International Journal of Environmental Science and Green Technology

Assessment of Zero Waste Management Systems in Universities: Waste Reduction Efficiency and Environmental Benefits

2026-02-14T10:35:26+00:00

This paper presents an assessment of waste generation on the campus using experimental and analytical methods, within the framework of the concept of "zero waste." The study is based on an analysis of campus infrastructure data from 2016 to 2024, using index and normalized methods. The indicator of specific intensity of waste generation (kg/m ²· year) was calculated. It was revealed that the optimization of the campus structure, carried out after 2018 and including a reduction in the area and number of buildings, did not lead to a commensurate decrease in the volume of generated waste. The largest specific generation of waste was found in food outlets and student dormitories, where the share of organic matter in waste is from 55 to 65%. Academic buildings form more stable flows, mainly consisting of paper and mixed waste. The data obtained indicate the primary influence of the functional purpose of objects and the characteristics of user behavior on the volume of waste, and not the spatial characteristics of the infrastructure. The possibility of using the university campus as a pilot project for the introduction and further expansion of zero waste strategies in the higher education system of Central Asia is being considered.

CRISPR/Cas9 for Environmental Sustainability and Ecosystem Protection

2026-02-14T10:53:35+00:00

The development of CRISPR/Cas9 genome editing technology has revolutionized modern biotechnology, offering powerful tools not only for medicine and agriculture but also for addressing critical environmental challenges. This review examines recent advances in CRISPR/Cas9 technology with a particular focus on its applications in ecology and environmental sustainability. The use of CRISPR-based approaches enables the conservation of biodiversity through genetic rescue of endangered species and the control of invasive organisms that disrupt ecosystem balance. In addition, CRISPR/Cas9 has shown significant potential in environmental bioremediation by genetically enhancing microorganisms capable of degrading pollutants, including heavy metals, pesticides, and plastic waste. In agricultural ecosystems, genome editing contributes to the development of climate-resilient crops that reduce reliance on chemical inputs, thereby minimizing ecological damage to soil and water systems. The review also discusses ethical, ecological, and biosafety considerations associated with releasing gene-edited organisms into natural environments, emphasizing the need for robust regulatory frameworks. Overall, CRISPR/Cas9 represents a transformative technology for promoting ecosystem stability, environmental protection, and sustainable development under changing global conditions.

Fire Classification and Early Detection Using Convolutional Neural Networks Based on MobileNetV2 with Transfer Learning

2026-01-05T10:48:44+00:00

Since fires pose a great threat to human life, ecology, and economy, their early detection is a very important issue. In this research, a convolutional neural network model based on the MobileNetV2 architecture was developed and tested using the transfer learning method for automatic fire classification. The study used a binary database created as part of the NASA Space Apps Challenge 2018 competition, which consists of 755 outdoor images with and without fires. Despite the uneven nature of the database, an equal distribution of data was carried out in the pre-processing and validation set, taking into account the class imbalance. The model was initialized with MobileNetV2 weights pre-trained on the ImageNet database, and the final layers were adapted by fine-tuning. The training process was carried out with the Adam optimizer, categorical cross-entropy loss function, and early stopping callback. As a result, the model achieved 98.00% accuracy on the test set, and the test cost was 0.07776. According to the classification report, the precision value of the fire class was 0.98, the recall value was 1.00, and the F1-score was 0.99; the no-fire class was 1.00, 0.90, and 0.95, respectively. Confusion matrix analysis showed that all fire images were correctly identified and that there were only a few false positives. The simplicity of the MobileNetV2 model allows it to be used on resource-limited devices. The results obtained exceed those in the literature. The study contributes to the improvement of early fire detection systems and provides a ready-to-use solution for real-time monitoring.

Biodiversity Assessment of Wild Animal Species in Barware, Gulli, and Atroshe Areas of Duhok Governorate, Kurdistan Region of Iraq

2026-01-20T21:01:36+00:00

This study was conducted in Duhok Governorate in Iraq's Kurdistan Region and evaluated the mammalian biodiversity within the eighteen rural regions of Barware, Gulli, and Atroshe districts. The five important mammalian taxa with resident populations were identified and quantified such as D. dama, C. lupus, C. aegagrus, U. arctos), and Acinonyx jubatus venaticus. Data analysis examined significant distribution in species and found heterogeneousness in the charted areas, Wild Goat populations displaying remarkably higher prevalence with the n=338 noted observations while Asiatic Cheetah remained remarkably rare with (n=2 recognized findings. This study highlights the considerable biological value of mountainous territory which regarded as vital shelter for vulnerable fauna, the targeted conservation measures require to prevent the fauna from habitat decline and anthropogenetic battle dynamics.