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Les cercueils de la grand-place de Nivelles : étude technique et archéologie expérimentale (BRW)
No full textVertical Structure of the Martian Atmosphere: The View from Mars Express
Full text linkLaunched in 2003, the European Space Agency’s Mars Express (MEX) has been orbiting Mars for 20 years and its instruments have performed continuous monitoring of the conditions in the Martian atmosphere, providing one of the most complete datasets of atmospheric parameters ever collected for Mars. This article provides an overview of the observations of the vertical structure of the Martian atmosphere performed by MEx, which led to the identification of peculiar phenomena that affect the atmospheric circulation and dynamics on different scales, from local to regional and global
A semi-supervised multi-temporal landslide and flash flood event detection methodology for unexplored regions using massive satellite image time series
No full textLandslides and flash floods are geomorphic hazards (GH) that often co-occur and interact and frequently lead to societal and environmental impact. The compilation of detailed multi-temporal inventories of GH events over a variety of contrasting natural as well as human-influenced landscapes is essential to understanding their behavior in both space and time and allows to unravel the human drivers from the natural baselines. Yet, creating multitemporal inventories of these GH events remains difficult and costly in terms of human labor, especially when relatively large regions are investigated. Methods to derive GH location from satellite optical imagery have been continuously developed and have shown a clear shift in recent years from conventional methodologies like thresholding and regression to machine learning (ML) methodologies given their improved predictive performance. However, these current generation ML methodologies generally rely on accurate information on either the GH location (training samples) or the GH timing (pre- and post-event imagery), making them unfit in unexplored regions without a priori information on GH occurrences. Currently, a detection methodology to create multi-temporal GH event inventories applicable in relatively large unexplored areas containing a variety of landscapes does not yet exist. We present a new semi-supervised methodology that allows for the detection of both location and timing of GH event occurrence with optical time series, while minimizing manual user interventions. We use the peak of the cumulative difference to the mean for a multitude of spectral indices derived from open-access, high spatial resolution (10 20 m) Copernicus Sentinel-2 time series and generate a map per Sentinel-2 tile that identifies impacted pixels and their related timing. These maps are used to identify GH event impacted zones. We use the generated maps, the identified GH events impacted zones and the automatically derived timing and use them as training sample in a Random Forest classifier to improve the spatial detection accuracy within the impacted zone. We showcase the methodology on six Sentinel-2 tiles in the tropical East African Rift where we detect 29 GH events between 2016 and 2021. We use 12 of these GH events (totalizing ~3900 GH features) with varying time of occurrence, contrasting landscape conditions and different landslide to flash flood ratios to validate the detection methodology. The average identified timing of the GH events lies within two to four weeks of their actual occurrence. The sensitivity of the methodology is mainly influenced by the differences in landscapes, the amount of cloud cover and the size of the GH events. Our methodology is applicable in various landscapes, can be run in a systematic mode, and is dependent only on a few parameters. The methodology is adapted for massive computation
Top-Down Evaluation of Volatile Chemical Product Emissions Using a Lagrangian Framework
Full text linkIn this study, we evaluate volatile chemical product (VCP; e.g., adhesives, personal care products) emissions in the McDonald et al. inventory using sector-specific tracers and the FLEXPART-WRF Lagrangian particle dispersion model. Observations of decamethylcyclopentasiloxane (D5-Siloxane) are used for optimizing emissions from personal care products, para-dichlorobenzene (PDCBZ) for insecticides, and parachlorobenzotrifluoride (PCBTF) for emissions from the construction (coatings + adhesives) subsector. Continuous ground-site measurements obtained in Las Vegas and Los Angeles (LA) during summer 2021 are used to optimize the temporal emission profiles of the area sources. Additionally, in situ aircraft-based observations (June 2021) over the LA region are used to evaluate emission factors for the basin. The configuration of the weather research and forecasting (WRF) model is optimized using vertical wind profile measurements obtained from the Pick-Up truck-based Mobile Atmospheric Sounder (PUMAS) deployed in the LA basin to minimize the uncertainty of the inversion due to meteorology. While the diurnal amplitude in emission rates from personal care products and insecticides is reduced after optimization, that of construction VCPs (coatings + adhesives) is enhanced. From the aircraft inversion, we find that the inventory underestimates the emissions originating from construction by a factor of 5.3 (95% confidence interval 4.3–6.3) in the LA basin. Emissions from consumer products (personal care + cleaning) and insecticides were reduced by a factor of 2.1 (1.7–2.5) and 5.2 (3.9–6.4), respectively, following optimization. AB - In this study, we evaluate volatile chemical product (VCP; e.g., adhesives, personal care products) emissions in the McDonald et al. inventory using sector-specific tracers and the FLEXPART-WRF Lagrangian particle dispersion model. Observations of decamethylcyclopentasiloxane (D5-Siloxane) are used for optimizing emissions from personal care products, para-dichlorobenzene (PDCBZ) for insecticides, and parachlorobenzotrifluoride (PCBTF) for emissions from the construction (coatings + adhesives) subsector. Continuous ground-site measurements obtained in Las Vegas and Los Angeles (LA) during summer 2021 are used to optimize the temporal emission profiles of the area sources. Additionally, in situ aircraft-based observations (June 2021) over the LA region are used to evaluate emission factors for the basin. The configuration of the weather research and forecasting (WRF) model is optimized using vertical wind profile measurements obtained from the Pick-Up truck-based Mobile Atmospheric Sounder (PUMAS) deployed in the LA basin to minimize the uncertainty of the inversion due to meteorology. While the diurnal amplitude in emission rates from personal care products and insecticides is reduced after optimization, that of construction VCPs (coatings + adhesives) is enhanced. From the aircraft inversion, we find that the inventory underestimates the emissions originating from construction by a factor of 5.3 (95% confidence interval 4.3–6.3) in the LA basin. Emissions from consumer products (personal care + cleaning) and insecticides were reduced by a factor of 2.1 (1.7–2.5) and 5.2 (3.9–6.4), respectively, following optimization
Environmental change and migrants transnational practices in favour of environmental adaptation in Morocco, Senegal and DR Congo? Insights from migrants in Belgium
No full textRelSIM: A Relativistic Semi-implicit Method for Particle-in-cell Simulations
Full text linkWe present a novel Relativistic Semi-Implicit Method (RelSIM) for particle-in-cell (PIC) simulations of astrophysical plasmas, implemented in a code framework ready for production runs. While explicit PIC methods have gained widespread recognition in the astrophysical community as a reliable tool to simulate plasma phenomena, implicit methods have been seldom explored. This is partly due to the lack of a reliable relativistic implicit PIC formulation that is applicable to state-of-the-art simulations. We propose the RelSIM to fill this gap: our new method is relatively simple, being free of nonlinear iterations and only requiring a global linear solve of the field equations. With a set of one- and two-dimensional tests, we demonstrate that the RelSIM produces more accurate results with much smaller numerical errors in the total energy than standard explicit PIC, in particular when characteristic plasma scales (skin depth and plasma frequency) are heavily underresolved on the numerical grid. By construction, the RelSIM also performs much better than the relativistic implicit-moment method, originally proposed for semi-implicit PIC simulations in the relativistic regime. Our results are promising to conduct large-scale (in terms of duration and domain size) PIC simulations of astrophysical plasmas, potentially reaching physical regimes inaccessible by standard explicit PIC codes
DNA-based species identification of mosquitoes collected with Malaise Traps in the Botanical Garden Jardin Massart (Diptera: Culicidae) <iframe id="fyvk4JtO" frameborder="0" src="chrome-extension://ekhagklcjbdpajgpjgmbionohlpdbjgc/translateSandbox/translateSandbox.html" style="width: 0px; height: 0px; display: none;"></iframe>
No full textIn the Botanic Garden Jean Massart in Auderghem (Brussels, Belgium), mosquitoes were collected with Malaise traps in 2016 and 2017, stored in 70% ethanol, and sorted out for morphological identification. Yet, in this way species-specific characters like scales may be lost, so that individuals become morphologically difficult to distinguish. Therefore, DNA-based techniques were applied for accurate species (or biotype for Culex pipiens s.s.) level identification of mosquitoes occurring in Belgium. This revealed the presence of six mosquito species, as well as two biotypes and their hybrids of Culex pipiens s.s., the most common and widespread mosquito species in Belgium. Some of the discovered species might act as vectors of arboviruses
