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Abstract In this study, crude cellulose derived from cornstalk, after bleaching, was used as raw material for the synthesis of sodium carboxymethyl cellulose (CMC) by reacting with the cellulose with NaOH and chloroacetic acid at 75 °C for 1.5 h. Effects of alkali dosage, concentration of chloroacetic acid on the physical and chemical properties of the CMC products were investigated. It was revealed that the reactants alkali reagent/chloroacetic acid/cellulose at the molar ratio of 4.6:2.8:1and 4:2.5:1, or at the molar ratio of NaOH/ClCH 2 COOH ≈1.6–1.64, resulted in CMC products of relatively high water solubility. The viscosity-average molecular weight M v of these two CMC products obtained at molar ratios of 4.0:2.5:1 and 4.6:2.8:1 is in the range of 1.94 × 10 4 –2.48 × 10 4 g mol −1 , and the average DS of the two products are 0.57 and 0.85, respectively. As the solute concentration is above 2 wt%, the viscosity of the CMC-water solution exhibits nonlinear (exponential) increasing with increasing the solute concentration (typical of non-Newton fluids).

Abstract Economically harvesting energy from a microbial fuel cell (MFC), increasing its electrical power production, and developing its role as a practical energy supply, needs a low-cost and high-performance design of the MFC compartments. According to this strategy, a novel monolithic membrane electrode assembly (MEA) was fabricated and evaluated as an air–cathode in a single-chamber MFC (SCMFC). The MEA was made of bacterial cellulose (BC), conductive multi-walled carbon nanotubes (CNT), and nano-zycosil (NZ). BC, as a nano-celluloses with oxygen barrier property, can maintain anaerobic conditions for the anode compartment. Binder-less CNT coating on BC avoids costly binders such as poly-tetra fluoro ethylene (PTFE) and Nafion and decreases the MEA charge transfer resistance. NZ, as a very cheap modifier, not only prevents the anolyte leakage but also provides more MEA’s active sites for the oxygen reduction reaction (ORR). The electrochemical performance of the MEA was compared to a PTFE- based gas diffusion electrode (GDE) in the SCMFC. The MEA cell provided a pulse power density of 1790 mW/m2, roughly twice as high as the pulse power density of GDE (920 mW/m2). SCMFC’s internal resistance decreased from 1.84 KΩ (with GDE) to 0.8 KΩ (with MEA). Also, the cell’s columbic efficiency increased from 4.2% (with GDE) to11.7% (with MEA). Additionally, the capacitance of the MEA (65 mF) was much higher than the value for GDE (0.73 mF). Thus, the MEA compared to the GDE showed higher performance in the SCMFC for electricity generation and wastewater treatment at a lower cost.

Urea is the most common nitrogen (N) fertilizer in agriculture, due to its cheaper price and high N content. Although the reciprocal influence between NO3- and NH4+ nutrition are well known, urea (U) interactions with these N-inorganic forms are poorly studied. Here, the responses of two tomato genotypes to ammonium nitrate (AN), U alone or in combination were investigated. Significant differences in root and shoot biomass between genotypes were observed. Under AN+U supply, Linosa showed higher biomass compared to UC82, exhibiting also higher values for many root architectural traits. Linosa showed higher Nitrogen Uptake (NUpE) and Utilization Efficiency (NUtE) compared to UC82, under AN+U nutrition. Interestingly, Linosa exhibited also a significantly higher DUR3 transcript abundance. These results underline the beneficial effect of AN+U nutrition, highlighting new molecular and physiological strategies for selecting crops that can be used for more sustainable agriculture. The data suggest that translocation and utilization (NUtE) might be a more important component of NUE than uptake (NUpE) in tomato. Genetic variation could be a source for useful NUE traits in tomato; further experiments are needed to dissect the NUtE components that confer a higher ability to utilize N in Linosa.

Abstract Italy reformed its water and sanitation services in 1994. The strategy aimed at transforming public entities, financed by the central budget, into self-sufficient professional companies regulated at arms' length. Nearly 20 years after, the reform has failed to deliver (despite some partial success). Italians have been divided in two parties: those blaming public sector inefficiencies and calling for competitive tendering; and those refusing to privatize water and willing to go back to the fiscal budget. In this article, we suggest that both parties are wrong. Underperformance is not related to the ownership structure of water companies, but rather to poor regulatory design and lack of understanding of the regulatory requirements that are implicit in the management model chosen, namely the concession contract.

Abstract Bitumen recovery by steam-solvent coinjection involves the coupled thermal/compositional mechanisms for reduction of bitumen viscosity. Reliable design of such processes requires reservoir flow simulation based on a proper phase-behavior model so that the oleic-phase viscosity near the steam-chamber edge can be modeled reliably. However, the effect of bitumen characterization (e.g., the number of pseudo components used) on steam-solvent coinjection simulation has not been studied in detail, and can be realized only after running multiple reservoir simulations, which is time consuming. There are two main objectives in this paper. One is to develop a reliable method for bitumen characterization by improving the fluid characterization method that was recently developed based on perturbation from n-alkanes (PnA). The other is to develop a novel analytical method for assessing the sensitivity of a particular coinjection simulation to bitumen characterization without having to perform reservoir simulations. A simulation case study is given to validate this analytical method. A proper number of pseudo components for bitumen characterization cannot be determined without considering the effect of phase behavior on the oleic-phase viscosity at chamber-edge conditions in steam-solvent coinjection simulation. Results show that the analytical method developed in this research can detect the sensitivity of recovery simulation to bitumen characterization without performing multiple flow simulations using different sets of fluid models. The PnA-based method developed for bitumen characterization gives reliable predictions of phase behavior for bitumen/solvent mixtures with a small amount of experimental data.

Abstract The development of predictive mathematical models for water management in polymer electrolyte membrane fuel cells requires detailed understanding of water distribution and water transport across the Nafion layer. The anisotropic microstructure of Nafion suggests the measurement of water content and mass transport should be along the fuel cell functional direction, i.e. across the membrane. Non-invasive, high resolution, microscopy measurements of this type are very challenging. We report here the calibration of a minimal mathematical model for diffusive water transport in Nafion against data from high-resolution water content maps determined with a new magnetic resonance imaging methodology developed for this purpose. A mock fuel cell was designed to permit well-controlled wetting and drying boundary conditions. With no chemical potential driving force involved, we assume the water transport behavior will be dominated by diffusion. Moreover we show that, in this context, our model is mathematically equivalent to the traditional permeation models based upon saturation dependent pressure gradients via a capillary pressure ansatz. The non-linear equilibrium water distribution across the Nafion membrane measured in this work suggests a bi-modal diffusivity. The model constructed associates distinct transport behaviors to water contents above and below a critical threshold, consistent with a rearrangement of a micro-structural pore network. The experimental observation and the model prediction agree with the primary features of Weber's model of Nafion, which predicts distinct modes of transport for hydration fronts traversing the through-plane direction of the membrane.

An ecosystem in a cold climate river basin is vulnerable to the effects of climate change affecting permafrost thaw and glacier retreat. We currently lack sufficient data and information if and how hydrological processes such as glacier retreat, snowmelt and freezing-thawing affect sediment and nutrient runoff and transport, as well as N2O emissions in cold climate river basins. As such, we have implemented well-established, semi-empirical equations of nitrification and denitrification within the Soil and Water Assessment Tool (SWAT), which correlate the emissions with water, sediment and nutrients. We have tested this implementation to simulate emission dynamics at three sites on the Canadian prairies. We then regionalized the optimized parameters to a SWAT model of the Athabasca River Basin (ARB), Canada, calibrated and validated for streamflow, sediment and water quality. In the base period (1990-2005), agricultural areas (2662 gN/ha/yr) constituted emission hot-spots. The spring season in agricultural areas and summer season in forest areas, constituted emission hot-moments. We found that warmer conditions (+13% to +106%) would have a greater influence on emissions than wetter conditions (-19% to +13%), and that the combined effect of wetter and warmer conditions would be more offsetting than synergetic. Our results imply that the spatiotemporal variability of N2O emissions will depend strongly on soil water changes caused by permafrost thaw. Early snow freshet leads to spatial variability of soil erosion and nutrient runoff, as well as increases of emissions in winter and decreases in spring. Our simulations suggest crop residue management may reduce emissions by 34%, but with the mixed results reported in the literature and the soil and hydrology problems associated with stover removal more research is necessary. This modelling tool can be used to refine bottom-up emission estimations at river basin scale, test plausible management scenarios, and assess climate change impacts including climate feedback.

AbstractMicroalgal biotechnology could generate substantial amounts of biofuels with minimal environmental impact if the economics can be improved by increasing the rate of biomass production. Chlorella kessleri was grown in a small‐scale raceway pond and in flask cultures with the entire volume, 1% (v/v) at any instant, periodically exposed to static magnetic fields to demonstrate increased biomass production and investigate physiological changes, respectively. The growth rate in flasks was maximal at a field strength of 10 mT, increasing from 0.39 ± 0.06 per day for the control to 0.88 ± 0.06 per day. In the raceway pond the 10 mT field increased the growth rate from 0.24 ± 0.03 to 0.45 ± 0.05 per day, final biomass from 0.88 ± 0.11 to 1.56 ± 0.18 g/L per day, and maximum biomass production from 0.11 ± 0.02 to 0.38 ± 0.04 g/L per day. Increased pigment, protein, Ca, and Zn content made the biomass produced with magnetic stimulation nutritionally superior. An increase in oxidative stress was measured indirectly as a decrease in antioxidant capacity from 26 ± 2 to 17 ± 1 µmol antioxidant/g biomass. Net photosynthetic capacity (NPC) and respiratory rate were increased by factors of 2.1 and 3.1, respectively. Loss of NPC enhancement after the removal of magnetic field fit a first‐order model well (R2 = 0.99) with a half‐life of 3.3 days. Transmission electron microscopy showed enlarged chloroplasts and decreased thylakoid order with 10 mT treatment. By increasing daily biomass production about fourfold, 10 mT magnetic field exposure could make algal oil cost competitive with other biodiesel feedstocks. Bioelectromagnetics 33:298–308, 2012. © 2011 Wiley Periodicals, Inc.

AbstractAutotrophs play an essential role in the cycling of carbon and nutrients, yet disease‐ecosystem relationships are often overlooked in these dynamics. Importantly, the availability of elemental nutrients like nitrogen and phosphorus impacts infectious disease in autotrophs, and disease can induce reciprocal effects on ecosystem nutrient dynamics. Relationships linking infectious disease with ecosystem nutrient dynamics are bidirectional, though the interdependence of these processes has received little attention. We introduce disease‐mediated nutrient dynamics (DND) as a framework to describe the multiple, concurrent pathways linking elemental cycles with infectious disease. We illustrate the impact of disease–ecosystem feedback loops on both disease and ecosystem nutrient dynamics using a simple mathematical model, combining approaches from classical ecological (logistic and Droop growth) and epidemiological (susceptible and infected compartments) theory. Our model incorporates the effects of nutrient availability on the growth rates of susceptible and infected autotroph hosts and tracks the return of nutrients to the environment following host death. While focused on autotroph hosts here, the DND framework is generalizable to higher trophic levels. Our results illustrate the surprisingly complex dynamics of host populations, infection patterns, and ecosystem nutrient cycling that can arise from even a relatively simple feedback between disease and nutrients. Feedback loops in disease‐mediated nutrient dynamics arise via effects of infection and nutrient supply on host stoichiometry and population size. Our model illustrates how host growth rate, defense, and tissue chemistry can impact the dynamics of disease–ecosystem relationships. We use the model to motivate a review of empirical examples from autotroph–pathogen systems in aquatic and terrestrial environments, demonstrating the key role of nutrient–disease and disease–nutrient relationships in real systems. By assessing existing evidence and uncovering data gaps and apparent mismatches between model predictions and the dynamics of empirical systems, we highlight priorities for future research intended to narrow the persistent disciplinary gap between disease and ecosystem ecology. Future empirical and theoretical work explicitly examining the dynamic linkages between disease and ecosystem ecology will inform fundamental understanding for each discipline and will better position the field of ecology to predict the dynamics of disease and elemental cycles in the context of global change.