Towards Remote Sensing of Atmospheric Trace Gases in the UV spectral range using Dual-Comb spectroscopy

Author(s):  
Clément Pivard ◽  
Sandrine Galtier ◽  
Patrick Rairoux

<p>The development of increasingly sensitive and robust instruments and new methodologies are essential to improve our understanding of the Earth’s climate and air pollution. In this context, Dual-Comb spectroscopy (DCS) appears as an emerging spectroscopy methodology to detect in situ, without air-sampling, atmospheric trace-gases.</p><p>DCS is a Fourier-transform type experiment that takes advantage of mode-locked femtosecond (fs) pulses. This methodology appears highly relevant for atmosphere remote-sensing studies because of its very fast acquisition rate (>kHz) that reduces the impact of atmospheric turbulences on the retrieved spectra. DCS has been successfully applied in near-infrared (NIR) spectral ranges for atmospheric greenhouse gas monitoring (water vapor, carbon dioxide, and methane) [1-2].</p><p>Its implementation in the UV range would offer a new spectroscopic intrumentation to target the most reactive species of the atmosphere (OH, HONO, BrO...) as they have their greatest absorption cross-sections in the UV range. UV-DCS would therefore be an answer to the lack of variability of today operationnal and in situ monitoring instrument for those reactive molecules.</p><p>We will present a potential light source for remote sensing UV-DCS and discuss the degree of immunity of UV-DCS to atmospheric turbulences. We will show to which extent the characteristics of the currently available UV sources are compatible with the unambiguous identification of UV absorbing gases by UV-DCS. We will finally present the performances of UV-DCS in terms of concentration detection limit for several UV absorbing molecules (OH, BrO, NO<sub>2</sub>, OClO, HONO, CH<sub>2</sub>O, SO<sub>2</sub>). This sensitivity study has been recently published [3] and the main results will be presented.</p><p> </p><p>[1] Rieker, G.B.; Giorgetta, F.R.; Swann, W.C.; Kofler, J.; Zolot, A.M.; Sinclair, L.C.; Baumann, E.; Cromer, C.;Petron, G.; Sweeney, C.; et al. « Frequency-comb-based remote sensing of greenhouse gases over kilometer air Paths ». Optica 1, p. 290–298 (2014)</p><p>[2] Oudin, J.; Mohamed, A.K.; Hébert, P.J. "IPDA LIDAR measurements on atmospheric CO2 and H2O using dual comb spectroscopy," Proc. SPIE 11180, International Conference on Space Optics — ICSO 2018, p. 111802N (12 July 2019)</p><p>[3] Galtier, S.; Pivard, C.; Rairoux, P. Towards DCS in the UV Spectral Range for Remote Sensing of Atmospheric Trace Gases. Remote Sens., 12, p.3444 (2020)</p>

2018 ◽  
Vol 40 (3) ◽  
pp. 180-187
Author(s):  
Tadeusz Majcherczyk ◽  
Zbigniew Niedbalski ◽  
Łukasz Bednarek

AbstractBack in the early 1980s, coal deposits occurring at depths of ~700 m below surface were already regarded as large-depth deposits. Meanwhile, today the borderline depth of large-depth mining has extended to >1,000 m. Design, excavation and maintenance of mining roadways at the depth of >1,000 m have, therefore, become crucial issues in a practical perspective in recent years. Hence, it is now extremely important to intensify research studies on the influence of large depths on the behaviour of rock mass and deformation of support in underground excavations. The paper presents the results of the study carried out in five mining excavations at depths ranging from 950 to 1,290 m, where monitoring stations with measurement equipment were built. The analysis of data from laboratory and coal mine tests, as well as in situ monitoring, helped to formulate a set of criteria for stability assessment of underground excavations situated at large depths. The proposed methodology of load and deformation prediction in support systems of the excavations unaffected by exploitation is based on the criteria referring to the depth of excavation and the quality of rock mass. The depth parameter is determined by checking whether the analysed excavation lies below the critical depth, whereas the rock mass quality is determined on the basis of the roof lithology index (WL) and the crack intensity factor (n)


2019 ◽  
Vol 11 (15) ◽  
pp. 1744 ◽  
Author(s):  
Daniel Maciel ◽  
Evlyn Novo ◽  
Lino Sander de Carvalho ◽  
Cláudio Barbosa ◽  
Rogério Flores Júnior ◽  
...  

Remote sensing imagery are fundamental to increasing the knowledge about sediment dynamics in the middle-lower Amazon floodplains. Moreover, they can help to understand both how climate change and how land use and land cover changes impact the sediment exchange between the Amazon River and floodplain lakes in this important and complex ecosystem. This study investigates the suitability of Landsat-8 and Sentinel-2 spectral characteristics in retrieving total (TSS) and inorganic (TSI) suspended sediments on a set of Amazon floodplain lakes in the middle-lower Amazon basin using in situ Remote Sensing Reflectance (Rrs) measurements to simulate Landsat 8/OLI (Operational Land Imager) and Sentinel 2/MSI (Multispectral Instrument) bands and to calibrate/validate several TSS and TSI empirical algorithms. The calibration was based on the Monte Carlo Simulation carried out for the following datasets: (1) All-Dataset, consisting of all the data acquired during four field campaigns at five lakes spread over the lower Amazon floodplain (n = 94); (2) Campaign-Dataset including samples acquired in a specific hydrograph phase (season) in all lakes. As sample size varied from one season to the other, n varied from 18 to 31; (3) Lake-Dataset including samples acquired in all seasons at a given lake with n also varying from 17 to 67 for each lake. The calibrated models were, then, applied to OLI and MSI scenes acquired in August 2017. The performance of three atmospheric correction algorithms was also assessed for both OLI (6S, ACOLITE, and L8SR) and MSI (6S, ACOLITE, and Sen2Cor) images. The impact of glint correction on atmosphere-corrected image performance was assessed against in situ glint-corrected Rrs measurements. After glint correction, the L8SR and 6S atmospheric correction performed better with the OLI and MSI sensors, respectively (Mean Absolute Percentage Error (MAPE) = 16.68% and 14.38%) considering the entire set of bands. However, for a given single band, different methods have different performances. The validated TSI and TSS satellite estimates showed that both in situ TSI and TSS algorithms provided reliable estimates, having the best results for the green OLI band (561 nm) and MSI red-edge band (705 nm) (MAPE < 21%). Moreover, the findings indicate that the OLI and MSI models provided similar errors, which support the use of both sensors as a virtual constellation for the TSS and TSI estimate over an Amazon floodplain. These results demonstrate the applicability of the calibration/validation techniques developed for the empirical modeling of suspended sediments in lower Amazon floodplain lakes using medium-resolution sensors.


2018 ◽  
Vol 23 ◽  
pp. 00030 ◽  
Author(s):  
Anshu Rastogi ◽  
Subhajit Bandopadhyay ◽  
Marcin Stróżecki ◽  
Radosław Juszczak

The behaviour of nature depends on the different components of climates. Among these, temperature and rainfall are two of the most important components which are known to change plant productivity. Peatlands are among the most valuable ecosystems on the Earth, which is due to its high biodiversity, huge soil carbon storage, and its sensitivity to different environmental factors. With the rapid growth in industrialization, the climate change is becoming a big concern. Therefore, this work is focused on the behaviour of Sphagnum peatland in Poland, subjected to environment manipulation. Here it has been shown how a simple reflectance based technique can be used to assess the impact of climate change on peatland. The experimental setup consists of four plots with two kind of manipulations (control, warming, reduced precipitation, and a combination of warming and reduced precipitation). Reflectance data were measured twice in August 2017 under a clear sky. Vegetation indices (VIs) such as Normalized Difference Vegetation Index (NDVI), Photochemical Reflectance Index (PRI), near-infrared reflectance of vegetation (NIRv), MERIS terrestrial chlorophyll index (MTCI), Green chlorophyll index (CIgreen), Simple Ration (SR), and Water Band Index (WBI) were calculated to trace the impact of environmental manipulation on the plant community. Leaf Area Index of vascular plants was also measured for the purpose to correlate it with different VIs. The observation predicts that the global warming of 1°C may cause a significant change in peatland behaviour which can be tracked and monitored by simple remote sensing indices.


2013 ◽  
Vol 13 (5) ◽  
pp. 1402-1409
Author(s):  
Adam Trescott ◽  
Elizabeth Isenstein ◽  
Mi-Hyun Park

The objective of this study was to develop cyanobacteria remote sensing models using Landsat 7 Enhanced Thematic Mapper Plus (ETM+) as an alternative to shipboard monitoring efforts in Lake Champlain. The approach allowed for estimation of cyanobacteria directly from satellite images, calibrated and validated with 4 years of in situ monitoring data from Lake Champlain's Long-Term Water Quality and Biological Monitoring Program (LTMP). The resulting stepwise regression model was applied to entire satellite images to provide distribution of cyanobacteria throughout the surface waters of Lake Champlain. The results demonstrate the utility of remote sensing for estimating the distribution of cyanobacteria in inland waters, which can be further used for presenting the initiation and propagation of cyanobacterial blooms in Lake Champlain.


2019 ◽  
Author(s):  
Guillaume Jouvet ◽  
Eef van Dongen ◽  
Martin P. Lüthi ◽  
Andreas Vieli

Abstract. Measuring the ice flow motion accurately is essential to better understand the time evolution of glaciers and ice sheets, and therefore to better anticipate the future consequence of climate change in terms of sea-level rise. Although there exist a variety of remote sensing methods to fill this task, in-situ measurements are always needed for validation or to capture high temporal resolution movements. Yet glaciers are in general hostile environments where the installation of instruments might be tedious and risky when not impossible. Here we report the first-ever in-situ measurements of ice flow motion using a remotely controlled Unmanned Aerial Vehicle (UAV). We used a multicopter UAV to land on a highly crevassed area of Eqip Sermia Glacier, West Greenland, to measure the displacement of the glacial surface with the aid of an on-board differential GNSS receiver. Despite the unfortunate loss of the UAV, we measured approximately 70 cm of displacement over 4.36 hours without setting foot onto the glacier – a result validated by applying UAV photogrammetry and template matching techniques. Our study demonstrates that UAVs are promising instruments for in-situ monitoring, and have a great potential for capturing short-term ice flow variations in inaccessible glaciers – a task that remote sensing techniques can hardly achieve.


2017 ◽  
Vol 21 (11) ◽  
pp. 5693-5708 ◽  
Author(s):  
Jordi Etchanchu ◽  
Vincent Rivalland ◽  
Simon Gascoin ◽  
Jérôme Cros ◽  
Tiphaine Tallec ◽  
...  

Abstract. Agricultural landscapes are often constituted by a patchwork of crop fields whose seasonal evolution is dependent on specific crop rotation patterns and phenologies. This temporal and spatial heterogeneity affects surface hydrometeorological processes and must be taken into account in simulations of land surface and distributed hydrological models. The Sentinel-2 mission allows for the monitoring of land cover and vegetation dynamics at unprecedented spatial resolutions and revisit frequencies (20 m and 5 days, respectively) that are fully compatible with such heterogeneous agricultural landscapes. Here, we evaluate the impact of Sentinel-2-like remote sensing data on the simulation of surface water and energy fluxes via the Interactions between the Surface Biosphere Atmosphere (ISBA) land surface model included in the EXternalized SURface (SURFEX) modeling platform. The study focuses on the effect of the leaf area index (LAI) spatial and temporal variability on these fluxes. We compare the use of the LAI climatology from ECOCLIMAP-II, used by default in SURFEX-ISBA, and time series of LAI derived from the high-resolution Formosat-2 satellite data (8 m). The study area is an agricultural zone in southwestern France covering 576 km2 (24 km  ×  24 km). An innovative plot-scale approach is used, in which each computational unit has a homogeneous vegetation type. Evaluation of the simulations quality is done by comparing model outputs with in situ eddy covariance measurements of latent heat flux (LE). Our results show that the use of LAI derived from high-resolution remote sensing significantly improves simulated evapotranspiration with respect to ECOCLIMAP-II, especially when the surface is covered with summer crops. The comparison with in situ measurements shows an improvement of roughly 0.3 in the correlation coefficient and a decrease of around 30 % of the root mean square error (RMSE) in the simulated evapotranspiration. This finding is attributable to a better description of LAI evolution processes with Formosat-2 data, which further modify soil water content and drainage of soil reservoirs. Effects on annual drainage patterns remain small but significant, i.e., an increase roughly equivalent to 4 % of annual precipitation levels with simulations using Formosat-2 data in comparison to the reference simulation values. This study illustrates the potential for the Sentinel-2 mission to better represent effects of crop management on water budgeting for large, anthropized river basins.


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