Biodiesel from lignocellulosic biomass – Prospects and challenges

Biodiesel can be a potential alternative to petroleum diesel, but its high production cost has impeded its commercialization in most parts of the world. One of the main drivers for the generation and use of biodiesel is energy security, because this fuel can be produced from locally available resources, thereby reducing the dependence on imported oil. Many countries are now trying to produce biodiesel from plant or vegetable oils. However, the consumption of large amounts of vegetable oils for biodiesel production could result in a shortage in edible oils and cause food prices to soar. Alternatively, the use of animal fat, used frying oils, and waste oils from restaurants as feedstock could be a good strategy to reduce the cost. However, these limited resources might not meet the increasing demand for clean, renewable fuels. Therefore, recent research has been focused the use of residual materials as renewable feedstock in order to lower the cost of producing biodiesel. Microbial oils or single cell oils (SCOs), produced by oleaginous microorganisms have been studied as promising alternatives to vegetable or seed oils. Various types of agro-industrial residues have been suggested as prospective nutritional sources for microbial cultures. Since the most abundant residue from agricultural crops is lignocellulosic biomass (LCB), this byproduct has been given top-priority consideration as a source of biomass for producing biodiesel. But the biological transformation of lignocellulosic materials is complicated due to their crystalline structure. So, pretreatment is required before they can be converted into fermentable sugar. This article compares and scrutinizes the extent to which various microbes can accumulate high levels of lipids as functions of the starting materials and the fermentation conditions. Also, the obstacles associated with the use of LCB are described, along with a potentially viable approach for overcoming the obstacles that currently preclude the commercial production of biodiesel from agricultural biomass.     

Removal of o-nitrophenol from water by electrochemical degradation using a lead oxide/titanium modified electrode

This study examined o-nitrophenol removal from aqueous solutions by electrochemical oxidation employing a modified electrode. The modified electrode was produced by electrodepositing lead oxide onto a titanium substrate. Following electrochemical oxidation of o-nitrophenol-containing solutions, the remaining o-nitrophenol concentration and chemical oxygen demand (COD) values were determined. The optimum parameters were current density of 40 mA cm(-2), pH of 2.47, 60 min of electrolysis time, 4 g L(-1) NaCl electrolyte solution and temperature of 30 degrees C. Under these optimum conditions of electrochemical degradation using a lead oxide/titanium modified electrode complete removal of o-nitrophenol and COD was achieved.     

Modeling and simulation of industrial water demand of Beijing municipality in China

Statistic and econometric regression models were established in this study to analyze and predict industrial water demand, water deficits, and their future uncertainty in Beijing—a Chinese city with a severe water stress problem. A forecasting model was selected based on a modeling evaluation by comparing predictions with observations. Four scenarios were designed to simulate and analyze the future uncertainty of industrial water demand and the water deficit of Beijing. The modeling results for industrial water demand suggested that Beijing industry would face a water deficit between 3.06 × 10⁸ m³ in 2008 and 2.77×10⁸ m³ in 2015, though its industrial water demand would decrease from 6.31×10⁸ m³ to 4.84 ×10⁸ m³ during this period of time. Results from simulated scenario illustrated that, due to the extreme water scarcity situation, industry in Beijing would still face a serious water deficit problem even with a very optimistic scenario for the future.     

Geo-accumulation index and contamination factors of heavy metals (Zn and Pb) in urban river sediment

The aim of the present study was to appraise the levels of heavy metal contamination (Zn and Pb) in sediment of the Langat River (Selangor, Malaysia). Samples were collected randomly from 15 sampling stations located along the Langat River. The parameters measured were pH, redox potential, salinity, electrical conductivity, loss of ignition, cation exchanges capacity (Na, Mg, Ca, K), and metal ions (Zn and Pb). The geo-accumulation index (I _geo) and contamination factor (C _f) were applied to determine and classify the magnitude of heavy metal pollution in this urban river sediment. Results revealed that the I _geo of Pb indicated unpolluted to moderately polluted sediment at most of the sampling stations, whereas Zn was considered to be within background concentration. The I _geo results were refined by the C _f values, which showed Pb with very high C _f at 12 stations. Zinc, on the other hand, had low to moderate C _f values. These findings indicated that the sediment of the Langat River is severely polluted with Pb. The Zn concentration at most sampling points was well below most sediment quality guidelines. However, 40% of the sampling points were found to have a Pb concentration higher than the consensus-based probable effect concentration of 128 mg/kg (concentrations above this value are likely to cause harmful effects). This result not only highlights the severity of Pb pollution in the sediment of the Langat River, but also the potential risk it poses to the environment.     

Water quality associated public health risk in Bo, Sierra Leone

Human health depends on reliable access to safe drinking water, but in many developing countries only a limited number of wells and boreholes are available. Many of these water resources are contaminated with biological or chemical pollutants. The goal of this study was to examine water access and quality in urban Bo, Sierra Leone. A health census and community mapping project in one neighborhood in Bo identified the 36 water sources used by the community. A water sample was taken from each water source and tested for a variety of microbiological and physicochemical substances. Only 38.9% of the water sources met World Health Organization (WHO) microbial safety requirements based on fecal coliform levels. Physiochemical analysis indicated that the majority (91.7%) of the water sources met the requirements set by the WHO. In combination, 25% of these water resources met safe drinking water criteria. No variables associated with wells were statistically significant predictors of contamination. This study indicated that fecal contamination is the greatest health risk associated with drinking water. There is a need to raise hygiene awareness and implement inexpensive methods to reduce fecal contamination and improve drinking water safety in Bo, Sierra Leone.     

A small subsurface ion mobility spectrometer sensor for detecting environmental soil-gas contaminants

A small subsurface ion mobility spectrometer (SS-IMS) was constructed and tested with several environmental contaminants to determine its potential for monitoring gaseous volatile organic compounds in the vadose zone. Trichloroethylene (TCE) and tetrachloroethylene (PCE) were detected and separated in IMS for the first time. Detection limits as low as 1 part per billion volume-to-volume (ppb(v)) were observed. Reduced mobility (K(0)) values were reported for 11 environmental contaminants. These data demonstrated the potential of ion mobility spectrometry as a viable technology for detecting and separating environmental soil-gas contaminants in the field, which may lead to a practical and simple approach for long-term monitoring of contaminated soils.     

Prediction of total bed material load for rivers in Malaysia: A case study of Langat,Muda and Kurau Rivers

A soft computational technique is applied to predict sediment loads in three Malaysian rivers. The feed forward-back propagated (schemes) artificial neural network (ANNs) architecture is employed without any restriction to an extensive database compiled from measurements in Langat, Muda, Kurau different rivers. The ANN method demonstrated a superior performance compared to other traditional sediment-load methods. The coefficient of determination, 0.958 and the mean square error 0.0698 of the ANN method are higher than those of the traditional method. The performance of the ANN method demonstrates its predictive capability and the possibility of generalization of the modeling to nonlinear problems for river engineering applications.