Application of a checklist for quality assistance in environmental modelling to an energy model

Large, complex energy models present considerable challenges to develop and test. Uncertainty assessments of such models provide only partial guidance on the quality of the results. We have developed a model quality assistance checklist to aid in this purpose. The model checklist provides diagnostic output in the form of a set of pitfalls for the model application. The checklist is applied here to an energy model for the problem of assessing energy use and greenhouse gas emissions. Use of the checklist suggests that results on this issue are contingent on a number of assumptions that are highly value-laden. When these assumptions are held fixed, the model is deemed capable of producing moderately robust results of relevance to climate policy over the longer term. Checklist responses also indicate that a number of details critical to policy choices or outcomes on this issue are not captured in the model, and model results should therefore be supplemented with alternative analyses.     

A study of the distribution of lead, cadmium and copper between water and kaolin, bentonite and a river sediment

Experiments were carried out to monitor the equilibrium distribution of lead, cadmium and copper between an aqueous phase modelling natural water and a solid phase modelling natural sediment, under varying conditions. The aqueous phase was analysed using ETAAS and differential pulse anodic stripping voltammetry (DPASV), whereas XRD and FTIR were used to study the solid phase. Sorption isotherms at constant pH were measured. Conditional distribution constants were calculated as functions of the pH, the time of equilibration and the amount of solid material. The results obtained stress the need for standardization of the approaches to the study of water-sediment interactions in order to be able to evaluate and compare the extensive data from field measurements and to predict these interactions.     

Assessment of Metal Contamination in Doñana National Park (Spain) using Crayfish (Procamburus Clarkii)

Water quality assessment in the Aznalcollar area was attempted using multivariate methods based on heavy metal concentrations in red swamp crayfish (Procamburus clarkii). Trace levels of four heavy metals, copper (Cu), zinc (Zn), cadmium (Cd) and lead (Pb), were detected in crayfish from eleven different stations. Principal component analysis (PCA) highlighted a gradient of contamination between the sampling stations. Cluster analysis (CA) distinguished three groups of stations. Discriminant analysis also differentiated three groups. The group centroids of the first discriminant function were used to devise an index that varies according to the source of the crayfish. These standardized values are proposed for use as a water quality index. The ability of this index to successfully predict environmental quality was proved with random samples.