A smart layer for remote laboratories

Commonly, when a weblab is developed to support remote experiments in sciences and engineering courses, a particular hardware/software architecture is implemented. However, the existence of several technological solutions to implement those architectures difficults the emergence of a standard, both at hardware and software levels. While particular solutions are adopted assuming that only qualified people may implement a weblab, the control of the physical space and the power consumption are often forgotten. Since controlling these two previous aspects may increase the quality of the weblab hosting the remote experiments, this paper proposes the useof a new layer implemented by a domotic system bus with several devices (e.g. lights, power sockets, temperature sensors, and others) able to be controlled through the Internet. We also provide a brief proof-of-concept in the form of a weblab equipped with a simple domotic system usually implemented in smart houses. The added value to the remote experiment hosted at the weblab is also identified in terms of power savings and environment conditions.

Predictivity Strength of the Spatial Variability of Phenanthrene Sorption Across Two Sandy Loam Fields

Sorption is commonly agreed to be the major process underlying the transport and fate of polycyclic aromatic hydrocarbons (PAHs) in soils. However, there is still a scarcity of studies focusing on spatial variability at the field scale in particular. In order to investigate the variation in the field of phenanthrene sorption, bulk topsoil samples were taken in a 15 × 15-m grid from the plough layer in two sandy loam fields with different texture and organic carbon (OC) contents (140 samples in total). Batch experiments were performed using the adsorption method. Values for the partition coefficient K d (L kg−1) and the organic carbon partition coefficient K OC (L kg−1) agreed with the most frequently used models for PAH partitioning, as OC revealed a higher affinity for sorption. More complex models using different OC compartments, such as non-complexed organic carbon (NCOC) and complexed organic carbon (COC) separately, performed better than single K OC models, particularly for a subset including samples with Dexter n < 10 and OC <0.04 kg kg−1. The selected threshold revealed that K OC-based models proved to be applicable for more organic fields, while two-component models proved to be more accurate for the prediction of K d and retardation factor (R) for less organic soils. Moreover, OC did not fully reflect the changes in phenanthrene retardation in the field with lower OC content (Faardrup). Bulk density and available water content influenced the phenanthrene transport mechanism phenomenon.