International Journal of Environmental Engineering (11 papers in press)

Regular Issues

• Correlation between Digital Economy Development and Regional Carbon Emissions through Spatial Spillover Effects  
  by Bing Xia 
  Abstract: In order to study the correlation between the digital economy and carbon emissions, this paper constructed a multiple regression model involving the digital economy and carbon emissions for cities above the prefecture level in China. Moreover, the spatial spillover effect was analyzed by introducing the spatial weights among cities during the construction process. It was found that the development of the digital economy had a spatial spillover effect and can effectively reduce local carbon emissions and drive green transition of industries. The research findings of this paper offer theoretical support and empirical evidence for developing interregional collaborative carbon reduction strategies.
  Keywords: digital economy; regional carbon emissions; spatial spillover effect; regression analysis.
  DOI: 10.1504/IJEE.2025.10073468
   
  
• Optimum and Multi-Objective Operation Based on the Economic and Pollution Aspects of a Multiple Energy System in Connection with the Upstream Electricity and Natural Gas Networks, Considering Renewable Sources  
  by Fan Bu, Weihao Ren 
  Abstract: This study addresses the environmental challenges posed by growing reliance on fossil fuels, highlighting the urgent need for sustainable energy systems amid rising fuel consumption and limited non-renewable resources. The research focuses on improving the efficiency of a multi-energy system integrated with both electric and natural gas networks, aiming to meet thermal and electrical demands sustainably. The proposed model pursues dual objectives: minimizing operational costs and reducing greenhouse gas emissions. Renewable sources, including solar panels and wind turbines, are employed, while a scenario generation technique manages the uncertainties of renewable energy production. Optimization is performed using the Simple Augmented -Constraint Method (ECM), and the fuzzy min-max approach selects the most balanced outcome. Simulation results demonstrate superior performance over traditional methods by avoiding suboptimal solutions. This work offers valuable insights into integrating renewable energy with advanced optimization techniques for environmentally and economically efficient multi-energy systems.
  Keywords: Multi-Energy Systems; Renewable Energy Integration; Multi-Objective Optimization; Load Management Program (LMP); Simple Augmented ?-Constraint Method; Fuzzy Min-Max Decision Method.
  DOI: 10.1504/IJEE.2025.10073618
   
  
• Urban and Rural Landscape Design Analysis Technology based on Image Semantic Segmentation Deep Learning and Remote Sensing Image Processing  
  by Xuen Hou, Qiuyue Shan 
  Abstract: This study addresses the rising demand for high-quality urban and rural environments by proposing a deep learning-based landscape analysis method. Utilising image semantic segmentation and remote sensing, the researchers collected and pre-processed landscape data, applying the Deeplab-v3+ model for segmentation. Through optimization, an improved version of Deeplab-v3+ was developed, showing significantly enhanced performance. Compared to X-DeepLab-v3+ and the original Deeplab-v3+, the optimised model achieved up to 58.3% higher intersection-over-union and 47.6% higher pixel accuracy. Additionally, it demonstrated strong alignment with real-world compactness and connectivity values, reaching 99% and 98% respectively. The model enables precise analysis of landscape fragmentation and ecological connectivity, offering valuable insights for environmental protection and landscape design.
  Keywords: Image semantic segmentation; Deeplab-v3+; Deep learning; Landscape analysis; Remote sensing image processing.
  DOI: 10.1504/IJEE.2025.10073759
   
  
• 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 centralized 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; GTFP; EBM; GML; fixed effect model; undesirable output; the industrial structure; urban construction; air and water pollution; environmental governance.
  DOI: 10.1504/IJEE.2025.10073782
   
  
• Automatic Extraction Method of Water Body Boundaries in Remote Sensing Images based on Deep Residual Network  
  by Qianchen Yang 
  Abstract: Water body extraction, which classifies each pixel in an image as either water or background, is a fundamental task in land-cover categorization. Accurate identification of water bodies is critical for urban hydrology applications such as water resource management and flood warning systems. While traditional index-based methods like NDWI and MNDWI have been widely used, deep convolutional neural networks (DCNNs) have recently shown promising improvements. However, training these networks requires large volumes of high-quality labe led data, which is often limited in remote sensing. Additionally, resulting in class imbalance. To address these challenges, we propose the Patch Adaptive Network (PAN), a novel data augmentation strategy. PAN improves performance across various models and datasets, yielding an average increase of 0.749 in mean Intersection over Union (m Io U). Moreover, PAN surpasses previous benchmarks without altering model architecture and demonstrates the added value of incorporating multispectral data.
  Keywords: Patch Adaptive Network (PAN); StyleGAN2; Dandelion Optimisation (DO); RGB/NIR; Binary Cross Entropy (BCE).
  DOI: 10.1504/IJEE.2025.10073857
   
  
• Research on Opportunities and Challenges of Ecological Environment Protection in Hebei Province From the Perspective of Big Data from 2013 to 2022  
  by Ying Zhao 
  Abstract: From 2013 to 2022, the ecological environment in Hebei Province has undergone historic, transformative, and global changes, which is one of the most significant areas of change in the past decade. This article takes Hebei Province as the research object, comprehensively evaluates environmental carrying capacity of the region over the past decade, analyzes its spatiotemporal evolution characteristics, and studies the structural and governance system of the ecological environment. The research results indicate that While the carrying capacity of the ecological e surroundings continues to improve, the foundation for a stable and positive ecological environment in Hebei Province is not yet solid. The turning point from quantitative change to qualitative change has not yet arrived, and it is still during a vital stage of pressure accumulation and progress under serious loads. Hebei Province has significant geographical advantages and a good development foundation.
  Keywords: big data; Ecological environment; protection.
  DOI: 10.1504/IJEE.2025.10073862
   
  
• The confined spaces and their additional risks: the reality of condominiums in Recife and greater Recife  
  by Cláudia Cândida De Lima Eustáquio, Felipe Mendes Da Cruz, Rogério Pontes De Araújo, Augusto César Cabral Santos 
  Abstract: Hazardous atmospheres pose significant risks to activities conducted in confined spaces, resulting in fatalities. The objective of this article is to investigate the atmospheric risks in confined spaces in condominiums, as well as to analyse the additional risks present in these locations, considered to be relevant. To this end, inspections were conducted in a commercial condominium and fifteen residential condominiums, applying a research checklist to characterise the confined spaces. A field experiment, using r apid-response sensors, was also conducted to measure the presence of gases and the deficiency or enrichment of oxygen in the business condominium. Measurements of concentrations and oxygen levels analysed the gases O₂, CO, CO₂, H₂S, and LEL and did not reveal the presence of harmful agents to the health, safety, and life of workers, according to the standard parameters. As for the residential condominiums, it was found that the risk of falls from height was very significant.
  Keywords: confined spaces; additional risks; hazardous atmospheres; atmospheric risks; rapid-response sensors.
  DOI: 10.1504/IJEE.2025.10071403
   
  
• Carbon footprint detector: an empirical approach for green and clean energy in smart cities  
  by Rohit Rastogi, Aditya Gola, Aditya Raj 
  Abstract: In the wake of high technology, carbon emission has increased that raises environmental degradation as a natural consequence. It threatens environmental sustainability and encourages persons and organisations to measure and minimise their carbon footprint. The article deals with designing and implementing a carbon footprint detector, a tool that attempts to measure and track carbon emissions according to the activities and patterns of consumption by users. It uses a combination of input data in terms of energy usage, kinds of transportation used, and product consumptions calculated for carbon equivalent emissions. The tool can also offer recommendations on how to reduce the overall carbon footprint in a household. Real-time feedback and historical data tracking help inform further, more sustainable choices. This detector acts as a very vital tool for raising awareness over some of the major behavioural changes that lead toward sustainability goals. Further, it gives simple solutions to solve excess carbon footprint at household levels.
  Keywords: air quality index; AQI; PM 2.5; PM 10; carbon footprint; green energy; climate change; sustainable development; human health; sustainable society; climate crisis; global warming.
  DOI: 10.1504/IJEE.2025.10071169
   
  
• Ecological evaluation of electromechanical equipment installation in environmental protection engineering  
  by Lingjian Wang, Jian Li, Guohu Luo, Jinmei Guo, Qiuxiang Yu 
  Abstract: This study aims to improve the installation technology of environmental engineering electromechanical equipment, enhance installation quality and ecological environment management level. This study used data review, survey interviews, and other methods to preliminarily identify safety risk factors in the construction of mechanical and electrical installation engineering, and evaluated them using the LEC evaluation method. Based on this, this article constructs a safety risk assessment index system and evaluation standards for mechanical and electrical installation engineering construction, and verifies the feasibility and reliability of the risk assessment system through specific engineering project examples. The research results indicate that the newly developed integrated configuration system for electromechanical equipment can help improve the efficiency and professionalism of designer configuration scheme design, and promote sustainable development in the field of architecture.
  Keywords: environmental protection engineering; mechanical and electrical equipment installation; ecological risk; risk assessment index system.
  DOI: 10.1504/IJEE.2025.10073089
   
  
• Machine learning approach for the estimation of the maximum dry density and optimum moisture content of the stabilised soils  
  by Jianmei Feng 
  Abstract: This research presents a machine learning framework to assess the maximum dry density and optimal moisture content of cement-stabilised soils. Two predictive models random forest regression and Gaussian process regression were created and refined by red-tailed hawk optimisation and sand cat swarm optimisation, yielding hybrid models. The random forest regression model, optimised by red-tailed hawk optimisation, exhibited exceptional performance, attaining coefficients of determination of 0.988 in training, 0.979 in validation, and 0.978 in testing for predicting maximum dry density, with corresponding root mean square error values of 30.72, 24.64, and 42.11, respectively. The model attained coefficients of determination of 0.993, 0.992, and 0.978. The random forest regression model augmented by red-tailed hawk optimisation demonstrated superior accuracy and reliability, serving as an effective instrument to diminish dependence on laborious laboratory testing and raise the efficiency of construction methodologies.
  Keywords: cement-stabilised soil; maximum dry density; MDD; optimum moisture content; OMC; machine learning; random forest regression; RFR; Gaussian process regression; GPR; red-tailed hawk optimisation; RHO; sand cat swarm optimisation; SCSO; soil compaction prediction.
  DOI: 10.1504/IJEE.2025.10073842
   
  
• Flame retardant pollution and economic coordinated development based on risk assessment and PCA-MLR method  
  by Li Li, Liang Li 
  Abstract: This study proposes a pollution and health risk assessment method based on risk assessment and principal component analysis multiple linear regression for flame retardant pollution in economically developed areas. This method uses hazard index and carcinogenic risk to assess its health impact and extracts the main influencing components using principal component analysis. Experiments have shown that the content of flame retardants in soil has gradually increased along the river flow direction, with values of 189 ng/g, 122 ng/g, and 48 ng/g in urban, suburban, and rural areas, respectively. Decabromodiphenyl ether had the highest contribution rate to the flame retardant content in soil, with an average of 82.5%, which was 73.3% and 76.3% higher than pentabromodiphenyl ether and octabromodiphenyl ether. Therefore, this study can effectively evaluate the pollution situation of flame retardants in soil and promote the coordinated development of pollution control and social economy.
  Keywords: polybrominated diphenyl ethers; PBDEs; flame retardant; PCA-MLR; risk assessment; coordinated economic development; CED.
  DOI: 10.1504/IJEE.2025.10072625