International Journal of Environment and Pollution (8 papers in press)

Regular Issues

• Open Access

  Public service system for green and sustainable development in marketing based on blockchain technology ( Free Full-text Access )

  by Baitong Zhang 
  Abstract: This paper introduced the significance of green and sustainable marketing and the strategies for green marketing. It then indicated that green marketing requires the establishment of a complete public service system, and analysed multiple factors. It also indicated that the development of a green and sustainable marketing public service system should be combined with Internet of Things (IoT) technology, automated marketing public service system should be constructed. Subsequently, blockchain technology (BT) was introduced. The paper introduced its core technologies, including the consensus mechanism, encryption algorithm, and smart contract. It analysed their application in the green and sustainable development (SD) of the marketing public service system. In the simulation experiment section, the effectiveness of the green marketing public service platform system based on a blockchain mechanism was tested across three aspects: the transaction volume per second over a given time period, the number of successful and failed system links to customers.
  Keywords: sustainable development; green marketing; blockchain technology; public service system; IoT; Internet of Things.
  DOI: 10.1504/IJEP.2026.10076322
   
  

• Open Access

  Monitoring and sustainable management of soil microbial environmental quality based on machine learning ( Free Full-text Access )

  by Miao Wang, Yu Zhang, Zeyu Wang, Yuxin Zhang, Yankui Chen, Jiao Zhang, Yu Zhang 
  Abstract: Soil microbial environmental quality is an essential indicator of ecosystem health and agricultural productivity. However, current monitoring and management face challenges, including difficulty in integrating multi-source data and the poor sustainability of management measures. To address these issues, this article investigated a comprehensive method based on multimodal learning and graph neural network (GNN). By utilising multimodal learning models, multiple data sources including microbial sequencing, soil physicochemical properties, and climate data were integrated, and the features of each modality were extracted and fused. Using a GNN, the complex relationships between microorganisms and environmental factors were modelled to generate reliable predictions of ecological quality. Based on the predicted results, an adaptive management framework was designed to adjust management measures using real-time monitoring data dynamically. Finally, automatic optimisation of management strategies was achieved by applying a dynamic management system.
  Keywords: soil microorganisms; environmental quality monitoring; multimodal learning; sustainable management; adaptive management framework; machine learning; graph neural networks.
  DOI: 10.1504/IJEP.2026.10076702
   
  

• Open Access

  Ecological services and improvement strategies of forest healthcare space environment under the background of carbon neutrality ( Free Full-text Access )

  by Zechen Xiao, Rui Guo 
  Abstract: This paper proposes a multidisciplinary optimisation strategy for achieving a carbon sink-healthcare-biodiversity triple win. Integrating data, a collaborative evaluation system is established to assess carbon sinks and ecological services using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model. A spatial planning model optimises the layout of forest healthcare bases, balancing carbon sink efficiency with healthcare functions and employing the Nondominated Sorting Genetic Algorithm II (NSGA-II) algorithm and analytic hierarchy process (AHP) for plan selection. Additionally, a community carbon sink return-sharing mechanism is designed, to enhance government goals, enterprise returns, and community satisfaction. The results show that based on the high ecological benefits of 82% government ecological goal achievement rate and 13.4% annual carbon sink growth rate, the enterprise still maintains a 12.1% return rate and 85% community satisfaction. The multidisciplinary approach achieves a triple-win situation of collaborative optimisation of carbon sinks, healthcare, and biodiversity.
  Keywords: forest healthcare space; ecological services; carbon neutrality; spatial planning model; benefit sharing mechanism.
  DOI: 10.1504/IJEP.2026.10076703
   
  

• Open Access

  Optimisation of rural green supply chain promoting social sustainable development: a case study based on intelligent environmental impact assessment ( Free Full-text Access )

  by Zhao Guo, Hong Chen 
  Abstract: To effectively address the environmental challenges confronting rural enterprises, optimizing the supply chain while ensuring sustainability is of paramount importance. This study proposes a green supply chain optimization framework specifically designed for rural enterprises to assess and mitigate their environmental impacts. An enhanced Mamba structure is first introduced to identify congestion points within rural supply chains. By integrating these congestion nodes with environmental parameters, a multi-objective optimization (MOO) strategy is developed to simultaneously reduce pollution and minimize resource loss. This approach facilitates the establishment of a green supply chain tailored to the distinctive operational characteristics of rural enterprises. Experimental results reveal that the proposed congestion node detection system achieves an F-value of 0.824, while the environmental impact detection accuracy of the optimized supply chain reaches 0.845, indicating a substantial improvement in supply chain performance within rural contexts.
  Keywords: sustainable development; impact assessment; rural supply chain improvement.
  DOI: 10.1504/IJEP.2026.10076965
   
  

• Open Access

  Mapping carbon disclosure research: bibliometric analysis and frontier exploration ( Free Full-text Access )

  by Jiawei Shi, Razif Bin Rosli, Zixuan Yuan 
  Abstract: This study presents a comprehensive bibliometric analysis of the research literature on carbon disclosure, aiming to reveal its knowledge structure, evolutionary trajectory, and emerging frontiers. By conducting analysis based on 985 articles gathered from the Web of Science Core Collection (19822024) using CiteSpace indicates exponential growth in publications and a paradigm shift within the global research landscape. China has become a leading contributor, joining established nations such as the USA and the UK. The main thematic research clusters identified include: 1) institutional legitimacy and value addition; 2) stakeholder engagement and institutional governance; 3) inter-country comparisons; and 4) policy effectiveness and innovation complementarity. Burst analysis reveals a shift in the research frontier from legitimacy theory to strategic management, with green innovation and investment emerging as recent focal areas. The research paradigm has evolved from a compliance-driven approach to one that integrates disclosure with corporate strategy and sustainable finance. A substantial knowledge gap remains between policy-driven and innovation-driven research, and the growing significance of non-Western institutional contexts is emphasised.
  Keywords: carbon disclosure; CiteSpace; bibliometrics; stakeholders; green innovation.
  DOI: 10.1504/IJEP.2026.10076983
   
  

• Open Access

  Health impact assessment of the cooling benefits of urban green infrastructure from the resilience perspective ( Free Full-text Access )

  by Zhirui Huang, Liping Ouyang, Xuan Wang, Qianming Yang 
  Abstract: In order to address the difficulty of quantifying the cooling benefits of urban green infrastructure as health benefits and the lack of comprehensive resilience evaluation, this paper develops a systematic evaluation framework that integrates environmental and health data. Firstly, this paper retrieves urban surface temperature from land satellite remote sensing images; secondly, uses the ENVI met model calibrated with local parameters to simulate the cooling intensity and spatial range of different types of green spaces on typical heat wave days; then, combines population distribution with exposure response relationships established based on local epidemiological data, adds the Social Vulnerability Index (SVI); and finally conducts Multi Criteria Decision Analysis (MCDA). The research results indicate that the Gini coefficient of high-risk and highly vulnerable populations decreases from 0.68 to 0.52, and the coverage rate of high-risk communities increases to 78.3%.
  Keywords: urban green infrastructure; cooling benefits; health impact assessment; social vulnerability; climate resilience.
  DOI: 10.1504/IJEP.2026.10077053
   
  

• Open Access

  Impact of sewage treatment plants on local tourism and ecotourism ( Free Full-text Access )

  by Rui Guo, Yuanyu Zhang, Long Zhang 
  Abstract: Sewage treatment plants (STP) significantly impact local tourism and ecotourism by improving water quality, enhancing scenic accessibility, and boosting tourist experiences. This study analysed STP effects in Xian, comparing suspended solids and tourism revenue in four scenic areas in June 2023 and June 2025. Results showed STP reduced suspended solids, improved environmental quality, and increased tourism revenue. Specifically, scenic areas exhibited notable decreases in water pollutants and substantial increases in income. STP supports ecosystem protection, enhances tourism resources, and promotes sustainable development. This highlights STPs role in balancing environmental protection and tourism growth, offering insights for sustainable ecotourism strategies.
  Keywords: sewage treatment plant; local tourism; ecotourism development; tourism revenue; tourist satisfaction.
  DOI: 10.1504/IJEP.2026.10077146
   
  

• Open Access

  Evaluation of factors affecting expansion of weak-base ASP flooding based on grey correlation analysis combined with BP neural network ( Free Full-text Access )

  by Bo Sun, Jingming Fan, Min Wang, Yunfeng Zhang, Qinan Chen, Meiling Jiang 
  Abstract: This study proposes an innovative coupled evaluation framework that integrates grey relational analysis (GRA) and an improved backpropagation neural network (BPNN) to address the challenge of high prediction uncertainty caused by complex multi factor interactions in weak alkali, surfactant, and polymer (ASP) flooding. Firstly, a multidimensional dataset consisting of 12 geological and engineering parameters is constructed through systematic data preprocessing and feature extraction; subsequently, GRA is used to quantify the dynamic correlation between each factor and the swept volume expansion, enabling the screening of seven main control variables based on threshold values; then, a three-layer feedforward PNN is developed using momentum term and adaptive learning rate optimisation to accelerate convergence and enhance nonlinear mapping capability. The experimental results indicate that the proposed method accurately identifies porosity, permeability, and polymer concentration as key influencing factors. The average grey correlation coefficients are 0.86, 0.83, and 0.79, respectively.
  Keywords: weakly alkaline surfactant polymer flooding; data-driven; evaluation of influencing factors; GRA; grey relational analysis; BPNN; back propagation neural network.
  DOI: 10.1504/IJEP.2026.10077349