ReviewEnvironmental monitoring and assessment2019
Geographical mapping and modelling of noise pollution from industrial motors: a case study of the Mbalmayo Thermal Power Plant in Cameroon.
Review in Environmental monitoring and assessment, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed, 4 citations in OpenAlex.
- Enhancing industrial acoustic environments through a mathematical model and 3D COMSOL acoustic simulation.Scientific reports · 2026Article
- Preparation of Industrial Noise Mapping and Improvement of Environmental Quality.Current pollution reports · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
To be able to geographically map, model and evaluate noisy sound emissions from industrial motors, emphases have been laid on various phenomena linked to the propagation of sound waves and their effects on the environment. The failure to respect factory-servicing norms coupled with the depreciation of parts of an industrial motor lead to additional sound production, which due to an accumulation in acoustic power and pressure levels contributes to environmental noise pollution. In this work, a study has been carried out on environmental noise pollution from a thermal power plant in Cameroon, using empirical, diagrammatic, analytical and noise map elaboration methods, with the aim of proposing an optimal protection of the surroundings of the thermal plant from the noise pollution. The results obtained show a similarity in propagation of acoustic pressure and power levels for the different types of frequencies considered. Besides these, the study has revealed that the inhabitants are exposed to sound levels higher than the upper limit of 50 dB and above the alert threshold level of 80 dB. At the geo-localized motors of the plant, the primary sources of acoustic power levels were found to fall within the range from 60 to 98 dB, which is very close to the acoustic pressure levels of between 60 and 95 dB. Due to dispersion of sound, the acoustic power levels are also felt at different points around the plant, considered here as secondary sources. From a general point of view, the observed distribution of the iso-sound contours from the collected data and their general NE-SW orientations show the development of new sources due to cumulative effects and superposition of sound waves at regular intervals. At the same time, the acoustic power and pressure levels have been found to be higher than 80 dB, which is the threshold value for human hearing. This therefore is considered detrimental to human health and wellbeing, provoking the need for a more profound investigation on the existing correlation between levels of sound due to stationary sources and frequency in a high sound medium and elaborating a strategic noise map for the town of Mbalmayo and its environs.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.