Template-Type: ReDIF-Article 1.0 Author-Name: Ibrahim Mugerwa Author-X-Name-First: Ibrahim Author-X-Name-Last: Mugerwa Author-Name: Jianxin Chen Author-X-Name-First: Jianxin Author-X-Name-Last: Chen Title: Plastic waste recycling product design based on sustainable concepts: study of improvement, developments, and innovations in Kampala City, Uganda Abstract: Plastic waste poses significant challenges globally, particularly in developing nations like Kampala, Uganda. This study focuses on innovative product design approaches for recycling plastic waste sustainably. Using quantitative data from surveys conducted in Kampala involving 127 participants, the research finds a moderate preference for recycled plastic products. Specifically, 45 participants expressed openness to using solar lanterns made from recycled plastic, addressing the city's need for efficient lighting. Moreover, a survey on lighting and energy sources, with 52 participants, reveals reliance on a mix of energy sources, highlighting the significance of addressing inadequate lighting. Kerosene lanterns are preferred but have limitations, whereas people frequently use solar lamps. These findings underscore the potential of integrating sustainable design principles into product development to address urban plastic waste challenges. Journal: Int. J. of Environmental Technology and Management Pages: 239-265 Issue: 1/2/3 Volume: 28 Year: 2025 Keywords: sustainable design; product design; recycled plastic products; urban waste management; Uganda. File-URL: http://www.inderscience.com/link.php?id=144497 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetma:v:28:y:2025:i:1/2/3:p:239-265 Template-Type: ReDIF-Article 1.0 Author-Name: Bryan Aleron Author-X-Name-First: Bryan Author-X-Name-Last: Aleron Author-Name: Ditdit Nugeraha Utama Author-X-Name-First: Ditdit Nugeraha Author-X-Name-Last: Utama Title: Teak trees computational modelling to measure environmental contribution using functional-structural plant modelling Abstract: Teak trees (<i>Tectona grandis</i>) are known for their excellent and expensive wood quality. However, teak trees have many contributions to the environment, such as maintaining soil stability and preventing erosion. Teak leaves also make an environmental contribution, namely producing oxygen and absorbing carbon. This study aims to create a plant computational model of teak trees using the functional-structural plant modelling (FSPM) method which is implemented on the growth grammar-related interactive modelling platform (GroIMP). This model can simulate the growth of teak trees morphologically and predict the contribution of teak trees to the environment such as the total oxygen produced, and the carbon absorption. The model simulated that one teak tree at the age of 20 can produce 1,800 grams of oxygen per day and absorb 670 grams of carbon per day, providing enough oxygen for three people in one day. Journal: Int. J. of Environmental Technology and Management Pages: 141-159 Issue: 1/2/3 Volume: 28 Year: 2025 Keywords: plant computational modelling; PCM; teak tree; environmental engineering; oxygen production; carbon sequestration; functional-structural plant modelling; FSPM. File-URL: http://www.inderscience.com/link.php?id=144498 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetma:v:28:y:2025:i:1/2/3:p:141-159 Template-Type: ReDIF-Article 1.0 Author-Name: Bahram Abdalrahman Faraj Author-X-Name-First: Bahram Abdalrahman Author-X-Name-Last: Faraj Title: Hydraulic modelling and flood hazard zoning in rivers of the urban basin of Sulaymaniyah using 2D modelling with HEC-RAS and GIS Abstract: The preparation of flood zoning maps is crucial in global urban development studies, serving as fundamental information for investment and project implementation assessments by relevant organisations. This study focused on hydraulic modelling and flood zoning in Sulaymaniyah urban basin using hydrologic model HEC-RAS and GIS. Given the escalating urban flood frequency, effective solutions are imperative. The 2D hydraulic model HEC-RAS was employed for a more accurate simulation of flow patterns, especially in flood-prone areas. Hydrological data, digital elevation model, and urban structure data were utilised for modelling, with the aim to identify vulnerable areas and propose damage reduction solutions. The study generated water surface profile maps, width, depth, and flow velocity for return periods of 2, 5, 10, 25, 50, and 100 years. With a 25-year return period, flood vulnerability was classified based on depth and flow velocity, revealing substantial risks in urban areas. H5 and H6 hazard zones covered 43.5% and 24.5% of these areas, posing threats to individuals, vehicles, and structures. The H4 hazard zone, comprising 8.8% of the flood-prone area, presented risks to people and vehicles. Also, the correctness of choosing Manning's roughness coefficient was evaluated. This research provides valuable insights for urban flood management and hazard mitigation. Journal: Int. J. of Environmental Technology and Management Pages: 111-140 Issue: 1/2/3 Volume: 28 Year: 2025 Keywords: HEC-RAS; urban flood management; flood zoning map; water surface profile; hazard zone. File-URL: http://www.inderscience.com/link.php?id=144499 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetma:v:28:y:2025:i:1/2/3:p:111-140 Template-Type: ReDIF-Article 1.0 Author-Name: Jing Xue Author-X-Name-First: Jing Author-X-Name-Last: Xue Author-Name: Jina Cui Author-X-Name-First: Jina Author-X-Name-Last: Cui Title: Carbon emission calculation and control of agricultural product supply chain under the background of energy conservation and emission reduction Abstract: To overcome the problems of low accuracy, long calculation time, and minimal carbon emission reduction in traditional carbon emission calculation and control methods, a new carbon emission calculation and control method of agricultural product supply chain under the background of energy conservation and emission reduction is proposed. The grey relational analysis and extended STIRPAT model are used to select the influencing factors of carbon emissions in the agricultural product supply chain, and the AOA-LSTM model is used to calculate the carbon emissions. The carbon emissions of the agricultural product supply chain under the background of energy conservation and emission reduction are controlled based on allocation adjustment factors, carbon emissions increment distribution ratios, and allocation quotas. The experimental results show that the accuracy of the proposed method varies between 94.9% and 97.9%, with a maximum calculation time of 1.03 s. The carbon emission reduction after nine months 1.238 × 10<SUP align="right"><SMALL>6</SMALL></SUP>t. Journal: Int. J. of Environmental Technology and Management Pages: 91-110 Issue: 1/2/3 Volume: 28 Year: 2025 Keywords: energy conservation and emission reduction; agricultural product; supply chain; carbon emission calculation; control; AOA-LSTM model. File-URL: http://www.inderscience.com/link.php?id=144500 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetma:v:28:y:2025:i:1/2/3:p:91-110 Template-Type: ReDIF-Article 1.0 Author-Name: Yali Liang Author-X-Name-First: Yali Author-X-Name-Last: Liang Author-Name: Zengli Fang Author-X-Name-First: Zengli Author-X-Name-Last: Fang Author-Name: Fang Wang Author-X-Name-First: Fang Author-X-Name-Last: Wang Author-Name: Gaoling Li Author-X-Name-First: Gaoling Author-X-Name-Last: Li Author-Name: Yongjian Guo Author-X-Name-First: Yongjian Author-X-Name-Last: Guo Title: Peak carbon emission prediction of expressway toll stations using GRA-LSTM under the dual carbon background Abstract: In order to reduce the error of carbon emission peak prediction and shorten the prediction time, an expressway toll station carbon emission peak prediction method based on the GRA-LSTM model is proposed in the background of dual carbon. Firstly, analyse the dual carbon goals and the characteristics of sustainable development. Secondly, convert the energy consumption generated during the vehicle's payment process into the vehicle's carbon emissions data. Finally, use the grey correlation analysis (GRA) method based on the collected carbon emission data, to calculate the correlation degree between the factors affecting carbon emissions. Using the long short-term memory (LSTM) model to construct a carbon emission peak prediction model, and the output result is the carbon emission peak prediction result. The experimental results show that the proposed method can shorten the prediction time while reducing the prediction RSME. Journal: Int. J. of Environmental Technology and Management Pages: 76-90 Issue: 1/2/3 Volume: 28 Year: 2025 Keywords: dual carbon background; GRA-LSTM model; expressway toll stations; carbon emissions; peak prediction. File-URL: http://www.inderscience.com/link.php?id=144501 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetma:v:28:y:2025:i:1/2/3:p:76-90 Template-Type: ReDIF-Article 1.0 Author-Name: Renzhong Jin Author-X-Name-First: Renzhong Author-X-Name-Last: Jin Title: Research on influencing factors of regional tourism carbon emission based on LMDI model Abstract: In response to the low accuracy and poor comprehensiveness of existing research on the factors affecting carbon emissions in regional tourism industry, this paper conducts research on the factors affecting carbon emissions in regional tourism industry based on the LMDI model. Firstly, carbon emission related data is collected from the tourism industry and the data is pre-processed using normalisation methods. Secondly, a bottom-up approach is adopted to estimate various energy consumption during the tourism process. Finally, the LMDI model is used for factor decomposition to study the factors affecting carbon emissions. Through experiments, it has been proven that the application of the LMDI model to analyse the influencing factors of carbon emissions can always be more than 90% comprehensive, and the error between the calculated carbon emissions and the actual carbon emissions is always less than 100,000 tons. The effect of analysing the influencing factors of carbon emissions is good. Journal: Int. J. of Environmental Technology and Management Pages: 61-75 Issue: 1/2/3 Volume: 28 Year: 2025 Keywords: LMDI model; tourism industry; carbon emissions; influencing factors; bottom-up. File-URL: http://www.inderscience.com/link.php?id=144502 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetma:v:28:y:2025:i:1/2/3:p:61-75 Template-Type: ReDIF-Article 1.0 Author-Name: Junzhi Song Author-X-Name-First: Junzhi Author-X-Name-Last: Song Title: A positive and negative balance accounting method for carbon emissions in parks based on K-nearest neighbour clustering algorithm Abstract: In order to improve accounting accuracy and shorten accounting time, the paper proposes a positive and negative balance accounting method for carbon emissions in parks based on K-nearest neighbour clustering algorithm. Firstly, collect and standardise the carbon emission data of the park. Then, K-nearest neighbour clustering algorithm is used to cluster the carbon emission management items. After reconstructing the data components, the reconstruction component with the highest sample entropy is decomposed twice to obtain the carbon emission coefficient of land use type. Finally, a carbon emission balance accounting model is constructed, and the accounting results are obtained by integrating various production factors in the model. The experimental shows that after applying this method, the accuracy and recall of carbon emission accounting can reach 96.09% and 99.6%, respectively. The time required for positive and negative balance accounting is only 2.5 minutes, indicating that this method has achieved the design expectations. Journal: Int. J. of Environmental Technology and Management Pages: 45-60 Issue: 1/2/3 Volume: 28 Year: 2025 Keywords: K-nearest neighbour algorithm; K-means clustering method; K-nearest neighbour clustering algorithm; secondary decomposition; carbon emissions. File-URL: http://www.inderscience.com/link.php?id=144503 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetma:v:28:y:2025:i:1/2/3:p:45-60 Template-Type: ReDIF-Article 1.0 Author-Name: Xuming Cai Author-X-Name-First: Xuming Author-X-Name-Last: Cai Title: Evaluation method of landscape ecological quality based on remote sensing ecological index Abstract: To enhance the accuracy and recall rate of landscape ecological quality assessment, this study proposes a method based on remote sensing ecological index (RSEI). Firstly, data on landscape architecture's ecological quality are collected, and the RSEI is derived from remote sensing images. Secondly, ecological quality assessment component indicators are constructed, and principal component analysis (PCA) is employed to combine these indicators. Lastly, the grey correlation model is utilised to analyse the ecological environment situation, and the equidistant separation method is applied to categorise RSEI into five levels. The ecological quality assessment results are obtained using spatial statistical methods. The findings reveal that the prediction error rate of RSEI values in this method is controlled within 2.87%, achieving an accuracy of 99.2% and a recall rate of 99.9%. This indicates that the method has the potential to improve the comprehensiveness of landscape ecological quality assessment. Journal: Int. J. of Environmental Technology and Management Pages: 32-44 Issue: 1/2/3 Volume: 28 Year: 2025 Keywords: grey correlation model; remote sensing ecological index; RSEI; PCA transformation; equidistant separation method; spatial statistical methods. File-URL: http://www.inderscience.com/link.php?id=144504 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetma:v:28:y:2025:i:1/2/3:p:32-44 Template-Type: ReDIF-Article 1.0 Author-Name: Wei He Author-X-Name-First: Wei Author-X-Name-Last: He Author-Name: Xiao Wang Author-X-Name-First: Xiao Author-X-Name-Last: Wang Author-Name: Yu Zhang Author-X-Name-First: Yu Author-X-Name-Last: Zhang Author-Name: Rui Hua Author-X-Name-First: Rui Author-X-Name-Last: Hua Title: Short-term load prediction of electric vehicle charging stations based on conditional generative adversarial networks Abstract: In order to solve the problems of high average absolute error and long time consumption in traditional forecasting methods, a short-term load prediction method of electric vehicle charging stations based on conditional generative adversarial networks is proposed. This method involves the analysis of the initial charging time, initial state of charge, and battery characteristics of electric vehicles. Based on the analysis results, a conditional generative adversarial networks (CGAN) model is constructed to anticipate the short-term load of electric vehicle charging stations. In the CGAN model, the charging start time, initial state of charge, and battery characteristics of electric vehicles serve as conditional values. Through training, the model learns the relationship between these conditions and the target, generating accurate load forecasting results. Experimental findings reveal that the proposed method boasts a maximum average absolute error of merely 1.4% and a minimum prediction time of just 1.26 seconds, thus demonstrating its practicality. Journal: Int. J. of Environmental Technology and Management Pages: 1-18 Issue: 1/2/3 Volume: 28 Year: 2025 Keywords: CGAN; electric vehicles; charging stations; short-term load forecasting; battery characteristics. File-URL: http://www.inderscience.com/link.php?id=144505 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetma:v:28:y:2025:i:1/2/3:p:1-18 Template-Type: ReDIF-Article 1.0 Author-Name: Lei Zhang Author-X-Name-First: Lei Author-X-Name-Last: Zhang Title: Automatic classification method of construction waste based on machine vision Abstract: In order to solve the problems of low accuracy and low efficiency of existing automatic classification methods of construction waste, an automatic classification method of construction waste based on machine vision was proposed. Firstly, the CCD camera is used to collect the image and enhance the image. Then, the maximum entropy method is used to obtain the optimal segmentation threshold of the image, and the construction waste image is segmented. Finally, the gradient information is used to obtain the image features of construction waste, and the automatic classification of construction waste is realised by combining with the SVM algorithm. The experimental results show that the classification accuracy of the proposed method is between 90% and 98%. When the number of construction waste images is 1,000, the classification time is 13 min, which indicates that the proposed method has high classification accuracy, high efficiency and good application performance. Journal: Int. J. of Environmental Technology and Management Pages: 19-31 Issue: 1/2/3 Volume: 28 Year: 2025 Keywords: machine vision; construction waste; automatic classification; histogram; maximum entropy segmentation. File-URL: http://www.inderscience.com/link.php?id=144506 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetma:v:28:y:2025:i:1/2/3:p:19-31 Template-Type: ReDIF-Article 1.0 Author-Name: Yurong Pan Author-X-Name-First: Yurong Author-X-Name-Last: Pan Author-Name: Chaoyong Jia Author-X-Name-First: Chaoyong Author-X-Name-Last: Jia Title: Study on comprehensive evaluation of environmental pollution in tourist attractions based on FCM algorithm Abstract: To address the shortcomings of traditional evaluation approaches for environmental pollution in tourist destinations, such as their limited precision, accuracy, and reliability, we must seek innovative strategies, a comprehensive evaluation method of environmental pollution in tourist attractions based on FCM algorithm is proposed. The comprehensive evaluation index system of environmental pollution in tourist attractions is established, and the evaluation index data are clustered by FCM algorithm. The improved principal component analysis is improved by logarithmic processing, so that the improved principal component analysis can process the evaluation index data with high quality, and environmental pollution evaluation results are obtained by combining the factor load matrix. The empirical findings indicate that the average precision of the evaluation index stands at an impressive 97.36%, the evaluation accuracy is between 96.5% and 98.3%, and the average reliability of the evaluation result is 0.97, which can realise the accurate evaluation of environmental pollution. Journal: Int. J. of Environmental Technology and Management Pages: 174-189 Issue: 1/2/3 Volume: 28 Year: 2025 Keywords: FCM algorithm; tourist attractions; environmental pollution; comprehensive evaluation; logarithmic processing; improved principal component analysis. File-URL: http://www.inderscience.com/link.php?id=144509 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetma:v:28:y:2025:i:1/2/3:p:174-189 Template-Type: ReDIF-Article 1.0 Author-Name: Chenghao Xu Author-X-Name-First: Chenghao Author-X-Name-Last: Xu Author-Name: Weixian Che Author-X-Name-First: Weixian Author-X-Name-Last: Che Author-Name: Baichong Pan Author-X-Name-First: Baichong Author-X-Name-Last: Pan Title: Carbon flow tracking methods for power systems in energy conservation and emission reduction environments Abstract: A carbon flow tracking method for the power system in an energy-saving and emission reducing environment is studied in order to accurately track the carbon flow of the power system and reduce the carbon footprint error rate. Firstly, carbon emission data is collected and features using Pearson correlation coefficients are extracted. Then, a carbon emission factor prediction model is established through neural networks, and the MDI method is used to calculate the carbon emission intensity of the power system. Finally, a DC power flow model is introduced with carbon emission intensity as input to achieve carbon flow tracking. The experimental results show that the carbon footprint error rate of the method proposed in this paper is 5.2%, the cost-effectiveness ratio of emission reduction is 80 yuan/ton of CO<SUB align="right"><SMALL>2</SMALL></SUB>, and it has strong anti-interference ability against data noise, demonstrating good carbon flow tracking performance. Journal: Int. J. of Environmental Technology and Management Pages: 160-173 Issue: 1/2/3 Volume: 28 Year: 2025 Keywords: energy conservation and emission reduction; power system; carbon flow tracking; neural networks; carbon emission factor; carbon emission intensity. File-URL: http://www.inderscience.com/link.php?id=144510 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetma:v:28:y:2025:i:1/2/3:p:160-173 Template-Type: ReDIF-Article 1.0 Author-Name: Mostafa A. Benzaghta Author-X-Name-First: Mostafa A. Author-X-Name-Last: Benzaghta Author-Name: Sleem A. Kreba Author-X-Name-First: Sleem A. Author-X-Name-Last: Kreba Author-Name: Masood A. Ali Author-X-Name-First: Masood A. Author-X-Name-Last: Ali Author-Name: Ibrahim S. Zaghinin Author-X-Name-First: Ibrahim S. Author-X-Name-Last: Zaghinin Title: Treated municipal wastewater for irrigation: a case study from Misurata City, Libya Abstract: Treated wastewater is frequently used as an unconventional water resource because water resources are important to preserve the environment and human health, particularly in arid and semiarid regions. The present work examined the suitability of treated wastewater from Sasso basin in Misurata City, Libya for agricultural irrigation. Physical, chemical, and biological characteristics of treated wastewater from Sasso basin during a six-month period were monitored twice a month and compared with Libyan, FAO, WHO, USEPA, and USSL standards. Quality indicators of treated wastewater were higher than the acceptable ranges of national and international standards. Treated wastewater from Sasso basin was not recommended for agricultural irrigation. The performance of the Al-Sikt Wastewater Treatment Plant should be rehabilitated and evaluated periodically before considering treated wastewater for irrigation. We suggest the use of secondary treatment methods such as constructed wetlands to improve treated wastewater quality from Al-Sikt plant. Journal: Int. J. of Environmental Technology and Management Pages: 190-212 Issue: 1/2/3 Volume: 28 Year: 2025 Keywords: wastewater reuse; agricultural irrigation; environmental management; Misurata Libya. File-URL: http://www.inderscience.com/link.php?id=144513 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetma:v:28:y:2025:i:1/2/3:p:190-212 Template-Type: ReDIF-Article 1.0 Author-Name: Mohammad Reza Mohammad Shafiee Author-X-Name-First: Mohammad Reza Mohammad Author-X-Name-Last: Shafiee Author-Name: Omolbanin Naghizadeh Dehno Author-X-Name-First: Omolbanin Naghizadeh Author-X-Name-Last: Dehno Author-Name: Zahra Shams Ghahfarokhi Author-X-Name-First: Zahra Shams Author-X-Name-Last: Ghahfarokhi Title: Preparation and characterisation of aloe vera/nanocellulose/bentonite biocomposite scaffold to remove arsenic from wastewater Abstract: Water is a critical substance for existence on earth, and if it is contaminated with pollutants, it will be impossible to survive. There are many techniques to remove the heavy metals present in water including chemical, physical, and biological processes. Today, biocomposites have been able to offer new solutions in the field of treatment of polluted waters. biocomposites have unique properties such as environmental friendliness, high porosity, and high mechanical strength. Polymer composites incorporating biomaterials have been widely studied for wastewater treatment because of their simple preparation, affordability, and resilience. In this research, aloe vera/ nanocellulose/bentonite (A.vera/NC/Bn) biocomposite scaffold was synthesised. this study aims to use this biocomposite scaffold to remove arsenic as a heavy metal in water, also by optimising the conditions such as the contact time of the biocomposite with contaminated water, adsorbent dosage, pH, and temperature, we can achieve better results. Journal: Int. J. of Environmental Technology and Management Pages: 225-238 Issue: 1/2/3 Volume: 28 Year: 2025 Keywords: wastewater; arsenic; biocomposite; adsorption; aloe vera; nanocellulose; bentonite. File-URL: http://www.inderscience.com/link.php?id=144515 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetma:v:28:y:2025:i:1/2/3:p:225-238 Template-Type: ReDIF-Article 1.0 Author-Name: Hinda Khelili Author-X-Name-First: Hinda Author-X-Name-Last: Khelili Author-Name: Ahou Florentine Kokora Author-X-Name-First: Ahou Florentine Author-X-Name-Last: Kokora Author-Name: Kouamé Gervais Konan Author-X-Name-First: Kouamé Gervais Author-X-Name-Last: Konan Author-Name: Messaoud Guellal Author-X-Name-First: Messaoud Author-X-Name-Last: Guellal Title: Combination of activated carbon and thermal energy system for the clarification of surface water at Bousellem Abstract: The aim of this study was to clarify drinking water. According to the results obtained from monitoring the turbidity of the water, the clarification efficiency increases up to a value of 50% and then stabilises at 378 K when heat alone is used. In addition, the tests carried out showed that the higher the temperature and the longer the treatment time, the greater the clarification efficiency of the polluted water up to the point of equilibrium. In addition, the addition of orange peel activated carbon (ACOP) to the tests demonstrated that ACOP improves water clarification efficiency. It was observed that there is an optimum temperature at which the efficiency becomes significantly stable (i.e., 92.5%) for a temperature of 373 K. Journal: Int. J. of Environmental Technology and Management Pages: 213-224 Issue: 1/2/3 Volume: 28 Year: 2025 Keywords: Bousellem; heat; activated carbon; water treatment. File-URL: http://www.inderscience.com/link.php?id=144517 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetma:v:28:y:2025:i:1/2/3:p:213-224 Template-Type: ReDIF-Article 1.0 Author-Name: Elisabeth Viles Author-X-Name-First: Elisabeth Author-X-Name-Last: Viles Author-Name: Javier Santos Author-X-Name-First: Javier Author-X-Name-Last: Santos Author-Name: Ana López Author-X-Name-First: Ana Author-X-Name-Last: López Author-Name: Oscar Revilla Author-X-Name-First: Oscar Author-X-Name-Last: Revilla Author-Name: Francisco-Javier Rios-Davila Author-X-Name-First: Francisco-Javier Author-X-Name-Last: Rios-Davila Title: Exploring sustainability in emerging technologies: a reference framework utilising multicase studies Abstract: Recent technological advancements are positioned as a remedy to contemporary challenges in sustainable development. However, existing methods for evaluating the sustainability impact of these technologies are insufficient, lacking comprehensive coverage of a technology's entire lifespan and proving less effective in initial developmental phases. This paper presents three case studies evaluating the sustainability of technological R%D projects in the metal sector, contributing to the advancement of sustainable technological propositions. As a result of the analysis, the paper proposes a robust framework for assessing emerging sustainable technologies. The relevant novelty of this framework is that it can be easily applied to assess technological projects from their conception, including the sustainable assessment of the development itself. Journal: Int. J. of Environmental Technology and Management Pages: 1-23 Issue: 7 Volume: 28 Year: 2025 Keywords: emerging technologies; technology assessment; sustainable technology; case studies. File-URL: http://www.inderscience.com/link.php?id=146352 File-Format: text/html File-Restriction: Open Access Handle: RePEc:ids:ijetma:v:28:y:2025:i:7:p:1-23 Template-Type: ReDIF-Article 1.0 Author-Name: Suli Zhang Author-X-Name-First: Suli Author-X-Name-Last: Zhang Author-Name: Yulin Jiao Author-X-Name-First: Yulin Author-X-Name-Last: Jiao Author-Name: Xinhua Wang Author-X-Name-First: Xinhua Author-X-Name-Last: Wang Title: Urban public transport planning methods under low carbon emission constraints Abstract: In order to reduce the carbon emissions of urban public transportation systems and improve service efficiency and coverage, a low-carbon emission constrained urban public transportation planning method is proposed. Firstly, three objective functions were set: minimising carbon emissions, minimising average waiting time for passengers, and maximising service coverage, with corresponding constraints clearly defined. Subsequently, based on these objective functions, a city public transportation planning model was constructed and solved using particle swarm optimisation algorithm. To enhance the efficiency of the problem-solving process, a mechanism capable of adaptation was devised to dynamically modify the inertia weight and acceleration constants within the particle swarm optimisation algorithm. The outcomes of the experiments indicate that this approach effectively curtails the average waiting period for passengers to 2.34 minutes and attains a substantial service coverage rate when the peak air quality index (AQI) reading is 88, thereby substantiating the efficacy of the planning methodology. Journal: Int. J. of Environmental Technology and Management Pages: 267-279 Issue: 4/5/6 Volume: 28 Year: 2025 Keywords: low carbon emissions; urban public transportation; transportation planning; particle swarm optimisation algorithm; adaptive mechanism. File-URL: http://www.inderscience.com/link.php?id=148980 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetma:v:28:y:2025:i:4/5/6:p:267-279 Template-Type: ReDIF-Article 1.0 Author-Name: Jie Luo Author-X-Name-First: Jie Author-X-Name-Last: Luo Title: An accurate prediction of environmental carrying capacity of tourist attractions under the coupling influence of multiple factors Abstract: In order to overcome the problems of low coordination degree of multi-factor coupling, large deviation of prediction results and low subordinate degree of multi-factor coupling in traditional prediction methods, an accurate prediction method of environmental carrying capacity of tourist attractions under the coupling influence of multiple factors is proposed. The multi-factors influencing the environmental carrying capacity of tourist attractions are described by three elements, and the membership degree of multi-factors is calculated by fuzzy matter-element analysis. The weight coefficient of the influencing factors is determined, so as to build an accurate prediction model, and the influencing factors are added into the model to get accurate prediction results. The experimental analysis has revealed that the utmost level of harmony exhibited in the integration of multiple factors through this approach can attain an exceptional 100% congruency, the prediction deviation rate of bearing capacity is 0.12%, and the membership degree of multi-factor coupling is high. Journal: Int. J. of Environmental Technology and Management Pages: 280-297 Issue: 4/5/6 Volume: 28 Year: 2025 Keywords: coupling influence of multiple factors; tourist attractions; environmental carrying capacity; weight coefficient. File-URL: http://www.inderscience.com/link.php?id=148981 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetma:v:28:y:2025:i:4/5/6:p:280-297 Template-Type: ReDIF-Article 1.0 Author-Name: Jing Zhang Author-X-Name-First: Jing Author-X-Name-Last: Zhang Author-Name: Zhengyang Peng Author-X-Name-First: Zhengyang Author-X-Name-Last: Peng Author-Name: Hui Li Author-X-Name-First: Hui Author-X-Name-Last: Li Author-Name: Xin Wen Author-X-Name-First: Xin Author-X-Name-Last: Wen Title: Carbon performance rating evaluation method for thermal power enterprises based on fuzzy-AHP Abstract: The shortcomings of traditional data processing techniques, characterised by their inherent uncertainty and ambiguity, give rise to flawed assessments of thermal power companies' carbon efficiency. Consequently, there is a pressing need for an innovative evaluation approach that leverages the fuzzy-AHP methodology. This method begins by scrutinising the essence of carbon performance metrics and the structural framework of thermal power businesses. It then proceeds to construct a comprehensive set of evaluation indicators for carbon performance. The fuzzy-AHP technique is employed to hierarchically organise the evaluation levels of carbon performance for thermal power enterprises. By integrating the weights of individual indicators and utilising a fuzzy evaluation matrix, this method calculates a cumulative carbon performance score, facilitating the comprehensive evaluation process. Experimental outcomes reveal that this method achieves an impressive accuracy rate of up to 98%, while simultaneously reducing the evaluation duration significantly. Journal: Int. J. of Environmental Technology and Management Pages: 298-311 Issue: 4/5/6 Volume: 28 Year: 2025 Keywords: fuzzy-AHP; thermal power enterprises; carbon performance; grade evaluation. File-URL: http://www.inderscience.com/link.php?id=148982 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetma:v:28:y:2025:i:4/5/6:p:298-311 Template-Type: ReDIF-Article 1.0 Author-Name: Jue Wu Author-X-Name-First: Jue Author-X-Name-Last: Wu Author-Name: Haibo Zhang Author-X-Name-First: Haibo Author-X-Name-Last: Zhang Author-Name: Qi Hu Author-X-Name-First: Qi Author-X-Name-Last: Hu Title: Evaluation method of ecological carrying capacity of vegetation landscape in nature reserves based on improved analytic hierarchy process Abstract: In order to accurately evaluate the ecological carrying capacity of vegetation landscape in nature reserves, and improve the accuracy and efficiency of evaluation, a method for evaluating the ecological carrying capacity of vegetation landscape in nature reserves based on improved analytic hierarchy process is proposed. Principles for evaluating the ecological carrying capacity of vegetation landscape are identified based on the Delphi method. Primary and secondary indicators are selected to construct an evaluation index system for the ecological carrying capacity of vegetation landscape in nature reserves. Due to the insufficient ability of traditional methods to handle fuzzy information, fuzzy theory is adopted to improve the traditional analytic hierarchy process, determine weights, and combine fuzzy comprehensive evaluation factors to comprehensively evaluate the ecological carrying capacity of vegetation landscape in nature reserves. The experimental results show that the evaluation weight calculation accuracy of the proposed method reaches 99%, and the time taken is less than 8.35 seconds. Journal: Int. J. of Environmental Technology and Management Pages: 341-354 Issue: 4/5/6 Volume: 28 Year: 2025 Keywords: analytic hierarchy process; AHP; nature reserves; vegetation landscape; ecological carrying capacity. File-URL: http://www.inderscience.com/link.php?id=148984 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetma:v:28:y:2025:i:4/5/6:p:341-354 Template-Type: ReDIF-Article 1.0 Author-Name: Weili Shen Author-X-Name-First: Weili Author-X-Name-Last: Shen Author-Name: Renhua Ge Author-X-Name-First: Renhua Author-X-Name-Last: Ge Author-Name: Peng Jiao Author-X-Name-First: Peng Author-X-Name-Last: Jiao Title: A method for urban and rural construction land layout planning based on GIS spatial analysis technology Abstract: To enhance the efficiency of urban and rural land resource management, a strategy for the spatial arrangement of urban and rural construction land utilising GIS spatial analysis technology is introduced. Collect geospatial data and perform interpolation, cleaning, standardisation, and fusion processing on the data to improve its quality and usability. Subsequently, these refined datasets are fed into a BP neural network to forecast the future needs for urban and rural construction land. The forecasts are then integrated into GIS software, where a spatial analysis model is developed to analyse the data spatially. A regression model is employed to synthesise the outcomes of the spatial analysis, leading to the optimised layout planning of urban and rural construction land. The efficacy of this approach is validated through experiments, demonstrating its robust spatial complexity, adaptable land use, and overall sustainability, affirming the positive impact of this planning methodology. Journal: Int. J. of Environmental Technology and Management Pages: 312-325 Issue: 4/5/6 Volume: 28 Year: 2025 Keywords: GIS spatial analysis; urban and rural construction land; layout planning; BP neural network; spatial analysis model. File-URL: http://www.inderscience.com/link.php?id=148985 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetma:v:28:y:2025:i:4/5/6:p:312-325 Template-Type: ReDIF-Article 1.0 Author-Name: Dong Liang Deng Author-X-Name-First: Dong Liang Author-X-Name-Last: Deng Author-Name: Xiong Chun Du Author-X-Name-First: Xiong Chun Author-X-Name-Last: Du Title: Fire warning of lithium battery energy storage power stations for environmental sustainable development Abstract: To enhance the precision of fire alerts for energy storage power stations and reduce the response time, a fire warning approach tailored for sustainable environmental development in lithium battery energy storage power stations is introduced. This method focuses on fires within lithium battery energy storage power stations, gathering data via temperature, smoke, and CO gas sensors, and employs the D-S evidence theory to fuse this data, quantifying uncertainty and facilitating information integration. Fire trends are simulated using the sigmoid membership function, with parameters dynamically adjusted to accurately discern fire indicators. Sensors relay data in real-time to the central computer, which promptly issues a warning upon confirming a fire. Experimental results indicate that the fire warning accuracy of the method proposed herein peaks at 95.3%, with a response time of no more than two seconds. Journal: Int. J. of Environmental Technology and Management Pages: 355-366 Issue: 4/5/6 Volume: 28 Year: 2025 Keywords: sustainable development of the environment; lithium batteries; energy storage power station; fire warning. File-URL: http://www.inderscience.com/link.php?id=148986 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetma:v:28:y:2025:i:4/5/6:p:355-366 Template-Type: ReDIF-Article 1.0 Author-Name: Yukai Hu Author-X-Name-First: Yukai Author-X-Name-Last: Hu Title: Evaluation of ecotourism environmental carrying capacity in nature reserves based on improved Bayesian network Abstract: To address the discrepancies between the assessment outcomes and the true evaluation outcomes, long time-consuming and low satisfaction rate of the traditional evaluation methods, an evaluation method of ecotourism environmental carrying capacity in nature reserves based on improved Bayesian network was proposed. Taking the coastal wetland nature reserve as the research object, this paper analyses the impact factors of ecotourism environmental carrying capacity, and establishes the evaluation index system. The evaluation model of ecotourism environmental carrying capacity based on an improved Bayesian network is established, and then the evaluation index data is added into the model to obtain the evaluation results of ecotourism environmental carrying capacity. The experimental results show that the evaluation results of the proposed method are consistent with the actual evaluation results, the maximum time is 5.3 min, and the satisfaction rate of bearing capacity evaluation results is 94%. Journal: Int. J. of Environmental Technology and Management Pages: 367-385 Issue: 4/5/6 Volume: 28 Year: 2025 Keywords: Bayesian network; nature reserves; ecotourism environment; carrying capacity. File-URL: http://www.inderscience.com/link.php?id=148987 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetma:v:28:y:2025:i:4/5/6:p:367-385 Template-Type: ReDIF-Article 1.0 Author-Name: Xiaohang Xiang Author-X-Name-First: Xiaohang Author-X-Name-Last: Xiang Title: Evaluation method of ecological quality of landscape architecture considering environmental pollution Abstract: To swiftly and precisely evaluate the ecological integrity of landscape design, a methodology that integrates environmental contamination factors into the evaluation of landscape architecture is introduced. Initially, various types of ecological pollution data are analysed, and a set of sensors are used to collect environmental pollution data. Subsequently, based on the collected pollution data and aiming at obtaining ecological pollution information, a monitoring framework for landscape ecological pollution is developed by applying self-organising neural networks. At the same time, a hierarchical index system for evaluating the ecological quality of landscape architecture is established. This system uses the multi-objective linear weighting method to calculate a comprehensive evaluation index, thus enabling a hierarchical evaluation of the ecological quality of landscape architecture. Empirical findings reveal that the proposed technique achieves an evaluation accuracy of 99.32%, while also reducing the duration required for evaluation. Journal: Int. J. of Environmental Technology and Management Pages: 326-340 Issue: 4/5/6 Volume: 28 Year: 2025 Keywords: environmental pollution; landscape architecture; ecological quality evaluation; comprehensive evaluation index. File-URL: http://www.inderscience.com/link.php?id=148988 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetma:v:28:y:2025:i:4/5/6:p:326-340 Template-Type: ReDIF-Article 1.0 Author-Name: Rachmawati Sugihhartati Dj Author-X-Name-First: Rachmawati Sugihhartati Author-X-Name-Last: Dj Author-Name: Gina Salsabila Author-X-Name-First: Gina Author-X-Name-Last: Salsabila Title: The relationship between the catchment area and water quality in the Upper Citarum River Abstract: Today, the water quality of the Indonesian Citarum River is deteriorating due to changes in land use within its catchment area. This study was conducted to assess the influence of land use on water quality in the river's upstream zone at two sampling points. The analysis of six parameters was performed using spectrophotometric methods. The results showed potential patterns of increased land use for settlements, agriculture, forests, and plantations (a 22% increase in total) from the upstream to the downstream regions, which contributed to an increase in ammonia, nitrite ions, and hydrogen sulphide beyond levels that could harm humans. A water safety plan is the right tool to handle this by implementing control measures to manage the risks from catchment areas into the river water used as a drinking water source, ensuring that safe water is delivered to customers. These measures include water treatment, land use management, and water resource management. Journal: Int. J. of Environmental Technology and Management Pages: 442-460 Issue: 4/5/6 Volume: 28 Year: 2025 Keywords: Citarum River; water quality; catchment area; land use; ammonia; nitrite; hydrogen sulphide; water safety plan; control measures; safe water. File-URL: http://www.inderscience.com/link.php?id=148989 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetma:v:28:y:2025:i:4/5/6:p:442-460 Template-Type: ReDIF-Article 1.0 Author-Name: Fangmin Chen Author-X-Name-First: Fangmin Author-X-Name-Last: Chen Author-Name: Zheng Ma Author-X-Name-First: Zheng Author-X-Name-Last: Ma Title: Carbon emission prediction method for urban regional energy system based on LSSVM Abstract: In order to address the issues of low mining rate, low prediction accuracy, and long time in traditional prediction methods, a carbon emission prediction method for urban regional energy system based on least squares support vector machine (LSSVM) is proposed. Filter the influencing factors of carbon emissions in urban regional energy systems, identifies abnormal influencing factor data using the density-based spatial clustering of applications with noise (DBSCAN) algorithm, reconstructs the data using a stacked denoising autoencoder. Using the reconstructed data as input for the model and the predicted carbon emissions as output, constructs a carbon emission prediction model for urban regional energy systems based on LSSVM and obtain relevant prediction results. The experimental results show that the mining rate of the influencing factors of the proposed method ranges from 96.7% to 98.2%, with a maximum prediction accuracy of 98.4% and an average prediction time of 0.81 seconds. Journal: Int. J. of Environmental Technology and Management Pages: 386-407 Issue: 4/5/6 Volume: 28 Year: 2025 Keywords: least squares support vector machine; LSSVM; urban regional energy system; carbon emission prediction; DBSCAN algorithm; stacked denoising autoencoder; SDAE. File-URL: http://www.inderscience.com/link.php?id=148992 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetma:v:28:y:2025:i:4/5/6:p:386-407 Template-Type: ReDIF-Article 1.0 Author-Name: Faten Aouay Author-X-Name-First: Faten Author-X-Name-Last: Aouay Title: Addressing barriers to innovation and eco-innovation: empirical evidence from Tunisia Abstract: Despite the extensive literature on eco-innovation, few studies analyse it in developing countries. Similarly, few studies address the barriers to eco-innovation. To fill this gap, this paper aims to analyse the barriers that prevent Tunisian firms from innovating and eco-innovating. It is evident that some firms face barriers to innovation and eco-innovation activities for various reasons. According to the survey conducted among 159 Tunisian industrial companies during the period 2018-2021, we find that 62% of them have failed to adopt and/or create eco-innovations. Using principal component analysis (PCA) and descriptive statistics, we identify three groups of barriers to eco-innovation: cost barriers, knowledge barriers and market barriers. However, limited financial availability and lack of mastery of new market needs are considered the main barriers for firms to innovate. Journal: Int. J. of Environmental Technology and Management Pages: 422-441 Issue: 4/5/6 Volume: 28 Year: 2025 Keywords: eco-innovation; innovation; barriers; industrial firms; principal component analysis; Tunisia. File-URL: http://www.inderscience.com/link.php?id=148995 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetma:v:28:y:2025:i:4/5/6:p:422-441 Template-Type: ReDIF-Article 1.0 Author-Name: Qinghai Ye Author-X-Name-First: Qinghai Author-X-Name-Last: Ye Title: Evaluation method for consumption capacity of renewable energy based on fuzzy DEA model Abstract: Dedicated to optimising the evaluation effect of consumption capacity, this paper designs an evaluation method based on fuzzy DEA model. Firstly, for the renewable energy system, its consumption capacity is preliminarily calculated. Secondly, from the perspectives of power grid operation, sustainable development, and economic returns, an evaluation index system is constructed. Thirdly, the weight and membership degree of the indicators are calculated. Then, the initial DEA model is constructed and fuzzification to the model is applied, adjusting the initial model based on the fuzzy efficiency score of each decision-making unit. Finally, the preliminary calculation results of consumption capacity of renewable energy, indicator membership degree, and weight are used as input information for the model to obtain the final evaluation result. In the experiment, the minimum value of the determination coefficient of the evaluation results obtained by this method can also reach 0.95, indicating that this method has achieved the goal of improving evaluation accuracy. Journal: Int. J. of Environmental Technology and Management Pages: 408-421 Issue: 4/5/6 Volume: 28 Year: 2025 Keywords: fuzzy DEA model; renewable energy; consumption capacity; capability assessment. File-URL: http://www.inderscience.com/link.php?id=148996 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetma:v:28:y:2025:i:4/5/6:p:408-421