Seasonal and diurnal patterns in the dispersion of SO2 from Mt. Nyiragongo

Mt. Nyiragongo is an active volcano located in the Democratic Republic of Congo, close to the border of Rwanda and about 15 km north of the city of Goma (~ 1,000,000 inhabitants). Gases emitted from Nyiragongo might pose a persistent hazard to local inhabitants and the environment. While both ground- and satellite-based observations of the emissions exist, prior to this study, no detailed analysis of the dispersion of the emissions have been made. We have conducted a dispersion study, using a modelling system to determine the geographical distribution of SO2.A combination of a meteorological model (WRF), a Lagrangian particle dispersion model (FLEXPART-WRF) and flux data based on DOAS measurements from the NOVAC-network is used. Since observations can only be made during the day, we use random sampling of fluxes and ensemble modelling to estimate night-time emissions.Seasonal variations in the dispersion follows the migration of the Inter Tropical Convergence Zone. In June-August, the area with the highest surface concentrations is located to the northwest, and in December-February, to the southwest of the source. Diurnal variations in surface concentrations were determined by the development of the planetary boundary layer and the lake-/land breeze cycle around lake Kivu. Both processes contribute to low surface concentrations during the day and high concentrations during the night. However, the strong northerly trade winds in November-March weakened the lake breeze, contributing to higher daytime surface concentrations along the northern shore of Lake Kivu, including the city of Goma. For further analysis and measurements, it is important to include both seasonal and diurnal cycles in order to safely cover periods of high and potentially hazardous concentrations

An algorithm for correction of atmospheric scattering dilution effects in volcanic gas emission measurements using skylight differential optical absorption spectroscopy

Differential Optical Absorption Spectroscopy (DOAS) is commonly used to measure gas emissions from volcanoes. DOAS instruments measure the absorption of solar ultraviolet (UV) radiation scattered in the atmosphere by sulfur dioxide (SO2) and other trace gases contained in volcanic plumes. The standard spectral retrieval methods assume that all measured light comes from behind the plume and has passed through the plume along a straight line. However, a fraction of the light that reaches the instrument may have been scattered beneath the plume and thus has passed around it. Since this component does not contain the absorption signatures of gases in the plume, it effectively “dilutes” the measurements and causes underestimation of the gas abundance in the plume. This dilution effect is small for clean-air conditions and short distances between instrument and plume. However, plume measurements made at long distance and/or in conditions with significant atmospheric aerosol, haze, or clouds may be severely affected. Thus, light dilution is regarded as a major error source in DOAS measurements of volcanic degassing. Several attempts have been made to model the phenomena and the physical mechanisms are today relatively well understood. However, these models require knowledge of the local atmospheric aerosol composition and distribution, parameters that are almost always unknown. Thus, a practical algorithm to quantitatively correct for the dilution effect is still lacking. Here, we propose such an algorithm focused specifically on SO2 measurements. The method relies on the fact that light absorption becomes non-linear for high SO2 loads, and that strong and weak SO2 absorption bands are unequally affected by the diluting signal. These differences can be used to identify when dilution is occurring. Moreover, if we assume that the spectral radiance of the diluting light is identical to the spectrum of light measured away from the plume, a measured clean air spectrum can be used to represent the dilution component. A correction can then be implemented by iteratively subtracting fractions of this clean air spectrum from the measured spectrum until the respective absorption signals on strong and weak SO2 absorption bands are consistent with a single overhead SO2 abundance. In this manner, we can quantify the magnitude of light dilution in each individual measurement spectrum as well as obtaining a dilution-corrected value for the SO2 column density along the line of sight of the instrument. This paper first presents the theory behind the method, then discusses validation experiments using a radiative transfer model, as well as applications to field data obtained under different measurement conditions at three different locations; Fagradalsfjall located on the Reykjanaes peninsula in south Island, Manam located off the northeast coast of mainland Papua New Guinea and Holuhraun located in the inland of north east Island

Measurement of Aromatic-hydrocarbons With the DOAS Technique

Long-path DOAS (differential optical absorption spectroscopy) in the ultraviolet spectral region has been shown to be applicable for low-concentration measurements of light aromatic hydrocarbons. However, because of spectral interferences among different aromatics as well as with oxygen, ozone, and sulfur dioxide, the application of the DOAS technique for this group of components is not without problems. This project includes a study of the differential absorption characteristics, between 250 and 280 nm, of twelve light aromatic hydrocarbons representing major constituents in technical solvents used in the automobile industry. Spectral overlapping between the different species, including oxygen, ozone, and sulfur dioxide, has been investigated and related to the chemical structure of the different aromatics. Interference effects in the DOAS application due to spectral overlapping have been investigated both in quantitative and in qualitative terms, with data from a field campaign at a major automobile manufacturing plant

Monitoring weeder robots and anticipating their functioning by using advanced topological data analysis

The present paper aims at analyzing the topological content of the complex trajectories that weeder-autonomous robots follow in operation. We will prove that the topological descriptors of these trajectories are affected by the robot environment as well as by the robot state, with respect to maintenance operations. Most of existing methodologies enabling efficient diagnosis are based on the data analysis, and in particular on some statistical quantities derived from the data. The present work explores the use of an original approach that instead of analyzing quantities derived from the data, analyzes the “shape” of the data, that is, the time series topology based on the homology persistence. We will prove that this procedure is able to extract valuable patterns able to discriminate the trajectories that the robot follows depending on the particular patch in which it operates, as well as to differentiate the robot behavior before and after undergoing a maintenance operation. Even if it is a preliminary work, and it does not pretend to compare its performances with respect to other existing technologies, this work opens new perspectives in considering quite natural and simple descriptors based on the intrinsic information that data contains, with the aim of performing efficient diagnosis and prognosis. Copyright © 2021 Frahi, Sancarlos, Galle, Beaulieu, Chambard, Falco, Cueto and Chinesta

A rapid deployment instrument network for temporarily monitoring volcanic SO2 emissions - a study case from Telica volcano

Volcanic gas emissions play a crucial role in describing geophysical processes; hence measurements of magmatic gases such as SO2 can be used as tracers prior and during volcanic crises. Different measurement techniques based on optical spectroscopy have provided valuable information when assessing volcanic crises. This paper describes the design and implementation of a network of spectroscopic instruments based on Differential Optical Absorption Spectroscopy (DOAS) for remote sensing of volcanic SO2 emissions, which is robust, portable and can be deployed in relative short time. The setup allows the processing of raw data in situ even in remote areas with limited accessibility, and delivers pre-processed data to end-users in near real time even during periods of volcanic crisis, via a satellite link. In addition, the hardware can be used to conduct short term studies of volcanic plumes in remotes areas. The network was tested at Telica, an active volcano located in western Nicaragua, producing what is so far the largest data set of continuous SO2 flux measurements at this volcano

Diagnosis and management of toxicities of immune checkpoint inhibitors in hepatocellular carcinoma

Immune checkpoint inhibitors (ICIs) have reshaped cancer therapy. ICIs enhance T cell activation through various mechanisms and may help reverse the exhausted phenotype of tumour-infiltrating lymphocytes. However, disrupting the key role that checkpoint molecules play in immune homeostasis may result in autoimmune complications. A broad range of immune-related adverse events (irAEs) involve almost every organ but mostly affect the skin, digestive system, lung, endocrine glands, nervous system, kidney, blood cells, and musculoskeletal system. They are usually manageable but can be life-threatening. The incidence of irAEs is not very different in patients with hepatocellular carcinoma (HCC) compared to other tumour types, although there is a trend towards a higher incidence of hepatic irAEs. HCC usually develops on a background of cirrhosis with associated systemic manifestations. Extrahepatic organ dysfunction in cirrhosis may cause signs and symptoms that overlap with irAEs or increase their severity. Available guidelines for the management of irAEs have not specifically considered the assessment of toxicities in the context of patients with liver cancer and cirrhosis. This review addresses the toxicity profile of ICIs in patients with HCC, focusing on the challenges that the underlying liver disease poses to their diagnosis and management. Challenges include late recognition, inadequate work-up and delayed treatment, overdiagnosis and inappropriate interruption of ICIs, complications caused by immunosuppressive therapy, and increased cost. A specific algorithm for the management of hepatic irAEs is provided