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.

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 ESTIMATION OF SURFACE SNOW WETNESS USING SENTINEL-2 MULTISPECTRAL DATA

2018 ◽  
Vol IV-5 ◽  
pp. 223-228 ◽  
Author(s):  
D. Varade ◽  
O. Dikshit
Keyword(s):  
Remote Sensing ◽  
Water Resource Management ◽  
Remote Sensing Data ◽  
Microwave Remote Sensing ◽  
In Situ Measurements ◽  
Physical Relationship ◽  
Sensing Data ◽  
Surface Snow ◽  
Sentinel 2

<p><strong>Abstract.</strong> Snow cover characterization and estimation of snow geophysical parameters is a significant area of research in water resource management and surface hydrological processes. With advances in spaceborne remote sensing, much progress has been achieved in the qualitative and quantitative characterization of snow geophysical parameters. However, most of the methods available in the literature are based on the microwave backscatter response of snow. These methods are mostly based on the remote sensing data available from active microwave sensors. Moreover, in alpine terrains, such as in the Himalayas, due to the geometrical distortions, the missing data is significant in the active microwave remote sensing data. In this paper, we present a methodology utilizing the multispectral observations of Sentinel-2 satellite for the estimation of surface snow wetness. The proposed approach is based on the popular triangle method which is significantly utilized for the assessment of soil moisture. In this case, we develop a triangular feature space using the near infrared (NIR) reflectance and the normalized differenced snow index (NDSI). Based on the assumption that the NIR reflectance is linearly related to the liquid water content in the snow, we derive a physical relationship for the estimation of snow wetness. The modeled estimates of snow wetness from the proposed approach were compared with in-situ measurements of surface snow wetness. A high correlation determined by the coefficient of determination of 0.94 and an error of 0.535 was observed between the proposed estimates of snow wetness and in-situ measurements.</p>

scholarly journals Bio-optical provinces in the eastern Atlantic Ocean and their biogeographical relevance

2011 ◽  
Vol 8 (12) ◽  
pp. 3609-3629 ◽  
Author(s):  
B. B. Taylor ◽  
E. Torrecilla ◽  
A. Bernhardt ◽  
M. H. Taylor ◽  
I. Peeken ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Atlantic Ocean ◽  
Large Scale ◽  
Chlorophyll Concentration ◽  
Remote Sensing Data ◽  
In Situ Measurements ◽  
High Spectral Resolution ◽  
Phytoplankton Assemblages ◽  
Eastern Atlantic Ocean

Abstract. The relationship between phytoplankton assemblages and the associated optical properties of the water body is important for the further development of algorithms for large-scale remote sensing of phytoplankton biomass and the identification of phytoplankton functional types (PFTs), which are often representative for different biogeochemical export scenarios. Optical in-situ measurements aid in the identification of phytoplankton groups with differing pigment compositions and are widely used to validate remote sensing data. In this study we present results from an interdisciplinary cruise aboard the RV Polarstern along a north-to-south transect in the eastern Atlantic Ocean in November 2008. Phytoplankton community composition was identified using a broad set of in-situ measurements. Water samples from the surface and the depth of maximum chlorophyll concentration were analyzed by high performance liquid chromatography (HPLC), flow cytometry, spectrophotometry and microscopy. Simultaneously, the above- and underwater light field was measured by a set of high spectral resolution (hyperspectral) radiometers. An unsupervised cluster algorithm applied to the measured parameters allowed us to define bio-optical provinces, which we compared to ecological provinces proposed elsewhere in the literature. As could be expected, picophytoplankton was responsible for most of the variability of PFTs in the eastern Atlantic Ocean. Our bio-optical clusters agreed well with established provinces and thus can be used to classify areas of similar biogeography. This method has the potential to become an automated approach where satellite data could be used to identify shifting boundaries of established ecological provinces or to track exceptions from the rule to improve our understanding of the biogeochemical cycles in the ocean.

scholarly journals Bio-optical provinces in the eastern Atlantic Ocean and their biogeographical relevance

2011 ◽  
Vol 8 (4) ◽  
pp. 7165-7219 ◽  
Author(s):  
B. B. Taylor ◽  
E. Torrecilla ◽  
A. Bernhardt ◽  
M. H. Taylor ◽  
I. Peeken ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Atlantic Ocean ◽  
Large Scale ◽  
Chlorophyll Concentration ◽  
Remote Sensing Data ◽  
In Situ Measurements ◽  
High Spectral Resolution ◽  
Phytoplankton Assemblages ◽  
Eastern Atlantic Ocean

Abstract. The relationship between phytoplankton assemblages and the associated optical properties of the water body is important for the further development of algorithms for large-scale remote sensing of phytoplankton biomass and the identification of phytoplankton functional types (PFTs), which are often representative for different biogeochemical export scenarios. Optical in-situ measurements aid in the identification of phytoplankton groups with differing pigment compositions and are widely used to validate remote sensing data. In this study we present results from an interdisciplinary cruise aboard the R/V Polarstern along a north-to-south transect in the eastern Atlantic Ocean in November 2008. Phytoplankton community composition was identified using a broad set of in-situ measurements. Water samples from the surface and the depth of maximum chlorophyll concentration were analyzed by high performance liquid chromatography (HPLC), flow cytometry, spectrophotometry and microscopy. Simultaneously, the above- and underwater light field was measured by a set of high spectral resolution (hyperspectral) radiometers. An unsupervised cluster algorithm applied to the measured parameters allowed us to define bio-optical provinces, which are compared to ecological provinces proposed elsewhere in the literature. This method has the potential to become an automated approach where satellite data could be used to identify shifting boundaries of established ecological provinces or to track exceptions from the rule to improve our understanding of the biogeochemical cycles in the ocean.

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
Sign in / Sign up

Export Citation Format

Share Document