6 research outputs found

    Data on the environmental exposure to lead in Iran

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    The data was obtained to present the environmental and occupational exposure to lead in Iranian populations based on the published articles. To acquire the data, online resources including Google Scholar, Magiran, SID, Iranmedex, PubMed, and Science Direct were searched and 104 articles were found out of which 70 that focused on the level of lead in blood, urine, milk, and hair of different Iranian populations were selected. Since the results of the studies were not homogenous, it was not possible to carry out a meta-analysis. The average blood lead level (BLL) among workers, ordinary people, patients with specific diseases, addicts, and pregnant women, women in labor, infants, and children are presented in this article. The average BLL was compared to the standards. © 2018 The Author

    System Dynamics Model For Hospital Waste Characterisation and Generation in Developing Countries.

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    Waste management policy makers always face the problem of how to predict the future amount and composition of medical solid waste, which in turn will help determine the most appropriate treatment, recycling and disposal strategy. An accurate prediction can assist in both the planning and design of medical solid waste management systems. Insufficient budget and unavailable management capacity are the main reasons for the scarcity of medical solid waste quantities and components historical records, which are so important in long-term system planning and short-term expansion programs. This paper presents a new technique, using system dynamics modelling, to predict generated medical solid waste in a developing urban area, based on a set of limited samples from Jenin District hospitals, Palestine. The findings of the model present the trend of medical solid waste generation together with its different components and indicate that a new forecasting approach may cover a variety of possible causative models and track inevitable uncertainties when traditional statistical least-squared regression methods are unable to handle such issues
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