International Journal of Environmental Engineering (7 papers in press)

Regular Issues

• Citizens' Perceptions on the Implementation of Pay-As-You-Throw (PAYT) Systems: Case Study of the Municipality of Kozani  
  by Theodoros Adamidis, Dionysis Latinopoulos 
  Abstract: Municipal solid waste management is a critical environmental challenge that requires innovative and fair economic instruments to reduce waste generation. This work explores both public acceptance and the potential impact of PAYT systems in the Municipality of Kozani, Greece. A web-based survey of 456 residents was conducted, and a mixed-method framework was applied: a Multiple-Criteria Decision Analysis (using Visual PROMETHEE software) to rank four PAYT alternatives (Bag, Bin, Card, Weighing), a SWOT analysis to identify key internal and external factors, and a Contingent Valuation Method to estimate citizens' Willingness to Pay. Findings suggest that the PAYT with bag option is the most preferred system, while the mean WTP for a prepaid 45L bag was Euros 0.592. Citizens expressed strong support for a fair and transparent charging based on the polluter pays principle. The proposed methodology can serve as a transferable reference for Greek municipalities preparing to implement PAYT schemes in order to comply with EU waste policy and can also inform national and EU policy targets.
  Keywords: Municipal Solid Waste Management (MSWM); Pay-As-You-Throw (PAYT); Multi-Criteria Decision Analysis (MCDA); Contingent Valuation Method (CVM); SWOT Analysis.
  DOI: 10.1504/IJEE.2025.10075899
   
  
• Semantic Segmentation of High-Resolution Remote Sensing Images Based on Multi-Scale Convolutional Neural Networks  
  by Shanshan Cheng 
  Abstract: High-resolution remote sensing imagery provides detailed spatial and semantic information essential for applications such as urban planning, agriculture, and disaster monitoring. However, challenges including intraclass variability, complex backgrounds, and large data volumes make semantic segmentation difficult. While advanced CNN-based models such as DeepLabV3+, PSPNet, and U-Net demonstrate strong performance, they often struggle with small object detection and computational efficiency. Multi-scale and attention-based approaches offer improvements but remain limited in robustness for multi-objective remote sensing tasks. To address these challenges, this study proposes a Multi-Scale Feature Convolutional Neural Network (MSFCNN) that integrates 3 x 3, 5 x 5, and 7 x 7 convolution filters with data augmentation and dropout regularisation. The model, trained on augmented high-resolution satellite imagery using TensorFlow with optimised hyperparameters and a multi-branch CNN architecture, achieves notable performance gains. Experimental results show an F1-score improvement of 1.09%, and overall accuracy of 95% on WHU and LEVIR-CD datasets, outperforming baseline models.
  Keywords: Multiscale CNN; Semantic Segmentation; High-Resolution images; Remote sensing; like DeepLabV3+; PSP Net.
  DOI: 10.1504/IJEE.2026.10076202
   
  
• Building energy efficiency design based on the multi-objective optimisation and particle swarm optimisation algorithm  
  by Zhenjie Tang, Tianze Pang 
  Abstract: The increasing global energy demand necessitates building energy efficiency design as a key driver of sustainability. Traditional methods often prioritise single objectives, failing to meet comprehensive performance requirements. This study proposes a multi-objective evolutionary algorithm combined with an improved particle swarm optimisation algorithm for building energy efficiency design. A multi-surrogate model assists in reducing simulation costs and enhancing optimisation accuracy. Results demonstrate that the method achieves a better balance between energy consumption and comfort. Its energy consumption in single office buildings and multi-residential buildings was reduced by 29.58% and 0.67% respectively compared to the comparative method, and the duration of discomfort was reduced by 11.79% and 1.57% respectively. The optimised approach also decreases computation time substantially. This research provides an efficient and practical tool for sustainable building design, supporting energy conservation and carbon reduction in the construction sector.
  Keywords: multi-objective optimisation; particle swarm optimisation; PSO; architecture; energy consumption; surrogate model.
  DOI: 10.1504/IJEE.2026.10076234
   
  
• Measurement and influencing factors of green total factor productivity of cities in the Yangtze River Economic Zone  
  by Bizhen Chen, Fengjiao Ye 
  Abstract: The Yangtze River Economic Zone is an important pattern of China's economic planning. This paper collected the data of cities in the Yangtze River Economic Zone from 2006 to 2018, by applying the epsilon-based measure (EBM) method and global Malmquist-Luenberger (GML) index, calculated the green total factor productivity (GTFP), and analysed the distribution and influencing factors of GTFP in time and space. The main conclusions are as follows: 1) the overall GTFP of cities in the Yangtze River Economic Zone has shown an upward trend over time, while the development of cities in the middle and lower reaches is better than that of upstream cities; 2) the per capita GDP, the proportion of the tertiary industry, and the centralised treatment rate of sewage treatment plants can significantly promote the growth of GTFP, while the proportion of secondary industry and the number of students in colleges and universities have negative effects.
  Keywords: Yangtze River Economic Zone; green total factor productivity; GTFP; epsilon-based measure; EBM; global Malmquist-Luenberger; GML; fixed effect model; undesirable output; the industrial structure; urban construction; air and water pollution; environmental governance; education level.
  DOI: 10.1504/IJEE.2025.10073782
   
  
• The manifestation of the complex structure of plant communities in the tourism landscape planning of traditional villages  
  by Yi Lin 
  Abstract: Traditional villages are important tourism resources, and the study of their landscape planning has certain value. This paper mainly studied the plant communities of traditional villages. It took three traditional villages, A, B, and C, in Guangdong and three traditional villages, D, E, and F, in Guangxi as the subjects to analyse their plant communities and investigate the species situation in these villages. Moreover, the importance and diversity of the species were calculated. The results showed that villages A, B, and C had fewer arbour families and genera than villages D, E, and F, and the villages in Guangxi had more abundant species resources. Importance calculation revealed that the dominant species in villages A, B, and C were mostly evergreen trees, while those in villages D, E, and F were mostly deciduous trees. Diversity calculation showed that Village F had better diversity and uniformity in all layers.
  Keywords: plant community; complex structure; traditional village; landscape planning; tourism.
  DOI: 10.1504/IJEE.2025.10074049
   
  
• Low-carbon logistics and distribution scheme for smart city by integrating internet of things technology and improved genetic hybrid algorithm  
  by Yanyan Jin, Xia Chen, Kaiyuan Zhang 
  Abstract: To find the optimal path for distribution, the experiment proposes a low-carbon logistics and distribution path optimisation method for smart cities based on the internet of things (IoT) technology and ant colony genetic hybrid algorithm. On dataset A, when iterating up to 62 times, the average running time of this method (5.54 s) is less than other algorithms. When the full load factor was only 30%, the research method started to get the minimum total cost. The overall cost did not increase noticeably with the tax when the carbon tax was between 0 and 100 yuan/ton. It indicated that the businesses in this range found the carbon tax to be acceptable. The research technique yielded a shorter optimal distribution path distance of 18.69 kilometres, as demonstrated by the application comparison. These results can provide a new theoretical basis for the low-carbon logistics and distribution in the smart city.
  Keywords: low carbon; logistics and distribution; ant colony algorithm; ACA; genetic algorithm; smart city; internet of things; IoT.
  DOI: 10.1504/IJEE.2025.10074171
   
  
• ENVI-met simulation-based study on the impact of urban small-scale public green spaces on airborne particulate matter concentration  
  by Jie Zhao, Lei Feng 
  Abstract: Airborne particulate matter (APM) concentration significantly affects urban environmental quality and residents' health. To explore how small-scale public green spaces regulate APM, a site in Zhengzhou, Henan Province, was studied using field measurements and ENVI-met simulations. Results show a diurnal APM pattern characterised by a morning peak, early afternoon trough, and evening rebound. Microclimate factors - wind speed, temperature, and humidity - have greater influence than vegetation structure, with APM negatively correlated with wind speed and temperature, and positively with humidity. Spatial configuration, vegetation structure, and the ratio of green to hard surfaces notably affect APM reduction efficiency. Wind-permeable vegetation layouts enhance APM dispersion. Optimisation strategies include reducing hard pavement, adopting open and connected spatial layouts, and increasing mixed plant communities around the area, offering practical guidance for improving air quality and microclimate in high-density urban environments.
  Keywords: small-scale public green space; airborne particulate matter; APM; concentration; variation pattern; ENVI-met simulation.
  DOI: 10.1504/IJEE.2025.10075312