The influence of geometry and draught shields on the performance of passive samplers

Passive samplers provide an excellent opportunity to perform indicative measurements or establish a dense network of measuring sites. A drawback compared with conventional active measuring methods is the larger spread of results. This variation can, to a large extent, be attributed to the influence of temperature, sampler geometry and wind on sampling results. A proper design of sampler geometry and optimum choice of draught shield can reduce the influence of wind velocity on a badge type sampler to less than 10%. Wire mesh screens prove to be inadequate in damping turbulence. Filters give good results. Attention should be paid to the size and isolation value of the walls of the sampler to prevent thermal updrafts occurring within the sampler. Tube type samplers are less influenced by wind, provided that turbulence is prevented from influencing diffusion within the sampler.     

Collaborative study to improve the quality control of rare earth element determinations in environmental matrices

In order to control the quality of rare earth determinations in environmental matrices, the Standards, Measurements and Testing Programme (formerly Community Bureau of Reference, BCR) of the European Commission has started a project, the final aim of which is to certify four types of matrices (tuna muscle, mussel tissue, aquatic plant and estuarine sediment) for their contents of a range of rare earth elements (Sc, Y and the lanthanides: La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb and Lu). The elements U and Th were added to the study. The first part of this project consisted of an interlaboratory study which aimed to test the feasibility of preparation of environmental reference materials and to detect and remove most of the pitfalls observed in rare earth determinations. This paper presents the preparation of the four matrices for the intercomparison study and for the candidate reference material. The main results are presented of the interlaboratory study that was carried out prior to the certification campaign. This collaborative trial is the first attempt ever carried out at this scale to evaluate the state-of-the-art of rare earth determinations in the environment. Its impact on the improvement of chemical measurements will have positive effects on the comparability of data necessary for environmental monitoring.     

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.     

Determining Ecoregions for Environmental and GMO Monitoring Networks

A representative environmental monitoring network at the regional scale cannot use raster-based or random sampling designs, but requires a stratified sampling procedure integrating different information layers, and it has to occur in ecologically differing homogeneous regions (ecoregions). These we have determined using a set of spatial strata with ecological variables which we analysed with classification and regression trees (CART). We present a framework for environmental monitoring, that covers different scales, and we transfer the framework to a potential GMO (genetically modified organisms) monitoring network. We use ecoregion and other environmental strata together with existing environmental monitoring networks to determine GMO monitoring sites more precisely.     

A Metamodeling Approach for Integrated Assessment of Air Quality Policies

A method is proposed to build integrated models (also called Metamodels) aimed at quantifying the economic efficiency of air quality policies. This Metamodeling approach is based on the coupling of two complementary models, that operate at different scales in space and time, and which represent the economic and the physical and chemical processes, respectively. The joint consideration of the physico-chemical and techno-economic structure of the pollution control problems permits a comprehensive evaluation of air pollution abatement strategies. The motivating pollution control problems include urban-regional air quality management through efficient energy and traffic control policies. A pilot study, exploiting data collected in the Geneva canton (Switzerland), is used to demonstrate the potential of the approach.     

Incremental cost-effectiveness of incorporating oestriol evaluation in down syndrome screening programmes

As screening for Down syndrome becomes increasingly sophisticated, it is important to evaluate the newer technologies in terms of their cost-effectiveness. One recent addition to Down syndrome screening programmes is maternal serum unconjugated oestriol (uE₃), especially when used in conjunction with maternal serum α-fetoprotein and human chorionic gonadotropin. Using assumptions used in a California proposal to justify an expanded screening programme for Down syndrome, we calculated both the average and the incremental cost-effectiveness of adding uE₃. Using the base case assumptions, including an $8 fee for the uE₃, the incremental cost-effectiveness of adding uE₃ to the proposed California programme is $119 100 per case detected, a value that compares favourably with other Down syndrome screening programmes. The sensitivity analysis supports this conclusion over a wide range of assumptions. However, because of the uncertainty with some key data, it is still too early to fully support the inclusion of uE₃ in Down syndrome screening programmes.