Journal of Environmental Engineering and Landscape Management
The Journal of Environmental Engineering and Landscape Management publishes original research about the environment with emphasis on sustainability. More information ...
Copyright © 2021 The Author(s). Published by Vilnius Gediminas Technical University. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
A PSO-optimized fuzzy neural model for evaluating the coordinated development of agricultural economy and ecological protection
The coordinated development of agricultural economy and ecological protection is essential for achieving sustainable agriculture, as the resulting ecological benefits have significant implications for both environmental security and economic stability. However, existing ecological benefit evaluation models often suffer from limited indicator coverage and insufficient intelligence in weight assignment, making it difficult to capture the coupled relationship between ecological and economic dimensions. To address these issues, this study proposes a comprehensive evaluation model based on fuzzy logic and a particle swarm optimized backpropagation neural network (PSO-FBP). A multi-level indicator system integrating ecological and economic value is constructed, and fuzzy logic is introduced to manage uncertainty, while PSO enables adaptive weight optimization. The proposed model demonstrates strong learning capability and robustness, enabling a comprehensive quantification of agricultural ecosystem services. A case study of a province shows that waste treatment, agricultural production, and soil conservation are the main contributors to ecological value, confirming the model’s effectiveness in real-world agricultural contexts. This research provides a scientific and practical tool for ecological benefit assessment, offering valuable support for decision-making in sustainable agricultural policy.
Copyright (c) 2026 The Author(s). Published by Vilnius Gediminas Technical University. http://creativecommons.org/licenses/by/4.0
Health sensitive decision-making for integrating artificial intelligence and landscape architecture in urban cities
Urban landscape architecture design plays an essential role in public health because it is influenced by several factors such as social connection, safety, walkability and amenities access. Traditional planning techniques are time-consuming and often result in suboptimal or aesthetically incoherent layout decisions, which diminish the accessibility and safety of landscape design. The research issue is addressed by integrating artificial intelligence (AI) techniques in architectural design to improve the overall aesthetic design while handling health decisions. This study uses Generative Adversarial Networks (GAN) and Reinforcement Learning (RL) to satisfy the health objectives via landscape layouts. The GAN uses the generator and discriminator to design the landscape layout that covers inputs such as functional requirements, site dimension, zone restrictions and health design principles. The combination of generator and discriminator helps to maximize the outcomes in injury prevention, mental restoration and physical activities. The generated layouts are further explored using RL rewards regarding usage, safety, and access, ensuring the layout appearance and aesthetics are directly tailored to health. The incorporation of new technology into landscape architecture can offer evidence-based approaches for constructing salutogenic landscapes. The scalable computational technique enables faster scenario evaluation, providing information for informed planning policies. Then, the excellence of the landscape layout is evaluated using experimental results.
Generative Adversarial Networks (GAN) and Reinforcement Learning (RL)
Sludge-based catalysts for the remediation of PAH-contaminated sediments
The advanced persulfate oxidation method is known for its efficiency, stability, and capacity to breakdown organic contaminants without secondary contamination. In this study, biochar derived from sludge containing iron and manganese from domestic wastewater treatment was produced via pyrolysis and utilized to activate persulfate for the degradation of benzo(a)pyrene (BaP) in sediments. Results demonstrated that biochar pyrolyzed at 800 °C for 2 hours exhibited the highest catalytic performance. Under optimal conditions: a catalyst concentration of 1 g/L, persulfate concentration of 0.4 mM, and a reaction pH of 3, BaP removal efficiency reached 99.85% after 180 min. Characterization of the biochar showed that it was rich in Fe and Mn oxides, along with functional groups such as C-O-C, C=C, and C=O, which facilitated the adsorption and catalytic degradation of BaP. Quenching experiments revealed that the degradation of BaP was driven by reactive species such as •SO₄⁻ and •OH radicals, as well as singlet oxygen (¹O₂). The integration of radical dand non-radical pathways was essential for effective BaP removal. This research presents an innovative method for managing polycyclic aromatic hydrocarbons (PAHs) contamination in sediments by utilizing sludge-derived biochar in conjunction with activated persulfate.
Impact of financial development, trade, and energy consumption on environmental footprint in India: evidence from QARDL and wavelet coherence approach
The aim of this study is to analyze the impact of financial development, trade openness, renewable energy, and nonrenewable energy consumption on CO2 emissions in India by analyzing the quarterly data from 1980 to 2020. Quantile ARDL and Wavelet Coherence methods are employed to examine the nexus. In the long and short run, nonrenewable energy consumption, financial development, and trade openness have a positive impact on CO2 emissions. When emissions are already high, it suggests that financial development may also lead to increased CO2 emissions. Moreover, Renewable energy consumption has a negative impact on CO2 emissions irrespective of the emission level that whether it is high or low in the nations, which shows that if financial enhancement increases, carbon emissions decrease. Finally, we test the EKC hypothesis, and the QARDL findings support the EKC in India. Additionally, the wavelet coherence study found a causal relationship between the CO2 emissions and independent variables, and the findings under the Wald test reject the parameter constancy for all variables. To create effective policies for environmental deterioration, the empirical findings of the current analysis can be used as guidelines for policy implications.
renewable and nonrenewable energy consumption
From waste to resource: bibliometric evaluation of the use of banana pseudostems as biodegradable material
The search for sustainable alternatives has positioned banana pseudostems as a promising material for the production of bioplastics, biopolymers, and eco-friendly composites. This bibliometric review of 119 publications (2003–2024) reveals growing academic interest in its use as a biodegradable material, with an annual growth rate of 8.91% and an average of 15.25 citations per article. Pseudostem fibers have superior mechanical properties, with a tensile strength of 458 MPa and a modulus of 17.14 GPa. Bioplastics derived from this biomass are not only viable alternatives to conventional plastics, especially in packaging, but also provide antibacterial and UV protection. In addition, these fibers function as efficient biosorbents, achieving up to 100% arsenic removal in water. Sentiment analysis of scientific abstracts indicates a predominant feeling of confidence and optimism, reinforcing the potential of banana pseudostems in sustainable industrial applications and highlighting their role in advancing the circular economy.
Modeling sustainable environmental responsibility behavior of students in private university
Using a novel integration of Environmental Literacy Theory, the Theory of Planned Behavior, and Sustainable Development Theory, this study models the determinants of environmentally responsible behavior (often termed organizational citizenship behavior for the environment [OCBE]) among undergraduates at private universities in Malaysia. Data were collected via stratified random sampling of 450 students and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings show that environmental attitudes and a sense of responsibility partially mediate the effect of environmental knowledge on OCBE, highlighting their pivotal roles. These results suggest that educational interventions should not only impart environmental knowledge but also foster pro-environmental attitudes and responsibility. The framework provides guidance for educators and policymakers to design curricula and policies that align with Malaysia’s Sustainable Development Goals (SDGs) and national environmental education targets. By highlighting these mediating factors, the study offers actionable insights for universities and policymakers aiming to advance Malaysia’s sustainability education agenda and SDGs.
A deep learning-based algorithm for unitizing ecologically sensitive areas in rural landscapes
The ecological sensitivity of rural landscapes exhibits complexity and diversity. Traditional evaluation methods, which merely take into account a single factor or a limited number of factors, struggle to effectively manage uncertain information. This leads to inaccurate classification of ecological units in rural landscape ecological images, thereby undermining the precise assessment of the distribution of ecological sensitivity in rural landscapes. Therefore, a deep learning based algorithm for dividing rural landscape ecological sensitive areas is proposed. By selecting six major factors that affect the ecological sensitivity of rural landscape, such as geological environment, ecological and hydrological conditions, an ecological sensitivity evaluation index system is constructed, which is used as an input vector, and fuzzy neural network is used to output the ecological sensitivity of rural landscape; In addition, support vector machine is used to divide the ecological units of the collected rural landscape ecological images, and the division results and the sensitivity evaluation results of each unit of rural landscape are used as the input data of ArcGIS software to realize the visual presentation of the unit division results of rural landscape ecological sensitive areas. The results showed that with the increase of slope, the ecological sensitivity of rural landscape showed a trend of first increasing and then decreasing, the vegetation coverage rate decreased, and the ecological sensitivity of rural landscape showed a trend of gradually increasing; This algorithm can effectively evaluate the sensitivity of each unit of rural landscape, and visually present the unit division results of ecological sensitive areas of rural landscape. This algorithm can compare and analyze the changes of ecological sensitivity under different time dimensions.
A Hybrid Fuzzy AHP-TOPSIS approach for green supplier selection: a case study in Sri Lanka
Green supplier selection is an important component of sustainable supply chain management, particularly in emerging markets where environmental rules and institutional support may be inadequate. This study addresses the need for a structured, sustainability-focused decision-making strategy by presenting a novel hybrid framework that merges the Fuzzy Analytic Hierarchy Process (Fuzzy AHP) with the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The suggested methodology enables systematic evaluation of suppliers by including both subjective expert judgment and objective performance data under conditions of uncertainty. A case study conducted inside the Sri Lankan construction sector demonstrates the practical applicability of the concept. Suppliers were evaluated on four important criteria: environmental, economic, social, and technological. The data reveal that Supplier A is the most suited choice, excelling mainly in environmental and social dimensions. Environmental compliance emerged as the most relevant element in the selection process. By merging fuzzy language assessments with quantitative analysis, the hybrid Fuzzy AHP–TOPSIS method promotes the accuracy, transparency, and consistency of supplier evaluation. The results give valuable insights for industry practitioners, procurement managers, and legislators aiming to connect purchasing choices with long-term sustainability goals. Additionally, the framework gives an accurate platform for future research and application in similar scenarios, helping the growth of green purchasing practices in developing nations.
Copyright (c) 2025 The Author(s). Published by Vilnius Gediminas Technical University. http://creativecommons.org/licenses/by/4.0
Does environmental decentralization promote green technology innovation? —Empirical evidence based on River Chief System
Based on the River Chief System policy characterized by Environmental Decentralization, a double difference model was used to empirically test the impact of Environmental Decentralization on Green Technology Innovation using panel data from 283 cities in China from 2005 to 2022. Research has found that there is a significant positive impact between Environmental Decentralization and Green Technology Innovation. Furthermore, the introduction of the spatial double difference model verifies the significant positive spatial spillover effect of Green Technology Innovation. Robustness testing is also conducted through a series of methods, such as replacing explanatory variables, to confirm the robustness and credibility of the results.
Modeling soil retention, erosion potential, and sedimentation risk using the InVEST SDR model
This study conducts an examination of the Ilam watershed, utilizing the InVEST and SDR models to assess soil retention, erosion, and transport. It incorporates factors like rainfall erosivity, soil erodibility, DEM, land use, vegetation, and conservation practices to explore the complex interplay between ecosystem services (ES) and disservices. The study found that the average soil retention in the watershed is 94.5 tons/ha/year, the average erosion potential is 62.8 tons/ha/year, and the average sediment transport is 10.5 tons/ha/year. Forest areas retain a significant portion of sediment (60%) with low discharge (13%), while agricultural and urban regions contribute more to erosion. This highlights the importance of integrating ES into land management strategies to mitigate environmental degradation. The study highlights the crucial role of ES in maintaining ecological balance and supporting human well-being. It advocates for innovative policies and customized solutions to mitigate land use impacts on soil conservation and sediment retention, thereby fostering awareness among managers and decision-makers for more sustainable land use planning.
Spatial pattern and its driving forces analysis of soil available nitrogen, phosphorus, and potassium in semi-arid grassland surface coal mining areas
Mining activities not only provide a large amount of material basis for socio-economic development but also cause great damage to the environment. It is of great significance to study the spatial variation characteristics of soil Available Nitrogen (AN), Available Phosphorus (AP), and Available potassium (AK) in mining areas for land reclamation and ecological protection. Currently, research on soil AN, AP, and AK in mining areas is lacking in large-scale survey, sampling, spatial pattern, and driving force research for surface coal mines in semi-arid grassland areas, and it is not possible to comprehensively grasp the distribution characteristics and driving forces of soil AN, AP, and AK in surface coal mines. Given this, this study took the Shengli Coal Field in Xilinhot City, the hinterland of Xilingol Grassland, as an example to study the spatial pattern and driving forces of soil AN, AP, and AK in the semi-arid grassland surface coal mining areas. The results showed that: (1) There was no strong spatial correlation among AN, AP, and AK in the soil of the study area, and the spatial pattern heterogeneity was strong. The content of AN, AP, and AK in southeast soil was relatively low. (2) The influence degree of each factor on the spatial pattern of AN was ranked as follows: NDVI > Agriculture > Water > Town > Mining > Industry; (3) The influence degree of each factor on the spatial pattern of soil AP was ranked as follows: NDVI > Mining > Water > Industry > Town > Agriculture; (4) The influence degree of each factor on the spatial pattern of soil AK was ranked as follows: NDVI > Town > Agriculture > Water > Mining > Industry; (5) The interaction between two factors presented two relationships: nonlinear enhancement and dual-factor enhancement. The interaction between various factors was higher than that of a single factor.
available nitrogen, phosphorus, and potassium
Enhanced nitrogen removal and sludge characteristic in aerobic SBR by simultaneous nitrification and denitrification bacteria
Four efficient heterotrophic nitrification and aerobic denitrification (HN-AD) strains were applied in sequencing batch reactors (SBRs) via two bioaugmentation strategies to enhance the nitrogen removal and sludge characteristic. Synthetic domestic wastewater with NH4-N concentrations of 30~50 mg L–1, was treated in three SBRs, with DO maintained at 4±0.5 mg L–1. Compared with the control (crude activated sludge), bioaugmentation improved TN removal by 7% averagely, increased nitration rate by 0.54 mg g–1 h–1, and reduced sludge volume index at 30 min (SVI30) by 3.5~14.7 mL g–1. The maximum TN removal efficiency reached 50.37% with effluent TN concentration of 14.64 mg L–1, meeting China’s Class 1A discharge standard (TN ≤ 15 mg L–1). SBR started by bacterial suspension without activated sludge exhibited high adaptability to low carbon/nitrogen ratio, achieving 35% TN removal at C/N = 3 (vs <10% in control), with <5% MLSS fluctuation versus 30% decline in control. Microbial community analysis revealed Saccharibacteria dominance (15.34% vs control’s 8.48%) coupled with 7.6% reduction in filamentous Saprospiraceae (12.78% to 5.18%), collectively explaining the enhanced nitrogen removal and sludge settleability. This study provides the first evidence of granular sludge formation via HN-AD bacterial coaggregation under low C/N conditions, offering a novel strategy for energy-efficient wastewater treatment.
simultaneous nitrification and denitrification
Motivation to pangolin conservation among Gen Z: applying the extended Theory of Planned Behavior
The study explores the factors influencing pangolin conservation intentions among Gen Z using the extended Theory of Planned Behavior (TPB). Despite ongoing conservation efforts, pangolins remain one of the most trafficked animals globally, facing severe threats from illegal wildlife trade. To address this, the research investigates the roles of attitudes, subjective norms, and perceived behavioral control, along with knowledge and experience, in shaping conservation behaviors. A quantitative approach was employed, utilizing a structured questionnaire to gather data from 377 respondents. Partial Least Squares Structural Equation Modeling (PLS-SEM) was applied for data analysis. The results show that subjective norms and perceived behavioral control are the most significant predictors of behavioral intentions, whereas attitudes, knowledge, and past experiences related to wildlife conservation or pangolins have a relatively weak influence. While they still have a positive effect, these factors do not influence the intention to engage in pangolin conservation behavior as strongly. These findings suggest that conservation campaigns should focus on leveraging social influences and enhancing individuals’ perceived control over their actions rather than solely increasing factual knowledge.
the extended of Theory of Planned Behavior
Changes in land use conflict and zoning optimization in rapidly developing mountainous cities: a case study of Guiyang, China
Mountainous cities, influenced by complex human activities and terrain, face severe land use conflict issues. However, the spatiotemporal characteristics of land use conflict changes and the scientific questions regarding their management in rapidly developing mountainous cities remain unresolved. Therefore, Guiyang, a typical mountainous city in China, was chosen as the study area. With the support of ArcGIS technology, this research analyzed land use conflict changes and conducted zoning optimization. The study reveals a rapid intensification of land use conflicts, with high conflict areas increasing by 369%, while moderate, general, and low conflict areas declined. The conflict between production and living spaces is the predominant one, expanding by 385%. Additionally, high conflict areas between production and ecological spaces rose by 760%. Integrating land suitability, conflict, and functional differences in zoning optimization enhances core functions, mitigates conflicts, and guides land use management. The results are valuable for optimizing land use patterns and promoting healthy urban development in mountainous cities.
Integration of ethnoecopreneuship, collaborative, and creative economy as an effort for sustainability of mangrove ecotourism
In the face of global tourism industry challenges, innovation in tourism services is essential for achieving sustainable development goals. This research aims to address the multifaceted challenges of sustainable mangrove ecotourism in Indonesia through an integrative approach combining ethnoecopreneuship, collaborative, and creative economy. Utilizing participatory rural appraisal (PRA) and focus group discussion (FGD), data analysis combines strengths, weaknesses, opportunities, threats (SWOT) analyses and analytic hierarchy process (AHP) method. The results emphasize the importance of community involvement, ecological considerations, effective promotion, and adoption of digital technology in the sustainability of mangrove ecotourism. The research calls for collaboration among stakeholders, policy emphasis on local government responsibilities, and active involvement of local communities and non-governmental organizations in mangrove conservation and management. This research underscores the potential for sustainable development, aligning with the sustainable development goals (SDGs) and enhancing economic and social outcomes in Indonesia’s mangrove ecotourism sector.
The impact of lakeshore modifications and constructions on visual landscape quality: a mixed methods study
Lakeshore areas continue to be threatened by increasing human activities and land use. Development and large construction projects in lakeshore areas affect both the lake’s ecological condition and its landscape quality and aesthetics. To minimize and prevent the occurrence of significant visual impacts, it is important to understand and evaluate the magnitude of damage and the factors contributing to such impacts from development activities. In this study, a mixed methods approach is used to assess the visual impact of modifications and constructions on the lakeshore landscape. This includes (1) an objective landscape indicator-based assessment method to measure the extent of construction and modification impacts on the visual landscape, and (2) a visual perception-based assessment method to capture receptors’ evaluations of the visual landscape changes and visual impact factors on the lakeshore. Integrating the results from both methods yields a comprehensive assessment of visual impact. The results of both assessment methods indicate that the visual quality of the lakeshore landscape declined significantly during the construction phase. In addition, this study concludes that this mixed approach to visual impact assessment has greater advantages than a single approach and provides more dimensional information, criteria, and perspectives.
Emergency risk assessment and rescue of groundwater pollution caused by mining based on 5G network
Recently, heavy metal pollution of soil, land degradation and groundwater pollution generated due to the lack of supporting environmental protection measure, which not only endanger human health, but also affect the sustainable development of mining industry. In order to avoid groundwater pollution, and improve risk assessment and rescue levels of underground water pollution, and a wireless remote emergency risk assessment and rescue system based on 5G core network is constructed, and emergency risk assessment model of groundwater pollution caused by mining is designed. The types of ground water pollution are analyzed. The emergency risk assessment of groundwater pollution is carried out, and the evaluation method of groundwater pollution is designed. A data mining algorithm is designed for optimizing 5G communication network. Taking groundwater in a mining area as the research object, 15 heavy metal indexes of 12 monitoring wells in the mining area were monitored and analyzed. The results show that proposed emergency risk evaluation and rescue of groundwater pollution caused by mining based on 5G network has better communication performance, indexes of as, Sb, Co, Fe and Mn in underground water exceed the standard. And then 5G core network construction of groundwater pollution emergency risk assessment and rescue concludes user plane function/mobile edge computing (UPF/MEC) sink and independent private network is achieved. A case study is carried out using a coal mine as researching object, results showed that proposed remote emergency risk assessment and rescue of groundwater pollution has less time delay and packet loss rate, therefore proposed emergency risk assessment and rescue of groundwater pollution has better communication performance. Finally, the emergency rescue countermeasures of groundwater pollution are taken according to evaluation results.
Study on suitability assessment method of vegetation restoration species in disturbed sites of transmission line engineering construction
Screening species that can adapt to the disturbed habitats resulting from transmission line construction is of great practical significance for the ecological restoration of primary vegetation degradation caused by such construction. Therefore, a suitability evaluation method for vegetation restoration species in disturbed areas of transmission line engineering construction is studied to improve the ecological restoration. Based on the principles of stability and durability, adapting to local conditions and trees, and comprehensive and dominant screening, an index system for evaluating the adaptability of vegetation restoration species is established. Determine the subjective weight of evaluation index by G1 method and G2 method. The objective weight of evaluation index is determined by improving entropy weight method and deviation method. Through the optimal combination weighting method, the final evaluation index weight is obtained by combining subjective weight and objective weight. Using cloud model combined with index weight to calculate the certainty of each index. According to the principle of maximum certainty, the evaluation grade corresponding to the maximum certainty is selected as the final suitability evaluation result. The experiments have demonstrated that the suitability evaluation index system of this method exhibits high reliability, and it can effectively determine the weights of the suitability evaluation indices and complete the suitability assessment for vegetation restoration species. Among these species, Elymus chinensis, Panicum miliaceum, Brassica napus, arugula, and rye exhibit the most promising ecological restoration effects.
Heavy rainfall resilience: adoption of climate smart agriculture among marginal farmers in a sub-basin of India
Heavy rainfall is a significant challenge for marginal farmers in the aspect of sustainable agriculture. This research analyzed data from eight grid points over 42 years to determine rainfall criteria: 50.91 mm to 79.65 mm for heavy rain, 76.95 mm to 101.21 mm for extreme rain, and 101.21 mm for rare 24-hour occurrences. The vulnerability mapping found 58 agriculturally susceptible communities. Research shows cashew nuts, coriander, sugarcane, sweet potatoes, and turmeric are the five main crops in the 58 most susceptible villages to heavy rainfall. These villages contain a greater number of marginal farmers. The DELPHI method revealed that coriander is the most susceptible crop. In this study, climate-smart agricultural practices such as Integrated Pest Management methods, shifting crop seasons, and Meghdoot application projections are used to minimize the damages caused by heavy rainfall. This includes protecting crops before heavy rainfall and monitoring them after heavy rainfall. For emission reduction as one of the pillars of Climate Smart Agriculture, biochar from biomass breakdown without oxygen is suggested. A poll found that 44% of respondents would use social entrepreneurship for biochar kilns. As, a result 33 farmers from 7 villages used the suggested Integrated Pest Management Technique and Meghdoot to harvest their second season with minimum losses.
Landscape change and perception along historical railway: the case of Yunnan-Vietnam Railway, China
Against the background of environmental change, this study investigates the relationship between landscape changes and perceptions along the historical railway using a combination of Historical Geographic Information Systems (HGIS) and Fuzzy-set Qualitative Comparative Analysis (fsQCA). After quantifying the changes by GIS, the research aims to understand how different types of landscape changes affect physical, psychological, and cultural perceptions among locals. By integrating historical maps with remote sensing data and questionnaire, the study provides a comprehensive analysis of landscape evolution over time. The findings reveal that cropland and urban areas both showed significant increases along the railway; forest and water body both decreased over 70 years. The presence of forest change led to significant cultural perceptions and cropland change influenced the psychological perceptions of landscape. This research contributes to the understanding of the interplay between landscape change and human perception, offering valuable insights for sustainable landscape management and heritage conservation.
Determination of suitable recreational areas in Adana Province Cukurova district by AHP technique
Recreation is people’s whole activity to regain their lost energy. In urban recreation areas, today’s people can escape city life and reach themselves and nature at some point. In this context, the distribution, size, and accessibility of recreation areas in cities gain importance. The research aims to determine potential recreation areas by considering the natural and physical characteristics of the Adana Province Cukurova district. The criteria and importance weights of the criteria related to the natural and physical characteristics of Cukurova district, which is the research area, were determined by Analytic Hierarchy Process (AHP) technique. The data layers of the criteria were overlapped using the “Weighted Linear Combination Technique” in ArcMap program using the importance weights and a map of potential recreation areas was created. The results show that 2.6% of the region has low, 72.2% has medium, and 25.2% has high recreational potential. The western part of Seyhan Dam Lake has been identified as the most suitable area for recreation. Providing a holistic green space system will enable the development of the city’s natural potential. In addition, the areas proposed to be planned as recreational areas will contribute to urban ecosystem services and improve the quality of urban life. To define recreational suitable areas provides effective and quick solutions to manage urban sprawl on ecological. (Referee 1).
Spatial-temporal evolution of land ecological health and influencing factors in China's ecological civilization pilot area
It is crucial to assess the land ecosystem health (LEH) in China’s national pilot zones (NPZ) for ecological conservation and identify the primary factors that impact it. This is crucial for developing China’s ecological civilization and fostering sustainable, eco-friendly economic development. The study utilizes the pressure-state-response (PSR) and environment-economy-society (EES) model, relying on the panel data of 11 cities of Jiangxi in the NPZ for ecological conservation from 2005 to 2020, measuring the LEH in the national ecological civilization pilot zone using the comprehensive index evaluation method. The main contribution of this study is to optimize the land ecological health index system, construct an improved PSR-NES theoretical model that is more suitable for NPZ, reveal the spatial and temporal evolution characteristics of LEH in NPZ from the city scale, and refine the key driving factors. Results show that (1) The LEH exhibited a general shift from a state of “less healthy” level to the “healthier” level; (2) Differences in LEH evolution in different cities. The overall trend of “north to south and east to west” is gradually improving. (3) Urbanization has a strong role in the promotion of LEH, and economic development shows a significant dampening effect.
national pilot zones for ecological conservation
Regeneration and characterization of spent bleaching earth: recycling in the corn oil bleaching process
The spent bleaching earth (SBE) is a solid waste from the edible oil refining industry which generates soil contamination was successfully recycled after deoiling through an extraction process using different organic solvents, followed by heat treatment. In the current study, the effects of factors, such as solvent to (SBE) ratio [1:1–5:1], temperature [20–40 °C], and stirring time [30–60 min] on the efficiency of extracted oil were investigated by maceration method. Characterization analyses (SEM, XRD, XRFA and TGA) were carried out to compare the characteristics of samples. The best oil extraction efficiency was obtained at the highest level of solvent to (SBE) ratio (MR = 5) at 30 °C temperature and at the 45 minutes stirring time this condition led to 72.82% oil extraction yield. The corn oil bleaching efficiency using the SBE treated at optimal condition and heated at 400 °C was improved to 84.75%.
Acetone, xylene and ammonia removal enhancement in the biofilter packed with steam modified biochar
The present study evaluated short-time effect of steam modified biochar with rhamnolipid solution on the removal of different volatile organic and inorganic compounds (acetone, xylene, ammonia) in biofilter with capillary system. Modification of pine wood biochar with steam governed better treatment of pollar acetone and ammonia compounds from the air stream with removal efficiencies of 93% and 96%, respectively. It was related to biochar’s higher average capillary radius, moisture content and lower air velocity. However, removal of xylene was much lower and reached 72% in the case of modified biochar. It can be explained by its higher Henry’s constant, hydrophobicity and non-polarity.
Copyright (c) 2022 The Author(s). Published by Vilnius Gediminas Technical University. http://creativecommons.org/licenses/by/4.0
The practices of public spaces in traditional neighborhoods: case of the Argoub district, city of M'sila-Algeria
Public space seems to have become one of the key elements of local development policies. As such, our study will focus on a traditional neighborhood called Argoub located in the center of the city of M’sila in Algeria, the public spaces of this neighborhood have long been the fundamental structure and the filter of reading of the neighborhood, they have deteriorated and to remedy this problem, the Observation shows that the public space in this district is distorted and its use for heterogeneous purposes than those previously planned, but this diversion of use continues to fragment the public space and reduce it to an obstructed space. The local authorities have carried out limited urban improvement of these spaces to perpetuate and improve their urban quality. This study aims to measure the quality of these spaces, to clarify the notion of traditional public space, and to identify its different practices. For this research, we chose as a methodology recurring observation reinforced by situational observation, while taking into account the urban and historical context of this district. Without permanent control from local authorities, illegal interventions by residents in the spaces in question have completely changed the alleys into stifling spaces used only for transition and not for social interaction. Despite the limited intervention of urban planning services to safeguard the urban fabric network and revive traditional public spaces, the ongoing change practices by residents have had a negative influence on the urban landscape of the neighborhood in general. As such, we will be faced with the following challenges: security, physical and visual quality, and economic attractiveness must, at the end of planning, require a real global reflection on these different urban forms so that their management is coherent and thoughtful. In this regard, the obvious question is: what practical measures should be taken to respond to the problems of landscape and spatial qualities of these spaces and contribute more generally to their sustainability?
Utilization of recycled carbide as adsorbent for adsorption of dyes and COD from textile waste
This study assessed the potential of carbide waste (CW), a by-product of the welding industry, as a cost-effective adsorbent for removing dyes and COD from textile wastewater. CW was prepared through drying, filtering, and shaping into 2 mm-thick tablets (3 mm diameter), followed by heating at 150 °C for 120 minutes. Characterization using FTIR and SEM-EDX confirmed functional groups like hydroxyl and carbonyl and significant surface morphological changes. Batch experiments achieved maximum color and COD removal efficiencies of 94.48% and 96.73%, respectively, at 75 g adsorbent dosage and 150 min contact time. Freundlich isotherm (R² = 0.9918 for color) indicated heterogeneous adsorption, and kinetic studies fit a pseudo-second-order model. The process was exothermic, spontaneous, and governed by physical adsorption. Regeneration trials showed COD removal efficiency remained 90% after four cycles. These findings establish CW as an efficient, sustainable adsorbent with promising environmental and industrial applications for textile wastewater treatment.
Landscape management for disaster-prone cities: disaster resilient park proposal
Elazığ is a disaster-prone city due to its geological structure, proximity to fault lines, and similar reasons. As part of the study, a disaster-resilient green space model applicable to the city has been developed. The study examines how green spaces should be planned and designed to be used in disaster situations. The methodology of the study consists of three phases. (1) The city of Elazığ was analyzed in terms of disasters. (2) UAV and GPS CORS devices were used to collect data in the area designated as the disaster park and three-dimensional spatial analysis was performed. (3) The disaster park was designed according to the data obtained. The results show that Elazığ is frequently affected by disasters. Therefore, it is understood that the city needs a disaster-resistant green system. Suggestions for the design of disaster parks and their inclusion in the landscape management of disaster-prone cities have been developed.
Prediction of the anti-carbonation performance of concrete based on random forest – least squares support vector machine model
Concrete carbonation is a critical factor influencing the durability and longevity of concrete structures, particularly in urban environments. Traditional methods for predicting the anti-carbonation performance (ACP) of concrete often lack precision and fail to account for complex interactions between influencing factors. In this study, a novel hybrid model combining random forest (RF) regression with a least squares support vector machine (LSSVM) is proposed to enhance the accuracy of ACP predictions. The RF regression is utilized for feature selection, identifying the most significant factors affecting ACP and optimizing the input features for the LSSVM model. Our hybrid model is validated against a comprehensive dataset, demonstrating superior performance in predicting concrete carbonation resistance compared to conventional methods. Quantitative results show that the RF-LSSVM model achieves a root mean square error (RMSE) of 5e–5 and a high coefficient of determination (R-squared) of 0.999, indicating robust predictive capability and accuracy. The main novelty of this work lies in the integration of RF and LSSVM to create a robust, accurate, and practical tool for assessing the durability of concrete structures.
least squares support vector machine (LSSVM) model
Study on the polymeric treatment with rice husk silica on sisal fiber in cementicious composites
This research evaluates how treating sisal fibers with expanded polystyrene (EPS) and rice husk silica (RHS) affects their absorption capacity, tensile strength, and adhesion when used in Portland cement matrices. The study on sisal fibers treated with EPS and RHS polymers found that the treatment significantly reduced water absorption by 70%, from 84.67% for untreated fibers to 15.18% for treated ones, due to the hydrophobic nature of EPS. Optical microscopy revealed an irregular polymer layer on the fibers, which, while improving dimensional stability, could impair fiber-matrix interaction. Despite these improvements, the treatment did not notably enhance the mechanical properties of the fibers, as the breaking strength remained similar to untreated fibers, and the rupture displacement slightly decreased.
Bibliometric mapping of MCDM methods in AEC industry: identifying trends for sustainable development
This study investigates integrating multi-criteria decision-making (MCDM) approaches to improve sustainability in the architecture, engineering, and construction (AEC) industry. Through a systemic literature analysis done through the Scopus database and the visualization of key elements through VOSViewer, the study examines the applications of MCDM in sustainable construction, with particular attention to material selection, contractor procurement, waste management, risk assessment, and technological integration, which are essential elements towards sustainable development of the AEC industry. The results highlight how common and successful hybrid MCDM and MADM methods are. These approaches provide all-encompassing answers to challenging problems, from project mitigation to material procurement. The evaluation emphasizes the value of MCDM methods in supporting sustainable practices across the construction lifecycle, streamlining supply chains, and enabling well-informed decision-making. In the end, this study emphasizes how critical it is to carry out further research and apply MCDM frameworks to promote sustainable development in the construction sector and balance development objectives with the protection of the environment and the welfare of society.