Seasonal and Regional Patterns in Performance for a Baltic Sea Drainage Basin Hydrologic Model

This study evaluates the ability of the Catchment SIMulation (CSIM) hydrologic model to describe seasonal and regional variations in river discharge over the entire Baltic Sea drainage basin (BSDB) based on 31 years of monthly simulation from 1970 through 2000. To date, the model has been successfully applied to simulate annual fluxes of water from the catchments draining into the Baltic Sea. Here, we consider spatiotemporal bias in the distribution of monthly modeling errors across the BSDB since it could potentially reduce the fidelity of predictions and negatively affect the design and implementation of land‐management strategies. Within the period considered, the CSIM model accurately reproduced the annual flows across the BSDB; however, it tended to underpredict the proportion of discharge during high‐flow periods (i.e., spring months) and overpredict during the summer low flow periods. While the general overpredictions during summer periods are spread across all the subbasins of the BSDB, the underprediction during spring periods is seen largely in the northern regions. By implementing a genetic algorithm calibration procedure and/or seasonal parameterization of subsurface water flows for a subset of the catchments modeled, we demonstrate that it is possible to improve the model performance albeit at the cost of increased parameterization and potential loss of parsimony.     

Uncertainties in integrated assessment modelling of abatement strategies: illustrations with the ASAM model

Following the signing of the Second Sulphur Protocol in 1994 under the 1979 Convention on Long-range Transboundary Air Pollution, preparations are now underway for a new multi-pollutant multi-effects protocol, under the auspices of the United Nations Economic Commission for Europe (UN ECE). A number of scientific models have been used to provide policy makers involved in these preparations with sound scientific information. These include the Abatement Strategies Assessment Model (ASAM). ASAM has recently been extended to cover abatement strategies for NH₃ and NOx as well as SO₂, in order to address the amelioration of acidification and eutrophication in the ECE region. It is important to be able to demonstrate that the scientific information provided to policy makers is robust to uncertainties, and hence there is a need for a thorough sensitivity analysis. In this study ASAM is used to demonstrate a large degree of robustness of derived abatement strategies to uncertainties in critical loads, meteorological data and cost information. This is based on a comparison of strategies at the same overall abatement cost. Systematic changes in data are shown to influence model results more profoundly than random changes.     

Current status and challenges of remediating petroleum‐derived PAHs in soils: Nigeria as a case study for developing countries

Polycyclic aromatic hydrocarbons (PAHs) are among the world's most significant environmental organic contaminants because of their carcinogenic properties. PAHs are widely distributed globally as a result of releases from numerous natural and anthropogenic activities. Consequently, several PAH monitoring studies have been conducted and remediation approaches explored. This article aims to provide the current status of PAH distribution in Nigeria's oil and gas industrial region in relation to the technologies adopted for PAH remediation. Ideally, the findings will provide insight into the challenges in managing organic contaminants derived from petroleum exploration activities in developing countries with Nigeria as a case study.     

Towards resolving the phosphorus chaos created by food systems

Ambio - The chaotic distribution and dispersal of phosphorus (P) used in food systems (defined here as disorderly disruptions to the P cycle) is harming our environment beyond acceptable limits. An...     

Reduced combustion mechanism for C1–C4 hydrocarbons and its application in computational fluid dynamics flare modeling

Emissions from flares constitute unburned hydrocarbons, carbon monoxide (CO), soot, and other partially burned and altered hydrocarbons along with carbon dioxide (CO₂) and water. Soot or visible smoke is of particular concern for flare operators/regulatory agencies. The goal of the study is to develop a computational fluid dynamics (CFD) model capable of predicting flare combustion efficiency (CE) and soot emission. Since detailed combustion mechanisms are too complicated for (CFD) application, a 50-species reduced mechanism, LU 3.0.1, was developed. LU 3.0.1 is capable of handling C₄ hydrocarbons and soot precursor species (C₂H₂, C₂H₄, C₆H₆). The new reduced mechanism LU 3.0.1 was first validated against experimental performance indicators: laminar flame speed, adiabatic flame temperature, and ignition delay. Further, CFD simulations using LU 3.0.1 were run to predict soot emission and CE of air-assisted flare tests conducted in 2010 in Tulsa, Oklahoma, using ANSYS Fluent software. Results of non-premixed probability density function (PDF) model and eddy dissipation concept (EDC) model are discussed. It is also noteworthy that when used in conjunction with the EDC turbulence-chemistry model, LU 3.0.1 can reasonably predict volatile organic compound (VOC) emissions as well.

Implications: A reduced combustion mechanism containing 50 C₁–C₄ species and soot precursors has been developed and validated against experimental data. The combustion mechanism is then employed in the computational fluid dynamics (CFD) of modeling of soot emission and combustion efficiency (CE) of controlled flares for which experimental soot and CE data are available. The validated CFD modeling tools are useful for oil, gas, and chemical industries to comply with U.S. Environmental Protection Agency’s (EPA) mandate to achieve smokeless flaring with a high CE.     

Removal of a red dye using noncommercial peroxidase extracted from rice bran

The present study investigates the application of a noncommercial peroxidase enzyme, which was extracted from rice bran, to decolorize wastewater that was simulating effluent from a textile manufacturer using a red dye in its coloration process.     

Understanding adaptive capacity and capacity to innovate in social–ecological systems: Applying a gender lens

Development policy increasingly focuses on building capacities to respond to change (adaptation), and to drive change (innovation). Few studies, however, focus specifically on the social and gender differentiation of capacities to adapt and innovate. We address this gap using a qualitative study in three communities in Solomon Islands; a developing country, where rural livelihoods and well-being are tightly tied to agriculture and fisheries. We find the five dimensions of capacity to adapt and to innovate (i.e. assets, flexibility, learning, social organisation, agency) to be mutually dependant. For example, limits to education, physical mobility and agency meant that women and youth, particularly, felt it was difficult to establish relations with external agencies to access technical support or new information important for innovating or adapting. Willingness to bear risk and to challenge social norms hindered both women’s and men’s capacity to innovate, albeit to differing degrees. Our findings are of value to those aspiring for equitable improvements to well-being within dynamic and diverse social–ecological systems.     

Effect of manganese on the concentration of amino acids in different regions of the rat brain

Abstract

The present study was designed to determine if chronic exposure of weanlings and adult rats to Mn produces significant alterations in amino acid concentrations in different regions of the rat brain. Weanling (30 day old) and adult (90 day old) male rats were exposed to 10 and 20 mg Mn/kg body weight per day, by gavage, for 30 days. Forty‐ eight hours after the last dose, animals were sacrificed by decapitation and brains were dissected into different regions to determine the concentration of amino acids by HPLC/EC. A dose dependent decrease in body weight gain was found in the adult, but not in the weanling rats. Significant increases occurred in concentrations of aspartate, glutamate, glutamine, taurine and y‐aminobutyric acid (GABA) in the cerebellum of the adult rats dosed with 20 mg/kg per day, Mn. A significant decrease in the concentration of glutamine was observed in caudate nucleus and hippocampus of weanling rats dosed with 10 mg/kg, Mn. These data suggest that chronic Mn exposure can produce a decrease in body weight gain in adult rats and alterations in amino acids in different regions of weanling and adult rat brains.