies, and Policy Scenarios Under Regulation (EU) 2023/2411

by Giovanni Peira, Sergio Arnoldi and Alessandro Bonadonna

Sustainability 2025, 17(20), 9055; https://doi.org/10.3390/su17209055 (registering DOI) - 13 Oct 2025

Abstract

Non-food geographical indications (GIs) are emerging as strategic policy instruments in the European Union after Regulation (EU) 2023/2411 extended protection to craft and industrial products. While the literature on agri-food GIs is extensive, empirical and comparative evidence on non-food GIs remains scarce and [...] Read more.

Non-food geographical indications (GIs) are emerging as strategic policy instruments in the European Union after Regulation (EU) 2023/2411 extended protection to craft and industrial products. While the literature on agri-food GIs is extensive, empirical and comparative evidence on non-food GIs remains scarce and fragmented. This study addresses this gap by constructing a harmonised dataset, combining 132 registered and 380 potential non-food GIs identified by EUIPO (512 in total across the EU). Using secondary institutional data, descriptive and comparative statistics, and a hierarchical clustering (Ward, squared Euclidean distance) on normalised indicators total GIs, GIs per million inhabitants (GI/POP), and GIs per € billion of GDP (GI/GDP), the analysis identifies three country typologies differing by scale and intensity. Results reveal a strong geographical concentration in Southern Europe but also unexpectedly high intensity in smaller or mid-sized economies such as Portugal, Cyprus, and Slovenia. A forward-looking scenario analysis based on Cost of Non-Europe (CoNE) estimates suggests that the full implementation of the new Regulation could generate 284,000–338,000 new jobs and € 37–50 billion in additional intra-EU trade. The study contributes to EU policy debates by introducing comparative indicators (GI/POP, GI/GDP) as monitoring tools for evidence-based policymaking and by highlighting the role of non-food GIs as hybrid institutions connecting industrial competitiveness, cultural identity, and sustainability transitions. Full article

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17 pages, 1732 KB

Open AccessArticle

Construction and Variation Analysis of Comprehensive Climate Indicators for Winter Wheat in Beijing–Tianjin–Hebei Region, China

by Chang Liu, Jie Hu, Lei Wang, Ming Li, Wenyi Xie, Yining Zhu, Ruijie Che, Lianxi Wang, Jing Hua and Jian Wang

Sustainability 2025, 17(20), 9054; https://doi.org/10.3390/su17209054 (registering DOI) - 13 Oct 2025

Abstract

Under the global climate change, variations in climatic elements such as temperature, precipitation, and sunshine duration significantly impact the growth, development, and yield formation of winter wheat. A precise understanding of the impact of climate change on winter wheat growth and the scientific [...] Read more.

Under the global climate change, variations in climatic elements such as temperature, precipitation, and sunshine duration significantly impact the growth, development, and yield formation of winter wheat. A precise understanding of the impact of climate change on winter wheat growth and the scientific use of meteorological resources are crucial for ensuring food security, optimizing agricultural planting structures and agricultural sustainability. This study uses statistical methods and focuses on the Beijing–Tianjin–Hebei region, utilizing data from 25 meteorological stations from 1961 to 2010 and winter wheat yield data from 1978 to 2010. Twelve refined indicators encompassing temperature, precipitation, and sunshine duration were constructed. Path analysis was employed to determine their weights, establishing a comprehensive climate indicator model. Results indicate: Temperature indicators in the region show an upward trend, with accumulated temperature of the whole growth period increasing at a rate of 61.1 °C·d/10a. Precipitation indicators reveal precipitation of the whole growth period rising at 3.9 mm/10a and pre-winter precipitation increasing at 4.2 mm/10a. Sunshine duration exhibits a declining trend, decreasing at 72.7 h/10a during the whole growth period. Comprehensive climate indicators decrease from south to north, with the southwest region exhibiting the highest tendency rate (18.41), while the central and southern regions show greater variability. This study provides scientific basis for optimizing winter wheat planting patterns and rational utilization of climate resources in the Beijing–Tianjin–Hebei region. It recommends prioritizing cultivation in western southern Hebei and improving water conditions in the central and northern areas through irrigation technology to support sustainable crop production. Full article

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17 pages, 3333 KB

Open AccessArticle

Resilient Frequency Control for Renewable-Energy Distributed Systems Considering Demand-Side Resources

by Jijiang Gu, Changzheng Shao, Ling Li, Hanxin Zhang, Chengrong Lin and Yangjun Zhou

Sustainability 2025, 17(20), 9053; https://doi.org/10.3390/su17209053 (registering DOI) - 13 Oct 2025

Abstract

Extreme natural disasters can force microgrids into islanded operation, where low system inertia and asynchronous, time-varying communication delays present severe challenges to frequency stability. These challenges threaten not only short-term reliability but also the sustainable operation of renewable-dominated energy systems. Existing frequency control [...] Read more.

Extreme natural disasters can force microgrids into islanded operation, where low system inertia and asynchronous, time-varying communication delays present severe challenges to frequency stability. These challenges threaten not only short-term reliability but also the sustainable operation of renewable-dominated energy systems. Existing frequency control methods are often unable to robustly handle heterogeneous delays, thereby limiting the resilience of power systems with high shares of renewables. To address this issue, we propose a parametric Riccati equation-based frequency control method that adaptively adjusts control parameters to balance system robustness and optimality under asynchronous delays. Controller stability is guaranteed by Barbalat’s lemma. The main contributions include: (i) developing a microgrid frequency control model that incorporates asynchronous delays, (ii) designing a delay-aware controller using the parametric Riccati equation, and (iii) validating its effectiveness on a modified New England 39-bus system. Simulation results confirm that the proposed method enhances frequency stability under disaster-induced islanding scenarios. By ensuring robust and reliable operation of renewable-rich power systems, the proposed approach contributes to the sustainable integration of renewable energy, reduces blackout risks, and supports long-term environmental and socio-economic sustainability goals. Full article

(This article belongs to the Special Issue Advances in Stability Control, Optimal Operation and Modeling Analysis of Power System with High-Level Renewable Energy)

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26 pages, 1018 KB

Open AccessArticle

The Effect of Students’ Material Status and Zoom Fatigue on Their Perception of Emergency Remote Teaching Satisfaction and Remote Teaching Sustainability from the Perspective of Education Faculty Students in Serbia

by Jelena R. Petrović, Ivko A. Nikolić and Uroš V. Šuvaković

Sustainability 2025, 17(20), 9052; https://doi.org/10.3390/su17209052 (registering DOI) - 13 Oct 2025

Abstract

The introduction of emergency remote teaching in university education during the COVID-19 pandemic was not a matter of choice, but an attempt to make education sustainable in times of crisis. However, some research, even before the COVID-19 pandemic, showed that digital inequality caused [...] Read more.

The introduction of emergency remote teaching in university education during the COVID-19 pandemic was not a matter of choice, but an attempt to make education sustainable in times of crisis. However, some research, even before the COVID-19 pandemic, showed that digital inequality caused by the unequal material status of students could have an impact on remote teaching. Also, before the COVID-19 pandemic, some researchers pointed out a new phenomenon, Zoom fatigue, as an accompanying phenomenon of video conferences with potential harm to the physical and mental health of consumers. The aim of this study is to examine the possibility that material status and Zoom fatigue may play the role of a moderator in the attitude of students towards ERT. The sample included 148 students attending education faculties in Serbia. The data obtained were frequencies, percentages, descriptive statistics, χ² test results, t test for independent samples, ANOVA, and linear regression.The results showed that 13% of students find the lack of financial funds for the purchase of an Internet connection with high-speed data flow to be an aggravating circumstance. Moreover, it transpires that Zoom fatigue may play the role of a moderator in students’ attitude towards ERT, particularly concerning the possibility of introducing remote teaching as a permanent form of teaching;in addition, certain aspects of students’ material status, primarily monthly household income, were a significant predictor of Zoom fatigue level on the ZEF scale. Full article

(This article belongs to the Special Issue Digital and Sustainable Transformation of Education: Technology Enhanced-Teaching, Learning and Social Inclusion—2nd Edition)

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26 pages, 490 KB

Open AccessArticle

From General Intelligence to Sustainable Adaptation: A Critical Review of Large-Scale AI Empowering People’s Livelihood

by Jiayi Li and Peiying Zhang

Sustainability 2025, 17(20), 9051; https://doi.org/10.3390/su17209051 (registering DOI) - 13 Oct 2025

Abstract

The advent of large-scale AI models (LAMs) marks a pivotal shift in technological innovation with profound societal implications. While demonstrating unprecedented potential to enhance human well-being by fostering efficiency and accessibility in critical domains like medicine, agriculture, and education, their rapid deployment presents [...] Read more.

The advent of large-scale AI models (LAMs) marks a pivotal shift in technological innovation with profound societal implications. While demonstrating unprecedented potential to enhance human well-being by fostering efficiency and accessibility in critical domains like medicine, agriculture, and education, their rapid deployment presents a double-edged sword. This progress is accompanied by significant, often under-examined, sustainability costs, including large environmental footprints, the risk of exacerbating social inequities via algorithmic bias, and challenges to economic fairness. This paper provides a balanced and critical review of LAMs’ applications across five key livelihood domains, viewed through the lens of sustainability science. We systematically analyze the inherent trade-offs between their socio-economic benefits and their environmental and social costs. We conclude by arguing for a paradigm shift towards ‘Sustainable AI’ and provide actionable, multi-stakeholder recommendations for aligning artificial intelligence with the long-term goals of a more equitable, resilient, and environmentally responsible world. Full article

(This article belongs to the Topic Recent Advances in Security, Privacy, and Trust)

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23 pages, 836 KB

Open AccessArticle

Decarbonizing a Sailboat Using Solar Panels, Wind Turbines, and Hydro-Generation for Zero-Emission Propulsion

by Hamdi Sena Nomak and İsmail Çiçek

Sustainability 2025, 17(20), 9050; https://doi.org/10.3390/su17209050 (registering DOI) - 13 Oct 2025

Abstract

The decarbonization of maritime transport has primarily targeted large vessels, leaving small craft largely dependent on fossil fuel despite their inherent use of wind propulsion. This study addresses that gap by designing and simulating a zero-emission propulsion system for a 12.5 m sailing [...] Read more.

The decarbonization of maritime transport has primarily targeted large vessels, leaving small craft largely dependent on fossil fuel despite their inherent use of wind propulsion. This study addresses that gap by designing and simulating a zero-emission propulsion system for a 12.5 m sailing yacht based on integrated renewable energy. The retrofit replaces the diesel engine with an electric drivetrain supported by static solar panels and wind turbines, as well as dynamic sources, including hydro-generators and a regenerative propeller. In addition to performance under typical weather profiles, we conducted a lifecycle environmental impact estimation and evaluated system resilience under low renewable input. Simulations used real mid-latitude meteorological data to assess operational and environmental sustainability. The results show that during two representative 24 h voyages, propulsion and hotel loads were sustained solely by onboard renewables, with battery state of charge remaining above 28–46%. In an emergency calm scenario, the yacht motored for four hours at 5–6 knots using only stored energy, with solar input extending range. The findings demonstrate that integrated multi-source renewables can provide complete energy autonomy for sailing yachts. The approach illustrates practical feasibility under real conditions, scalability to eco-tour boats and ferries, and alignment with international decarbonization targets. Full article

(This article belongs to the Special Issue Sustainable Marine Engineering and Efficient Marine Transportation of Energy)

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21 pages, 10338 KB

Open AccessArticle

Sustainable Mining of Open-Pit Coal Mines: A Study on Intelligent Strip Division Technology Based on Multi-Source Data Fusion

by Shuaikang Lv, Ruixin Zhang, Yabin Tao, Zijie Meng, Sibo Wang and Zhigao Liu

Sustainability 2025, 17(20), 9049; https://doi.org/10.3390/su17209049 (registering DOI) - 13 Oct 2025

Abstract

The rational delineation of open-pit mining areas constitutes the core foundation for achieving safe, efficient, economical, and sustainable mining operations. The quality of this decision-making directly impacts the economic benefits experienced throughout the mine’s entire lifecycle and the efficiency of resource recovery. Traditional [...] Read more.

The rational delineation of open-pit mining areas constitutes the core foundation for achieving safe, efficient, economical, and sustainable mining operations. The quality of this decision-making directly impacts the economic benefits experienced throughout the mine’s entire lifecycle and the efficiency of resource recovery. Traditional open-pit mining area delineation relies on an experience-driven manual process that is inefficient and incapable of real-time dynamic data optimization. Thus, there is an urgent need to establish an intelligent decision-making model integrating multi-source data and multi-objective optimization. To this end, this study proposes an intelligent mining area division algorithm. First, a geological complexity quantification model is constructed, incorporating innovative adaptive discretisation resolution technology to achieve precise quantification of coal seam distribution. Second, based on the quantified stripping-to-mining ratio within grids, a block-growing algorithm generates block grids, ensuring uniformity of the stripping-to-mining ratio within each block. Subsequently, a matrix of primary directional variations in the stripping-to-mining ratio is constructed to determine the principal orientation for merging blocks into mining areas. Finally, intelligent open-pit mining area delineation is achieved by comprehensively considering factors such as the principal direction of mining areas, geological conditions, boundary shapes, and economic scale. Practical validation was conducted using the Shitoumei No. 1 Open-Pit Coal Mine in Xinjiang as a case study in engineering. Engineering practice demonstrates that adopting this methodology transforms mining area delineation from an experience-driven to a data-driven approach, significantly enhancing delineation efficiency. Manual simulation of a single scheme previously required approximately 15 days. Applying the methodology proposed herein reduces this to just 0.5 days per scheme, representing a 96% increase in efficiency. Design costs were reduced by approximately CNY 190,000 per iteration. Crucially, the intelligently recommended scheme matched the original design, validating the algorithm’s reliability. This research provides crucial support for theoretical and technological innovation in intelligent open-pit coal mining design, offering technical underpinnings for the sustainable development of open-pit coal mines. Full article

(This article belongs to the Collection Sustainable Development of Coal Based Energy: Technology, Environment, Humanities, Economy, and Education)

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17 pages, 1738 KB

Open AccessArticle

Plant-Growth-Promoting Rhizobacteria as a Sustainable Strategy for Enhancing Quinoa Resilience to Salt Stress in Arid Regions

by Fahad N. Al-Barakaha and Abdulaziz G. Alghamdi

Sustainability 2025, 17(20), 9048; https://doi.org/10.3390/su17209048 (registering DOI) - 13 Oct 2025

Abstract

Soil salinity and water scarcity are major challenges limiting agricultural productivity in arid and semi-arid regions. Quinoa (a climate-resilient crop) offers potential for sustainable food production under these harsh conditions; however, its growth and yield are often constrained by salt and water stress. [...] Read more.

Soil salinity and water scarcity are major challenges limiting agricultural productivity in arid and semi-arid regions. Quinoa (a climate-resilient crop) offers potential for sustainable food production under these harsh conditions; however, its growth and yield are often constrained by salt and water stress. This study evaluated the role of plant-growth-promoting rhizobacteria (PGPR) in enhancing Chenopodium quinoa Willd performance under deficit irrigation (DI) with saline water. A greenhouse pot experiment was conducted with four irrigation levels (40%, 60%, 80%, and 100% of the growth water requirement, GWR) and two water qualities (fresh water, EC = 0.8 dS m⁻¹; and saline water, EC = 6.0 dS m⁻¹), each tested with and without PGPR inoculation. The results showed that PGPR application significantly (p < 0.05) improved quinoa tolerance to salinity, leading to higher biomass, yield, and crop water productivity (CWP) under saline irrigation. Yield reductions were most severe at 40% GWR (53.9% and 82.6% under saline and fresh water, respectively), but PGPR inoculation mitigated yield losses, with increases of 83.3% and 130.8% under 40% and 100% GWR saline irrigation, respectively. Notably, PGPR did not show a clear effect with freshwater irrigation. In addition, inoculated plants exhibited improved nutrient uptake and reduced heavy metal accumulation. Overall, PGPR demonstrated strong potential to enhance salinity resilience and water-use efficiency in quinoa. Future studies should extend these findings under field conditions and investigate the long-term impacts of PGPR on sustainable crop production in saline- and water-limited environments. Full article

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24 pages, 441 KB

Open AccessArticle

Digital Government Construction and Common Prosperity in China: Effect and Transmission Channel

by Bin Xiong, Baocheng Yu and Yalan Tang

Sustainability 2025, 17(20), 9047; https://doi.org/10.3390/su17209047 (registering DOI) - 13 Oct 2025

Abstract

How to achieve common prosperity has become the key to enhancing residents’ well-being in digital government construction (DG), which is particularly important for developing countries with relatively large income gaps. Using Chinese provincial panel data from 2018 to 2023, this study employs the [...] Read more.

How to achieve common prosperity has become the key to enhancing residents’ well-being in digital government construction (DG), which is particularly important for developing countries with relatively large income gaps. Using Chinese provincial panel data from 2018 to 2023, this study employs the entropy weight method and two-way fixed effects models to empirically examine the nonlinear impact of digital government development on common prosperity. This study has found that DG has a significant U-shaped impact on common prosperity, which first inhibits and then promotes. This effect operates primarily through improving digital inclusive finance and increasing education expenditure. Regional heterogeneity analysis indicates that the U-shaped relationship is more significant in the eastern region. From a single dimension of DG, service supply capacity and service intelligence capacity have a significant U-shaped impact on common prosperity. This study enriches the theory of the relationship between DG and common prosperity, providing policy references for promoting common prosperity and sustainable development. Full article

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18 pages, 2022 KB

Open AccessArticle

Research on the Spatiotemporal Effects of Water Temperature in the Construction of Cascade Dams on the Yangtze River Main Stream Based on Optimized CNN-LSTM Attention Model

by Shanghong Zhang, Hao Wang, Ruicheng Zhang, Hua Zhang and Yang Zhou

Sustainability 2025, 17(20), 9046; https://doi.org/10.3390/su17209046 (registering DOI) - 13 Oct 2025

Abstract

Hydrothermal conditions are a key indicator influencing the evolution of aquatic ecosystems, closely affecting the physical, chemical, and biological properties of water bodies. The construction of cascaded dams on the main stem of the Yangtze River has altered the natural water temperature regime, [...] Read more.

Hydrothermal conditions are a key indicator influencing the evolution of aquatic ecosystems, closely affecting the physical, chemical, and biological properties of water bodies. The construction of cascaded dams on the main stem of the Yangtze River has altered the natural water temperature regime, impacting the hydrothermal status of the water. Utilizing multi-source remote sensing data from Google Earth Engine to invert river surface water temperatures, a parameter-optimized CNN-LSTM-Attention hybrid interpretable water temperature prediction model was constructed. The model demonstrated credible accuracy. Based on the inversion results, the study revealed the spatiotemporal evolution characteristics of water temperature in the main stem of the Yangtze River before and after cascaded dam construction in the lower Jinsha River region and the Three Gorges Reservoir area. The results found that after the construction of the Three Gorges Dam, the annual average water temperature increased significantly by 0.813 °C. The “cold water stagnation effect” induced by cascaded development caused the water temperature amplitude to increase from 8.96 °C to 10.6 °C. Furthermore, the regulating effect of tributary confluence exhibited significant differences. For instance, colder tributaries like the Yalong River reduced the main stem water temperature, while warmer tributaries like the Jialing River, conversely, increased the main stem temperature. The construction of cascaded dams led to distinct variation characteristics in the areas downstream of the dams within the reservoir regions, where tributary inflows caused corresponding changes in the main stem water temperature. This study elucidates the long-term spatiotemporal variation characteristics of water temperature in the main stem of the Yangtze River. The model prediction results can assist in constructing an early warning indicator system for water temperature changes, providing reliable data support for promoting water environment sustainability and ecological civilization construction in the river basin. Full article

(This article belongs to the Special Issue Leveraging the Multidisciplinary Insights to Solve Watershed Management Problems)

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16 pages, 1026 KB

Open AccessArticle

Multi-Criteria Evaluation of Bioavailable Trace Elements in Fine and Coarse Particulate Matter: Implications for Sustainable Air-Quality Management and Health Risk Assessment

by Elwira Zajusz-Zubek and Zygmunt Korban

Sustainability 2025, 17(20), 9045; https://doi.org/10.3390/su17209045 (registering DOI) - 13 Oct 2025

Abstract

Bioavailable fractions of particulate-bound trace elements are key determinants of inhalation toxicity, yet air-quality assessments typically rely on total metal concentrations, which may underestimate health risks. This study integrates the exchangeable (F1) and reducible (F2) fractions of trace elements in fine (PM_2.5 [...] Read more.

Bioavailable fractions of particulate-bound trace elements are key determinants of inhalation toxicity, yet air-quality assessments typically rely on total metal concentrations, which may underestimate health risks. This study integrates the exchangeable (F1) and reducible (F2) fractions of trace elements in fine (PM_2.5) and coarse (PM₁₀) particulate matter with multi-criteria decision-making (TOPSIS) and similarity-based classification (Czekanowski’s method). Archival weekly-integrated samples from the summer season were collected at eight industrially influenced sites in southern Poland. Sequential extraction (F1–F2) and ICP-MS were applied to quantify concentrations of cadmium, cobalt, chromium, nickel, and lead in PM_2.5 and PM₁₀. Aggregated hazard values were then derived with TOPSIS, and site similarity was explored using Czekanowski’s reordered distance matrices. Regulatory targets for cadmium and nickel, and the limit for lead in PM₁₀ were not exceeded, but F1/F2 profiles revealed pronounced site-to-site differences in potential mobility that were not evident from total concentrations. Rankings were consistent across size fractions, with site P₁ exhibiting the lowest hazard indices and P₈ the highest, while mid-rank sites formed reproducible similarity clusters. The proposed chemical-fractionation and multivariate framework provides a reproducible screening tool for multi-element exposure, complementing compliance checks and supporting prioritisation of sites for targeted investigation and environmental management. In the sustainability context, bioavailability-based indicators strengthen air-quality assessment by linking monitoring data with health-relevant and cost-effective management strategies, supporting efficient resource allocation and reducing exposure in vulnerable populations. Full article

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26 pages, 1339 KB

Open AccessArticle

Do Physical and Transition Climate Risks Drive the Volatility and Dynamic Correlations Between Fossil Energy Markets and Stocks Prices of Clean Energy?

by Ying Zhang, Weifeng Li and Li Yang

Sustainability 2025, 17(20), 9044; https://doi.org/10.3390/su17209044 (registering DOI) - 13 Oct 2025

Abstract

Climate risks are one of the major challenges facing sustainable development. This study examines how physical and transition climate risks influence the volatility and correlation of fossil energy futures and clean energy stock indices, using a mixed-frequency modeling framework. Taking the Paris Agreement [...] Read more.

Climate risks are one of the major challenges facing sustainable development. This study examines how physical and transition climate risks influence the volatility and correlation of fossil energy futures and clean energy stock indices, using a mixed-frequency modeling framework. Taking the Paris Agreement as the starting point for the global energy transition, we aim to compare the impacts of climate risks on various fossil energy assets and clean energy assets and investigate how the dynamic linkages between clean energy and fossil energy assets have evolved under the influence of climate risks. The results show that climate risks have increased the volatility of fossil energy and clean energy assets to varying degrees. Correlation patterns vary by energy type: crude oil futures and clean energy indices exhibit a decoupling trend under climate risks, while natural gas futures show a more consistent, positive linkage. These findings not only provide useful guidance for investors in formulating more effective strategies under increasing climate risks but also offer policymakers valuable insights into designing optimal approaches to balance decarbonization objectives with energy security. Full article

(This article belongs to the Topic Climate Change Impacts and Adaptation: Interdisciplinary Perspectives, 2nd Edition)

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19 pages, 935 KB

Open AccessArticle

Risk Aversion Mediates the Impact of Environmental Change Perceptions on Farmers’ Livelihood Strategies: A PLS-SEM Study

by Guokui Wang, Yangyang Li and Guoqin Wu

Sustainability 2025, 17(20), 9043; https://doi.org/10.3390/su17209043 (registering DOI) - 13 Oct 2025

Abstract

Farmers’ perceptions of environmental change are a key trigger for livelihood behaviors. However, it remains unclear how these perceptions become specific livelihood strategies through internal psychological processes. To address this, this study constructs an analytical framework. It integrates multidimensional environmental perceptions, risk aversion, [...] Read more.

Farmers’ perceptions of environmental change are a key trigger for livelihood behaviors. However, it remains unclear how these perceptions become specific livelihood strategies through internal psychological processes. To address this, this study constructs an analytical framework. It integrates multidimensional environmental perceptions, risk aversion, and livelihood strategies. Particular focus is given to the mediating role of risk aversion in the link between perception of environmental change and livelihood strategy. The proposed mechanism is tested using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings indicate that farmers pursue both adaptive and defensive livelihood strategies. They balance security with development opportunities. Perceptions of ecological transition and market volatility significantly affect both adaptive and defensive strategies. Perception of social dynamics mainly influences adaptive strategies. The perception of policy adjustment has no significant effect. Risk aversion mediates these relationships. It strengthens defensive behaviors while promoting adaptive actions, showing its dual function in risk management and proactive adaptation. These findings underscore the complexity of decision-making in rural areas. They elucidate how environmental perceptions shape risk awareness and responses to livelihoods. This offers insights for policies aimed at enhancing rural resilience. Full article

(This article belongs to the Section Sustainable Urban and Rural Development)

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24 pages, 415 KB

Open AccessArticle

Does Managerial Myopia Affect Corporate Carbon Information Disclosure? Evidence from China

by Keyu An, Zhijun Lin and Yunjian Yang

Sustainability 2025, 17(20), 9042; https://doi.org/10.3390/su17209042 (registering DOI) - 13 Oct 2025

Abstract

Corporate carbon information disclosure (CID) is gradually transitioning from being voluntary to mandatory, consistent with the global consensus on addressing climate change and achieving sustainable development. CID reflects corporate environmental performance and is a crucial source for the market to comprehend corporate environmental [...] Read more.

Corporate carbon information disclosure (CID) is gradually transitioning from being voluntary to mandatory, consistent with the global consensus on addressing climate change and achieving sustainable development. CID reflects corporate environmental performance and is a crucial source for the market to comprehend corporate environmental risks and assess their long-term value. However, corporate operations are often influenced by managers’ behavioral preferences when formulating disclosure strategies, as managerial cognitive vision and values directly affect strategic decisions. This study used a sample of Chinese A-share-listed companies for 2010 to 2023 to investigate the relationship between managerial myopia and CID. The findings indicate that managerial myopia significantly inhibits CID by reducing executive environmental awareness and corporate green innovation capabilities. A heterogeneity analysis shows that managerial myopia has a stronger inhibitory effect on CID in companies with weak governance structures and those that are not technology-intensive, providing valuable references for environmental performance and CID practice in emerging countries. Full article

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22 pages, 283 KB

Open AccessArticle

Corporate Governance and Sustainability: The Moderating Role of Board Gender Diversity in the Relationship Between Environmental Innovation and Emission Performance

by Iman Babiker, Mansour Ahmed Elmansour Elfaki, Abdelrahman Mohamed Mohamed Saeed, Amani Ebnaoof, Sawsan Abdelhfiz Hassan Khattab and Amira Abdalrhman Almekki Abdalbagi

Sustainability 2025, 17(20), 9041; https://doi.org/10.3390/su17209041 (registering DOI) - 13 Oct 2025

Abstract

This study examines the effect of environmental innovation on emission performance and the moderating role of board gender diversity among firms in the Middle East and North Africa (MENA) region. Using a panel dataset of 2319 firm-year observations from 13 countries between 2013 [...] Read more.

This study examines the effect of environmental innovation on emission performance and the moderating role of board gender diversity among firms in the Middle East and North Africa (MENA) region. Using a panel dataset of 2319 firm-year observations from 13 countries between 2013 and 2024, the analysis applies fixed-effects regression and robustness checks using the Generalized Method of Moments (GMM). The findings show that environmental innovation significantly improves emissions performance, confirming its strategic role in achieving sustainability goals. Board gender diversity has a positive direct impact on emissions outcomes, suggesting that diverse boards enhance sustainability-oriented governance. However, the interaction term has a negative and significant effect, indicating that gender diversity, while beneficial overall, can weaken the link between environmental innovation and emission performance, possibly because of complex decision-making processes. This study contributes theoretically by extending the Resource-Based View and Porter Hypothesis to an under-researched context, while emphasizing the need for governance mechanisms that leverage diversity without slowing innovation implementation. Future research should incorporate qualitative insights and examine other governance factors to deepen our understanding of how board composition influences sustainability strategies. Full article

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