Human Health Risk Assessment (HHRA) is a widely applied method to make decisions about the environmental status of sites affected by toxic substances. Its conclusions are affected by the variability and uncertainty of the input variables in the HHRA model. The aim of this work is to apply an algorithm based on 2D Monte Carlo simulations to integrate the variability and uncertainty of exposure factors, concentration, and bioaccessibility, reported by various information sources, to assess and compare their influence on the risk outcome. The method is applied to a specific case study of exposure of children to arsenic from accidental soil ingestion in a residential setting in the city of Madrid (Spain) by combining information from 12 studies. The consideration of the variability and uncertainty of the exposure parameters in the Baseline Risk Assessment (BRA, deterministic) resulted in a greater reduction in the numerical value of risk estimations than that produced by considering only the bioaccessibility factor. The results of the Probabilistic Risk Assessment (PRA) showed that the risk distribution was more sensitive to the variabilities of the accidental soil intake rate and the total arsenic concentration than to other variables such as bioaccessibility. In this case study, the uncertainty introduced by using the "default" reasonable maximum exposure factors in the HHRA model and the variability of the concentration term produce overestimates of risk that are at least in the range of those produced by omitting the bioaccessibility term. Thus, the inclusion of bioaccessibility is, alone, insufficient to improve the HHRA since the selection of the exposure factors can significantly affect the estimates of risk for the soil ingestion pathway. In other sites or for other contaminants, however, the role of the uncertainties associated with the bioaccesible fraction could be more pronounced. The method applied in this work may be useful in updating exposure factors to reduce uncertainties in HHRAs.
High school students start their first year at the university with very different levels of knowledge and skills. Chemistry and Technical Drawing are two appropriate examples to study this complex situation. Due to the flexible high school academic curricula and the lack of strict requirements to enter university degrees in the case of, for example, engineering degrees, it is possible for a student to access without studying Chemistry or Technical Drawing in the last years of high school. The challenge of teaching heterogeneous and large groups has been addressed using different methodologies. In particular, this work has compared two methodologies that can be named as the "classical" and "innovative" approaches. The first one tries to level the students before the standard lessons, applying a flip teaching technique. The second one face heterogeneity, not as problem, but as an opportunity: collaborative learning using working teams tries to level the students through interactions between them. The results of both methodologies have been measured using different external controls: tests, chronological development of activities, continuous assessment questionnaires or final tests. An important conclusion is that both methodologies have a clear impact in the motivation of the students, however this motivation does not well translate into final improvements of the students' marks in the subjects. Flip teaching videos must be done according to the learning objectives and students need to get used to watching videos to prepare the lessons because, in general, it is something new for them. Collaborative learning produces synergy that contributes to the learning process, but interactions between students and teachers must be encouraged. Finally, the authors suggest a critical reflection of the optionality of some subjects in the last years of high school and the possibility to access some degrees without having essential knowledge of some subjects.
The ubiquity of radon in the subsurface, its ease of analytical detection in the field and its preferential partitioning in organic phases (i.e. non-aqueous phase organic contaminants or NAPLs) make it ideal for delineating subsurface organic contamination processes [1,2].This contribution presents the results of 4 field campaigns at a site affected by a dense NAPL (DNAPL). A total of 505 Rn determinations in soil air were obtained in successive blind sampling campaigns (i.e., no prior information was disclosed on the location of hot-spots or the extent of the contamination) and were subsequently used for surface mapping of Rn activity in soil air.The results of the 222 Rn-deficit technique were compared with direct information from boreholes and monitoring wells at the site. 222 Rn measurements correctly predicted the location of contaminated areas already identified by conventional characterization methods but also unveiled a large, previously overlooked DNAPL accumulation. These results indicate the ability of the 222 Rn-deficit technique to detect not only the presence of organic contaminants in the vadose zone (as described in previous publications [3,4], but also of dense free phases in the saturated zone.
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