Molecular identification and nanoremediation of microbial contaminants in algal systems using untreated wastewater

Wastewater-algal biomass is a promising option to biofuel production. However, microbial contaminants constitute a substantial barrier to algal biofuel yield. A series of algal strains, Nannochloris oculata and Chlorella vulgaris samples (n = 30), were purchased from the University of Texas, and were used for both stock flask cultures and flat-panel vertical bioreactors. A number of media were used for isolation and differentiation of potential contaminants according to laboratory standards (CLSI). Conventional PCR amplification was performed followed by 16S rDNA sequencing to identify isolates at the species level. Nanotherapeutics involving a nanomicellar combination of natural chitosan and zinc oxide (CZNPs) were tested against the microbial lytic groups through Minimum Inhibitory Concentration (MIC) tests and Transmission Electronic Microscopy (TEM). Results indicated the presence of Pseudomonas spp., Bacillus pumilus/ safensis, Cellulosimicrobium cellulans, Micrococcus luteus and Staphylococcus epidermidis strains at a substantial level in the wastewater-fed algal reactors. TEM confirmed the effectiveness of CZNPs on the lytic group while the average MICs (mg/mL) detected for the strains, Pseudomonas spp, Micrococcus luteus, and Bacillus pumilus were 0.417, 3.33, and 1.458, respectively. Conclusively, CZNP antimicrobials proved to be effective as inhibitory agents against currently identified lytic microbial group, did not impact algae cells, and shows promise for in situ interventions.     

Macro,Meso, and Micro‐Efficiencies in Water Resources Management: A New Framework Using Water Balance1

Haie, Naim and Andrew A. Keller, 2012. Macro, Meso, and Micro‐Efficiencies in Water Resources Management: A New Framework Using Water Balance. Journal of the American Water Resources Association (JAWRA) 48(2): 235‐243. DOI: 10.1111/j.1752‐1688.2011.00611.x Abstract: One of the most important performance indicators for water resources systems (WRSs) management is efficiency. Here, water balance, based on mass conservation, is utilized to systemically develop three levels of composite efficiency indicators for a WRS, which are configurable based on two types of water totals: total inflow and total consumption (outflow that effectively is not available for reuse). The indices characterize hydrology of an area by including in their formulations the flow dynamics at three integrated levels. Furthermore, the usefulness of water is incorporated into the indicators by defining two weights: one for quality, and the other for beneficial attributes of water use. Usefulness Criterion is the product of quality and beneficial weights, emphasizing the equal significance of the two dimensions. Both of these weights depend on the system itself and the priorities of the supervising organization, which also are shaped by the objectives and values of the given society. These concepts lead to the definition of Macro, Meso, and Micro‐Efficiencies, which form a set of integrated indicators that explicitly promotes stakeholder involvement in evaluation and design of WRSs. Macro, Meso, and Micro‐Efficiencies should be maximized for both water totals, which is an integrated prerequisite for sustainability and is less promoted by competing stakeholders. To demonstrate this new framework, it is applied to published data for urban and agricultural cases and some results are explained.     

Concentrations and bioaccessibilities of metals in exterior urban paints

Paint fragments have been collected from a variety of structures (e.g. walls, lamp posts, doors, railings) from the urban environment of Plymouth, UK, and concentrations of metals determined following acid digestion. Concentrations of most metals were highly variable and spanned several orders of magnitude among the samples (e.g. Pb = 4.5 to 36 900 μg g⁻¹; Cr = 1.9 to 775 μg g⁻¹; Zn = 39 to 23 500 μg g⁻¹). The bioaccessibilities of the metals were evaluated using a physiologically based extraction test that simulates the chemical conditions of the human stomach and intestine. The bioaccessibility of a given metal was highly variable among the samples and was greater in the stomach than the intestine in some cases (e.g. Cd, Pb) and greater in the intestine in others (e.g. Co, Cr). Based on total and bioaccessible concentrations in urban paints, Pb remains the metal of greatest concern from a human health perspective.     

Adsorption of trace metals to plastic resin pellets in the marine environment

Plastic production pellets collected from beaches of south west England contain variable concentrations of trace metals (Cr, Co, Ni, Cu, Zn, Cd and Pb) that, in some cases, exceed concentrations reported for local estuarine sediments. The rates and mechanisms by which metals associate with virgin and beached polyethylene pellets were studied by adding a cocktail of 5 μg L(-1) of trace metals to 10 g L(-1) pellet suspensions in filtered seawater. Kinetic profiles were modelled using a pseudo-first-order equation and yielded response times of less than about 100 h and equilibrium partition coefficients of up to about 225 ml g(-1) that were consistently higher for beached pellets than virgin pellets. Adsorption isotherms conformed to both the Langmuir and Freundlich equations and adsorption capacities were greater for beached pellets than for virgin pellets. Results suggest that plastics may represent an important vehicle for the transport of metals in the marine environment.     

Livelihood adaptations to climate variability: insights from farming households in Ghana

Climate variability poses a significant threat to many sectors of Sub-Saharan Africa’s economy. Agriculture is one of the most climate sensitive sectors because of its dependence on rain-fed cultivation. This paper identifies the main adaptation strategies used by farming households in the Sudan savannah and forest-savannah transitional agro-ecological zones of Ghana, in order to reduce the adverse impacts of climate variability on their livelihood activities. It combines questionnaire surveys, key informant interviews and a range of participatory methods. Results show that households employ a range of on- and off-farm adaptation strategies including changing the timing of planting, planting early maturing varieties, diversification of crops, support from family and friends, and changing their diets to manage climate variability. Results reveal that most households use adaptation strategies linked to livelihood diversification to adapt to the increased climate variability seen in recent decades. Most households now engage in multiple non-arable farming livelihood activities in an attempt to avoid destitution because of crop failure linked to climate variability (particularly drought). The findings suggest that policy makers need to formulate more targeted climate adaptation policies and programmes that are linked to enhancing livelihood diversification, as well as establishing communication routes for farming communities to better share their knowledge on successful local climate adaptation strategies.     

Spatio-temporal modelling of electric vehicle charging demand and impacts on peak household electrical load

This paper presents a composite methodology for obtaining spatial and temporal projections of charging demand and peak-shaving potential from plug-in electric vehicles (EVs), and the associated spatio-temporal impacts on peak household electrical load. The methodology comprises a suite of models of future EV uptake, travel by households, household electricity demand and recharge/discharge of EVs at their home locations. The analysis is disaggregated to hourly time-steps over a full year, and spatially to mesh blocks comprising around 250 houses per block. The modelling suite is applied to an analysis of peak household load impacts across the state of Victoria, Australia, under nine different combinations of EV uptake and charging/discharging behaviour. The projected increase in peak household electrical loads under expected penetration rates and charging demands is less than 10 % on most high-demand days, but can be up to 15 % on a handful of days and geographic locations. Peak-load impacts under off-peak charging are mostly less than 5 %. With judicious EV discharging strategies, there is potential to shave peak loads on the highest demand days by up to 5 %.     

Statistical modelling of district-level residential electricity use in NSW, Australia

Electricity network investment and asset management require accurate estimation of future demand in energy consumption within specified service areas. For this purpose, simple models are typically developed to predict future trends in electricity consumption using various methods and assumptions. This paper presents a statistical model to predict electricity consumption in the residential sector at the Census Collection District (CCD) level over the state of New South Wales, Australia, based on spatial building and household characteristics. Residential household demographic and building data from the Australian Bureau of Statistics (ABS) and actual electricity consumption data from electricity companies are merged for 74 % of the 12,000 CCDs in the state. Eighty percent of the merged dataset is randomly set aside to establish the model using regression analysis, and the remaining 20 % is used to independently test the accuracy of model prediction against actual consumption. In 90 % of the cases, the predicted consumption is shown to be within 5 kWh per dwelling per day from actual values, with an overall state accuracy of ?1.15 %. Given a future scenario with a shift in climate zone and a growth in population, the model is used to identify the geographical or service areas that are most likely to have increased electricity consumption. Such geographical representation can be of great benefit when assessing alternatives to the centralised generation of energy; having such a model gives a quantifiable method to selecting the ‘most’ appropriate system when a review or upgrade of the network infrastructure is required.     

Standard inocula preparations reduce the bacterial diversity and reliability of regulatory biodegradation tests

OECD ready biodegradability tests have been central to understanding the biodegradation of chemicals from a regulatory perspective for many decades. They are not fit for contemporary prioritisation of chemicals based on persistence, however, due to the low concentration of inocula used, short duration and high variability between tests. Two OECD standard inoculum pretreatment methods (settlement and filtration) were investigated to observe their effect on the probability of biodegradation and associated changes in bacterial community structure and diversity of inocula sourced from the activated sludge process of wastewater treatment plants. Both settlement and filtration were shown to dramatically and significantly reduce the probability and increase the variability of biodegradation of 4-nitrophenol compared to the use of unprocessed inocula. These differences were associated with a significant hundred-fold reduction in cell numbers and solids content and a significant shift in bacterial community structure that was sometimes accompanied by significant reductions in detectable operational taxonomic unit richness and evenness. The natural variation (between different environments) and variation due to differential selection of bacterial communities (by different pretreatment methods) is offered as an explanation for the historical high variability in standard OECD ready biodegradability tests.     

Bayesian importance parameter modeling of misaligned predictors: soil metal measures related to residential history and intellectual disability in children

In this paper, we propose a novel spatial importance parameter hierarchical logistic regression modeling approach that includes measurement error from misalignment. We apply this model to study the relationship between the estimated concentration of soil metals at the residence of mothers and the development of intellectual disability (ID) in their children. The data consist of monthly computerized claims data about the prenatal experience of pregnant women living in nine areas within South Carolina and insured by Medicaid during January 1, 1996 and December 31, 2001 and the outcome of ID in their children during early childhood. We excluded mother-child pairs if the mother moved to an unknown location during pregnancy. We identified an association of the ID outcome with arsenic (As) and mercury (Hg) concentration in soil during pregnancy, controlling for infant sex, maternal race, mother’s age, and gestational weeks at delivery. There is some indication that Hg has a slightly higher importance in the third and fourth months of pregnancy, while As has a more uniform effect over all the months with a suggestion of a slight increase in risk in later months.