Compression of polymer brushes: quantitative comparison of self-consistent field theory with experiment

The self-consistent field theory (SCFT) prediction for the compression force between two semi-dilute polymer brushes is compared to the benchmark experiments of Taunton et al. [Nature, 1988, 332, 712]. The comparison is done with previously established parameters, and without any fitting parameters whatsoever. The SCFT provides a significant quantitative improvement over the classical strong-stretching theory (SST), yielding excellent quantitative agreement with the experiment. Contrary to earlier suggestions, chain fluctuations cannot be ignored for normal experimental conditions. Although the analytical expressions of SST provide invaluable aids to understanding the qualitative behavior of polymeric brushes, the numerical SCFT is necessary in order to provide quantitatively accurate predictions.

The influence of carbon surface oxygen groups on Dubinin–Astakhov equation parameters calculated from CO2 adsorption isotherm

We present the results of a systematic study of the influence of carbon surface oxidation on Dubinin–Astakhov isotherm parameters obtained from the fitting of CO2 adsorption data. Using GCMC simulations of adsorption on realistic VPC models differing in porosity and containing the most frequently occurring carbon surface functionalities (carboxyls, hydroxyls and carbonyls) and their mixtures, it is concluded that the maximum adsorption calculated from the DA model is not strongly affected by the presence of oxygen groups. Unfortunately, the same cannot be said of the remaining two parameters of this model i.e. the heterogeneity parameter (n) and the characteristic energy of adsorption (E0). Since from the latter the pore diameters of carbons are usually calculated, by inverse-type relationships, it is concluded that they are questionable for carbons containing surface oxides, especially carboxyls.

Single versus multiple occupancy - Effects on toxicity parameters measured on Eisenia fetida in lead nitrate-treated soil

The mortality (7 and 14 d), weight change (7 and 14 d), and metal uptake of Eisenia fetida (Savigny, 1826) kept in Pb(NO3)(2)-treated Kettering loam soil in single- and multiple-occupancy (10 earthworms) test containers were determined. The number of earthworms to dry mass (g) ratio of soil was 1:50 in both sets of test containers. Lead concentrations were in the nominal range of 0 to 10,000 mg Pb/kg soil (mg/kg hereafter). Levels of mortality at a given concentration were statistically identical between the single- and multiple-occupancy tests, except at 1,800 mg/kg, at which significantly (p less than or equal to 0.05) more mortality occurred in the multiple-occupancy tests. Death of individual earthworms in the multiple-occupancy tests did not trigger death of the other earthworms in that soil. The LC50 values (concentration statistically likely to kill 50% of the population) were identical between the multiple- and single-occupancy soils: 2,662 mg/kg (2,598-2,984, 7 d) and 2,589 mg/kg (2,251-3,013, 14 d) for the multiple-occupancy soils and 2,827 mg/kg (2,443-3,168, both 7 and 14 d) for the single-occupancy soils (values in brackets represent the 95% confidence intervals). Data were insufficient to calculate the concentration statistically likely to reduce individual earthworm mass by 50% (EC50), but after 14 d, the decrease in earthworm weight in the 1,800 and 3,000 mg/kg tests was significantly greater in the multiple- than in the single-occupancy soils. At 1,000, 1,800, and 3,000 mg/kg tests, earthworm Pb tissue concentration was significantly (p less than or equal to 0.05) greater in earthworms from the multiple-occupancy soils. The presence of earthworms increased the NH3 content of the soil; earthworm mortality increased NH3 concentrations further but not to toxic levels.

Identifying the critical parameters of a cyanobacterial growth and movement model by using generalised sensitivity analysis

Bloom-forming and toxin-producing cyanobacteria remain a persistent nuisance across the world. Modelling of cyanobacteria in freshwaters is an important tool for understanding their population dynamics and predicting the location and timing of the bloom events in lakes and rivers. A new deterministic-mathematical model was developed, which simulates the growth and movement of cyanobacterial blooms in river systems. The model focuses on the mathematical description of the bloom formation, vertical migration and lateral transport of colonies within river environments by taking into account the major factors that affect the cyanobacterial bloom formation in rivers including, light, nutrients and temperature. A technique called generalised sensitivity analysis was applied to the model to identify the critical parameter uncertainties in the model and investigates the interaction between the chosen parameters of the model. The result of the analysis suggested that 8 out of 12 parameters were significant in obtaining the observed cyanobacterial behaviour in a simulation. It was found that there was a high degree of correlation between the half-saturation rate constants used in the model.

Effects of metals on life cycle parameters of the earthworm Eisenia fetida exposed to field-contaminated, metal-polluted soils

Two control and eight field-contaminated, metal-polluted soils were inoculated with Eisenia fetida (Savigny, 1826). Three, 7, 14, 21, 28 and 42 days after inoculation, earthworm survival, body weight, cocoon production and hatching rate were measured. Seventeen metals were analysed in E.fetida tissue, bulk soil and soil solution. Soil organic carbon content, texture, pH and cation exchange capacity were also measured. Cocoon production and hatching rate were more sensitive to adverse conditions than survival or weight change. Soil properties other than metal concentration impacted toxicity. The most toxic soils were organic-poor (1-10 g C kg(-1)), sandy soils (c. 74% sand), with intermediate metal concentrations (e.g. 7150-13, 100 mg Ph kg(-1), 2970-53,400 mg Zn kg(-1)). Significant relationships between soil properties and the life cycle parameters were determined. The best coefficients of correlation were generally found for texture, pH, Ag, Cd, Mg, Pb, Tl, and Zn both singularly and in multivariate regressions. Studies that use metal-amended artificial soils are not useful to predict toxicity of field multi-contaminated soils. (c) 2007 Elsevier Ltd. All rights reserved.

An application of the GLUE methodology for estimating the parameters of the INCA-N model

The conceptual and parameter uncertainty of the semi-distributed INCA-N (Integrated Nutrients in Catchments-Nitrogen) model was studied using the GLUE (Generalized Likelihood Uncertainty Estimation) methodology combined with quantitative experimental knowledge, the concept known as 'soft data'. Cumulative inorganic N leaching, annual plant N uptake and annual mineralization proved to be useful soft data to constrain the parameter space. The INCA-N model was able to simulate the seasonal and inter-annual variations in the stream-water nitrate concentrations, although the lowest concentrations during the growing season were not reproduced. This suggested that there were some retention processes or losses either in peatland/wetland areas or in the river which were not included in the INCA-N model. The results of the study suggested that soft data was a way to reduce parameter equifinality, and that the calibration and testing of distributed hydrological and nutrient leaching models should be based both on runoff and/or nutrient concentration data and the qualitative knowledge of experimentalist. (c) 2006 Elsevier B.V. All rights reserved.

Calibration and sensitivity analysis of a river water quality model under unsteady flow conditions

Water quality models generally require a relatively large number of parameters to define their functional relationships, and since prior information on parameter values is limited, these are commonly defined by fitting the model to observed data. In this paper, the identifiability of water quality parameters and the associated uncertainty in model simulations are investigated. A modification to the water quality model `Quality Simulation Along River Systems' is presented in which an improved flow component is used within the existing water quality model framework. The performance of the model is evaluated in an application to the Bedford Ouse river, UK, using a Monte-Carlo analysis toolbox. The essential framework of the model proved to be sound, and calibration and validation performance was generally good. However some supposedly important water quality parameters associated with algal activity were found to be completely insensitive, and hence non-identifiable, within the model structure, while others (nitrification and sedimentation) had optimum values at or close to zero, indicating that those processes were not detectable from the data set examined. (C) 2003 Elsevier Science B.V. All rights reserved.

Robust dynamics of Amazon dieback to climate change with perturbed ecosystem model parameters

Climate change science is increasingly concerned with methods for managing and integrating sources of uncertainty from emission storylines, climate model projections, and ecosystem model parameterizations. In tropical ecosystems, regional climate projections and modeled ecosystem responses vary greatly, leading to a significant source of uncertainty in global biogeochemical accounting and possible future climate feedbacks. Here, we combine an ensemble of IPCC-AR4 climate change projections for the Amazon Basin (eight general circulation models) with alternative ecosystem parameter sets for the dynamic global vegetation model, LPJmL. We evaluate LPJmL simulations of carbon stocks and fluxes against flux tower and aboveground biomass datasets for individual sites and the entire basin. Variability in LPJmL model sensitivity to future climate change is primarily related to light and water limitations through biochemical and water-balance-related parameters. Temperature-dependent parameters related to plant respiration and photosynthesis appear to be less important than vegetation dynamics (and their parameters) for determining the magnitude of ecosystem response to climate change. Variance partitioning approaches reveal that relationships between uncertainty from ecosystem dynamics and climate projections are dependent on geographic location and the targeted ecosystem process. Parameter uncertainty from the LPJmL model does not affect the trajectory of ecosystem response for a given climate change scenario and the primary source of uncertainty for Amazon 'dieback' results from the uncertainty among climate projections. Our approach for describing uncertainty is applicable for informing and prioritizing policy options related to mitigation and adaptation where long-term investments are required.