Temporal analysis of environmental noise and air pollution nearby a government hospital in Suburban Klang Valley, Malaysia

Introduction: Exposure to ambient noise and air pollution from road traffic has been associated with an increased risk of adverse health effects, such as heart disease and mental health. Although recent studies have identified tem- poral variations of noise and air pollution in urban areas, there has been limited data on the levels within sensitive areas such as a hospital. Thus, this study presents the scenario of noise and air quality level in the temporal dimen- sion assessed near a hospital located in the suburban area of Klang Valley, Malaysia. Methods: A-weighting noise level (dBA) 3M™ Edge™ 5 Personal Noise Dosimeter and PM2.5 concentration Dusttrak II Handheld Aerosol Monitor Model 8523 (μg/m3) were measured simultaneously with a 1-min interval. All measurements were taken from 0700 hrs until 1900 hrs on weekdays and weekends. Results: High noise level (min= 61.1 dBA, max= 62.0 dBA) and PM2.5 concentrations (min= 20 μg/m3, max= 29 μg/m3) were observed during morning peak hours on weekdays and weekends. Noise levels measured are exceeded the Department of Environment (DOE) guideline limit (55 dBA) and PM2.5 concentrations complied with the annual standard (35 μg/m3). We observed moderate correlations between noise and particulate pollution PM2.5 during weekdays and weekends (r= 0.66, p<0.01). Conclusion: Noise level and PM2.5 concentration varied widely over time and could have a negative impact on human health. Our case study rec- ommends that measurement of both noise and air pollution deserved further investigation to allow detailed exposure characterisation of this relationship

Calibration model of a low-cost air quality sensor using an adaptive neuro-fuzzy inference system

Conventional air quality monitoring systems, such as gas analysers, are commonly used in many developed and developing countries to monitor air quality. However, these techniques have high costs associated with both installation and maintenance. One possible solution to complement these techniques is the application of low-cost air quality sensors (LAQSs), which have the potential to give higher spatial and temporal data of gas pollutants with high precision and accuracy. In this paper, we present DiracSense, a custom-made LAQS that monitors the gas pollutants ozone (O3), nitrogen dioxide (NO2), and carbon monoxide (CO). The aim of this study is to investigate its performance based on laboratory calibration and field experiments. Several model calibrations were developed to improve the accuracy and performance of the LAQS. Laboratory calibrations were carried out to determine the zero offset and sensitivities of each sensor. The results showed that the sensor performed with a highly linear correlation with the reference instrument with a response-time range from 0.5 to 1.7 min. The performance of several calibration models including a calibrated simple equation and supervised learning algorithms (adaptive neuro-fuzzy inference system or ANFIS and the multilayer feed-forward perceptron or MLP) were compared. The field calibration focused on O3 measurements due to the lack of a reference instrument for CO and NO2. Combinations of inputs were evaluated during the development of the supervised learning algorithm. The validation results demonstrated that the ANFIS model with four inputs (WE OX, AE OX, T, and NO2) had the lowest error in terms of statistical performance and the highest correlation coefficients with respect to the reference instrument (0.8 < r < 0.95). These results suggest that the ANFIS model is promising as a calibration tool since it has the capability to improve the accuracy and performance of the low-cost electrochemical sensor

The impacts of traditional eastern diet on the community health and environment sustainability

Traditional Eastern diets are often based on grains, beans, and other healthful foods. It is usually low in red meat and rich in whole grains, vegetables, fruits, and seafood [1]. According to the World Health Organization, a healthy diet includes fruits, vegetables, legumes, nuts, whole grains, meat, fish, eggs, and milk. Each intake varies depending on individual characteristics such as age, gender, lifestyle, and level of physical activity. A healthy diet is essential because it provides a balanced diet to protect against many chronic non-communicable diseases, such as heart disease, diabetes, and cancer [2]. Healthy and sustainable food choices contribute to a series of Sustainable Development Goals, including SDG 2, SDG 3, SDG 11, and SDG 12. These goals are to ensure food security, an improvement in health and well-being, sustainable cities, and communities, and lastly, responsible consumption and production

Characteristics and source apportionment of Black Carbon (BC) in a suburban area of Klang Valley, Malaysia

Black carbon (BC) is of concern due to its contribution to poor air quality and its adverse effects human health. We carried out the first real-time monitoring of BC in Malaysia using an AE33 Aethalometer. Measurements were conducted between 1 January and 31 May 2020 in a university area in a suburban location of the Klang Valley. The measurement period coincided with the implementation of a movement control order (MCO) in response to COVID-19. The mean concentration of BC before the MCO was 2.34 µg/m3 which decreased by 38% to 1.45 µg/m3 during the MCO. The BC is dominated by fossil-fuel sources (mean proportion BCff = 79%). During the MCO, the BCff concentration decreased by more than the BCbb concentration derived from biomass burning. BC and BCff show very strong diurnal cycles, which also show some weekday–weekend differences, with maxima during the night and just before noon, and minima in the afternoon. These patterns indicate strong influences on concentrations from both traffic emissions and boundary layer depth. BC was strongly correlated with NO2 (R = 0.71), another marker of traffic emission, but less strongly with PM2.5 (R = 0.52). The BC absorption Ångström exponent (AAE) ranged between 1.1 and 1.6. We observed pronounced diurnal cycles of lower AAE in daytime, corresponding to BCff contributions from traffic. Average AAE also showed a pronounced increase during the MCO. Our data provides a new reference for BC in suburban Malaysia for the public and policy-makers, and a baseline for future measurements