Explorative Data Analysis Methods: Application to Laser-Induced Breakdown Spectroscopy Field Data Measured on the Island of Vulcano, Italy.

One of the strengths of laser-induced breakdown spectroscopy (LIBS) is that a large amount of data can be measured relatively easily in a short time, which makes LIBS interesting in many areas, from geomaterial analysis with portable handheld instruments to applications for the exploration of planetary surfaces. Statistical methods, therefore, play an important role in analyzing the data to detect not only individual compositions but also trends and correlations. In this study, we apply two approaches to explore the LIBS data of geomaterials measured with a handheld device at different locations on the Aeolian island of Vulcano, Italy. First, we use the established method, principal component analysis (PCA), and second we adopt the principle of the interesting features finder (IFF), which was recently proposed for the analysis of LIBS imaging data. With this method it is possible to identify spectra that contain emission lines of minor and trace elements that often remain undetected with variance-based methods, such as PCA. We could not detect any spectra with IFF that were not detected with PCA when applying both methods to our LIBS field data. The reason for this may be the nature of our field data, which are subject to more experimental changes than data measured in laboratory settings, such as LIBS imaging data, for which the IFF was introduced first. In conclusion, however, we found that the two approaches complement each other well, making the exploration of the data more intuitive, straightforward, and efficient.

Nitrate and Nitrite Variability at the Seafloor of an Oxygen Minimum Zone Revealed by a Novel Microfluidic In-Situ Chemical Sensor.

Microfluidics, or lab-on-a-chip (LOC) is a promising technology that allows the development of miniaturized chemical sensors. In contrast to the surging interest in biomedical sciences, the utilization of LOC sensors in aquatic sciences is still in infancy but a wider use of such sensors could mitigate the undersampling problem of ocean biogeochemical processes. Here we describe the first underwater test of a novel LOC sensor to obtain in situ calibrated time-series (up to 40 h) of nitrate+nitrite (ΣNOx) and nitrite on the seafloor of the Mauritanian oxygen minimum zone, offshore Western Africa. Initial tests showed that the sensor successfully reproduced water column (160 m) nutrient profiles. Lander deployments at 50, 100 and 170 m depth indicated that the biogeochemical variability was high over the Mauritanian shelf: The 50 m site had the lowest ΣNOx concentration, with 15.2 to 23.4 µM (median=18.3 µM); while at the 100 site ΣNOx varied between 21.0 and 30.1 µM over 40 hours (median = 25.1 µM). The 170 m site had the highest median ΣNOx level (25.8 µM) with less variability (22.8 to 27.7 µM). At the 50 m site, nitrite concentration decreased fivefold from 1 to 0.2 µM in just 30 hours accompanied by decreasing oxygen and increasing nitrate concentrations. Taken together with the time series of oxygen, temperature, pressure and current velocities, we propose that the episodic intrusion of deeper waters via cross-shelf transport leads to intrusion of nitrate-rich, but oxygen-poor waters to shallower locations, with consequences for benthic nitrogen cycling. This first validation of an LOC sensor at elevated water depths revealed that when deployed for longer periods and as a part of a sensor network, LOC technology has the potential to contribute to the understanding of the benthic biogeochemical dynamics.