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Geochemical characterisation of hypersaline waters is difficult as high concentrations of salts hinder the analysis of constituents at low concentrations, such as trace metals, and the collection of samples for trace metal analysis in natural waters can be easily contaminated. This is particularly the case if samples are collected by non-conventional techniques such as those required for aquatic subglacial environments. In this paper we present the first analysis of a subglacial brine from Taylor Valley, (~ 78°S), Antarctica for the trace metals: Ba, Co, Mo, Rb, Sr, V, and U. Samples were collected englacially using an electrothermal melting probe called the IceMole. This probe uses differential heating of a copper head as well as the probe’s sidewalls and an ice screw at the melting head to move through glacier ice. Detailed blanks, meltwater, and subglacial brine samples were collected to evaluate the impact of the IceMole and the borehole pump, the melting and collection process, filtration, and storage on the geochemistry of the samples collected by this device. Comparisons between melt water profiles through the glacier ice and blank analysis, with published studies on ice geochemistry, suggest the potential for minor contributions of some species Rb, As, Co, Mn, Ni, NH4+, and NO2−+NO3− from the IceMole. The ability to conduct detailed chemical analyses of subglacial fluids collected with melting probes is critical for the future exploration of the hundreds of deep subglacial lakes in Antarctica.
An approach to automatically generate a dynamic energy simulation model in Modelica for a single existing building is presented. It aims at collecting data about the status quo in the preparation of energy retrofits with low effort and costs. The proposed method starts from a polygon model of the outer building envelope obtained from photogrammetrically generated point clouds. The open-source tools TEASER and AixLib are used for data enrichment and model generation. A case study was conducted on a single-family house. The resulting model can accurately reproduce the internal air temperatures during synthetical heating up and cooling down. Modelled and measured whole building heat transfer coefficients (HTC) agree within a 12% range. A sensitivity analysis emphasises the importance of accurate window characterisations and justifies the use of a very simplified interior geometry. Uncertainties arising from the use of archetype U-values are estimated by comparing different typologies, with best- and worst-case estimates showing differences in pre-retrofit heat demand of about ±20% to the average; however, as the assumptions made are permitted by some national standards, the method is already close to practical applicability and opens up a path to quickly estimate possible financial and energy savings after refurbishment.