One of the most critical problems faced by modern civilization is the depletion of freshwater resources due to their continuous consumption and contamination with different organic and inorganic pollutants. This paper considers the potential of already discovered MXenes in combination with carbon nanomaterials to address this problem. MXene appears to be a highly promising candidate for water purification due to its large surface area and electrochemical activity. However, the problems of swelling, stability, high cost, and scalability need to be overcome. The synthesis methods for MXene and its composites with graphene oxide, carbon nanotubes, carbon nanofibers, and cellulose nanofibers, along with their structure, properties, and mechanisms for removing various pollutants from water, are described. This review discusses the synthesis methods, properties, and mechanisms of water purification using MXene and its composites. It also explores the fundamental aspects of MXene/carbon nanocomposites in various forms, such as membranes, aerogels, and textiles. A comparative analysis of the latest research on this topic shows the progress in this field and the limitations for the practical application of MXene/carbon nanocomposites to solve the problem of drinking water scarcity. Consequently, this review demonstrates the relevance and promise of the material and underscores the importance of further research and development of MXene/carbon nanocomposites to provide effective water treatment solutions.

Gas sensors are essential for safety and quality of life, with broad applications in industry, healthcare, and environmental monitoring. As urbanization and industrial activities intensify, the need for advanced air quality monitoring becomes critical, driving the demand for more sensitive, selective, and reliable sensors. Recent advances in nanotechnology, particularly 1D nanostructures like nanofibers and nanowires, have garnered significant interest due to their high surface area and improved charge transfer properties. Electrospinning stands out as a promising technique for fabricating these nanomaterials, enabling precise control over their morphology and leading to sensors with exceptional attributes, including high sensitivity, rapid response, and excellent stability in harsh conditions. This review examines the current research on chemoresistive gas sensors based on 1D nanostructures produced by electrospinning. It focuses on how the morphology and composition of these nanomaterials influence key sensor characteristics—sensitivity, selectivity, and stability. The review highlights recent advancements in sensors incorporating metal oxides, carbon nanomaterials, and conducting polymers, along with their modifications to enhance performance. It also explores the use of fiber-based composite materials for detecting oxidizing, reducing, and volatile organic compounds. These composites leverage the properties of various materials to achieve high sensitivity and selectivity, allowing for the detection of a wide range of gases in diverse conditions. The review further addresses challenges in scaling up production and suggests future research directions to overcome technological limitations and improve sensor performance for both industrial and domestic air quality monitoring applications.

Nowadays numerous sorbents based on graphene and other carbon nanomaterials have been synthesized for the removal or collecting of oil remains due to its unique physico-chemical properties. Obtaining of aerogels based on graphene oxide and carbon nanotubes with addition of chitosan solution as a binder component is shown in this paper. Aerogels were synthesized by reduction of aqueous dispersion of graphene oxide using the reducing agents, followed by ultrasonic and thermal treatment. Ultrasound destroys the graphene layers, decreasing them in size, thereby exposing new layers to form edges that already have no stabilizing carboxyl groups, which are located at the edges, and participate in the formation of bonds. The surface morphology of obtained aerogels was studied by SEM. The study of the sorption capacity showed that graphene/CNTs aerogel is characterized by short absorption time and high sorption ability that depend on densities of the used solvents. All experimental results show the possibility of using the aerogels based on graphene and CNTs as sorbents for collection of oil residues.

The increasing reliance on electronic technologies has elevated the urgency of effective electromagnetic interference (EMI) shielding materials. This review explores the development and potential of magnetite-incorporated one-dimensional (1D) carbon nanostructure hybrids, focusing on their unique properties and synthesis methods. By combining magnetite’s magnetic properties with the electrical conductivity and mechanical strength of carbon nanostructures such as carbon nanotubes (CNTs) and carbon fibers (CFs), these hybrids offer superior EMI shielding performance. Various synthesis techniques, including solvothermal synthesis, in situ growth, and electrostatic self-assembly, are discussed in detail, highlighting their impact on the structure and properties of the resulting composites. This review also addresses the challenges in achieving homogeneous dispersion of nanofillers and the environmental and economic considerations of large-scale production. The hybrid materials’ multifunctionality, including enhanced mechanical strength, thermal stability, and environmental resistance, underscores their suitability for advanced applications in aerospace, electronics, and environmental protection. Future research directions focus on optimizing synthesis processes and exploring new hybrid configurations to further improve electromagnetic properties and practical applicability.

The air quality within urban public transport is a critical determinant of passenger health. In the crowded and poorly ventilated cabins of Almaty’s metro, buses, and trolleybuses, concentrations of CO₂ and PM_2.5 often accumulate, elevating the risk of respiratory and cardiovascular diseases. This study investigates the air quality along three of the city’s busiest transport corridors, analyzing how the concentrations of CO₂, PM_2.5, and PM₁₀, as well as the temperature and relative humidity, fluctuate with the passenger density and time of day. Continuous measurements were collected using the Tynys mobile IoT device, which was bench-calibrated against a commercial reference sensor. Several machine learning models (logistic regression, decision tree, XGBoost, and random forest) were trained on synchronized environmental and occupancy data, with the XGBoost model achieving the highest predictive accuracy at 91.25%. Our analysis confirms that passenger occupancy is the primary driver of in-cabin pollution and that these machine learning models effectively capture the nonlinear relationships among environmental variables. Since the surveyed routes serve Almaty’s most densely populated districts, improving the ventilation on these lines is of immediate importance to public health. Furthermore, the high-temporal-resolution data revealed short-term pollution spikes that correspond with peak ridership, advancing the current understanding of exposure risks in transit. These findings highlight the urgent need to combine real-time monitoring with ventilation upgrades. They also demonstrate the practical value of using low-cost IoT technologies and data-driven analytics to safeguard public health in urban mobility systems.