HEALTH EFFECTS OF NOISE FROM TIMBER PROCESSING PLANTS ON RESIDENTS AND THE ENVIRONMENT IN IKOT EKPENE CITY, AKWA IBOM STATE, SOUTHERN NIGERIA

International Journal of Advanced Scientific and Technical Research ISSN 2249-9954 Available online on http://www.rspublication.com/ijst/index.html volume 15, No. 5, 2025 DOI: 10.5281/zenodo.17284967 1 Original Article ©2025 RS Publication, [email protected] 243 HEALTH EFFECTS OF NOISE FROM TIMBER PROCESSING PLANTS ON RESIDENTS AND THE ENVIRONMENT IN IKOT EKPENE CITY, AKWA IBOM STATE, SOUTHERN NIGERIA Veronica M. Akpan Department of Science Technology, Akwa Ibom State Polytechnic Ikot Osurua, Akwa Ibom State, Nigeria | +234 808 481 7644 |✉ veronicamkp[email protected]om Udeme U. Inyang Department of Science Technology, Akwa Ibom State Polytechnic Ikot Osurua, Akwa Ibom State, Nigeria | +234 806 748 0807 | ✉ [email protected] Emmanuel F. Akpan Department of Science Technology, Akwa Ibom State Polytechnic Ikot Osurua, Akwa Ibom State, Nigeria | +234 708 458 0329 | ✉ elderemmanuelak[email protected]m ARTICLE INFO ABSTRACT Paper ID: IJASTR68DBC9942A3B3 Received: 2025-09-06 Published: 2025-10-07 DOI: https://dx.doi.org /10.5281/zenodo.17 284967 Page No: 243-256 This study aimed to investigate the health effects of noise generated by timber processing facilities on residents and the environment in Ikot Ekpene city, Akwa Ibom State, Nigeria. The study sites were Ibiakpan, Uruk Uso, Urua Aran, and Utu, where three examples each of a table saw, surface planer, carving machine, and curving machine were examined. Noise levels were quantified during unloading and loading operations with a sound level meter at distances between 1m and 10m from each wood processing facility. Validated questionnaires were administered in conjunction with semi-structured interviews conducted with workers and plant managers to get qualitative data regarding the health implications of noise exposure. The data acquired from the study were evaluated and interpreted. It was determined that elevated noise levels were potentially produced by the plants at load conditions in contrast to no-load scenarios, and the noise-distance connections exhibited an exponential decay. The findings indicated that, even at a distance of 10 meters from the surface planer and carving machine under operational load, the recommended maximum noise exposure level of 70 dB was surpassed; however, a distance of at least 8 meters may be considered safe in other instances of equipment use and for both operational scenarios. The discovered noise-induced health issues and their highest prevalence rates were hearing loss (39.1%), sleep disturbance (67.9%), elevated stress (76.2%), and concentration loss (66.7%). These findings indicate the necessity for enhanced noise management methods in timber processing plants. Keywords – GPS Coordinates, Hearing loss, Noise level, Sound level meter Corresponding Author: Akpan, V. M. International Journal of Advanced Scientific and Technical Research Available online on http://www.rspublication.com/ijst/index.html ISSN 2249-9954 Original Article Cite This Paper : Veronica Mkpouto Akpan Udeme Udofia Inyang And Emmanuel Friday Akpan(2025). "HEALTH EFFECTS OF NOISE FROM TIMBER PROCESSING PLANTS ON RESIDENTS AND THE ENVIRONMENT IN IKOT EKPENE CITY, AKWA IBOM STATE, SOUTHERN NIGERIA". INTERNATIONAL JOURNAL OF ADVANCED SCIENTIFIC AND TECHNICAL RESEARCH (IJASTR), vol. 15, no. 5, 2025, pp. 243-256 DOI: https://dx.doi.org/10.5281/zenodo.17284967 International Journal of Advanced Scientific and Technical Research ISSN 2249-9954 Available online on http://www.rspublication.com/ijst/index.html volume 15, No. 5, 2025 DOI: 10.5281/zenodo.17284967 1 Original Article ©2025 RS Publication, [email protected] 244 INTRODUCTION Noise is any sound that annoys, disrupts, or distracts, potentially leading to detrimental physiological and psychological impacts on individuals if not managed (Salam et al, 2024). Noise is categorized into two primary classes: environmental noise, defined as any harmful or unwanted sound present in the surroundings, and occupational noise, which pertains to loud tasks and machinery in work settings (Ibhadode et al, 2018). The detrimental effects of noise on humans render it a significant environmental issue, as elevated noise levels can contaminate surroundings, resulting in safety and health concerns, particularly with prolonged exposure (Oyedepo et al, 2013). Sources of noise pollution include, but are not limited to, religious edifices (such as churches and mosques), generators, concert venues, political demonstrations, vehicular traffic, air transportation, athletic events, construction activities, and industrial operations (Ibhadode et al, 2018). The industrial sector is among the sources with a significant risk of noise pollution (Oguntunde et al, 2019; Bolaji et al, 2018). LITERATURE REVIEW Industrial noise pollution has become a notable environmental and occupational health issue, notably in developing regions undergoing swift modernization. Although industrial growth significantly enhances economic development, the resultant noise emissions pose serious concerns for human health and environmental integrity (Sternfeld et al, 2015). Timber processing plants are significant contributors to noise pollution among industrial sources, owing to their equipment-intensive operations such as sawmilling, planing, and material handling (Engelmann et al, 2015). Noise generation in timber processing plants is regulated by intricate physical concepts that encompass mechanical vibrations, impact forces, and sound propagation (Thompson, 2017). The amalgamation of diverse noise-producing mechanisms, such as machinery operation, material handling, and processing operations, engenders a formidable environment for both employees and adjacent communities (Barber et al, 2010). Occupational noise exposure is common, particularly during product processing, and exposure to other dangers on the job can lead to injuries or illnesses, according to Salam et al. (2024). The health impact measurement for work-related hearing loss is approximately 4 million disability adjusted life-years, and 16–24% of all hearing impairments are work-related, according to Nelson et al. (2005). Anxieties and irritability, foetal development, mental health crisis, cardiovascular disorders in pregnant women, sleep disruption and insomnia, myocardial infarction and peptic ulcers, cardiocerebrovascular diseases, type 2 diabetes incidence, and children's communication and retentive abilities (Tesoriere et al. 2018) are all adversely affected by noise pollution, according to reports. There is a lack of data regarding the particular health effects of noise from urban wood processing plants, despite the increasing amount of literature on industrial noise pollution. Pretzsch et al. (2021) emphasized that noise is one of the most common occupational dangers nowadays, hence it is urgently necessary to fill the existing gap. Consequently, this study's overarching objective is to investigate the effects of timber processing plant noise on human and environmental health in the Ikot Ekpene metropolis of Nigeria's Akwa Ibom State. This study region is a perfect match for the research since it is a International Journal of Advanced Scientific and Technical Research ISSN 2249-9954 Available online on http://www.rspublication.com/ijst/index.html volume 15, No. 5, 2025 DOI: 10.5281/zenodo.17284967 1 Original Article ©2025 RS Publication, [email protected] 245 typical urban context with dense human population and ongoing large-scale timber production. Annually, 2.78 million people lose their lives as a result of injuries or illnesses sustained on the job (Salam et al, 2024). The World Health Organization (WHO) has predicted that over 900 million individuals globally would experience deafness by the year 2050 (Fauzan, 2023). They also predict that highand middle-income nations will rank hearing loss as one of the top 10 causes of disease burden by 2030. In particular, using the current noise reduction techniques into account, we will evaluate, analyze, and draw conclusions based on the WHO recommendations about the noise levels produced by a subset of timber processing units. In order to safeguard the health of workers and encourage sustainable industrial practices, this study aims to provide evidence-based policies and actions. The levels of noise pollution in main sections of Ota city were researched and assessed by Oguntunde et al. (2019). Over the course of a day, researchers in Ota metropolitan gathered data on noise pollution levels at 41 different sites. Minitab version 17.0 was used to perform descriptive statistics and analysis of variance. In either case, the noise pollution levels were predicted using the data set that was best described by the probability model that was chosen using the Easy fit software. As it turned out, the decibel levels were much over the safe zone set by the World Health Organization. The impacts of the noise pollution levels were also not significantly different across all time periods. According to the Kolmogorov Smirnov goodness of fit test, the dataset was best fitted by the log-logistic distribution. In the end, it was determined that the fitted probability model might improve public health by aiding in noise pollution prediction and serving as a benchmark for reducing noise pollution. An interventional study was conducted by Khajenasiri et al. (2016) to investigate how exposure to high noise levels impacts the performance and rate of error in manual tasks. Half of the students at Shiraz University of Medical Sciences were female and the other half were male. Each participant served as a control, and the researchers measured the impact of noise at 70, 90, and 110 dB on their performance. The research used a Two-Arm Coordination Test in addition to two physical characteristics and the generation of varying sound source conditions. The data was processed with SPSS version 16, and in order to compare the duration of performance and the errors measured in the test, repeated measurements were utilized. The duration of the performance was shown to be directly and significantly correlated with the volume levels. In addition, the results demonstrated that the levels of sound had a substantial impact on the participants' performance; at 110 dB, it was lower than at 70 and 90 dB (p < 0.05 and p < 0.001, respectively). Located at the intersection of Abdullah Lubis Street and Pattimura Medan Street, State Elementary School (SDN 060882) was the site of a noise survey by Buchari (2017) to ascertain the extent to which the noise affected students' ability to learn. Using the Threshold Limit Value (TLV), the noise level was measured at 24 different sites. According to the Minister of Environment's Decree No. KEP/48/MENLH/11/1996, the noise levels were determined to be higher than the standard TLV >55 dBA. The school's decibel level was 70.79 dBA, as a result of the data processing and the Noise Mapping, the classrooms were categorized as having a decibel level of 70.79 dBA. Classes IIIa, IVb, and VI were located in the Red Zone, where the International Journal of Advanced Scientific and Technical Research ISSN 2249-9954 Available online on http://www.rspublication.com/ijst/index.html volume 15, No. 5, 2025 DOI: 10.5281/zenodo.17284967 1 Original Article ©2025 RS Publication, [email protected] 246 noise level ranged from 69 to 75 dBA. Those in the Yellow Zone, ranging from 65 to 69 dBA, were also classified as Class II, Class IIIa, Class Iva, and Class V. What's more, the noise had a physiological impact causing dizziness at 22% and an emotional and uncomfortable feeling at 21%; a communication impact causing a disturbance to the teacher's explanation at 22%; and a decline in students' learning performance at 22%. A number of suggestions were made to lessen the noise level in the school, including moving the windows, installing acoustic material on the walls of the classrooms, and landscaping with bamboo trees or grasses. A study conducted by Huang et al. (2024) examined the potential health consequences of occupational noise exposure over a 9-year period utilizing data from health examinations conducted by a prominent Taiwanese manufacturing business. One hundred sixty-six workers, split evenly between noisy and quieter departments, had their health measured using twenty different indices. Age, sex, and years of experience were all factors in making this hiring decision. By including a unique range ratio into linear regression models, we were able to quantify the index fluctuations owing to noise and evaluate the temporal impact of noise exposure on each health index. A 16.594 K/mL increase in platelet count, with a 1.228 K/mL yearly increment, was observed in workers who were exposed to occupational noise. The blood urea nitrogen level of workers in noisy workplaces increased significantly by 0.438 mg/dL, and this rise persisted year after year by 0.171 milligrams per deciliter. The carcinoembryonic antigen level in the employees' blood was considerably elevated by 0.187 ng/mL, with an average yearly rise of 0.034 ng/mL. Exposure to noise was determined to be the only cause of an increase in systolic blood pressure (2.015 mmHg), a drop in red blood cell count (0.107M/mL), and an increase in heart rate (4.620 beats/min) and white blood cell count (0.536K/mL). This longitudinal study highlights the negative health effects of long-term exposure to high levels of occupational noise, finding that it greatly raises the risk of cardiovascular, renal, and colorectal disorders. In order to determine the impact of noise pollution on Nepalese citizens' health, Karki et al. (2024) conducted a comprehensive literature study. Hearing loss, disturbed sleep, cardiovascular illness, social handicaps, decreased productivity, negative social conduct, irritation reactions, absenteeism, and accidents were among the several kinds of consequences that were taken into account. The relevant prior material was compiled and examined from a variety of internet sites. Additionally, in order to get expertise about this topic, the researchers gathered secondary sources of information. In order to review the existing literature on the topic of noise pollution and its impact on human health, they utilized a qualitative narrative design and combed through several internet resources. Reducing noise pollution may be possible through the implementation of noise rules and the No Horn Regulation, according to the study. It is critical to take action to decrease noise pollution in order to safeguard public health, but additional efforts will be required to monitor and enforce these restrictions because noise pollution can cause a range of health concerns. International Journal of Advanced Scientific and Technical Research ISSN 2249-9954 Available online on http://www.rspublication.com/ijst/index.html volume 15, No. 5, 2025 DOI: 10.5281/zenodo.17284967 1 Original Article ©2025 RS Publication, [email protected] 247 EXPERIMENTAL PROCEDURE COLLECTION OF MATERIALS This research utilized a calibrated sound level meter (Model IF045985), a 100-meter surveyor's tape, a GPS device (Map 78s, manufactured in Taiwan), a relative humidity meter, and digital thermometers with a precision of 0.1 °C for the collection of quantitative data. The Worker Noise Exposure and Health Questionnaire was utilized. The wood processing facilities examined in the study included the table saw, surface planer, carving machine, and curving saw, which are extensively utilized in the timber markets of Ibiakpan, Uruk Uso, Urua Aran, and Utu within the Ikot Ekpene city, Nigeria as shown in figure 1. Fig.1: (a) Map of Nigeria indicating the location of Akwa Ibom State (b) Map of Akwa Ibom State highlighting the location of Ikot Ekpene. (c) Map of Ikot Ekpene showing the timber markets surveyed in this study. DATA ACQUISITION AND ANALYSIS Noise levels were quantified with a sound level meter at distances between 1 m and 10 m from each of the chosen machines/wood processing facilities. Three identical samples from each processing facility were surveyed at each site, after which the mean and accompanying standard error values of the collected data for each distance were calculated. Noise level measurements were conducted under two operational circumstances of the surveyed machines: unloading and loading, during which the machines were externally powered. Throughout each noise measurement session, the sound meter was positioned at the height of the machine stage International Journal of Advanced Scientific and Technical Research ISSN 2249-9954 Available online on http://www.rspublication.com/ijst/index.html volume 15, No. 5, 2025 DOI: 10.5281/zenodo.17284967 1 Original Article ©2025 RS Publication, [email protected] 248 above the ground, ensuring that the sound propagation line from the machine was aligned with the meter's elevation above the ground. The average maximum distance of the machine operator was ascertained for all loading scenarios. In each study location, environmental data, including geographical coordinates and meteorological parameters (temperature and relative humidity), were recorded using a GPS device, thermometer, and relative humidity meter, respectively. Figure 2 displays the images captured during the noise level assessment at one of the research locations. Fig. 2: Photos taken at a site during noise level measurements To collect qualitative data that elucidates the health effects of exposure to the recorded noise levels, questionnaires were sent to workers and plant managers, accompanied by semistructured interviews. The parameters evaluated for obtaining pertinent qualitative data from the respondents (workers and plant managers) included the duration of exposure to occupational noise within the processing plants, health issues encountered during and after work, social demographics, and clinical examinations. The requested information was obtained with the guarantee of complete confidentiality and anonymity. The noise-distance data were graphically examined utilizing Origin software (Version 2019b). The filled questionnaires were gathered and organized. Subjects receiving drugs were excluded, and the remaining participants were appropriately employed for this research. The subjects' answers were quantified and characterized according to the frequencies of each detected health challenge. International Journal of Advanced Scientific and Technical Research ISSN 2249-9954 Available online on http://www.rspublication.com/ijst/index.html volume 15, No. 5, 2025 DOI: 10.5281/zenodo.17284967 1 Original Article ©2025 RS Publication, [email protected] 249 RESULTS AND DISCUSSION Table 1 presents the recorded geographical and meteorological data at the study sites. The latitudes and longitudes are around 5°N and 7°E at the locations, suggesting that site changes may have negligible impact on the measured noise levels. The maximum temperature was documented at Utu timber market, while the minimum was noted at Ibikpan timber market. The outcome is contingent upon the location where the in-situ measurements were initiated. Although temperature affects the velocity of sound propagation, the variance in this instance is approximately 16.7%, which seems trivial, rendering its impact negligible. A comparable situation is noted for relative humidity, since the 13.1% fluctuation from 84.0% at Utu to 95.0% at Ibiakpan timber market is minimal and, therefore, unlikely to significantly influence noise propagation from any of the investigated plants. Table 1. Geographical coordinates and Weather parameters per study location Geographical Coordinates Weather Parameters during Noise Measurements Timber Market Location Latitude (N) Longitude (E) Temperature ( 0 C) Relative Humidity (%) Ibiakpan 5 0 09.858’ 7 0 43.958’ 24.0 95.0 Uruk Uso 5 0 10.662’ 7 0 43.215’ 25.0 94.0 Urua Aran 5 0 11.831’ 7 0 42.857’ 26.0 92.0 Utu 5 0 02.415’ 7 0 58.522’ 28.0 84.0 Table 2 indicates that the wood processing facilities chosen for the investigation were constructed to maintain their stage at a height of approximately 1 meter from the ground. In comparison to the instances at Urua Aran and Utu, the maximum distances of the operator from the machines at Ibiakpan and Uruk Uso are smaller. Nevertheless, the observed distances, which range from 0.36 m to 0.90 m, demonstrate that an unprotected operator is unable to avoid the cacophony that is produced. It is evident that long-term exposure at short distances could be as lethal as short-term exposure at long distances, provided that other influencing factors remain unaltered. International Journal of Advanced Scientific and Technical Research ISSN 2249-9954 Available online on http://www.rspublication.com/ijst/index.html volume 15, No. 5, 2025 DOI: 10.5281/zenodo.17284967 1 Original Article ©2025 RS Publication, [email protected] 250 Table 2. Particulars of the wood processing plants at each location Timber market location Description of the surveyed plants/machines Name Code used H (m) D (m) Ibiakpan Table Saw IBS1 0.90 0.48 Surface planer IBS2 0.90 0.45 Carving Machine IBS3 0.90 0.50 Curving Saw IBS4 0.90 0.48 Uruk Uso Table Saw UKS1 1.00 0.36 Surface planer UKS2 1.00 0.44 Carving Machine UKS3 1.00 0.38 Curving Saw UKS4 1.00 0.41 Urua Aran Table Saw URS1 0.94 0.90 Surface planer URS2 0.94 0.87 Carving Machine URS3 0.94 0.85 Curving Saw URS4 0.84 0.90 Utu Table Saw UTS1 0.92 0.70 Surface planer UTS2 0.90 0.67 Carving Machine UTS3 0.94 0.78 Curving Saw UTS4 1.00 0.72 H = Height of the machine stage from the ground; D = Average max. distance of operator from the machine Table 3 presents the acquired noise-distance statistics for each surveyed equipment under noload operational conditions. The IBS2, IBS3, UKS2, and UKS3 produce elevated noise levels. These results signify that working on the carving machines is the most risky activity, followed by operation of the surface planer, curving machine, and then table saw. This trend manifests in all locales. In comparison to the noise levels of the identical machines under load, as detailed in Table 4, the descending sequence of noise levels varies, with the exception of the surface planer and carving machine. At Ibiakpan and Uruk Uso, the table saw produces greater noise than the curving saw under load, and the opposite occurs at Urua Aran and Utu. The inconsistencies may be ascribed to differences in the ages of the machines, as it is plausible that they were not all installed on the same day, nor utilized for the same duration. International Journal of Advanced Scientific and Technical Research ISSN 2249-9954 Available online on http://www.rspublication.com/ijst/index.html volume 15, No. 5, 2025 DOI: 10.5281/zenodo.17284967 1 Original Article ©2025 RS Publication, [email protected] 251 Distance At Ibiakpan At Uruk Uso (m) IBS1 IBS2 IBS3 IBS4 UKS1 UKS2 UKS3 UKS4 1.0 86.5 ± 0.5 101.3 ± 106.5 ± 92.6 ± 0.4 86.8 ± 103.1 ± 107.8 ± 94.2 ± 0.9 0.9 0.4 0.5 0.5 0.4 2.0 78.5 ± 0.5 92.8 ± 0.6 96.3 ± 0.3 85.7 ± 0.4 79.1 ± 94.0 ± 0.4 98.6 ± 0.4 87.8 ± 0.8 0.7 3.0 73.2 ± 0.8 87.0 ± 0.3 90.3 ± 0.4 79.6 ± 0.5 72.4 ± 87.6 ± 0.3 91.7 ± 0.7 81.8 ± 0.9 0.4 4.0 69.3 ± 0.8 80.4 ± 0.8 85.0 ± 0.3 74.3 ± 0.4 68.6 ± 82.0 ± 0.5 85.5 ± 0.6 75.9 ± 0.8 0.6 5.0 65.9 ± 0.7 76.0 ± 0.5 80.9 ± 0.3 69.4 ± 0.3 64.9 ± 76.7 ± 0.3 79.8 ± 0.8 70.4 ± 0.9 0.7 6.0 62.5 ± 0.5 71.2 ± 0.7 76.3 ± 0.4 65.7 ± 0.3 62.0 ± 72.3 ± 0.4 76.1 ± 0.3 65.7 ± 0.9 0.7 7.0 59.6 ± 0.4 67.8 ± 0.6 72.3 ± 0.4 61.4 ± 0.4 59.3 ± 69.2 ± 0.5 71.9 ± 0.4 61.7 ± 0.5 0.6 8.0 56.3 ± 0.5 65.3 ± 0.9 68.7 ± 0.3 58.2 ± 0.2 56.1 ± 66.7 ± 0.5 68.3 ± 0.6 58.5 ± 0.7 0.5 9.0 53.3 ± 0.6 62.1 ± 0.8 65.4 ± 0.5 55.6 ± 0.4 53.5 ± 63.6 ± 0.4 65.2 ± 0.5 56.3 ± 0.6 0.6 10.0 51.4 ± 0.4 59.9 ± 0.7 63.5 ± 0.4 53.0 ± 0.2 51.8 ± 61.3 ± 0.4 63.4 ± 0.5 54.1 ± 0.5 0.5 Table 3 Contd Distance At Urua Aran At Utu (m) URS1 URS2 URS3 URS4 UTS1 UTS2 UTS3 UTS4 1.0 86.8 ± 0.2 106.3 ± 108.8 ± 96.7 ± 0.5 87.8 ± 101.3 ± 106.9 ± 98.6 ± 0.2 0.5 0.7 0.4 0.3 1.0 2.0 78.6 ± 0.4 98.8 ± 0.6 101.1 ± 88.5 ± 0.6 79.9 ± 93.0 ± 0.3 96.8 ± 0.8 90.9 ± 0.7 0.6 0.5 3.0 71.1 ± 0.4 91.5 ± 0.6 93.2 ± 0.8 81.9 ± 0.8 72.5 ± 86.9 ± 0.3 91.1 ± 0.9 83.9 ± 0.7 0.4 4.0 67.7 ± 0.3 84.0 ± 0.6 86.0 ± 0.2 75.3 ± 0.7 68.4 ± 80.6 ± 0.4 86.0 ± 0.7 77.6 ± 0.4 0.4 5.0 64.0 ± 0.3 77.9 ± 0.4 81.6 ± 0.6 70.4 ± 0.6 64.5 ± 76.3 ± 0.3 81.5 ± 0.4 73.2 ± 0.3 0.4 6.0 61.0 ± 0.3 72.1 ± 0.4 76.8 ± 0.8 66.2 ± 0.7 61.6 ± 72.1 ± 0.3 77.2 ± 0.5 68.6 ± 0.4 0.4 7.0 58.1 ± 0.4 68.1 ± 0.5 71.9 ± 0.4 62.0 ± 0.7 59.1 ± 68.0 ± 0.4 73.3 ± 0.5 63.7 ± 0.5 0.3 8.0 55.8 ± 0.3 65.3 ± 0.6 67.4 ± 0.4 58.5 ± 0.5 56.4 ± 65.2 ± 0.4 69.6 ± 0.4 58.9 ± 0.6 0.3 9.0 53.8 ± 0.4 63.0 ± 0.7 65.3 ± 0.6 55.3 ± 0.5 54.5 ± 62.3 ± 0.5 66.4 ± 0.4 56.2 ± 0.5 0.4 10.0 51.8 ± 0.4 61.1 ± 0.6 63.8 ± 0.5 53.6 ± 0.4 52.5 ± 60.4 ± 0.5 64.2 ± 0.5 54.5 ± 0.4 0.4 Table 3. Measured noise levels under unloading condition