Effect of water washing on the thermal behavior of rice straw

Rice straw can be used as a renewable fuel for heat and power generation. It is a viable mean of replacing fossil fuels and preventing pollution caused by open burning, especially in the areas where this residual biomass is generated. Nevertheless, the thermal conversion of rice straw can cause some operating problems such as slag formation, which negatively affects thermal conversion systems. So, the main objective of this research is studying the combustion behavior of rice straw samples collected from various regions by applying thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC). In addition, the thermal behavior of ashes from rice straw was also analyzed in order to detect their melting points, and ash sintering was detected at different temperatures within the range between 550 and 1000 °C. Since washing rice straw with water could reduce the content of undesirable inorganic compounds related to the ash fusibility, samples of washed rice straw were analyzed under combustion conditions to investigate its differences regarding the thermal behavior of rice straw. The results showed that rice straw washing led to a significant improvement in its thermal behavior, since it reduced the ash contents and sintering formation.     

Biosorption of Direct Yellow 12 from aqueous solution using green alga Ulva lactuca

The potential of commonly available green alga Ulva lactuca was investigated as viable biomaterials for removal of synthetic azo dye (Direct Yellow 12, DY-12) from aqueous solution. The results obtained from the batch experiments revealed that the ability of the U. lactuca to remove DY-12 from its aqueous solution was dependent on the dye concentration, pH, and algal biomass but less dependent on the particle size of the U. lactuca. The equilibrium conditions and kinetics of adsorption were investigated, and the adsorption kinetic was consistent with the pseudo-second-order model (R²=1). The adsorption isotherm followed only the Freundlich model with a correlation coefficient R²=0.99. This study demonstrated that the U. lactuca could be used as an effective biosorbent for the removal of DY-12 from its aqueous solution.     

An assessment of heavy-metal contamination in surface sediments of the Suez Gulf using geoaccumulation indexes and statistical analysis

An assessment of marine pollution due to metals was made in the Suez Gulf based on surface costal sediment collected from 18 locations along the Gulf. The samples were dried and acid-digested, and the metal contents (Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, and Zn) were determined using a flame atomic absorption spectrophotometer (air-acetylene) with deuterium background correction. An evaluation of the heavy-metal pollution status of the Gulf was carried out using enrichment factors (EF) and geo-accumulation Indexes (I_geo). Also, heavy-metal concentrations in Suez Gulf sediments were evaluated using the Effect Range-Low (ERL) and the Effect Range-Median (ERM). The results of a Spearman correlation and factor and cluster analysis of the heavy metals analysed in the collected sediment were discussed. The main source of contamination is offshore oil field and industrial wastes, which arise due to the ineffective and inefficient operation equipments, illegal discharge and lack of supervision, and prosecution of offenders.     

Comparative study of heavy metal distribution in some coastal seaweeds of Alexandria, Egypt

The distribution of Cd, Cu, Fe, Hg, Mn, Ni, Pb, and Zn concentration in five algae species (Enteromorpha intestinalis, Enteromorpha linza, Ulva lactuca, Corallina mediterranea, Pterocladia capillacea) collected from three areas having different types of metal contamination along Alexandria coastal waters (Egypt) were determined by Atomic Absorption Spectrometry. The recovery study was carried out using a Certified Reference Material TORT-2. The obtained heavy metal contents indicate that different species demonstrate various degree of metal accumulation. Enteromorpha intestinalis (green algae) recorded the highest levels of Fe and Mn while Corallina mediterranea (Calcareous red algae) recorded the highest concentration of Pb, Ni, and Cd in the three areas under study. According to the present study, filamentous algae (Enteromorpha intestinalis) showed the ability to concentrate greater amount of trace elements than the foliaceous ones (Enteromorpha linza). In each area, mercury concentration has nearly the same value for all species under study.     

Speciation of organotin compounds in sediments of semi-closed areas along the Mediterranean coast of Alexandria

Organotin compounds were measured in sediments of four different semi-closed areas of the Mediterranean coast of Alexandria: the Eastern Harbour, Western Harbour, El-Max Bay, and Abu-Qir Bay. Due to the commercial trade activity inside the Western Harbour, in addition to the effect of wastes discharged from El Noubaria canal, it shows the highest concentrations of total tin (6.34 μg g^-1 dry weight), dibutyl tin (1.63 μg g^-1 wet weight), tributyl tin (0.33 μg g^-1 wet weight) and diphenyl tin (1.06 μg g^-1 wet weight) compared with other locations. The concentrations of TBT species showed the highest contents compared with DBT and DPhT compounds in all sampling areas. This trend might be due to the worldwide use of TBT not only as biocides in antifouling paints but also as preserving agents for wood, fungicides in agricultural activities, and heat and UV stabilizers of PVC, which results in a direct release of TBT into the water body, accumulation in aquatic fauna. There is also precipitation into sediments and a decrease in degradation rate into its derivatives. Variations, types, concentrations, and distribution of different organotin compounds are discussed in the areas under investigation. The study reveals a new record of organotin compounds along the Alexandria coast and makes comparisons with other surrounding areas of interest.     

NONLINEAR MODELING AND PREDICTION OF A RIVER FLOW SYSTEM1

ABSTRACT: Model estimation and prediction of a river flow system are investigated using nonlinear system identification techniques. We demonstrate how the dynamics of the system, rainfall, and river flow can be modeled using NARMAX (Nonlinear Autoregressive Moving Average with eXogenuous input) models. The parameters of the model are estimated using an orthogonal least squares algorithm with intelligent structure detection. The identification of the nonlinear model is described to represent the relationship between local rainfall and river flow at Enoree station (inputs) and river flow at Whitmire (output) for a river flow system in South Carolina.