Search Results (5,623)

Cooking-related emissions represent a major contributor to indoor air pollution in residential kitchens, producing complex mixtures of volatile organic compounds (VOCs), odor-causing gases, oil vapors, particulate matter (PM_2.5), and combustion-related pollutants (CO and NO_x). In this study, a controlled ozone-assisted oxidation approach was integrated into a recirculating (ductless) domestic kitchen hood equipped with a confined reaction chamber and experimentally evaluated under closed-loop operating conditions where treated air was returned to the indoor environment after post-treatment. A multivariate Response Surface Methodology (RSM) framework based on the Box–Behnken design was employed to quantify and optimize the coupled effects of temperature (20–30 °C), relative humidity (40–60%), ozone dosage (1–3 ppm within the confined reaction zone), and airflow rate (150–250 m³/h) on multi-pollutant removal performance. The results demonstrate that ozone assistance substantially improves the abatement of oxidation-sensitive pollutants, particularly VOCs and odor, while airflow rate strongly governs transport-dominated pollutants such as PM_2.5 and oil vapors. In contrast, CO and NO_x exhibited limited improvement, indicating that ozone-assisted oxidation alone is insufficient for comprehensive control of combustion-related gases under short-residence-time recirculating hood conditions. The main contribution of this work is the implementation of a demand-driven ozone management strategy, supported by dual ozone sensing for reaction-zone control and outlet safety verification, where ozone generation is activated only in the presence of reactive gaseous pollutants and automatically reduced or terminated once pollutant concentrations fall below predefined thresholds, minimizing unnecessary oxidant release. Residual ozone downstream of the reaction stage was continuously monitored to prevent excess ozone return to the occupied zone. Overall, the proposed closed-loop, feedback-controlled ozone-assisted recirculating range hood concept demonstrated device-level reductions in measured VOC/odor signals under controlled conditions, while also highlighting the need for complementary post-treatment components for particle- and combustion-related pollutants. However, the potential formation of secondary oxidation byproducts was not characterized in this study, and therefore the results should be interpreted with respect to device-level pollutant removal rather than comprehensive indoor air quality improvement. Full article

Indoor speech propagation causes minute vibrations in surrounding objects, enabling remote speech recovery through passive eavesdropping. Unlike traditional methods that rely on acoustic waves, passive eavesdropping uses object vibrations, making it difficult to defend against, even in soundproof environments. However, weak vibration signals and noise interference make speech recovery challenging. Existing studies mainly focus on deep learning for signal reconstruction, requiring large datasets and high computational power, which complicates real-time, on-device deployment. To address this, we propose a lightweight passive speech recovery system based on millimeter-wave radar. Without prior knowledge of object locations or numbers, the system can adaptively fuse multi-source signals for real-time speech reconstruction. To counteract the noise characteristics of millimeter-wave radar and the weak amplitude of vibration signals, we designed a set of low-complexity noise suppression and signal enhancement algorithms, ensuring efficient operation on edge devices. Experimental results demonstrate that in single-target scenarios, the proposed system achieved a Mel Cepstral Distortion (MCD) of 3.923 and a Word Error Rate (WER) of 12.9%. In multi-target scenarios, the SNR improved by 3.65 dB, MCD decreased by an average of 1.52, and WER decreased by an average of 15.83%, making the method effective and practical in complex acoustic environments. Full article

Standard 16000-8 of the International Organization for Standardization (ISO 16000-8) specifies the assessment of ventilation performance using age-of-air concepts and tracer gas techniques. Since its publication in 2007, ventilation systems and assessment practices have evolved considerably, driven by increased use of mixed-mode and decentralized ventilation and advances in modeling and measurement technologies. This review examines how ISO 16000-8 can be modernized to harmonize with adjacent ventilation and indoor air quality standards while remaining applicable to contemporary systems and emerging approaches. A structured literature search of Web of Science and Google Scholar identified 76 studies (2007–2026) that engage with ISO 16000-8, age-of-air metrics, or tracer gas-based assessment. The literature was synthesized qualitatively using the framework of Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA), classifying studies into performance assessment, measurement–simulation convergence, and standardization discourse. The synthesis shows that while the conceptual foundations of ISO 16000-8 remain valid, assumptions of homogeneous mixing and steady-state conditions are often violated in real buildings, leading to inconsistent application of age-of-air indicators. Field and laboratory studies under point-source conditions demonstrate reduced ventilation effectiveness of 0.73–0.82 in classrooms and 0.5–1.4 in various indoor environments, instead of ≈1 for perfect mixing. Spatial heterogeneity is also observed in mixed-mode systems, with an efficiency around 0.5. In decentralized and façade-integrated systems, air exchange effectiveness deviates from theoretical expectations, indicating inhomogeneous air renewal and short-circuiting. Field measurements show configuration-dependent discrepancies in air exchange rates (e.g., carbon dioxide vs. perfluorocarbon tracer methods under varying door positions), while wind induces time-varying infiltration. Collectively, the literature demonstrates systematic violations of well-mixed and steady-state assumptions underpinning ISO 16000-8. Fragmentation between ventilation performance standards and indoor air quality regulation limits practical uptake. Emerging experimental, numerical, and data-driven methods complement ISO 16000-8, provided applicability domains and uncertainties are addressed. The review concludes that ISO 16000-8 should be modernized toward a harmonized, performance-based framework integrating diverse ventilation systems and assessment technologies. Full article

Quantifying moisture transport through building envelope materials is vital for durability, energy efficiency, and healthy indoor environments. Water vapour diffusion resistivity (µ-value) is a key parameter for hygrothermal modelling, moisture control, and mould risk assessment. Globally, data for solid wood species are scarce, and in Australia—despite the rising use of plantation-grown timber—critical hygrothermal properties remain undocumented. To close this gap, this study experimentally evaluated Eucalyptus nitens, a plantation-grown hardwood widely used in Australian construction. Solid-wood specimens prepared from industry-sourced boards were tested at 23 °C and 50% RH using both the wet-cup and dry-cup methods of the gravimetric technique. For wet-cup tests, µ-values ranged from 24 to 33; for dry-cup tests, µ-values ranged from 179 to 273, showing clear variability linked to differences in relative humidity. Experimental issues included surface cupping, sealing integrity, and extended equilibration time during dry-cup testing. These findings provide the first empirical µ-value dataset for E. Nitens under moderate-humidity conditions, delivering essential input parameters for hygrothermal models and supporting moisture-safe, energy-efficient design strategies for the broader construction sector. Full article

The building façade serves as the primary interface between the built environment and external climate, marking the transition from static regulation to dynamic response in climate-adaptive design. While existing research predominantly addresses periodic climatic elements such as temperature and solar radiation, the highly stochastic wind environment and its potential for internal acoustic problems remain systematically unexplored. This study investigates the acoustic modulation mechanism of building façades under dynamic wind conditions through a simulation-based methodology. The primary aim is to demonstrate the use of active control to mitigate the influence of fluctuating wind on the internal acoustic environment of buildings with open windows or semi-open boundaries, focusing on the coupling between stochastic wind fields and architectural acoustics in humid subtropical climates. We propose a wind-responsive adaptive acoustic façade system employing fractal geometry and configurable delay strategies, and develop a high-fidelity simulation framework to quantify how façade geometry and activation logic regulate acoustic parameters under varying wind conditions (1–8 m/s). Results indicate that: (1) support vector regression-based mapping of wind speed to delay strategies maintains key sound-field parameters (Lateral Fraction (LF), Speech Clarity (C₅₀), and Early Decay Time to Reverberation Time ratio (EDT/RT₃₀)) within 10% fluctuation across wind regimes; (2) fractal configurations achieve balanced wide-band (125 Hz–8 kHz) performance, with SPL fluctuation <3 dB, spectral tilt (+0.3 dB), and reverberation time slope <0.3; (3) configurational switching between column (high LF) and row (high C₅₀) arrangements enables dynamic trade-off between spatial impression and speech clarity. This work establishes an integrated framework coupling wind dynamics, façade morphology, and acoustic modulation to regulate objective indoor acoustic parameters. Based on the simulated omnidirectional point-source model, the results show that key acoustic indicators remain stable across varying wind conditions, providing a theoretical and quantifiable basis for climate-responsive acoustic envelope design. Future work will include empirical prototype testing and listening tests to determine whether these simulated acoustic parameters translate into improved comfort and well-being for occupants. Full article

A compact and low-profile S-slot antenna for millimeter-wave wireless communication applications is presented in this paper. The antenna employs an S-shaped slot etched within a ground plane and excited by a hook-shaped microstrip feeding line to radiate a linearly polarized wave with a bidirectional broadside radiation beam. The antenna geometrical parameters are optimized to cover the n257 and n261 5G bands of the 5G mobile communications. The proposed antenna is fabricated and measured. Simulated and measured results demonstrate good impedance matching, with a measured fractional bandwidth of 18.3% and a maximum realized gain of 4.8 dBi across the desired operating bandwidth for the S-slot antenna with extended ground plane necessary for the purpose of measurements. The performance remains largely unaffected when the ground plane is reduced, highlighting the antenna’s suitability for compact implementations. Consequently, the proposed antenna is well suited for indoor 5G small-cell deployments and future railway wireless communication systems. Moreover, it can serve as a unit element in MIMO arrays or larger antenna configurations. To further demonstrate scalability and system-level applicability, the antenna element is extended into a compact eight-element MIMO array providing dual linear polarization. The array exhibits low mutual coupling, an envelope correlation coefficient on the order of ${10}^{-3}$, and a diversity gain approaching 10 dB. These results demonstrate highly independent radiation characteristics and reliable MIMO performance in multipath environments. Full article

The onset of the COVID-19 pandemic prompted the rapid development and deployment of novel strategies and methodologies to manage the dissemination of microorganisms. Understanding the crucial role that contaminated surfaces play in the spread of viruses highlights the importance of having effective cleaning and disinfection protocols in place for inanimate objects. A variety of antimicrobial agents have shown strong effectiveness against the SARS-CoV-2 virus. Various factors can impact on the performance of these agents. As a result, technologies utilizing ozone’s microbicidal effects have been developed or improved for cleaning indoor areas, surfaces, and materials, despite ozone’s diverse uses being known for years. Ozone offers the advantage of adaptability for both gaseous and aqueous use, depending on the nature of the decontaminated surfaces. Moreover, ozone-infused water is ecologically benign, possesses microbial-fighting capabilities, and synergistically reinforces the biocidal action of other chemical disinfectants. This review aims to summarize the efforts dedicated to harnessing gaseous and aqueous ozone as a valuable means to eliminate the SARS-CoV-2 virus from environments, surfaces, clinical equipment, and office supplies. This review sourced evidence-based articles from electronic databases, including MEDLINE (via PubMed), EMBASE, the Cochrane Library (CENTRAL), and preprint repositories. The findings illustrated that ozone could serve as an additional tool for curbing the proliferation of COVID-19 and other viral infections. Additionally, we elucidated the operational attributes of ozone, the variables that influence its disinfection potency, and the mechanisms of its virucidal action. Notably, this review does not encompass the disinfection of the COVID-19 virus in wastewater. Full article

Fine particulate matter PM_2.5 continues to pose a critical public health risk in Northern Thailand, particularly in Chiang Mai, where traditional filtration methods often face limitations in cost and efficiency for large-scale applications. This study introduces a novel “Evaporator Condensation Growth Particle Scrubber (ECGP)” designed to enhance the collection efficiency of sub-micron particles by enlarging their physical size through a pressure-driven growth mechanism. The ECGP system utilizes synergistic effects between solid nuclei, high relative humidity, and mechanical pressure modulation. The ECGP system integrates solid nuclei, ~95% relative humidity and mechanical pressure modulation within a single chamber. Using incense smoke as a PM surrogate, the process utilizes controlled adiabatic cycles to induce stable heterogeneous condensation. The results indicate that the integrated process effectively shifts particle size distribution, reducing the PM_2.5/PM₁₀ mass ratio from 1.00 to 0.83. This indicates that approximately 17.5% (with a standard deviation < 1% across 10 trials, p < 0.05) of the fine mass successfully transitioned into the larger, more filterable PM₁₀ fraction and exhibited high physical stability and resistance to re-evaporation, effectively overcoming the low-efficiency threshold (typically <10%) of standard mechanical scrubbers and cyclones for sub-micron dust. This study concludes that ECGP technology offers a promising, cost-effective alternative for improving indoor air quality in large public infrastructures by leveraging particle inertia for enhanced removal, providing a scalable solution to the persistent smog crisis. Full article

Heating, ventilation, and air conditioning (HVAC) systems are essential for indoor air quality and thermal comfort but can simultaneously act as vectors for microbial contamination, particularly bacteria and fungi. While the COVID-19 pandemic intensified focus on airborne viral transmission, bacterial and fungal contamination in indoor environments remains a persistent and significant health risk. This study presents a detailed case study of a restaurant HVAC system, analysing the impact of different ventilation strategies on bacterial contamination, infection transmission risk, energy consumption, and thermal comfort. By focusing on a real-world application, the research evaluates practical challenges and trade-offs associated with HVAC operation modifications aimed at mitigating microbial risks while maintaining acceptable energy and comfort levels. The research compares three operational scenarios: normal operation with air recirculation, 24 h operation with 100% outdoor air, and extended operation periods. Results demonstrate that while strategies emphasizing outdoor air intake and extended operation reduce infection probability by up to 60–65%, they simultaneously increase energy consumption by over 1700% and compromise thermal comfort parameters. In the h24 case, the pre-heat coil rises from 2421.7 to 43,923.7 kWh and the post-heat coil from 24,812.8 to 152,970.4 kWh, while the Plus 2 h strategy reduces the energy penalty by roughly 42–51% with respect to the h24 case. The findings are contextualized within current research on bacterial and fungal risks in HVAC systems, highlighting the critical need for balanced ventilation strategies that integrate health protection, energy efficiency, and comfort considerations. Full article

Ultra-wideband (UWB) technology has been widely adopted for indoor positioning due to its high temporal resolution. However, the accuracy of UWB-based indoor positioning is fundamentally limited by ranging measurement errors, particularly under non-line-of-sight (NLOS) conditions, where systematic bias and uncertainty are introduced into the measured distances. In this paper, a measurement error mitigation method is proposed to improve UWB ranging reliability in complex indoor environments. The method first identifies NLOS measurements using low-dimensional physical features and a lightweight machine learning classifier. Subsequently, an error compensation strategy is applied to correct biased ranging observations, which are then incorporated into a nonlinear least squares positioning model. Experimental results obtained in typical indoor environments demonstrate that the proposed method significantly reduces ranging errors and improves positioning accuracy compared with conventional approaches. The results indicate that the proposed framework effectively enhances measurement robustness without increasing system complexity. Full article

Traditional pedestrian inertial navigation (PDR) algorithms usually assume that the carrying mode of a smartphone is fixed and remains horizontal, while ignoring the significant impact of dynamic changes in the carrying mode on heading estimation, which is the core element of PDR algorithms. In practical application scenarios, pedestrians often change their way of carrying smart terminals (e.g., calling) according to their needs, corresponding to the difference in the heading estimation method; especially when the mode is switched, it will cause a sudden change in heading, which will lead to a significant increase in the localization error if it cannot be corrected in time. Existing smart terminal carrying mode recognition methods that rely on traditional machine learning or set thresholds have poor robustness; lack of universality, especially weak diagnostic ability for mutation; and can not effectively reduce the heading error. Based on these practical problems, this paper innovatively proposes a PDR framework that tries to overcome these limitations. Based on this research purpose, firstly, this paper classifies four types of common carrying modes based on practical applications and designs a CNN-LSTM hybrid model, which can classify the four common carrying modes in near real-time, with a recognition accuracy as high as 99.68%. Secondly, based on the mode recognition results, a multi-layer heading correction strategy is introduced: (1) introducing a quaternion-based universal filter (VQF) algorithm to realize the accurate estimation of initial heading; (2) designing an algorithm to accurately detect the mode switching point and developing an adaptive offset correction algorithm to realize the dynamic compensation of heading in the process of mode switching to reduce the impact of sudden changes; and (3) considering the motion characteristics of pedestrians walking in a straight line segment where lateral displacement tends to be close to zero. This study designs a heading optimization method with lateral displacement constraints to further inhibit the drifting of the heading caused by the slight swaying of the smart terminal. In this study, two validation experiments are carried out in two different environment—an indoor corridor and a tree shelter—and the results show that based on the proposed multi-layer heading optimization strategy, the average heading error of the system is lower than 1.5°, the cumulative positioning error is lower than 1% of the walking distance, and the root mean square error of the checkpoints is lower than 2 m, which significantly reduces the positioning error and shows the effectiveness of the framework in complex environments. Full article

Reliable change detection in indoor environments remains a challenge for autonomous robotic systems using 3D LiDAR. Existing methods often require manual annotation, computationally intensive architectures, or focus on outdoor scenes. This paper presents SPICD-Net, a lightweight Siamese PointNet framework for indoor 3D change detection trained exclusively on synthetically generated anomalies, eliminating manual labeling. The framework offers three deployment-oriented contributions: a three-class Siamese formulation separating no-change, changed, and geometrically inconsistent tile pairs; a pre-FPS anomaly injection strategy that aligns synthetic training with inference-time preprocessing; and a stochastic-gated Chamfer-statistics branch that complements learned embeddings with explicit geometric cues under consumer-grade hardware constraints. Evaluated on 14 controlled simulation experiments in an indoor corridor dataset, SPICD-Net achieved aggregated Precision = 0.86, Recall = 0.82, F1-score = 0.84, and Accuracy = 0.96, with zero false positives in the no-change baseline and mean inference time of 22.4 s for a 172-tile map on a single consumer GPU. Additional robustness experiments identified registration accuracy as the main operational prerequisite. A limited real-world validation in one unseen room (four scans, 67 tiles) achieved Precision = 0.583, Recall = 1.000, and F1 = 0.737. Full article

The development of effective fluorescent probes for the detection of acids and bases, both in solution and in the solid state, is of particular interest worldwide, due to the possibility of preventing hazardous consequences for human health and the environment. In the present work, the synthesis of a 1,8-naphthalimide derivative, designed as a “fluorophore-receptor₁-spacer-receptor₂” model, is considered. The compound contains two receptors for analytes in one molecule and can operate as a fluorescent probe via PET and ICT mechanisms. The photophysical behavior of the synthesized derivative in solution, on strip paper, and in thin film was investigated. It was found that the transition from acidic to alkaline medium in solution is associated with a change in color that is visible with the naked eye (yellow–orange-red–blue). The change in fluorescence, both in solution and spread on a supporting surface (strip paper and thin film), can be spectrophotometrically observed. The influence of various volatile acids on the sensing activity of the synthesized compound in solution and deposited on a solid support was investigated. It was found that with increasing acid strength, the fluorescence intensity increases. The strip paper and thin film obtained with the synthesized compound show reversible switching between the “off” and “on” states of fluorescence. The strip paper exhibited good cycling under acid–base vapor stimulation. The results obtained demonstrate the possibility of application of the synthesized compound as a colorimetric and fluorescent probe for determination of pH in solution, and detection of acids, bases, and their vapors in indoor and outdoor residential and industrial premises, as well as in the environment. Full article

Atmospheric particulate matter poses a high risk by carrying potentially toxic components such as polycyclic aromatic hydrocarbons (PAHs). The major sources of these potentially toxic compounds include traffic-related emissions and winter heating, implying the combustion of fossil fuels or biomass. Air pollution, especially chronic exposure, poses the most serious human health hazard in childhood, and several studies emphasise the importance of research on the potential impacts of air pollution in school environments. While indoor air quality studies are already available in Hungary, investigations on outdoor air pollution in school environments are missing. To fill this gap, in a medium-sized Hungarian town, Veszprém, six schools were selected to assess air quality in the outdoor environments where schoolchildren spend their breaks and have physical training. These schools represent different locations and conditions, from high-trafficked sites to suburban environments. Using resuspended dust samples, environmental quality was assessed based on PAH contents of the samples and ecotoxicity tests (Vibrio fischeri bacterial bioassay). Ecotoxicity of the samples moved in a wide range, from highly toxic to non-toxic. PAH measurements indicated considerable contamination in the case of one sample taken from a suburban area. Source apportionment demonstrated that winter heating is also an important pollution source. Full article

Adolescent vaping has become a persistent health and behavioural challenge in schools, yet many institutions lack reliable tools to detect and respond to concealed e-cigarette use. This study addresses this problem by evaluating the real-world performance of a low-cost “Internet of Things” (IoT) vape detection system deployed across 37 high-risk restroom and change-room locations at a large Australian Independent school. The aim was to determine whether an IoT-based environmental monitoring platform could accurately identify vaping events, support timely staff intervention, and provide actionable insights into student behaviour patterns. A longitudinal case study design was used, collecting continuous particulate matter (PM_2.5 and PM₁₀) data at one-minute intervals over an 18-month period, where PM₂.₅ and PM₁₀ refer to particulate matter with aerodynamic diameters ≤ 2.5 µm and ≤ 10 µm, respectively, reported in micrograms per cubic metre (µg/m³). Threshold-based alerting, cloud-based data processing, and school-led Closed-circuit television (CCTV) verification were combined to assess detection accuracy, temporal trends, and operational responses. The system recorded more than 300 vaping-related incidents, with clusters aligned to predictable times of day and higher prevalence among senior students. Operational detection performance was high, with alert events characterised by rapid, concurrent PM_2.5 and PM₁₀ excursions consistent with vaping-related aerosol profiles, although staff responsiveness declined over time due to alert fatigue and competing priorities. A major environmental smoke event demonstrated the need for context-aware logic to reduce false positives. The findings demonstrate that real-time aerosol monitoring is not only technically reliable but also highly effective in detecting vaping within school environments. These perspectives help explain why user engagement, alert fatigue, and institutional follow-through are as critical as sensor accuracy itself. Ultimately, the effectiveness of vape detection relies on strong organisational commitment, well-defined response workflows, and alignment with broader wellbeing and policy strategies. When these elements are in place, such systems can evolve from simple detection tools into intelligent, integrated components of school health governance. Full article