Evaluation of the host-specificity and prevalence of enterococci surface protein (esp) marker in sewage and its application for sourcing human fecal pollution

The suitability of the enterococci surface protein (esp) marker to detect human fecal pollution was evaluated by testing 197 fecal samples from 13 host groups in Southeast Queensland, Australia. Overall, this marker was detected in 90.5% of sewage and septic system samples and could not be detected in any fecal samples from 12 animal host groups. The sensitivity of the esp primer to detect the human-specific esp marker in sewage and septic samples was 100 and 67%, respectively. The overall specificity of this marker to distinguish between human and animal fecal pollution was 100%. Its prevalence in sewage was also determined by testing samples from the raw sewage, secondary effluent, and treated effluent of a sewage treatment plant (STP) over five consecutive days. Of the 15 samples tested, 12 (80%) were found to be positive for this marker. In contrast, it was not found in three samples from the treated effluent and these samples did not contain any culturable enterococci. The PCR limit of detection of this marker in freshwater samples was up to dilution 1 x 10(-4) and the number of culturable enterococci at this dilution was 4.8 x 10(1) +/- 7.0 x 10 degrees colony forming unit (CFU). The utility of this marker was evaluated by testing water samples from three non-sewered catchments in Pine Rivers in Southeast Queensland. Of the 13 samples tested, eight were positive for this marker with the number of enterococci ranging between 1.8 x 10(3) to 8.5 x 10(3) CFU per 100 mL of water. Based on the results, it can be concluded that the esp marker appears to be sewage specific and could be used as a reliable marker to detect human fecal pollution in surface waters in Southeast Queensland, Australia.     

Chemical Compositions and Sources of Organic Matter in Fine Particles of Soils and Sands from the Vicinity of Kuwait City

Fine particles in the atmosphere from soil and sand resuspension contain a variety of organic compounds from natural biogenic and anthropogenic matter. Soil and sand samples from various sites near Kuwait city were collected, sieved to retain the fine particles, and extracted with a mixture of dichloromethane and methanol. The extracts were derivatized and analyzed by gas chromatography-mass spectrometry in order to characterize the chemical compositions and sources of the organic components. The major inputs of organic compounds were from both natural biogenic and anthropogenic sources in these samples. Vegetation was the major natural source of organic compounds and included n-alkanols, n-alkanoic acids, n-alkanes, sterols and triterpenoids. Saccharides had high concentrations (31–43%) in the sand dune and seafront samples, indicating sources from decomposed vegation materials and/or the presence of viable microbiota such as bacteria and fungi. Vehicular emission products, leakage of lubricating oils, discarded plastics and emissions from cooking operations were the major anthropogenic inputs in the samples from the urban areas. This input was mainly UCM, n-alkanes, hopanes, plasticizers and cholesterol, respectively.     

Description of hydrogeologic heterogeneity and evaluation of radionuclide transport at an underground nuclear test

Realistic models of contaminant transport in groundwater demand detailed characterization of the spatial distribution of subsurface hydraulic properties, while at the same time programmatic constraints may limit collection of pertinent hydraulic data. Fortunately, alternate forms of data can be used to improve characterization of spatial variability. We utilize a methodology that augments sparse hydraulic information (hard data) with more widely available hydrogeologic information to generate equiprobable maps of hydrogeologic properties that incorporate patterns of connected permeable zones. Geophysical and lithologic logs are used to identify hydrogeologic categories and to condition stochastic simulations using Sequential Indicator Simulation (SIS). The resulting maps are populated with hydraulic conductivity values using field data and Sequential Gaussian Simulation (SGS). Maps of subsurface hydrogeologic heterogeneity are generated for the purpose of examining groundwater flow and transport processes at the Faultless underground nuclear test, Central Nevada Test Area (CNTA), through large-scale, three-dimensional numerical modeling. The maps provide the basis for simulation of groundwater flow, while transport of radionuclides from the nuclear cavity is modeled using particle tracking methods. Sensitivity analyses focus on model parameters that are most likely to reduce the long travel times observed in the base case. The methods employed in this study have improved our understanding of the spatial distribution of preferential flowpaths at this site and provided the critical foundation on which to build models of groundwater flow and transport. The results emphasize that the impacts of uncertainty in hydraulic and chemical parameters are dependent on the radioactive decay of specific species, with rapid decay magnifying the effects of parameters that change travel time.     

Social support and managerial affective responses to job stress

This research examines the moderating or buffering effects of two social support variables—support from the work group and from the supervisor—on the relationships of role conflict and ambiguity to intrinsic job satisfaction, job involvement and job anxiety. Data were collected from a sample of 89 middle-lower managerial personnel in a large, heavy equipment manufacturing firm in the Midwest. The moderated regression technique was used in data analysis. Significant interactions were obtained between the role variables and both social support variables. The results were in the predicted direction for positive work outcomes (i.e. job satisfaction and involvement) and contrary to prediction for negative work outcome (i.e. job anxiety). Implications of the findings for future research, the management of stress and leadership behaviour are discussed.     

Heavy Metals Monitoring using Bivalves from Mediterranean Sea and Red Sea

The concentrations of heavy metals (Cd, Co, Cu, Fe, Mn, Ni, Pd and Zn) were measured in the Bivalves (Modiolus auriculatus and Donax trunculus) collected from the Egyptian coasts of Mediterranean Sea and Brachiodonates sp. from the Egyptian coasts of Red Sea. The average concentrations of the heavy metals analyzed exhibited the following decreasing order: Fe > Zn > Cu > Mn > Ni > Co > Pb > Cd for both Mediterranean Sea and Red Sea. The analyses of Cd, Co, Ni, Pb, and Zn showed higher average concentrations for samples collected from Red Sea than that collected from Mediterranean Sea, while Fe, Cu and Mn showed the reverse results. Fe was used as a normalizing agent for all studied metals and exhibited presence of two locations from each of Mediterranean Sea and Red Sea have anthropogenic inputs of heavy metals. These results suggest that the coastal area in both Mediterranean Sea and Red Sea of Egypt might be considered relatively unpolluted with heavy metal.     

Influence of biomass density and food to microorganisms ratio on the mixed culture type I methanotrophs enriched from activated sludge

Methanotrophic based process can be the remedy to offset the wastewater treatment facilities increasing energy requirements due to methanotroph's unique ability to integrate methane assimilation with multiple biotechnological applications like biological nitrogen removal and methanol production. Regardless of the methanotrophic process end product, the challenge to maintain stable microbial growth in the methanotrophs cultivation bioreactor at higher cell densities is one of the major obstacles facing the process upscaling. Therefore, a series of consecutive batch tests were performed to attentively investigate the biomass density influence on type I methanotrophs bacterial growth. In addition, food to microorganisms(F/M), carbon to nitrogen(C/N) and nitrogen to microorganisms(N/M) ratio effect on the microbial activity was studied for the first time. It was clarified that the F/M ratio is the most influencing factor on the microbial growth at higher biomass densities rather than the biomass density increase, whereas C/N and N/M ratio change, while using nitrate as the nitrogen source,does not influence methanotrophs microbial growth. These study results would facilitate the scaling up of methanotrophic based biotechnology by identifying that F/M ratio as the key parameter that influences methanotrophs cultivation at high biomass densities.     

Wastewater degradation by iron/copper nanoparticles and the microorganism growth rate

Nowadays, trends in wastewater treatment by zero-valent iron (ZVI) were turned to use bimetallic NZVI particles by planting another metal onto the ZVI surface to increase its reactivity. Nano size zero-valent iron/copper (NZVI/Cu⁰) bimetallic particles were synthesized in order to examine its toxicity effects on the wastewater microbial life, kinetics of phosphorus, ammonia stripping and the reduction of chemical oxygen demand (COD). Various concentrations of NZVI/Cu⁰ and operation conditions both aerobic and anaerobic were investigated and compared with pure NZVI experiment. The results showed that addition 10 mg/L of NZVI/Cu⁰ significantly increased the numbers of bacteria colonies under anaerobic condition, conversely it inhibited bacteria activity with the presence of oxygen. Furthermore, the impact of nanoparticles on ammonia stripping and phosphorus removal was also linked to the emitted iron ions electrons. It was found that dosing high concentration of bimetallic NZVI/Cu⁰ has a negative effect on ammonia stripping regardless of the aeration condition. In comparison to control, dosing only 10 mg/L NZVI/Cu⁰, the phosphorus removal increased sharply both under aerobic and anaerobic conditions, these outcomes were obtained as a result of complete dissolution of bimetallic nanoparticles which formed copper-iron oxides components that are attributed to increasing the phosphorus adsorption rate.     

Modeling Change-Pattern-Value Dynamics on Land Use: An Integrated GIS and Artificial Neural Networks Approach

The use of spatial methods to detect and characterize changes in land use has been attracting increasing attention from researchers. The objectives of this article were to formulate the dynamics of land use on the temporal and spatial dimensions from the perspectives of the Change-Pattern-Value (CPV) and driving mechanism, based on multitemporal remote sensing data and socioeconomic data. The Artificial Neural Networks were used to identify the factors driving changes in land use. The Pearl River Delta Region of southeast China, which was experiencing rapid economic growth and widespread land conversion, has been selected as the study region. The results show that from 1985 to 2000 in the study region (1) the most prominent characteristics of change in land use were the expansion of the urban land at the expense of farmland, forests, and grasslands, (2) the land-use pattern was being optimized during this period, (3) in an analysis of value, built-up land can yield a return of more than 30 times that of farmland, water area, and forests lands, and (4) rapid economic development, growth in population, and the development of an infrastructure were major driving factors behind ecological land loss and the nonecological land expansion.