Reduce Noise Pollution Research Articles

Damping and acoustic properties of nanosilica filled poly(styrene-acrylate) interpenetrating polymer networks (IPNs): Effect of nanocomposite preparation method

Research on noise pollution reduction has focused on utilizing damping coatings and polymer nanocomposites to enhance sound absorption. Nanosilica/poly(styrene-acrylate) nanocomposites as a water-based coating were prepared through in-situ emulsion polymerization and direct mixing methods at varying concentrations of 1, 2, and 3 wt% of nanosilica. Fourier transform infrared (FTIR) spectroscopy revealed that the inclusion of surfactant-containing micelles and a more extended synthesis period in the in-situ synthesis technique enhanced the interaction between silica nanoparticles and polymer chains. Dynamic light scattering (DLS) analysis showed a unimodal distribution and an acceptable range of polydispersity index (PDI) for neat and nanocomposite latexes. The addition of silica nanoparticles enhanced the stability of latex particles, especially evident in the direct mixing method. The field emission scanning electron microscopy (FESEM) and transmission electron microscopy (TEM) images confirmed the better dispersion of nanoparticles within the polymer matrix in the in-situ method. The addition of nanosilica resulted in a significant increase in pseudoplastic behavior and viscosity, notably in the in-situ synthesis. In both the in-situ synthesis and direct mixing techniques, the addition of 1 wt% of nanosilica resulted in an increase in the damping factor of nanocomposite films to about 2. However, when the nanosilica content was further increased to 3 wt%, the damping factor decreased. Acoustic tests demonstrated improved sound absorption with silica nanoparticles, yielding noise reduction coefficient (NRC) values of 0.49 and 0.46 for in-situ synthesis and direct mixing. The direct mixing method notably enhanced tensile properties at all nanoparticle content levels. Dried nanocomposite films exhibited superior UV-blocking capabilities compared to neat polymer films.

Effectiveness of noise barriers in sensitive urban areas: a comprehensive study on noise reduction strategies and public health implications.

This study investigates the effectiveness of noise management strategies, focusing on installing barriers to reduce urban noise pollution, particularly around hospitals. The research in Sakarya, Turkey, employs comprehensive noise measurements and modeling techniques to evaluate barrier interventions. The study included 24-h noise averages and specific measures for daytime, evening, and nighttime noise levels, using SoundPlan software for modeling and mapping. Results reveal that noise levels frequently exceed international thresholds, especially in high-traffic areas. However, introducing noise barriers significantly reduces noise levels, particularly at specific measurement points, demonstrating their effectiveness. This underscores the crucial role of noise management strategies in sensitive urban areas and highlights the urgency for proactive interventions to manage noise pollution. The study identifies the need for future research, including long-term studies to assess noise barriers' durability and sustained effectiveness, and the integration of other noise reduction measures such as green infrastructure. Practical applications of this research include informing urban planners and policymakers about effective strategies for mitigating noise pollution and improving public health. In conclusion, this study provides valuable insights into urban noise management by empirically demonstrating the effectiveness of barrier interventions in reducing noise pollution. It underscores the importance of proactive measures to protect human health and preserve environmental balance in sensitive urban areas. The findings advocate for the broader implementation of noise barriers and other complementary strategies in urban planning to enhance the quality of urban life.

Facile fabrication of 3D-printed cellulosic fiber/polylactic acid composites as low-cost and sustainable acoustic panels

This work presents a green, cost-effective and eco-friendly strategy to reduce noise pollution by developing biopolymer-based 3D-printed acoustic panels. We successfully fabricated two series of composites by varying the weight percentage (wt%) of cellulose fibers of water hyacinth (WH) and pineapple leaf (PAL), with polylactic acid (PLA) as the matrix via the heat-press method. All samples were characterized using Fourier transform infrared (FTIR) spectroscopy, thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), and scanning electron microscopy (SEM). Physico-mechanical properties, including hardness, tensile, and impact strength, were improved with increasing fiber loading. Filaments of 1 wt% water hyacinth fibers (WHFs) in PLA (1 WHF/PLA) and 1 wt% pineapple leaf fibers (PALFs) in PLA (1 PALF/PLA) were prepared and tested for 3D printability. The sound absorption coefficients (α) of the 3D-printed panels were investigated from 500 to 5000 Hz sound frequency range. The 3D-printed 1 WHF/PLA and 1 PALF/PLA acoustic panels achieve a maximum α (α-max) of 0.55 and 0.83 at 5000 and 4000 Hz, respectively, featuring the first work to report α-max > 0.5 at low fiber loadings in the high-frequency sound range. The tensile strength of the 3D-printed versions is significantly higher than non-3D-printed counterparts and commercial acoustic absorbers. Our data suggest the prepared 3D-printed panels are excellent candidates for acoustic applications at high-frequency noises. This study exhibits a facile, environmentally benign and sustainable approach to construct highly efficient and mechanically robust biopolymer-based 3D-printed sound-proof panels, which have promising potential as green engineering materials. Interestingly, this research also proposes a mitigation technology for the freshwater invader, Eichhornia crassipes (water hyacinths).

Investigation of ultrasonic propagation in high attenuation porous materials

This research examines ultrasonic wave propagation in air-saturated plastic foams used for noise pollution reduction, questioning the effectiveness of current models such as the well known Johnson-Champoux-Allard model at high frequencies. These foams present a challenge for existing models to accurately depict visco-inertial and thermal interactions within their pores. The study highlights the model's failure to align experimental results with theoretical predictions. It introduces novel parameters denoted as Σ and V for viscous effects, and Σ′ and V ′ for thermal effects, to improve the representation of fluid-sturcture interactions. These parameters suggest a more significant boundary layer effect within the pores than previously considered. This approach aims to provide additional physical context for the principles governing the behavior of highly attenuating porous media and to explore new avenues for material characterization that surpass the limitations of existing models.

Eco-Friendly and Biocompatible Material to Reduce Noise Pollution and Improve Acoustic Comfort in Healthcare Environments

Noise pollution negatively impacts people’s mental and physiological health. Unfortunately, not only is noise present in hospital environments, but its level frequently exceeds recommended thresholds. The efficacy of passive acoustic absorbers in reducing indoor noise in these scenarios has been well-documented. Conversely, given their inorganic composition and their origin in the petrochemical industry, most of these materials present a risk to human health. Over the last few years, there has been a notable increase in research on eco-friendly, low-toxicity, and biocompatible materials. This work outlines a methodology for fabricating recycled acoustic panels from plastic bottles and PET felt composites. This study encompasses three key objectives: (i) a comprehensive biocompatibility assessment of the panels, (ii) an evaluation of their thermal and acoustic properties, and (iii) their applicability in several case studies to evaluate potential acoustic enhancements. Specifically, antifungal resistance tests, Volatile Organic Compound (VOC) emission assessment, and cell viability experiments were conducted successfully. Additionally, experimental procedures were performed to determine the thermal conductivity and thermal resistance of the proposed material, along with its sound absorption coefficients in diffuse field conditions. Finally, the potential benefits of using this biomaterial in healthcare environments to reduce noise and improve acoustic comfort were demonstrated.

Оценка влияния вредных факторов производственной среды в литейном цехе

Harmful factors in the working area of foundry operators are considered. The complexity of workflows affects the quality of air in the foundry. The casting process is accompanied by the generation of a significant amount of dust as well as high levels of noise and vibration. The relevant aspect of the study is the assessment of the state of occupational safety, considering the harmful factors at the production in question. Dust content has been thoroughly investigated by dispersive and elemental analysis of dust using X-ray fluorescence analysis and laser diffraction. The impact of the vibroacoustic factor has been studied. An analysis of the sound pressure level in the working areas of the foundry has been provided. The authors have proposed technical measures to reduce dust content and the level of impact of the vibroacoustic factor. The development of a system of measures to minimize harmful impact has been based on a combined analysis of factors. Methods to reduce noise and dust content at workplaces are proposed as follows: organizing a highly efficient system of post-treatment of dust emissions, increasing equipment sound absorption, installing structures to reduce noise pollution, and using a coating system made of dense rubber structures (compounds). Ensuring safe working conditions in working areas of the foundry has been studied; the improvement of working conditions due to the improvement of existing and installation of new noise and vibration protection means has been proposed. An integrated approach to the assessment of production factors has been provided, which has been the key element for the development of engineering and organizational protection measures. The integrated analysis helped identify the degree of impact of harmful factors such as noise, and dust content on machine operators during the casting process and to conduct a comparative assessment of sound pressure levels. The sound pressure can be reduced by 8–10 dB using improved mechanisms of shot-blasting chamber operator protection. More extensive dust protection measures are proposed due to the sample content of 85% of the dust mass less than 100 microns and multicomponent dust with a high content of silicon and iron. The findings provide a technical value for the substantiation of the modernization of noise and dust reduction systems at foundry operator workplaces.

Experimental Analysis of Noise Characteristics on Different Types of Pavements inside and outside Highway Tunnels

Aiming to reduce noise pollution and optimize the acoustic quality in highway tunnels, the noise characteristics on different types of pavements were analyzed and compared in this research, based on the on-site noise measurement in two tunnels with the free fields as a control group. Specifically, the noise characteristics include two aspects: various noise and noise time attenuation performance. Various noise includes on-board sound intensity (OBSI) noise and cabin noise. The noise time attenuation performance uses the indicator of reverberation time. Three types of pavements were measured, including dense-graded asphalt concrete (DAC) and single-layered and double-layered porous asphalt (PA) pavement. The results showed that, for the same type of pavement, compared with the free fields, the difference in OBSI noise in tunnels was within a range of less than 1 dBA; the cabin noise increased by 3.4 dBA~6.6 dBA. The noise level in tunnels was greater than that outside tunnels, and the longer tunnel exhibited higher traffic noise and worse noise time attenuation performances. For the same tunnel, PA pavement could reduce the cabin noise by 3.8 dBA~6.7 dBA. PA pavement also exhibited shorter reverberation time. The application of PA pavement could effectively improve the acoustic quality in the tunnel. This research contributes to noise pollution abatement and the improvement of the comfort and safety of drivers in tunnels.

The effect of muffler design on reducing the noise pollution of a small two-stroke engine

Designing an efficient muffler for single-cylinder IC engines is not an easy task due to the limitation in designing a large muffler and the possibility of engine suffocation. In this regard, this research aims to experimentally investigate the feasibility of inexpensive muffler modification of a small portable two-stroke engine to reduce noise pollution. In experiments, the default muffler as a control treatment and a modified muffler together with a redesigned muffler have been examined to investigate the effect of muffler internal geometry and muffler design on sound emission characteristics. Based on the obtained results, the sound pressure level (SPL) of the modified and redesigned mufflers decreased by 5.31 and 6.86 percent compared to the default muffler, respectively. Meanwhile, installing the modified and redesigned mufflers increased the transmission loss (TL) equal to 8.62 % and 10.08 % compared to the default muffler, respectively. Also, the outcome of Discrete Fourier Transform (DFT) revealed that the intensity and amplitude of output frequencies from the redesigned muffler was significantly reduced in the frequency range of 2–6 kHz. As a general conclusion of this study, by installing the redesigned muffler, the maximum working times of the operator increased by 12.1 h at 5000 rpm.

Exploring multi-pollution variability in the urban environment: geospatial AI-driven modeling of air and noise

ABSTRACT This study addresses the critical need for comprehensive multi-pollution modeling in urban environments by employing Geospatial Artificial Intelligence (GeoAI) techniques. Specifically, it aims to elucidate the variability of air and noise pollution levels in Tehran, Iran, and develop precise multi-pollution susceptibility maps. A spatial database was compiled, encompassing annual average data (2019–2022) of the Air Quality Index (AQI) and Equivalent Continuous Sound Level (Leq), along with 19 influential factors related to both pollutants. The study utilized the CatBoost machine learning algorithm, enhanced with Grey Wolf Optimizer (GWO) and Harris Hawks Optimization (HHO) algorithms, to model and predict pollution patterns. Key quantitative achievements include a remarkable 15% reduction in Root Mean Square Error (RMSE) for air pollution and a 12% reduction in noise pollution when using the CatBoost-HHO configuration compared to the standalone CatBoost algorithm. Validation of the multi-pollution maps utilizing the Area Under the Curve (AUC) analysis showed high accuracy, with the CatBoost-HHO achieving AUC values of 0.943 for air pollution and 0.936 for noise pollution, outperforming CatBoost-GWO and standalone CatBoost models. These results underscore the efficacy of our approach in accurately identifying and mapping multi-pollution hotspots, contributing valuable insights for urban environmental management and public health preservation.

Design of Robust Broadband Frequency-Invariant Broadside Beampatterns for the Differential Loudspeaker Array

The directional loudspeaker array has various applications due to its capability to direct sound generation towards the target listener and reduce noise pollution. Differential beamforming has recently been applied to the loudspeaker line array to produce a broadside frequency-invariant radiation pattern. However, the existing methods cannot achieve a compromise between robustness and broadband frequency-invariant beampattern preservation. This paper proposed a robust broadband differential beamforming design to allow the loudspeaker line array to radiate broadside frequency-invariant radiation patterns with robustness. Specifically, we propose a method to determine the ideal broadside differential beampattern by combining multiple criteria, namely null positions, maximizing the directivity factor, and achieving a desired beampattern with equal sidelobes. We derive the above ideal broadside differential beampattern into the target beampattern in the modal domain. We propose a robust modal matching method with Tikhonov regularization to optimize the loudspeaker weights in the modal domain. Simulations and experiments show improved frequency-invariant broadside beamforming over the 250–4k Hz frequency range compared with the existing modal matching and null-constrained methods.

Analysing type of plants for reducing noise pollution in climate change adaptation

Abstract The noisier a region or city is, the faster the rate of global warming. Noise is not a substance. However, most sources of carbon dioxide and other greenhouse gases are also sources of noise; for example, busy highways in cities can occasionally see as many as 100 cars per hour. Planting trees to mitigate noise pollution has been identified as one of the most sustainable methods to employ, since plants may function as a buffer and absorb sounds. Several plant species were chosen to assess noise absorption based on parameters such as leaf thickness, breadth, surface area, and length. The initial goal of this study is to estimate the noise absorption on the selected flora native to the Malaysian environment, where the noise was measured using an in-house developed impedance tube to discover the effective acoustic characteristics of leaves. The investigation was then carried on by assessing the data on the correlation coefficient parameter in order to determine the link between noise absorption and leaf features. Because of the freshness and perishability of the materials, measurements were repeated twice. Only 100% and 50% vegetation quantity size were measured for 10 sample species during the initial data collection. According to the findings, half of the leaves’ features were connected with noise absorption. This might be owing to the freshness state, which cannot be maintained for an extended period of time. To acquire a better value, the experiment was repeated within the permissible freshness time. The findings are as predicted, with the maximum noise absorption and features correlation at 100% plant density including twigs. When the vegetation amount is lowered to 50%, this will progressively diminish. The notion is confirmed by the fact that a tube packed with thicker samples absorbs more noise. The correlation study identifies that each leaf has its unique capacity for noise absorption dependent on its properties and freshness level.

Effects of warm-mix additives, anti stripping agent, and graphene nanoplatelet on the cracking resistance, moisture susceptibility, and cost effectiveness of stone mastic asphalt

Moisture and cracking damages are two of the most common asphalt pavement distresses in the United States. The use of stone matrix asphalt mixture has gained popularity due to its high durability, resistance to permanent deformation and cracking, and reduced noise pollution. Warm-mix additives and nanomaterials have also gained significant interest as promising asphalt binder additives. In order to achieve enhanced resistance to moisture and cracking in extremely wet regions, this study investigated the effects of three warm-mix additives, an anti-stripping agent, and one nanomaterial (graphene nanoplatelet) on the cracking and moisture resistance performance of stone matrix asphalt. Fourier transform infrared spectroscopy and sessile drop tests were used to evaluate the functional groups and moisture susceptibility of the modified asphalt binder blends, respectively. The indirect tensile asphalt cracking test and the modified Lottman tests were used to evaluate the mixtures' resistance to cracking and stripping damage. A cost-effectiveness analysis as well as a two-dimensional performance interaction diagram were employed based on the laboratory performance of the mixtures. Results indicated that the graphene nanoplatelet modification of the asphalt binder had the highest wettability potential, adhesion, and debonding properties, as well as moisture resistance potential compared to other additives. In terms of mixture cracking performance, both the graphene nanoplatelet and a chemical warm-mix asphalt significantly improved the mix cracking performance by 34.1 and 30.0 %, respectively, compared to the control mix. However, the graphene nanoplatelet modification had a tensile strength ratio of 0.76, which is below the acceptance threshold of 0.80 set by AASHTO T 283 for moisture damage resistance of asphalt mixture. Overall, all mixtures with warm-mix additives showed adequate cracking and stripping damage resistance performance and are expected to be cost-effective.

Sustainability and Covid-19 Pandemic: The Implications of Social Isolation on The Environment

Objective: The objective of this research was to analyze the environmental impacts of social isolation from the COVID-19 pandemic. Methodology: An integrative review was carried out, using databases from Google Academic and Scielo, with specific inclusion criteria for selecting scientific articles. Only scientific articles in Portuguese, Brazilians, associated with the central theme of research and published between 2020 and 2023 were selected. The data was analyzed in two stages: reading abstracts and titles, followed by a complete reading of the selected articles. Results and Data Analysis: Four scientific articles were selected that addressed the impacts of social isolation in the pandemic on the environment. The identified studies reported a significant reduction in air and noise pollution, as well as minor impacts on aquatic pollution during the quarantine period. The decrease in human activities was associated with a fall in pollutant emissions, bringing benefits to air quality and public health. However, the transitional nature of these benefits has been highlighted, highlighting the need to rethink consumption and production practices to ensure environmental sustainability. Conclusions: The conclusions highlight the need for effective structural measures to control pollution and promote sustainable habits to ensure lasting environmental benefits in the post-pandemic.

Improving Traffic-noise-mitigation Strategies with LiDAR-based 3D Tree-canopy Analysis

The leaves on trees absorb road noise and serve as noise barriers. Tree structures such as tree belts and isolated trees have various methods for absorbing sounds. The depth, surface area, and noise-absorption coefficient of trees contribute to noise absorption. Therefore, this study aims to address this issue of traffic-noise pollution through the use of trees; in particular, by analyzing the noise-absorption coefficient of leaves, the surface area of the leaves, and the depths of the trees. However, the study stresses the need for 3D tree-canopy visualization to identify these factors. To achieve this, the study used LiDAR point clouds to provide accurate data for the convex hull visualizations of canopies. Additionally, a formulated equation for calculating traffic noise after absorption has been suggested by combining the traffic-noise absorption and Henk de Kluijver traffic-noise models. The study also compares the effectiveness of tree belts and isolated trees in reducing noise pollution, concluding that, below a canopy of trees, there is no noise reduction. Finally, the study has demonstrated that the number and sizes of leaves affect noise absorption, showing that noise pollution can be reduced by 1 to 3 dB(A) in the research area by using trees.

Structural and sound absorption properties of polyethylene terephthalate (PET) and recycled polyethylene terephthalate (r-PET) nanofibers

Sound-absorbing materials are used to reduce noise pollution since noise is one of the important environmental factors affecting human health. Due to their high porosity and large specific surface area, nanofibers can be preferred as a better sound absorption material. In this study, nanofiber-based sound-absorbing materials are produced using polyethylene terephthalate (PET) and recycled polyethylene terephthalate (r-PET) in the electrospinning method in order to obtain a thin and high-sound absorbing material. Another objective of this study is to investigate the performance of r-PET compared to PET from the sound absorbing properties points of view to contribute sustainability which is one of the most important issues of today. For these purposes, solutions of three different concentrations (10%, 15% and 20% owf) were prepared by dissolving PET and r-PET polymers in trifluoroacetic acid (TFA):dichloromethane (DCM) solvent mixture. It will also be possible to help sustainability issues by reducing environmental pollution and raw material costs by using r-PET. Samples were electrospun on a polypropylene based nonwoven structure using solutions at different flow rates (0.1-0.3-0.5 ml/h) and needle tip-collector distances (4–8 cm). The fiber diameter, thickness, bulk density, porosity and pore size properties of the produced samples were investigated. The sound absorption coefficient (SAC) was measured with a dual microphone impedance tube device. The relationship between the structural properties of the samples and the SAC was evaluated. SAC decreased with increasing fiber diameter, bulk density, pore size and increased with high porosity. These values were compared with different sound absorbing materials which are commonly used. According to the results, the developed nanofiber-based material with a 0.3 mm thickness has high SAC values compared to conventional sound absorbing materials with 10–16 mm thickness values, especially in middle frequency levels. Recycled polymer may be preferred when PET and r-PET nanofibers show similar results.

Temporal and spatial biosonar activity of the recently established uppermost Yangtze finless porpoise population downstream of the Gezhouba Dam: Correlation with hydropower cascade development, shipping, hydrological regime, and light intensity.

Numerous dams disrupt freshwater animals. The uppermost population of the critically endangered Yangtze finless porpoise has been newly formed below the Gezhouba Dam, however, information regarding the local porpoise is scarce. Passive acoustic monitoring was used to detect the behaviors of porpoises below the Gezhouba Dam. The influence of shipping, pandemic lockdown, hydrological regime, and light intensity on the biosonar activity of dolphins was also examined using Generalized linear models. Over the course of 4 years (2019-2022), approximately 848, 596, and 676 effective monitoring days were investigated at the three sites, from upstream to downstream. Observations revealed significant spatio-temporal biosonar activity. Proportion of days that are porpoise positive were 73%, 54%, and 61%, while porpoise buzz signals accounted for 78.49%, 62.35%, and 81.30% of all porpoise biosonar at the three stations. The biosonar activity of porpoises was much higher at the confluence area, particularly at the MZ site, during the absence of boat traffic, and during the Pandemic shutdown. Temporal trends of monthly, seasonal, and yearly variation were also visible, with the highest number of porpoises biosonar detected in the summer season and in 2020. Significant correlations also exist between the hydrological regime and light intensity and porpoise activity, with much higher detections during nighttime and full moon periods. Hydropower cascade development, establishment of a natural reserve, fish release initiatives, and implementation of fishing restrictions may facilitate the proliferation of the porpoise population downstream of the Gezhouba Dam within the Yichang section of the Yangtze River. Prioritizing restoration designs that match natural flow regimes, optimize boat traffic, and reduce noise pollution is crucial for promoting the conservation of the local porpoises.

Biochar as a slag foaming agent in EAF – A novel experimental setup

Slag foaming practice is employed widely in electric arc furnace steelmaking to improve the energy efficiency, protect the furnace structures and reduce noise pollution. Slag foaming is typically launched by injecting fossil-based carbonaceous material (e.g. coke dust) into the melt. In this study, a novel laboratory-scale experimental setup was used for studying the substitution of fossil carbon by biochar as slag foaming agent. The setup was equipped with an injection device for feeding carbon and a camera system for observing the foaming phenomenon and recording the process. A set of experiments was conducted for studying the foaming in slag-carbon systems using two carbonaceous materials: 1) coke dust was used as a reference material and 2) a high-quality biochar was used as a possible replacement. In the experiments, sufficient foaming was achieved with both of the carbonaceous materials. The biochar produced almost equal foaming behavior as coke dust. The results indicate that biochar could be used to substitute carbon for slag foaming in the EAF.

Optimization of data-center immersion cooling using liquid air energy storage

The evaporation process of liquid air leads to a high heat absorption capacity, which is expected to be a viable cooling technology for high-density data center. Therefore, this paper proposes a liquid air-based cooling system for immersion cooling in data centers. The proposed cooling system not only directly cools the data center, but also possesses the capability of power generation through direct expansion of the high-pressure air, which can be utilized again to cool the data center. A mathematical model of data-center immersion cooling using liquid air energy storage is developed to investigate its thermodynamic and economic performance. Furthermore, the genetic algorithm is utilized to maximize the cost effectiveness of a liquid air-based cooling system taking the time-varying cooling demand into account. The research results indicate that the proposed system exhibits optimal levelized cost of cooling and cooling capacity, which are $0.245/MJ and 0.544 MJ/kg, respectively. In this case, the data center's pPUE and footprint density are 1.006 and 416.8 kW/m2, representing a 5 % reduction and a 159 % increase, respectively, compared to traditional evaporative cooling towers. Additionally, using liquid air for data center cooling can reduce noise pollution and the consumption of water. Considering the time-varying characteristics of data center utilization, understanding the dynamic thermal response characteristics of this system and implementing efficient control techniques will contribute to the further promotion of this technology.

Assessment and mapping of noise pollution in recreation spaces using geostatistic method after COVID-19 lockdown in Turkey

Increased use of recreational areas after the lifting of COVID-19 pandemic restrictions has led to increased noise levels. This study aims to determine the level of noise pollution experienced in recreational areas with the increasing domestic and international tourism activities after the lifting of pandemic lockdowns, to produce spatial distribution maps of noise pollution, and to develop strategic planning suggestions for reducing noise pollution in line with the results obtained. Antalya-Konyaaltı Beach Recreation Area, the most important international tourism destination of Turkey, is determined as the study area. To determine the existing noise pollution, 31 measurement points were marked at 100 m intervals within the study area. Noise measurements were taken during the daytime (07:00–19:00), evening (19:00–23:00), and nighttime (23:00–07:00) on weekdays (Monday, Wednesday, Friday) and weekends (Sunday) over 2 months in the summer when the lockdown was lifted. In addition, the sound level at each measurement point was recorded for 15 min, while the number of vehicles passing through the area during the same period was determined. The database created as a result of measurements and observations was analyzed using statistical and geostatistical methods. After the analysis of the data, it was found that the co-kriging-stable model showed superior performance in noise mapping. Additionally, it was revealed that there is a high correlation between traffic density and noise intensity, with the highest equivalent noise level (Leq) on weekdays and weekend evenings due to traffic and user density. In conclusion, regions exposed to intense noise pollution were identified and strategic planning recommendations were developed to prevent/reduce noise sources in these identified regions.

Influence of Environmental Conditions and The Students' Health

Healthy students are not merely a result of good genes; they are also a product of an environment that fosters and encourages their well-being through a mutual influence of environmental conditions. This study determined the influence of environmental conditions on students' health in one of the basic education schools in Ozamiz City during the S.Y. 2023-2024. It employed a descriptive-correlational design with 249 Senior High School respondents chosen through simple random sampling. The Environmental Conditions and Students' Health Questionnaires with a five-point Likert scale were used as data gathering instruments. Mean, Standard Deviation, and the Pearson Product Moment Correlation Coefficient were used as the statistical tools to analyze the gathered data. Results revealed that the students' environmental conditions on air quality, water quality, access to green spaces, built environment, social and community support, transportation, and commute, and environmental were good, while noise pollution and temperature were fair. The students' overall health was good, including their physical, mental, and social health. The students' environmental conditions greatly influenced their health and well-being. The learning environment of students plays an important role in their health and well-being. School administrators may prioritize reducing noise pollution and regulating temperature while investing in sustainable practices, green spaces, and community support to create a healthier learning environment.