Dataset on noise level measurement in Ota metropolis, Nigeria

Comparative Diagnosis of the Urban Noise Problem from Infrastructural and Social Sensing Approaches: A Case Study in Ningbo, China

Urban noise causes a variety of health problems, and its prevention and control have thus become an important research topic in urban governance. Although existing literature is fairly comprehensive in revealing the physical noise patterns, it lacks the concern of people’s perceived seriousness, especially at the macroscopic, i.e., citywide scale. In this paper, we borrow from the “exposure-perception-behavior” theory in environmental psychology, and propose an analytical framework for diagnosing the urban noise problem that integrates the Infrastructural and Social Sensing perspectives. Utilizing noise monitoring data that fills the spatiotemporal granularity gaps of official noise monitoring, as well as the “12345” urban complaint hotline records which serve as a proxy for residents’ perceived noise levels, we empirically examine the mechanisms for physical magnitude and perceived seriousness of urban noise, respectively, by taking the Jiangbei District of Ningbo City, China as an example. Results show that the existence of perceptual bias and behavioral preference effects did shape people’s perceived noise problem map that is vastly different from that of the physical noise magnitude, in which the semantics of urban places, temporal rhythms of life, and population demographics significantly influenced people’s tolerance of noise. We conclude the paper with suggestions on updating the existing National Standard for urban noise regulation to reflect the perceptual aspect, and also methodological discussions on possible ways to recognize and utilize the perceptual bias in social-sensing big-data to better accommodate urban governance.

Environmental health situation in Nigeria: current status and future needs

Environmental health-related risks are becoming a primary concern in Nigeria, with diverse environmental problems such as air pollution, water pollution, oil spillage, deforestation, desertification, erosion, and flooding (due to inadequate drainage systems) caused mostly by anthropogenic activities. This paper reviews the pre-existing and current environmental health problems, proffer future research and needs, policy needs, and recommendations necessary to mitigate Nigeria's environmental health situation. Data from the Institute of Health Metric and Evaluation on Global Burden of Disease (GBD) was used to ascertain the causes of Death and Disability-adjusted Life Years (DALYs) in Nigeria from 2007-2017 and published literatures where reviewed. According to the world health data report, most of the highest-ranked causes of DALYs in Nigeria are related to environmental risk factors. The lower respiratory infection associated with air pollution has advanced from the 4th in 2007 to the highest ranked cause of death in 2017. Other predominant causes of death associated with environmental risk factors include chronic respiratory diseases, cardiovascular diseases, enteric infections, diarrheal diseases, communicable, maternal, neonatal, and nutritional disease, which has resulted in approximately 800 thousand deaths and 26 million people living with DALYs per annum in Nigeria. Major environmental risk factors include household air pollution, ambient air pollution, water, sanitation, and hygiene (WaSH), which shows a prolonged but progressive decline. In contrast, ambient particulate matter pollution, ambient ozone pollution, and lead exposure show a steady rise associated with death and DALYs in Nigeria, indicating a significant concern in an environmental health-related risk situation. Sustaining a healthy environment is critical in improving the quality of life and the span of a healthy life. Therefore, environmentally sustainable development policies and practices should be essential to the population and policymakers for a healthy life.

Exposure assessment to road traffic noise levels and health effects in an arid urban area

Road traffic noise exposures have been recognized as serious environmental health concerns, especially in most developing countries with arid climate conditions, rapid increase in vehicle population, and limited traffic management systems. The excessive noise exposure level is associated with increase in the incidence of cardiovascular diseases and anxiety, including annoyance. This study aimed at determining traffic noise levels in residential areas, including the assessment of its annoyance and health effects based on the people's perception and reportage. To do so, field measurement and traffic noise modeling were carried out in six road points to estimate the current noise levels along various roads close to human inhabitants in Muscat Governorate, Sultanate of Oman. The detailed measured noise levels in urban residential areas across the selected roads showed that noise levels have exceeded the local and international threshold limits at all locations during the entire day. The high sound levels (48.0-56.3 dBA) were observed using the US Federal Highway Administration's Traffic Noise Model (TNM, version 2.5) results, which were in agreement with the observed (56.3-60.4 dBA) data. To assess health implication to residents through interviews (n = 208), annoyance at home was found to be little (32%), moderate (28%), and high (9%) in comparison with workplace settings of 42%, 43%, and 15%, respectively. Nineteen percent of the interviewees had difficulties in sleeping, while 19.8% experienced stress due to road traffic noise exposures. Moreover, a strong association (p < 0.05) was established between the use and objection of noise barriers. The study revealed high noise levels and the prevalence of annoyance and health effects among the exposed population. Therefore, immediate action is required to tackle the current noise levels.

A Study of Noise Pollution Measurements and Possible Effects on Public Health in Ota Metropolis, Nigeria

BACKGROUND:

Noise pollution has become a major environmental problem leading to nuisances and health issues.

AIM:

This paper aims to study and analyse the noise pollution levels in major areas in Ota metropolis. A probability model which is capable of predicting the noise pollution level is also determined.

METHODS:

Datasets on the noise pollution level in 41 locations across Ota metropolis were used in this research. The datasets were collected thrice per day; morning, afternoon and evening. Descriptive statistics were performed, and analysis of variance was also conducted using Minitab version 17.0 software. Easy fit software was however used to select the appropriate probability model that would best describe the dataset.

RESULTS:

The noise levels are way far from the WHO recommendations. Also, there is no significant difference in the effects of the noise pollution level for all the times of the day considered. The log-logistic distribution provides the best fit to the dataset based on the Kolmogorov Smirnov goodness of fit test.

CONCLUSION:

The fitted probability model can help in the prediction of noise pollution and act as a yardstick in the reduction of noise pollution, thereby improving the public health of the populace.