Iranian Journal of

Background and Objective: Noise pollution causes many physiological, psychological, economic and social effects on human life. This issue is more important in the environment of industrial workplaces. This research aimed to adopt the functions of GIS for evaluating and spatial analysis of noises in industrial environments.
Materials and Methods: At the initial step, the spatial data for industrial halls were collected and stored as map layers into GIS database. Then, the noise pollution data sampled. The data, including the locations and values of sound pressure levels, were used for the relevant spatial analyses.
Results: The analyses included: the estimation of sound pressure levels in different areas of halls and at the given distance from machines, determination of noisy areas, development of sound noise risk map, interpolation of sound pressure level data, prioritization of the sound sources (i.e., machines) for a given point, prediction of sound pressure levels by moving machines, and optimal site selection and distribution of machines. The mean of noise pressure level was 95 dB for knitting hall,  93 dB for spinning hall 1 and 88 dB for spinning hall 2.
Conclusion: GIS plays a key role in the assessment of noise pollution in industrial workplaces. It is an appropriate tool to store, analyze, manage, and present all types of sound pressure spatial data. Specifically, the use of such system provides spatial intelligence and could help monitor, detect, control, and solve real word sound noise pollution issues.
 

Background and Objective: Heavy metal contamination in vegetable oils is a major food safety concern due to its potential adverse effects on public health. This study aimed to measure the concentrations of heavy metals (As, Pb, Cu, and Fe) in various types of vegetable oils and to assess the associated health risks from human consumption.
Materials and Methods: In this study, 72 samples of vegetable oils—including sesame, sunflower, and rapeseed—were systematically collected from markets in Sabzevar. The oil samples were accurately weighed and digested using a mixture of nitric acid, sulfuric acid, and hydrogen peroxide. The resulting digested solutions were filtered and analyzed for Pb, As, Cu, and Fe concentrations using microwave plasma atomic emission spectrometry (MP-AES). All procedures were performed in triplicate, following national Iranian standards. To accurately evaluate health risks, the hazard quotient (HQ) for non-carcinogenic effects and the lifetime cancer risk (LTCR) were calculated using Monte Carlo simulation (MCS). A daily intake of 0.227 kg of vegetable oils was assumed, based on national dietary data, to estimate chronic exposure.
Results: The results showed that the highest levels of heavy metals in vegetable oils were as follows: Pb (0.058 mg/kg) in sesame oil, As (0.090 mg/kg) in sunflower oil, and Cu and Fe (0.143 mg/kg and 0.847 mg/kg, respectively) in rapeseed oil. The Target Hazard Quotient (THQ) values for Pb (THQ = 0.146), Cu (THQ = 0.022), and Fe (THQ = 0.01) were within the safe range. However, the THQ for As (THQ = 1.905) was found to be significantly elevated. The cancer risk assessment indicated that the consumption of these oils is generally within the acceptable risk range, but the risk associated with As was estimated to be approximately 100 times higher than that of Pb.
Conclusion: The results of this study suggest that, although the carcinogenic risk associated with vegetable oil consumption is low, continuous monitoring of these products—particularly for heavy metal contaminants—is essential to ensure consumer safety.