On-line production of ferrate with an electrochemical method and its potential application for wastewater treatment – A review

A number of studies on the oxidation of various organic/inorganic contaminants by ferrate(VI) were reported in the 1980s and 1990s. The exploration of the use of ferrate(VI) for water and wastewater treatment has been well addressed recently. However, challenges have existed for the implementation of ferrate(VI) technology in practice due to the instability of a ferrate solution or high production cost of solid ferrate products. The research has been carried out aiming at the generation and application of ferrate(VI) in situ. This paper thus reviews ferrate chemistry and its overall performance as a water treatment chemical, discusses the factors affecting the ferrate yield efficiency using the electrochemical method, and finally, summarises the work on the production and use of ferrate in situ which is currently under study.     

Removal of dinitrotoluenes from water via reduction with iron and peroxidase-catalyzed oxidative polymerization: a comparison between Arthromyces ramosus peroxidase and soybean peroxidase

A two-step process for the removal of dinitrotoluene from water is presented: zero-valent iron reduction is coupled with peroxidase-catalyzed polymerization of the resulting diaminotoluenes (DAT). The effect of pH was examined in the reduction step: at pH 6 the reaction occurred much more rapidly than at pH 8. In the second step, optimal pH and substrate ratio, minimal enzyme concentration and effect of polyethylene glycol (PEG) as an additive for greater than 95% conversion of DAT, over a 3h reaction period were determined using high performance liquid chromatography. Two enzymes were investigated and compared: Arthromyces ramosus peroxidase (ARP) and soybean peroxidase (SBP). The optimal pH values were 5.4 and 5.2 for ARP and SBP, respectively, but SBP was more resistant to mild acid whereas ARP was more stable in neutral solutions. SBP was found to have a greater hydrogen peroxide demand (optimal peroxide/DAT molar ratio for SBP: 2.0 and 3.0 for 2,4-diaminotoluene (2,4-DAT) and 2,6-diaminotoluene (2,6-DAT), respectively; for ARP: 1.5 and 2.75 for 2,4-DAT and 2,6-DAT, respectively) but required significantly less enzyme (0.01 and 0.1 U ml(-1) for 2,4-DAT and 2,6-DAT, respectively) to convert the DAT than ARP (0.4 and 1.5 U ml(-1) for 2,4-DAT and 2,6-DAT, respectively). PEG was shown to have no effect upon the degree of substrate conversion for either enzyme.     

Water Quality Changes in Chini Lake, Pahang, West Malaysia

A study of the water quality changes of Chini Lake was conducted for 12 months, which began in May 2004 and ended in April 2005. Fifteen sampling stations were selected representing the open water body in the lake. A total of 14 water quality parameters were measured and Malaysian Department of Environment Water Quality Index (DOE-WQI) was calculated and classified according to the Interim National Water Quality Standard, Malaysia (INWQS). The physical and chemical variables were temperature, dissolved oxygen (DO), conductivity, pH, total dissolved solid (TDS), turbidity, chlorophyll-a, biochemical oxygen demand (BOD), chemical oxygen demand (COD), total suspended solid (TSS), ammonia-N, nitrate, phosphate and sulphate. Results show that base on Malaysian WQI, the water in Chini Lake is classified as class II, which is suitable for recreational activities and allows body contact. With respect to the Interim National Water Quality Standard (INWQS), temperature was within the normal range, conductivity, TSS, nitrate, sulphate and TDS are categorized under class I. Parameters for DO, pH, turbidity, BOD, COD and ammonia-N are categorized under class II. Comparison with eutrophic status indicates that chlorophyll-a concentration in the lake was in mesotrophic condition. In general water quality in Chini Lake varied temporally and spatially, and the most affected water quality parameters were TSS, turbidity, chlorophyll-a, sulphate, DO, ammonia-N, pH and conductivity.     

A mathematical model to predict the composition and generation of hospital wastes in Iran

The aim of this study is to investigate the quality and quantity of hospital wastes in Iran. The generated hospital wastes have been estimated by the number of hospitals and the number of active beds in each province of Iran in 2001. All data and information have been gathered from: (i) Iran Statistics Center, (ii) literature review, and (iii) hospital waste investigations for an average hospital. Physical analyses have been conducted in terms of various materials (plastic, textile, paper, metal, and others) and components (biological, infectious, medical, and regular wastes). Based on the above-mentioned investigation and information, a mathematical model has been developed to calculate the generation of (infectious) hospital wastes for any desired year. Utilizing the model, generated infectious hospital wastes has been estimated as 698,937 tones for 2008 (short-term) and 3,494,387 tones for 2028 (long-term period). If the real infectious wastes are collected separately, then the generated infectious wastes will be reduced by 15.1% of the above-mentioned amount (139,787 tones for 2008, and 698,877 tones for 2028). Results of physical analysis show the components of the hospital waste as: (a) infectious, 67.3%; (b) medical, 8.8%; (c) biological, 1.8%; and (d) common municipal wastes, 22.1%. An appropriate collection method requires training the staff at hospitals along with preparation of the required facilities. Of course, both of these requirements are cost intensive.     

Effect of metal tolerant plant growth promoting Bradyrhizobium sp. (vigna) on growth, symbiosis, seed yield and metal uptake by greengram plants

The nickel and zinc tolerant plant growth promoting Bradyrhizobium sp. (vigna) RM8 was isolated from nodules of greengram, grown in metal contaminated Indian soils. The plant growth promoting (PGP) potentials of strain RM8 was assessed both in the presence and absence of nickel and zinc under in vitro conditions. Strain RM8 tolerated a high level of nickel (300 microg ml(-1)) and zinc (1400 microg ml(-1)) on yeast extract mannitol agar medium. Bradyrhizobium sp. (vigna) strain RM8 produced 13.3 microg ml(-1) of indole acetic acid in Luria Bertani broth at 100 microg ml(-1) of tryptophan which increased to 13.6 microg ml(-1) at 50 microg Ni ml(-1) and 13.5 microg ml(-1) at 300 microg Zn ml(-1). Strain RM8 was positive for siderophore, HCN and ammonia both in the absence and presence of nickel and zinc. The PGP activity of this strain was further evaluated with increasing concentrations of nickel and zinc using greengram as a test crop. The bioinoculant enhanced the nodule numbers by 82%, leghaemoglobin by 120%, seed yield by 34%, grain protein by 13%, root N by 41% and shoot N by 37% at 290 mg Ni kg(-1) soil. At 4890 mg Zn kg(-1) soil, the bioinoculant increased the nodule numbers by 50%, leghaemoglobin by 100%, seed yield by 36%, grain protein by 13%, root N by 47% and shoot N by 42%. The bioinoculant strain RM8 reduced the uptake of nickel and zinc by plant organs compared to plants grown in the absence of bioinoculant. This study suggested that the bioinoculant due to its intrinsic abilities of growth promotion and attenuation of the toxic effects of nickel and zinc could be exploited for remediation of metal from nickel and zinc contaminated sites.     

Oil spill cleanup cost estimation—Developing a mathematical model for marine environment

The field of oil spill cost modelling is not as well explored as desirable. Generally speaking, the existing models have either low accuracy, in that their predictions are far from the real cost, or low applicability, in that they are only valid under very specific conditions; such as in one particular country. This work strives to construct a model that is functional in a global scope and still possess a high level of accuracy. The resulting attempt is in many ways superior to the publicly available competitors, not only because of its predictive capacity but also because the model is quick to use, and its input variables should be readily available to any informed user. The model is more accurate comparing with similar available models. However, further study is needed to modify it to obtain more realistic results.     

A Modeling System to Assess Land Cover Land Use Change Effects on SAV Habitat in the Mobile Bay Estuary

Estuarine ecosystems are largely influenced by watersheds directly connected to them. In the Mobile Bay, Alabama watersheds we examined the effect of land cover and land use (LCLU) changes on discharge rate, water properties, and submerged aquatic vegetation, including freshwater macrophytes and seagrasses, throughout the estuary. LCLU scenarios from 1948, 1992, 2001, and 2030 were used to influence watershed and hydrodynamic models and evaluate the impact of LCLU change on shallow aquatic ecosystems. Overall, our modeling results found that LCLU changes increased freshwater flows into Mobile Bay altering temperature, salinity, and total suspended sediments (TSS). Increased urban land uses coupled with decreased agricultural/pasture lands reduced TSS in the water column. However, increased urbanization or agricultural/pasture land coupled with decreased forest land resulted in higher TSS concentrations. Higher sediment loads were usually strongly correlated with higher TSS levels, except in areas where a large extent of wetlands retained sediment discharged during rainfall events. The modeling results indicated improved water clarity in the shallow aquatic regions of Mississippi Sound and degraded water clarity in the Wolf Bay estuary. This integrated modeling approach will provide new knowledge and tools for coastal resource managers to manage shallow aquatic habitats that provide critical ecosystem services.     

Integrated Approach for Prioritizing Watersheds for Management: A Study of Lidder Catchment of Kashmir Himalayas

The Himalayan watersheds are susceptible to various forms of degradation due to their sensitive and fragile ecological disposition coupled with increasing anthropogenic disturbances. Owing to the paucity of appropriate technology and financial resources, the prioritization of watersheds has become an inevitable process for effective planning and management of natural resources. Lidder catchment constitutes a segment of the western Himalayas with an area of 1,159.38 km². The study is based on integrated analysis of remote sensing, geographic information system, field study, and socioeconomic data. Multicriteria evaluation of geophysical, land-use and land-cover (LULC) change, and socioeconomic indicators is carried out to prioritize watersheds for natural resource conservation and management. Knowledge-based weights and ranks are normalized, and weighted linear combination technique is adopted to determine final priority value. The watersheds are classified into four priority zones (very high priority, high priority, medium priority, and low priority) on the basis of quartiles of the priority value, thus indicating their ecological status in terms of degradation caused by anthropogenic disturbances. The correlation between priority ranks of individual indicators and integrated indicators is drawn. The results reveal that socioeconomic indicators are the most important drivers of LULC change and environmental degradation in the catchment. Moreover, the magnitude and intensity of anthropogenic impact is not uniform in different watersheds of Lidder catchment. Therefore, any conservation and management strategy must be formulated on the basis of watershed prioritization.     

Effect of Tinospora cordifolia on the reduction of ultraviolet radiation‐induced cytotoxicity and DNA damage in PC12 cells

The safety of Tinospora cordifolia and its potential to protect against ultraviolet radiation‐induced cytotoxicity and DNA damage in PC12 cells were investigated. To evaluate the safety of T. cordifolia, cell viability and agarose gel electrophoresis were carried out using PC12 cells treated with 0 to 100 μg mL^?1 of methanol extract of T. cordifolia. T. cordifolia extracts did not show cytotoxicity ranging 0 to 100 μg mL^?1. In addition, T. cordifolia extracts significantly increased cell viability at 1 ng, 10 ng and 1 μg mL^?1 concentrations in serum‐deprived medium compared to control. To confirm the protective role against UV‐induced damage, PC12 cells alone or in the presence of 10 ng, 100 ng, or 1 μg mL^?1 of T. cordifolia extract were exposed to 250, 270 and 290 nm of UV radiation, which corresponded to doses of 120, 150 and 300 mJ cm^?2, respectively. Treatment with T. cordifolia extracts significantly increased the cell survival rate irradiated at 290 nm. In addition, T. cordifolia extracts significantly reduced cyclobutane pyrimidine dimer formation induced by UV irradiation at all wavelengths. In conclusion, T. cordifolia is not toxic and safe for cells. Our findings can support its application as phototherapy in the medical sector.     

Optimal temporal scale for the correlation of AOD and ground measurements of PM2.5 in a real-time air quality estimation system

Aerosol optical depth (AOD), an indirect estimate of particulate matter using satellite observations, has shown great promise in improving estimates of PM_2.5 (particulate matter with aerodynamic diameter less than or equal to 2.5 μm) surface. Currently, few studies have been conducted to explore the optimal way to apply AOD data to improve the model accuracy of PM_2.5 in a real-time air quality system. We believe that two major aspects may be worthy of consideration in that area: 1) an approach that integrates satellite measurements with ground measurements in the estimates of pollutants and 2) identification of an optimal temporal scale to calculate the correlation of AOD and ground measurements. This paper is focused on the second aspect, identifying the optimal temporal scale to correlate AOD with PM_2.5. Five following different temporal scales were chosen to evaluate their impact on the model performance: 1) within the last 3 days, 2) within the last 10 days, 3) within the last 30 days, 4) within the last 90 days, and 5) the time period with the highest correlation in a year. The model performance is evaluated for its accuracy, bias, and errors based on the following selected statistics: the Mean Bias, the Normalized Mean Bias, the Root Mean Square Error, Normalized Mean Error, and the Index of Agreement. This research shows that the model with the temporal scale: within the last 30 days, displays the best model performance in a southern multi-state area centered in Mississippi using 2004 and 2005 data sets.