Forthcoming Articles

International Journal of Environment and Health

International Journal of Environment and Health (IJEnvH)

Forthcoming articles have been peer-reviewed and accepted for publication but are pending final changes, are not yet published and may not appear here in their final order of publication until they are assigned to issues. Therefore, the content conforms to our standards but the presentation (e.g. typesetting and proof-reading) is not necessarily up to the Inderscience standard. Additionally, titles, authors, abstracts and keywords may change before publication. Articles will not be published until the final proofs are validated by their authors.

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International Journal of Environment and Health (4 papers in press)

Regular Issues

  • Phytochemical composition, antioxidant properties, and larvicidal activity of Ricinus communis leaf extracts against Culex pipiens and Culiseta longiareolata larvae   Order a copy of this article
    by Niamat Allah Chennaoui, Youssef Salama, Mohammed Chennaoui, Abdelhadi Makan 
    Abstract: Ricinus communis is a widely distributed plant in Morocco with promising potential for biological applications. This study investigated the phytochemical composition, antioxidant activity, and larvicidal efficacy of leaf extracts obtained using solvents of different polarities. Methanolic and ethyl acetate extracts were the richest in polyphenols, flavonoids, and condensed tannins, and exhibited the highest antioxidant activities. GC/MS analysis of the essential oil identified 65 compounds (99.9% of the total composition), mainly aldehydes, ketones, and oxygenated monoterpenes. The methanolic extract showed significant larvicidal activity against third- and fourth-instar larvae of Culex pipiens and Culiseta longiareolata, with LC50 values of 1.9 and 2.0 mg/mL, respectively. However, the larvicidal activity of the essential oil was not evaluated, representing a limitation of this study. Overall, these findings highlight the potential of R. communis methanolic extract as a natural larvicidal agent for vector control applications.
    Keywords: Ricinus communis; phytochemicals; antioxidant activity; larvicidal activity; Culex pipiens; Culiseta longiareolata.
    DOI: 10.1504/IJENVH.2026.10079234
     
  • Environmental and health consequences of sawmilling activities on workers in timber processing markets   Order a copy of this article
    by Dele Simeon, Fidelis O. Achi, Oyindamola Adedeyin, Akorede Esther Adesina 
    Abstract: Timber is an important resource for construction and furniture work. However, its manufacturing process poses risks to human health and nearby ecosystems. This study investigated the environmental and health consequences of sawmilling operations on workers. The study employed a multi-sampling technique, using both purposive and stratified sampling techniques to collect 128 questionnaires from medical practitioners and 405 from sawmilling workers in Lagos State. The study found that sawmills expose workers to 46 adverse health effects, categorized into 11 groups, including respiratory issues, noise-induced injuries, musculoskeletal illnesses, skin conditions, and eye injuries. Besides, the results revealed the prevalence of treatments provided for conditions such as exhaustion, eye redness, physiological disorders, and eye injury. Moreover, workers perceive sawmill environmental risks as significantly more severe than medical practitioners do. The study concludes that sawmilling workers continuously face preventable workplace hazards, and their productivity and health are likely to decline without adequate intervention.
    Keywords: lumber; occupational hazards; public health; sawmill; sawmilling activities; sawmilling workers; timber; wood; wood products.
    DOI: 10.1504/IJENVH.2026.10079444
     
  • Innovation, sustainability and AI in the food system: a thought-starter   Order a copy of this article
    by Sheraz Malik, Sara Abdulrahim Arafah 
    Abstract: Artificial intelligence (AI) has re-emerged as a crucial driver in complex food systems; however, concerns regarding its impact on overall sustainability remain. AI has impacted the food system at different stages, but three (pre-production, production, and post-production) are key to an in-depth understanding of its utility and risks. These stages must be viewed as supporting innovation and technology drivers within the broader context of the food supply chain. A modified comprehensive food system framework is suggested, which can integrate well with the diets of adolescents and children. An in-depth review has linked specific AI tools at these three stages of the food system to its sustainability dimensions. Broader areas of intersection are pest control, crop management, food safety, and tracking. In contrast, risks are associated with accessibility, economic viability, affordability, data integrity, and high energy use offering key direction for policy makers in food innovation and sustainability.
    Keywords: AI; food system; sustainability; food safety; food innovation.
    DOI: 10.1504/IJENVH.2026.10079692
     
  • Smart IoT network for indoor-air comfort monitoring and mould-risk prevention   Order a copy of this article
    by Andreja Naumoski, Georgina Mirceva, Tomislav Shuminoski 
    Abstract: Indoor mould growth threatens occupant health and imposes substantial remediation costs. This study presents a smart-home IoT sensor network that continuously measures temperature, relative humidity, and dew point to forecast mould-risk windows up to 45 days in advance. Over a threemonth residential deployment, high-frequency data acquisition and automated dewpoint-based algorithms were integrated via an OpenHAB-MQTT platform. Multi-platform alerts and automated environmental adjustments align with indoor-air-quality (IAQ) regulations, offering facility managers cost-effective, data-driven maintenance strategies. Using a predictive clustering trees (PCT) machine learning algorithm trained on real-time data, the system performs datadriven refinement of the dewpoint threshold. The model identified dewpoint as the dominant predictor, confirming the commonly used 13
    Keywords: IoT; Internet of Things; indoor mould risk; dewpoint monitoring; smart-home sensor networks; environmental health; machine-learning analytics.
    DOI: 10.1504/IJENVH.2026.10079833
     

 

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