International Journal of Environmental Technology and Management (13 papers in press)

Regular Issues

• Plastic waste recycling product design based on sustainable concepts: study of improvement, developments, and innovations in Kampala City, Uganda  
  by Ibrahim Mugerwa, Jianxin Chen 
  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.
  Keywords: sustainable design; product design; recycled plastic products; urban waste management; Uganda.
  
  

Special Issue on: Environmental Science and Technologies for the Management of Natural Ecosystems and the Sustainable Development of Urban Areas

• Teak trees computational modelling to measure environmental contribution using functional-structural plant modelling  
  by Bryan Aleron, Ditdit Nugeraha Utama 
  Abstract: Teak trees (Tectona grandis) 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.
  Keywords: plant computational modelling; PCM; teak tree; environmental engineering; oxygen production; carbon sequestration; functional-structural plant modelling; FSPM.
  
  
• Hydraulic modelling and flood hazard zoning in rivers of the urban basin of Sulaymaniyah using 2D modelling with HEC-RAS and GIS  
  by Bahram Abdalrahman Faraj 
  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, aiming 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.
  Keywords: HEC-RAS; urban flood management; flood zoning map; water surface profile; hazard zone.
  
  
• Carbon emission calculation and control of agricultural product supply chain under the background of energy conservation and emission reduction  
  by Jing Xue, Jina Cui 
  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 x 106t.
  Keywords: energy conservation and emission reduction; agricultural product; supply chain; carbon emission calculation; control; AOA-LSTM model.
  
  
• Peak carbon emission prediction of expressway toll stations using GRA-LSTM under the dual carbon background  
  by Yali Liang, Zengli Fang, Fang Wang, Gaoling Li, Yongjian Guo 
  Abstract: In order to reduce the error of carbon emission peak prediction and shorten the prediction time, a 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, based on the collected carbon emission data, the grey correlation analysis (GRA) method is used 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.
  Keywords: dual carbon background; GRA-LSTM model; expressway toll stations; carbon emissions; peak prediction.
  
  
• Research on influencing factors of regional tourism carbon emission based on LMDI model  
  by Renzhong Jin 
  Abstract: n 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, collect carbon emission related data from the tourism industry and pre-process the data 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.
  Keywords: LMDI model; tourism industry; carbon emissions; influencing factors; bottom-up.
  
  
• A positive and negative balance accounting method for carbon emissions in parks based on K-nearest neighbour clustering algorithm  
  by Junzhi Song 
  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.
  Keywords: K-nearest neighbour algorithm; K-means clustering method; K-nearest neighbour clustering algorithm; secondary decomposition; carbon emissions.
  
  
• Evaluation method of landscape ecological quality based on remote sensing ecological index  
  by Xuming Cai 
  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.
  Keywords: grey correlation model; remote sensing ecological index; RSEI; PCA transformation; equidistant separation method; spatial statistical methods.
  
  
• Short-term load prediction of electric vehicle charging stations based on conditional generative adversarial networks  
  by Wei He, Xiao Wang, Yu Zhang, Rui Hua 
  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.
  Keywords: CGAN; electric vehicles; charging stations; short-term load forecasting; battery characteristics.
  
  
• Automatic classification method of construction waste based on machine vision  
  by Lei Zhang 
  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 segmtioned. 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.
  Keywords: machine vision; construction waste; automatic classification; histogram; maximum entropy segmentation.
  
  
• Study on comprehensive evaluation of environmental pollution in tourist attractions based on FCM algorithm  
  by Yurong Pan, Chaoyong Jia 
  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.
  Keywords: FCM algorithm; tourist attractions; environmental pollution; comprehensive evaluation; logarithmic processing; improved principal component analysis.
  
  
• Carbon flow tracking methods for power systems in energy conservation and emission reduction environments  
  by Chenghao Xu, Weixian Che, Baichong Pan 
  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, collect carbon emission data and extract features using Pearson correlation coefficients. 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 CO2, and it has strong anti-interference ability against data noise, demonstrating good carbon flow tracking performance.
  Keywords: energy conservation and emission reduction; power system; carbon flow tracking; neural networks; carbon emission factor; carbon emission intensity.
  
  

Special Issue on: Novel Decision Technology Analytics for Evaluating Sustainable Strategies and Environmental Operations

• Urban public transport planning methods under low carbon emission constraints  
  by Suli Zhang, Yulin Jiao, Xinhua Wang 
  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.
  Keywords: low carbon emissions; urban public transportation; transportation planning; particle swarm optimisation algorithm; adaptive mechanism.