Iranian Journal of

Background and Objectives:  In recent years, poor industrial waste managements have created many crises in human societies. The aim of this study was to investigate industrial waste management located between Tehran and Karaj zone in 2009-2010.
Materials and Methods: This study is descriptive and sectional which was done by site visits, (Iranian environmental protection organization)  use of questionnaires, database production and results analysis. The questionnaire consisted of 45 questions mainly about industrial waste quantity, quality and management. Total number of industries with over 50 personnel's, calculated as 283. Class-weighted sampling was used in which the sample size contained 50 industries.
Results: Total generated industrial waste was 123451, kg per day. Major hazardous waste generated in industrial  sections included: chemical and plastic making. About 45.28% of waste generated disposed by private sectors. Landfill with 62% and reuse with 17% were the first and second alternative of common methods for final disposal of solid waste in this zone.
Conclusion: In order to reduce hazardous waste generation in this zone, reuse and recovery maximization of the waste must be noted in short-term. In long-term, some industries such as chemical-plastic and electronics which have high rate of hazardous waste production must be replaced with other industries with low rate production, such as wood-cellulose and paper industries.

Background & Objectives: The prediction and quality control of the Karaj River water, as one of the important needed water supply sources of Tehran, possesses great importance. In this study, performance of artificial neural network (ANN), combined wavelet-neural network (WANN), and multi linear regression (MLR) models were evaluated to predict next month nitrate and dissolved oxygen of “Pole Khab” station located in Karaj River. Materials and Methods: A statistical period of 11 years was used for the input of the models. In combined WANN model, the real monthly-observed time series of river discharge (Q) and the quality parameters (nitrate and dissolved oxygen) were analyzed using wavelet analyzer. Then, their completely effective time series were used as ANN input. In addition, the ability of all three models were investigated in order to predict the peak points of time-series that have great importance. The capability of the models was evaluated by coefficient of efficiency (E) and the root mean square error (RMSE). Results: The research findings indicated that the accuracy and the ability of hybrid model of wavelet neural network with the attitude of elimniations of time series noise had beeb better than the other two modes so that hybrid model of Wavelet artificial neural network wase able the improve the rate of RMSE for Nitrate ions in comparison with neural network and multiple linear regression models respectively, amounting to 35.6% and 75.92%, for Dissolved Oxygen ion as much as 40.57% and 60.13%. Conclusion: owing of the high capability wavelet neural network and the elimination of the time series noises in the prediction of quality parameters of river’s water, this model can be convenient and fast way to be proposed for management of water quality resources and assursnce from water quality monitoring results and reduction its costs.

Background and Objectives: Although amount of hospital waste generation is less than urban waste generation, but because of health risks involved, these wastes need to be managed precisely and specifically. Therefore, the purpose of this study was to survey quality and quantity of waste generation in Emam Khomaini Hospital, Karaj, Iran and to estimate its generation process in future. Materials and Methods: the total amount of different waste percentage and its weight were examined and analyzed through monthly sampling from segregated waste (including general, infectious, pharmaceutical, and sharp wastes) in Emam Khomaini Hospital in Karaj during four years (2010-2013). Results: the hospital waste generation rate became double during four years of study. Among different types of waste, the highest monthly averages per bed for general and infectious waste was 48.3 and 46.5% respectively. In addition, the most and least amount of waste generation was observed in April and September respectively. Analysis of variance showed that the increasing trend of waste generation had a significant difference (P<0.001). Moreover, the estimate of waste generation process through ARIMA time series model represented continuation of increasing trend of waste generation up to 6.3 (kg bed^-1 day^-1) on December 2014. Conclusion: Waste generation in Emam Khomaini’s hospital follows an increase trend ( average generation from 2.98 to 4.44 kg bed^-1 day^-1 in 2010 to 2012 respectively, reflecting the increasing trend in the waste generation. ARIMA time series model shows that the waste generation rate would be 1.5 fold more in autumn 2014. Estimate of waste generation is necessary for planning and designing of waste management.

Background and Objectives: Heavy metals are seriously dangerous for the human body and their accumulation in the body can cause pathological changes in the organs and this can result in cardiovascular, liver and bone diseases, and even cancer. Human is exposed daily to these pollutants via consumption of food and water.

Materials and Methods: Considering the cumulative properties of these metals in plant organs, the amount of Cr, Mn, and Fe in soil and leaf, stem, and root tissues of cabbage, lettuce, spinach, and onions in Karaj City were investigated. For this purpose, 15 samples were randomly collected from each part of the plants, and then, the density of heavy metals was measured via atomic absorption spectrometer after cleansing, grinding, drying, and acid digestion. The data were then analyzed using SPSS software.

Results: It was found that leaves of spinach, cabbage, lettuce, and onion have higher concentrations of Cr, Mn, and Fe rather than their stems and roots. The roots of plants contain the least densities of metals. Moreover, concentrations of Fe, Cr, and Mn in soil were 11.87, 3.99 and 17.78 mg/kg, respectively. This was due to the high transportation of these metals to air-related parts of the plant like leaves. This research also showed that the densities of Cr, Mn, and Fe in leaves of studied spinach, onion, cabbage, and lettuce exceeded the FAO/WHO standard limitations (0.15, 0.3, and 0.3 mg/kg for Cr, Fe and Mn, respectively).

Conclusion: Due to the high concentrations of Cr, Mn, and Fe in studied vegetables in Karaj City, the consumption of these kinds of vegetables by citizens must be taken into consideration by regulatory agencies.