Journal of Advances in Environmental Health Research
Volume:1 Issue: 2, Autumn 2013

Inappropriate handling and disposal practices of healthcare waste (HCW) at healthcare centers are significantly increasing health and environmental hazards. This paper summarizes the existing situation of HCW handling and management practices at healthcare facilities in Kodagu district (India). This study was conducted for a period of six months using well-designed checklists along with field observations and personal interviews with healthcare workers. Various HCW management issues like quantitative generation, category-wise handling, source level segregation, existing treatment, and disposal methods were studied. Moreover, drawbacks and practices in segregation, collection, transportation, storage, and final disposal methods of HCW in healthcare centers were investigated. The present study showed that lack of knowledge, guilty attitude, negligence of healthcare workers, and poor infrastructure were the major reasons for failure in the HCW handling and management system in the district. In addition to HCW management and infrastructures, associated health and environmental impacts were also discussed. Based on the existing situation and HCW management practices, suggestions and recommendations were made that may ensure the potential HCW handling and management practices and environmental risks minimization.

Of the problematic agents in the ecosystem, heavy metals have special importance because they are unabsorbable and have physiologic effects on living beings at low concentrations. This study has investigated the effect of silk worm cocoon on reducing mobility of zinc (Zn) and copper (Cu) for the first time. To this end, 5% cocoon adsorbent was added to the studied soil, which had been contaminated with Cu and Zn in separate containers at concentration of 600 mg/l. The experiment was performed in three repeats and two treatments (with and without adsorbent). Samples were incubated at 28°C at constant humidity for 3 hours, 1, 3, 7, 14, 21, and 28 days. Then both treatments were extracted using sequential extraction method and the concentration of Zn and Cu was processed using atomic absorption spectrophotometry. The results showed that there were changes in mobility of the Zn and Cu added to soil; adding silk worm cocoon to soil increased organic phase of Zn and Cu as compared to the soil without adsorbent. Data were analyzed by SPSS software. All comparisons of the means were performed at statistical level of 5% using Student’s independent t-test. Student’s independent t-test showed that the highest significant difference (P

Concentration and daily intake (DI) of heavy metals [lead (Pb), chromium (Cr), cadmium (Cd) and copper (Cu)] were investigated in four common edible vegetables including coriander, dill, radish root and radish leaf grown at peri-urban sites in Sanandaj, Iran. A total of 120 composite samples of vegetables were taken from ten vegetable farms during six months from May to October 2012. Inductively coupled plasma optical emission spectroscopy (ICP-OES) was used to estimate the levels of heavy metals. The results showed that Pb and Cr concentrations exceeded the safety limits given by Food and Agriculture Organization (FAO) or the World Health Organization (WHO) for human consumption with the exception of copper and cadmium that were lower than the permissible leveling in all of the samples. Furthermore, the results showed that there was a significant variation in the levels of these metals among the examined vegetables (P

Application of a reliable forecasting model for any water treatment plant (WTP) is essential in order to provide a tool for predicting influent water quality and to form a basis for controlling the operation of the process. This would minimize the operation and analysis costs, and assess the stability of WTP performances. This paper focuses on applying an artificial neural network (ANN) approach with a feed-forward back-propagation non-linear autoregressive neural network to predict the influent water quality of Sanandaj WTP. Influent water quality data gathered over a 2-year period were used to building the prediction model. The study signifies that the ANN can predict the influent water quality parameters with a correlation coefficient (R) between the observed and predicted output variables reaching up to 0.93. The prediction models developed in this work for Alkalinity, pH, calcium, carbon dioxide, temperature, total hardness, turbidity, total dissolved solids, and electrical conductivity have an acceptable generalization capability and accuracy with coefficient of determination (R2) ranging from 0.86 for alkalinity to 0.54 for electrical conductivity. The predicting ANN model provides an effective analyzing and diagnosing tool to understand and simulate the non-linear behavior of the influent water characteristics. The developed predicting models can be used by WTP operators and decision makers.

We assessed the physico-chemical status of twelve surface water samples from the Birjand flood plain (east of Iran) during fall 2010. The sampling points were selected on the basis of their importance. The physico-chemical parameters such as pH, temperature (T), electrical conductivity (EC), total dissolved solids (TDS), total hardness (TH), calcium (Ca2), magnesium (Mg2 ), sodium (Na), potassium (K), chloride (Cl-), sulphtate (SO42-), bicarbonate (HCO3–), carbonate (CO32–), nitrite (NO2–), nitrate (NO3–), dissolved oxygen (DO), biochemical oxygen demand (BOD5), and chemical oxygen demand (COD) of surface water were determined. The results showed that there were a statistical significant positive correlation between the pH and DO. pH and temperature indicated negative association with most of the parameters. Furthermore, EC showed highly significant positive association with TDS, TH, Ca2, Na, and Cl-. Results showed that the quality of surface water was not suitable for drinking, with references to the concentrations of EC, TDS, TH, Na, HCO3-, and BOD5 which were more than the prescribed limits, in most sites.

Failures in the water distribution network are some most important factors in water losses, water shortage and dissatisfaction of users and secondary pollutions as well. This research aimed to analyze failure in water distribution networks during 2006-2008, for better water management. Daily failure reports in Ahvaz, Iran distribution network during 2006-2008, were collected from emergency department of Ahvaz water and Wastewater Company; thereafter, they were entered into an Excel database, also failures were defined by pipes type, pipe diameter, and cause of the failure, and finally the data were analyzed. Results indicated that asbestos and polyethylene pipes show maximum failures; maximum failure and fracture has occurred in pipes with 100 and 150 mm diameters. The most important factors affecting on failure were corrosion, traffic load and landslide. In addition, simultaneous influence of type and the diameter of the pipe on the failures were statistically significant. The depth of pipes establishment, corrosion and obsolescence of pipes as well as improper type of pipes were the most important causes of failures in Ahvaz Water Distribution Network. In this regard, upgrading pipe material setting standards and renewing water pipe network are the main strategies for failures minimization.