scholarly journals Airborne remote sensing and in situ measurements of atmospheric CO<sub>2</sub> to quantify point source emissions

2018 ◽  
Vol 11 (2) ◽  
pp. 721-739 ◽  
Author(s):  
Thomas Krings ◽  
Bruno Neininger ◽  
Konstantin Gerilowski ◽  
Sven Krautwurst ◽  
Michael Buchwitz ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Carbon Dioxide ◽  
Mass Balance ◽  
Power Plants ◽  
Greenhouse Gas Emission ◽  
In Situ Measurements ◽  
Emission Rates ◽  
Airborne Remote Sensing ◽  
In Situ Data

Abstract. Reliable techniques to infer greenhouse gas emission rates from localised sources require accurate measurement and inversion approaches. In this study airborne remote sensing observations of CO2 by the MAMAP instrument and airborne in situ measurements are used to infer emission estimates of carbon dioxide released from a cluster of coal-fired power plants. The study area is complex due to sources being located in close proximity and overlapping associated carbon dioxide plumes. For the analysis of in situ data, a mass balance approach is described and applied, whereas for the remote sensing observations an inverse Gaussian plume model is used in addition to a mass balance technique. A comparison between methods shows that results for all methods agree within 10 % or better with uncertainties of 10 to 30 % for cases in which in situ measurements were made for the complete vertical plume extent. The computed emissions for individual power plants are in agreement with results derived from emission factors and energy production data for the time of the overflight.

scholarly journals Airborne remote sensing and in-situ measurements of atmospheric CO<sub>2</sub> to quantify point source emissions

2016 ◽  
Author(s):  
Thomas Krings ◽  
Bruno Neininger ◽  
Konstantin Gerilowski ◽  
Sven Krautwurst ◽  
Michael Buchwitz ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Carbon Dioxide ◽  
Mass Balance ◽  
Power Plants ◽  
Greenhouse Gas Emission ◽  
Remote Sensing Data ◽  
In Situ Measurements ◽  
Emission Rates ◽  
Airborne Remote Sensing

Abstract. Reliable techniques to infer greenhouse gas emission rates from localised sources require accurate measurement and inversion approaches. In this study airborne remote sensing observations by the MAMAP instrument and airborne in-situ measurements are used to infer emission estimates of carbon dioxide released from a cluster of coal fired power plants. For the analysis of in-situ data, a mass balance approach is described and applied. Whereas for the remote sensing observations an inverse Gaussian plume model is used in addition to a mass balance technique. A comparison between methods shows that results for all methods agree within a few percent for cases where in-situ measurements were made for the complete vertical plume extent. Even though the power plants are partly in close proximity and the associated carbon dioxide plumes are overlapping it is possible to derive emission rates from remote sensing data for individual power plants that agree well with results derived from emission factors and energy production data for the time of the overflight.

SMART – Space monitoring of Arctic Tundra landscapes

2021 ◽  
Author(s):  
Jennifer Sobiech-Wolf ◽  
Tobias Ullmann ◽  
Wolfgang Dierking
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Land Surface ◽  
In Situ Measurements ◽  
German Research Foundation ◽  
Marine Research ◽  
In Situ Data ◽  
Spatial Coverage ◽  
Infrared Measurements

&lt;p&gt;Satellite remote sensing as well as in-situ measurements are common tools to monitor the state of Arctic environments. However, remote sensing products often lack sufficient temporal and/or spatial resolution, and in-situ measurements can only describe the environmental conditions on a very limited spatial scale. Therefore, we conducted an air-borne campaign to connect the detailed in-situ data with poor spatial coverage to coarse satellite images. The SMART campaign is part of the ongoing project &amp;#8222;Characterization of Polar Permafrost Landscapes by Means of Multi-Temporal and Multi-Scale Remote Sensing, and In-Situ Measurements&amp;#8220;, funded by the German Research Foundation (DFG).&amp;#160; The focus of the project is to close the gap between in-situ measurements and space-borne images in polar permafrost landscapes. The airborne campaign SMART was conducted in late summer 2018 in north-west Canada, focussing on the Mackenzie-Delta region, which is underlain by permafrost and rarely inhabited. The land cover is either dominated by open Tundra landscapes or by boreal forests. The Polar-5 research-aircraft from the Alfred Wegener Institute, Helmholtz Center for Polar and Marine Research, Germany, was equipped with a ground penetrating radar, a hyperspectral camara, a laserscanner, and an infrared temperature sensor amongst others. In parallel to the airborne acquisition, a team collected in-situ data on ground, including manual active layer depth measurements, geophysical surveying using 2D Electric Resistivity Tomography (ERT), GPR, and mapping of additional land cover properties. The database was completed by a variety of satellite data from different platforms, e.g. MODIS, Landsat, TerraSAR-X and Sentinel-1. &amp;#160;As part of the project, we analysed the performance of MODIS Land surfaces temperature products compared to our air-borne infrared measurements and evaluated, how long the land surface temperatures of this Arctic environment can be considered as stable. It turned out that the MODIS data differ up to 2&amp;#176;C from the air-borne measurements. If this is due to the spatial difference of the measurements or a result of data processing of the MODIS LST products is part of ongoing analysis.&lt;/p&gt;

scholarly journals Estimating CH<sub>4</sub>, CO<sub>2</sub> and CO emissions from coal mining and industrial activities in the Upper Silesian Coal Basin using an aircraft-based mass balance approach

2020 ◽  
Vol 20 (21) ◽  
pp. 12675-12695
Author(s):  
Alina Fiehn ◽  
Julian Kostinek ◽  
Maximilian Eckl ◽  
Theresa Klausner ◽  
Michał Gałkowski ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Mass Balance ◽  
Greenhouse Gas ◽  
Greenhouse Gas Emission ◽  
Climate Mitigation ◽  
Emission Inventories ◽  
Ch4 Emission ◽  
Coal Basin ◽  
Upper Silesian Coal Basin

Abstract. A severe reduction of greenhouse gas emissions is necessary to reach the objectives of the Paris Agreement. The implementation and continuous evaluation of mitigation measures requires regular independent information on emissions of the two main anthropogenic greenhouse gases, carbon dioxide (CO2) and methane (CH4). Our aim is to employ an observation-based method to determine regional-scale greenhouse gas emission estimates with high accuracy. We use aircraft- and ground-based in situ observations of CH4, CO2, carbon monoxide (CO), and wind speed from two research flights over the Upper Silesian Coal Basin (USCB), Poland, in summer 2018. The flights were performed as a part of the Carbon Dioxide and Methane (CoMet) mission above this European CH4 emission hot-spot region. A kriging algorithm interpolates the observed concentrations between the downwind transects of the trace gas plume, and then the mass flux through this plane is calculated. Finally, statistic and systematic uncertainties are calculated from measurement uncertainties and through several sensitivity tests, respectively. For the two selected flights, the in-situ-derived annual CH4 emission estimates are 13.8±4.3 and 15.1±4.0 kg s−1, which are well within the range of emission inventories. The regional emission estimates of CO2, which were determined to be 1.21±0.75 and 1.12±0.38 t s−1, are in the lower range of emission inventories. CO mass balance emissions of 10.1±3.6 and 10.7±4.4 kg s−1 for the USCB are slightly higher than the emission inventory values. The CH4 emission estimate has a relative error of 26 %–31 %, the CO2 estimate of 37 %–62 %, and the CO estimate of 36 %–41 %. These errors mainly result from the uncertainty of atmospheric background mole fractions and the changing planetary boundary layer height during the morning flight. In the case of CO2, biospheric fluxes also add to the uncertainty and hamper the assessment of emission inventories. These emission estimates characterize the USCB and help to verify emission inventories and develop climate mitigation strategies.

scholarly journals Supplementary material to "Methane emissions from a Californian landfill, determined from airborne remote sensing and in-situ measurements"

2016 ◽  
Author(s):  
Sven Krautwurst ◽  
Konstantin Gerilowski ◽  
Haflidi H. Jonsson ◽  
David R. Thompson ◽  
Richard W. Kolyer ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Methane Emissions ◽  
In Situ Measurements ◽  
Airborne Remote Sensing ◽  
Supplementary Material

scholarly journals HSRL-2 aerosol optical measurements and microphysical retrievals vs. airborne in situ measurements during DISCOVER-AQ 2013: an intercomparison study

2016 ◽  
Author(s):  
Patricia Sawamura ◽  
Richard H. Moore ◽  
Sharon P. Burton ◽  
Eduard Chemyakin ◽  
Detlef Müller ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Surface Area ◽  
Mie Theory ◽  
In Situ Measurements ◽  
Optical Measurements ◽  
High Spectral Resolution ◽  
Size Distributions ◽  
In Situ Data ◽  
Intercomparison Study

Abstract. Over 700 vertically-resolved retrievals of effective radii, number, volume, and surface-area concentrations of aerosols obtained from inversion of airborne multiwavelength High Spectral Resolution Lidar (HSRL-2) measurements are compared to vertically resolved airborne in situ measurements obtained during DISCOVER-AQ campaign from 2013 in California and Texas. In situ measurements of dry and humidified scattering, dry absorption, and dry size distributions are used to estimate hygroscopic adjustments which, in turn, are applied to the dry in situ measurements before comparison to HSRL-2 measurements and retrievals. The HSRL-2 retrievals of size parameters agree well with the in situ measurements once the hygroscopic adjustments are applied to the latter, with biases smaller than 25 % for surface-area concentrations, and smaller than 10 % for volume concentration. A closure study is performed by comparing the extinction and backscatter measured with the HSRL-2 with those calculated from the in situ size distributions and Mie theory, once refractive indices (at ambient RH) and hygroscopic adjustments are calculated and applied. The results of this closure study revealed discrepancies between the HSRL-2 optical measurements and those calculated from in situ measurements, in both California and Texas datasets, with the aerosol extinction and backscatter coefficients measured with the HSRL-2 being larger than those calculated from the adjusted in situ measurements and Mie theory. These discrepancies are further investigated and discussed in light of the many challenges often present in closure studies between in situ and remote sensing systems, such as: limitations in covering the same size range of particles with in situ and remote sensing instruments, as well as simplified parameterizations and assumptions used when dry in situ data are adjusted to account for aerosol hygroscopicity.

Estimating emissions of methane and carbon dioxide sources using analytical Bayesian inversion system based on WRF-GHG tagged tracer simulations

2020 ◽  
Author(s):  
Michał Gałkowski ◽  
Julia Marshall ◽  
Frank-Thomas Koch ◽  
Jinxuan Chen ◽  
Alina Fiehn ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Anthropogenic Sources ◽  
Bayesian Inversion ◽  
Emission Rates ◽  
Atmospheric Measurements ◽  
Mixing Ratios ◽  
In Situ Data ◽  
Ventilation Shaft ◽  
Research Aircraft

&lt;p&gt;During May and June 2018, the intensive campaign CoMet (Carbon dioxide and Methane mission) made atmospheric measurements of greenhouse gases over Europe, with the upper Silesian coal basin (USCB) in southern Poland as a specific focus area. CoMet aimed at characterising the distribution of CH&lt;sub&gt;4&lt;/sub&gt; and CO&lt;sub&gt;2&lt;/sub&gt; over significant regional sources with the use of a fleet of research aircraft, as well as to validate remote sensing measurements from state-of-the-art instrumentation installed on-board against a set of independent in-situ observations.&lt;/p&gt;&lt;p&gt;In order to link atmospheric mixing ratios to source emission rates, high-resolution simulations with WRF-GHG v 3.9.1.1. (10 km x10 km Europe + nested 2 km x 2 km domain over the USCB), driven by short-term meteorological forecasts from the ECMWF IFS model and forecasts from CAMS (Copernicus Atmospheric Monitoring Service) for initial and lateral tracer boundary conditions were performed. Biogenic fluxes of CO2 were calculated online using the VPRM model driven by MODIS indices. Anthropogenic emissions over Europe were taken from the database of TNO, Department of Climate, Air and Sustainability (7 km x 7 km), augmented with an internal emissions database developed within CoMet that uses coal mine ventilation shaft emission measurements in combination with recent updates of the E-PRTR (European Pollutant Release and Transfer Register).&lt;/p&gt;&lt;p&gt;Tagged tracers were used to simulate a robust set of over 100 distinct anthropogenic sources of CH&lt;sub&gt;4&lt;/sub&gt; and CO&lt;sub&gt;2&lt;/sub&gt; from the study area, and these forward simulations were then used as the transport operator in an analytical Bayesian inversion system. Here we discuss the results of an analysis performed with the use of selected in-situ data measured over the course of the three-week campaign, including results and sensitivity tests.&lt;/p&gt;

Mass balance study of the Znosko glacier, Antarctica, using remote sensing and in situ measurements

2021 ◽  
Author(s):  
Cinthya Bello ◽  
Wilson Suarez ◽  
Fabian Brondi ◽  
Gilbert Gonzales
Keyword(s):  
Remote Sensing ◽  
Mass Balance ◽  
Antarctic Peninsula ◽  
Austral Summer ◽  
In Situ Measurements ◽  
Glacier Mass Balance ◽  
Atmospheric Conditions ◽  
Glacier Surface ◽  
Balance Study

&lt;p&gt;Glaciers are a key indicator of climate change. Since the second half of the 20th century several glaciers in Antarctica have retreated. In situ measurements of glacier mass balance in the Antarctic Peninsula and its surrounding islands are very scarce because this area is inaccessible due to rough terrain and inhospitable atmospheric conditions, but there is a necessity in study peripheral glaciers dynamics to know their future contribution to sea level rise. To fill this gap, remote sensing is an alternative tool to enable timely monitoring of dynamic glaciers and quantifying spatial-temporal changes. Here we combine remote sensing (satellite imaginary and aerial photos) and in situ measurements to calculate mass balance for the Znosko glacier (King George Island, Antarctic Peninsula) and compare the accuracy of this methods. Two field campaigns were carried out during the XXVI and XXVII Peruvian Antarctic Operation (austral summer 2018/19 and 2019/20). 19 stakes were fixed on the glacier surface, in situ mass balance data were collected from yearly stake measurements. Also, digital elevation models were generated through aerial photogrammetry and auxiliary data from the ICESat-2 mission were included into the analysis. &amp;#160;We find that mass balances estimated with these methods are consistent and confirm the mass loss (heterogeneous pattern between accumulation and ablation zone) and retreat of Znosko glacier. We illustrate how participatory mapping (interdisciplinary team) can complement initial remote sensing land cover classification and assist ground checks.&lt;/p&gt;

scholarly journals Estimating CH<sub>4</sub>, CO<sub>2</sub>, and CO emissions from coal mining and industrial activities in the Upper Silesian Coal Basin using an aircraft-based mass balance approach

2020 ◽  
Author(s):  
Alina Fiehn ◽  
Julian Kostinek ◽  
Maximilian Eckl ◽  
Theresa Klausner ◽  
Michał Gałkowski ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Mass Balance ◽  
Greenhouse Gas ◽  
Greenhouse Gas Emission ◽  
Climate Mitigation ◽  
Emission Inventories ◽  
Ch4 Emission ◽  
Coal Basin ◽  
Upper Silesian Coal Basin

Abstract. A severe reduction of greenhouse gas emissions is necessary to reach the objectives of the Paris Agreement. The implementation and continuous evaluation of mitigation measures requires regular independent information on emissions of the two main anthropogenic greenhouse gases, carbon dioxide (CO2) and methane (CH4). Our aim is to employ an observation-based method to determine regional-scale greenhouse gas emission estimates with high accuracy. We use aircraft- and ground-based in situ observations of CH4, CO2, carbon monoxide (CO), and wind speed from two research flights over the Upper Silesian Coal Basin (USCB), Poland, in summer 2018. The flights were performed as a part of the Carbon Dioxide and Methane (CoMet) mission above this European CH4 emission hot spot region. A kriging algorithm interpolates the observed concentrations between the downwind transects of the trace gas plume and then the mass flux through this plane is calculated. Finally, statistic and systematic uncertainties are calculated from measurement uncertainties and through several sensitivity tests, respectively. For the two selected flights, the in situ derived annual CH4 emission estimates are 13.8 ± 3.6 kg/s and 15.1 ± 3.0 kg/s, which is well within the range of emission inventories. The regional emission estimates of CO2, which were determined to be 1.21 ± 0.72 t/s and 1.12 ± 0.37 t/s, are in the lower range of emission inventories. CO mass balance emissions of 10.1 ± 3.2 kg/s and 10.7 ± 2.9 kg/s for the USCB are slightly higher than the emission inventory values. The CH4 emission estimate has a relative error of 21–26 %, the CO2 estimate of 33–60 %, and the CO estimate of 27–32 %. These errors mainly result from the uncertainty of atmospheric background mole fractions and the changing planetary boundary layer height during the morning flight. In the case of CO2, biospheric fluxes also add to the uncertainty and hamper the assessment of emission inventories. These emission estimates characterize the USCB and help to verify emission inventories and develop climate mitigation strategies.

Testing the temporal and spatial validity of site-specific models derived from airborne remote sensing of phytoplankton

1995 ◽  
Vol 52 (5) ◽  
pp. 1094-1107 ◽  
Author(s):  
David F. Millie ◽  
Bryan T. Vinyard ◽  
Michael C. Baker ◽  
Craig S. Tucker
Keyword(s):  
Remote Sensing ◽  
Phytoplankton Biomass ◽  
Significant Proportion ◽  
Regression Tree ◽  
Airborne Remote Sensing ◽  
Site Specific ◽  
In Situ Data ◽  
Tree Modeling ◽  
Chlorophyll Distribution

Validations of predictive models are necessary for the accurate application of remotely sensed imagery within ecological research and fisheries management. Multiple regression models derived from airborne imagery on 16 May 1990 accurately depicted phytoplankton biomass and turbidity within aquaculture impoundments. To examine their temporal validity, the exact models, as well as identical model forms, were fit to similar imagery and in situ data collected on 20 June 1990. None of the exact models for 16 May accurately predicted in situ data on 20 June; however, model forms were robust for describing in situ variables. To examine their spatial validity, identical model forms were fit to in situ data partitioned among phytoplankton composition and biomass. The fit of the models and the contribution of imagery variables to the models varied among in situ variables. Although imagery variables explained all of the observed variability for turbidity, regression tree modeling indicated that a significant proportion of the variability in chlorophyll distribution both among and within impoundments was explained through both imagery variables and phytoplankton biomass. Consequently, universal models for the airborne remote sensing of water-quality variables in systems having distinct optical signatures is unlikely. Rather, robust site-specific models will need to be developed.

Particulate matter variability in Kathmandu based on in-situ measurements, remote sensing, and reanalysis data

2021 ◽  
pp. 105623
Author(s):  
Stefan Becker ◽  
Ramesh Prasad Sapkota ◽  
Binod Pokharel ◽  
Loknath Adhikari ◽  
Rudra Prasad Pokhrel ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Particulate Matter ◽  
Reanalysis Data ◽  
In Situ Measurements
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