scholarly journals Global carbon monoxide as retrieved from SCIAMACHY by WFM-DOAS

2004 ◽  
Vol 4 (7) ◽  
pp. 1945-1960 ◽  
Author(s):  
M. Buchwitz ◽  
R. de Beek ◽  
K. Bramstedt ◽  
S. Noël ◽  
H. Bovensmann ◽  
...  
Keyword(s):  
Carbon Monoxide ◽  
Near Infrared ◽  
Weighting Function ◽  
Constant Factor ◽  
Retrieval Algorithm ◽  
First Results ◽  
Infrared Spectral ◽  
The Difference ◽  
Global Carbon

Abstract. First results concerning the retrieval of tropospheric carbon monoxide (CO) from satellite solar backscatter radiance measurements in the near-infrared spectral region (~2.3µm) are presented. The Weighting Function Modified (WFM) DOAS retrieval algorithm has been used to retrieve vertical columns of CO from SCIAMACHY/ENVISAT nadir spectra. We present detailed results for three days from the time periode January to October 2003 selected to have good overlap with the daytime CO measurements of MOPITT onboard EOS Terra. Because the WFM-DOAS Version 0.4 CO columns presented in this paper are scaled by a constant factor of 0.5 to compensate for an obvious overestimation we focus on the variability of the retrieved columns rather than on their absolute values. It is shown that plumes of CO resulting from, e.g. biomass burning in Africa, are detectable with single overpass SCIAMACHY data. Globally, the SCIAMACHY CO columns are in reasonable agreement with the Version 3 CO column data product of MOPITT. For example, for measurements over land, where the quality of the data is typically better than over ocean due to higher surface reflectivity, the standard deviation of the difference with respect to MOPITT is in the range 0.4-0.6x1018 molecules/cm2 and the linear correlation coefficient is between 0.4 and 0.7. The level of agreement between the data of both sensors depends on time and location but is typically within 30% for most latitudes. In the southern hemisphere outside Antarctica SCIAMACHY tends to give systematically higher values than MOPITT. More studies are needed to find out what the reasons for the observed differences with respect to MOPITT are and how the algorithm can be modified to improve the quality of the CO columns as retrieved from SCIAMACHY.

scholarly journals Three years of global carbon monoxide from SCIAMACHY: comparison with MOPITT and first results related to the detection of enhanced CO over cities

2007 ◽  
Vol 7 (9) ◽  
pp. 2399-2411 ◽  
Author(s):  
M. Buchwitz ◽  
I. Khlystova ◽  
H. Bovensmann ◽  
J. P. Burrows
Keyword(s):  
Carbon Monoxide ◽  
Near Infrared ◽  
Retrieval Algorithm ◽  
Vertical Column ◽  
Data Set ◽  
Retrieval Method ◽  
First Results ◽  
Long Time ◽  
Global Carbon ◽  
Good Agreement

Abstract. Carbon monoxide (CO) is an important atmospheric constituent affecting air quality and climate. SCIAMACHY on ENVISAT is currently the only satellite instrument that can measure the vertical column of CO with nearly equal sensitivity at all altitudes down to the Earth's surface because of its near-infrared nadir observations of reflected solar radiation. Here we present three years' (2003–2005) of SCIAMACHY CO columns consistently retrieved with the latest version of our retrieval algorithm (WFMDv0.6). We describe the retrieval method and discuss the multi-year global CO data set focusing on a comparison with the operational CO column data product of MOPITT. We found reasonable to good agreement (~20%) with MOPITT, with the best agreement for 2004. We present detailed results for various regions (Europe, Middle East, India, China) and discuss to what extent enhanced levels of CO can be detected over populated areas including individual cities. The expected CO signal from cities is close to or even below the detection limit of individual measurements. We show that cities can be identified when averaging long time series.

scholarly journals Three years of global carbon monoxide from SCIAMACHY: comparison with MOPITT and first results related to the detection of enhanced CO over cities

2007 ◽  
Vol 7 (1) ◽  
pp. 405-428 ◽  
Author(s):  
M. Buchwitz ◽  
I. Khlystova ◽  
H. Bovensmann ◽  
J. P. Burrows
Keyword(s):  
Carbon Monoxide ◽  
Near Infrared ◽  
Retrieval Algorithm ◽  
Vertical Column ◽  
Data Set ◽  
Retrieval Method ◽  
First Results ◽  
Long Time ◽  
Global Carbon ◽  
Good Agreement

Abstract. Carbon monoxide (CO) is an important atmospheric constituent affecting air quality and climate. SCIAMACHY on ENVISAT is currently the only satellite instrument that can measure the vertical column of CO with nearly equal sensitivity at all altitudes down to the Earth's surface because of its near-infrared nadir observations of reflected solar radiation. Here we present three years' (2003–2005) of SCIAMACHY CO columns consistently retrieved with the latest version of our retrieval algorithm (WFMDv0.6). We describe the retrieval method and discuss the multi-year global CO data set focusing on a comparison with the operational CO column data product of MOPITT. We found reasonable to good agreement (~20%) with MOPITT, with the best agreement for 2004. We present detailed results for various regions (Europe, Middle East, India, China) and discuss to what extent enhanced levels of CO can be detected over populated areas including individual cities. The expected CO signal from cities is close to or even below the detection limit of individual measurements. We show however that cities can be identified when averaging long time series.

scholarly journals Global carbon monoxide as retrieved from SCIAMACHY by WFM-DOAS

2004 ◽  
Vol 4 (3) ◽  
pp. 2805-2837 ◽  
Author(s):  
M. Buchwitz ◽  
R. de Beek ◽  
K. Bramstedt ◽  
S. Noël ◽  
H. Bovensmann ◽  
...  
Keyword(s):  
Carbon Monoxide ◽  
Near Infrared ◽  
Weighting Function ◽  
Lower Troposphere ◽  
Quantitative Information ◽  
Scaling Factor ◽  
Retrieval Algorithm ◽  
Absorption Bands ◽  
Spectral Fitting ◽  
Data Product

Abstract. Vertical columns of CO have been retrieved from SCIAMACHY/ENVISAT short wave/near infrared (~2.3µm) nadir spectra using the Weighting Function Modified (WFM) DOAS retrieval algorithm. WFM-DOAS has been applied to a small spectral fitting window located in SCIAMACHY's channel 8 (~2365 nm) covering four CO absorption lines. The focus of this paper is to demonstrate that quantitative information on carbon monoxide (CO) on a global scale can be retrieved from SCIAMACHY. It is shown that plumes of CO resulting from, e.g. biomass burning in Africa, are clearly detectable with SCIAMACHY. The SCIAMACHY CO columns are in good agreement with the CO column data product of MOPITT (V3). For example, the correlation between SCIAMACHY and MOPITT CO columns for cloud free pixels over land is typically in the range r=0.4–0.7, where r is the correlation coefficient. In order to retrieve good CO columns it was necessary to improve the calibration of the SCIAMACHY nadir spectra. Nevertheless, there is still room for significant improvement. The fit residuals, for example, are dominated by stable and systematic spectral artifacts on the order of the weak CO lines. These artifacts are most pronounced in spectral regions of strong overlapping methane and water vapour absorption bands. They might result from spectrometer slit function uncertainties. The CO columns of the WFM-DOAS Version 0.4 CO column data product presented in this paper have been multiplied by a constant and ground scene independent scaling factor of 0.5 to quantitatively adjust the WFM-DOAS retrieved CO columns to the MOPITT CO data. If and how this scaling factor is influenced by SCIAMACHYs much higher sensitivity to the lower troposphere and boundary layer CO and/or by the currently not perfect spectral fitting needs further investigation.

scholarly journals A COMPARISON OF HAZE REMOVAL ALGORITHMS AND THEIR IMPACTS ON CLASSIFICATION ACCURACY FOR LANDSAT IMAGERY

2017 ◽  
Vol 23 (1) ◽  
pp. 55-71 ◽  
Author(s):  
Yang Xiao ◽  
Zhiyun Ouyang ◽  
Zhiming Zhang ◽  
Chaofan Xian
Keyword(s):  
Classification Accuracy ◽  
Near Infrared ◽  
Landsat Imagery ◽  
Spectral Response ◽  
Landsat Images ◽  
Haze Removal ◽  
Reference Images ◽  
The Difference ◽  
Spatially Varying

The quality of Landsat images in humid areas is considerably degraded by haze in terms of their spectral response pattern, which limits the possibility of their application in using visible and near-infrared bands. A variety of haze removal algorithms have been proposed to correct these unsatisfactory illumination effects caused by the haze contamination. The purpose of this study was to illustrate the difference of two major algorithms (the improved homomorphic filtering (HF) and the virtual cloud point (VCP)) for their effectiveness in solving spatially varying haze contamination, and to evaluate the impacts of haze removal on land cover classification. A case study with exploiting large quantities of Landsat TM images and climates (clear and haze) in the most humid areas in China proved that these haze removal algorithms both perform well in processing Landsat images contaminated by haze. The outcome of the application of VCP appears to be more similar to the reference images compared to HF. Moreover, the Landsat image with VCP haze removal can improve the classification accuracy effectively in comparison to that without haze removal, especially in the cloudy contaminated area

The Circumnuclear Starburst in NGC 7552: First Results from Near‐Infrared Spectral Synthesis

1997 ◽  
Vol 488 (1) ◽  
pp. 174-194 ◽  
Author(s):  
E. Schinnerer ◽  
A. Eckart ◽  
A. Quirrenbach ◽  
T. Boker ◽  
L. E. Tacconi‐Garman ◽  
...  
Keyword(s):  
Near Infrared ◽  
Spectral Synthesis ◽  
First Results ◽  
Infrared Spectral

scholarly journals Atmospheric methane and carbon dioxide from SCIAMACHY satellite data: initial comparison with chemistry and transport models

2004 ◽  
Vol 4 (6) ◽  
pp. 7217-7279 ◽  
Author(s):  
M. Buchwitz ◽  
R. de Beek ◽  
J. P. Burrows ◽  
H. Bovensmann ◽  
T. Warneke ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Reasonable Agreement ◽  
Near Infrared ◽  
Weighting Function ◽  
Lower Surface ◽  
Retrieval Algorithm ◽  
Atmospheric Methane ◽  
Mixing Ratios ◽  
Data Products ◽  
Carbon Dioxide Co2

Abstract. The remote sensing of the atmospheric greenhouse gases methane (CH4) and carbon dioxide (CO2) in the troposphere from instrumentation aboard satellites is a new area of research. In this manuscript, results obtained from observations of the up-welling radiation in the near-infrared by SCIAMACHY (Scanning Imaging Absorption spectroMeter for Atmospheric CHartographY), which flies on board ENVISAT, are presented. Vertical columns of CH4, CO2 and oxygen (O2) have been retrieved and the (air or) O2-normalized CH4 and CO2 column amounts, the dry air column averaged mixing ratios XCH4 and XCO2 derived. In this manuscript the first results, obtained by using the version 0.4 of the Weighting Function Modified (WFM) DOAS retrieval algorithm applied to SCIAMACHY data, are described and compared with global models. This is an important step in assessing the quality and information content of the data products derived from SCIAMACHY observations. This study investigates the behaviour of CO2 and CH4 in the period from January to October 2003. The SCIAMACHY greenhouse gas column amounts and their mixing ratios for cloud free scenes over land are shown to be in reasonable agreement with models. Over the ocean, as a result of the lower surface spectral reflectance and resultant low signal to noise with the exception of sun glint conditions, the accuracy of the individual data products is poorer. The measured methane column amounts agree with the model columns within a few percent. The inter-hemispheric difference of the methane mixing ratios, determined from single day cloud free measurements over land, is in the range 30–110 ppbv and in reasonable agreement with the corresponding model data (48–71 ppbv). For the set of individual measurements the standard deviations of the difference with respect to the models are in the range ~100–200 ppbv (5–10%) and ±14.4 ppmv (3.9%) for XCH

scholarly journals A scientific algorithm to simultaneously retrieve carbon monoxide and methane from TROPOMI onboard Sentinel-5 Precursor

2019 ◽  
Author(s):  
Oliver Schneising ◽  
Michael Buchwitz ◽  
Maximilian Reuter ◽  
Heinrich Bovensmann ◽  
John P. Burrows ◽  
...  
Keyword(s):  
Carbon Monoxide ◽  
Systematic Error ◽  
Random Error ◽  
Weighting Function ◽  
Synthetic Data ◽  
Solar Spectrum ◽  
Retrieval Algorithm ◽  
Data Set ◽  
Airborne Measurements ◽  
Global Coverage

Abstract. Carbon monoxide (CO) is an important atmospheric constituent affecting air quality and methane (CH4) is the second most important greenhouse gas contributing to human-induced climate change. Detailed and continuous observations of these gases are necessary to better assess their impact on climate and atmospheric pollution. While surface and airborne measurements are able to accurately determine atmospheric abundances on local scales, global coverage can only be achieved using satellite instruments. The TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor satellite, which was successfully launched in October 2017, is a spaceborne nadir viewing imaging spectrometer measuring solar radiation reflected by the Earth in a push-broom configuration. It has a wide swath on the terrestrial surface and covers wavelength bands between the ultraviolet (UV) and the shortwave infrared (SWIR) combining a high spatial resolution with daily global coverage. These characteristics enable the determination of both gases with unprecedented level of detail on a global scale introducing new areas of application. Abundances of the atmospheric column-averaged dry air mole fractions XCO and XCH4 are simultaneously retrieved from TROPOMI's radiance measurements in the 2.3 μm spectral range of the SWIR part of the solar spectrum using the scientific retrieval algorithm Weighting Function Modified DOAS (WFM-DOAS). We introduce the algorithm in detail, including expected error characteristics based on synthetic data, a machine learning-based quality filter and a shallow learning calibration procedure applied in the post-processing of the XCH4 data. The quality of the results based on real TROPOMI data is assessed by validation with ground-based Fourier Transform Spectrometer (FTS) measurements providing realistic error estimates of the satellite data: The XCO data set is characterised by a random error of 5.1 ppb (5.7 %) and a systematic error of 1.9 ppb (2.1 %); the XCH4 data set exhibits a random error of 14.0 ppb (0.8 %) and a systematic error of 4.4 ppb (0.2 %). The natural XCO and XCH4 variations are well captured by the satellite retrievals, which is demonstrated by a high correlation to the reference data (R = 0.97 for XCO and R = 0.91 for XCH4 based on daily averages). We also present selected results from mission start until end of 2018, including a first comparison to the operational products and examples of the detection of emission sources in a single satellite overpass, such as CO emissions from the steel industry and CH4 emissions from the energy sector.

scholarly journals A climate-scale satellite record for carbon monoxide: the MOPITT Version 7 product

2017 ◽  
Vol 10 (7) ◽  
pp. 2533-2555 ◽  
Author(s):  
Merritt N. Deeter ◽  
David P. Edwards ◽  
Gene L. Francis ◽  
John C. Gille ◽  
Sara Martínez-Alonso ◽  
...  
Keyword(s):  
Carbon Monoxide ◽  
Near Infrared ◽  
Retrieval Algorithm ◽  
Bias Drift ◽  
New Strategy ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Atmospheric Carbon Monoxide ◽  
Climate Scale ◽  
Cloud Mask

Abstract. The MOPITT (Measurements of Pollution in the Troposphere) satellite instrument has been making observations of atmospheric carbon monoxide since 2000. Recent enhancements to the MOPITT retrieval algorithm have resulted in the release of the version 7 (V7) product. Improvements include (1) representation of growing atmospheric concentrations of N2O, (2) use of meteorological fields from the MERRA-2 (Modern-Era Retrospective Analysis for Research and Applications) reanalysis for the entire MOPITT mission (instead of MERRA), (3) use of the MODIS (Moderate-Resolution Imaging Spectroradiometer) Collection 6 cloud mask product (instead of Collection 5), (4) a new strategy for radiance-bias correction and (5) an improved method for calibrating MOPITT's near-infrared (NIR) radiances. Statistical comparisons of V7 validation results with corresponding V6 results are presented, using aircraft in situ measurements as the reference. Clear improvements are demonstrated for V7 products with respect to overall retrieval biases, bias variability and bias drift uncertainty.

scholarly journals Curing Assessment of Concrete with Hyperspectral Imaging

Materials ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 3848
Author(s):  
Lisa Ptacek ◽  
Alfred Strauss ◽  
Barbara Hinterstoisser ◽  
Andreas Zitek
Keyword(s):  
Hyperspectral Imaging ◽  
Near Infrared ◽  
Strength Development ◽  
Contactless Method ◽  
Infrared Spectral ◽  
Young Concrete ◽  
Negative Effect ◽  
High Level ◽  
Destructive Measurement

The curing of concrete significantly influences the hydration process and its strength development. Inadequate curing leads to a loss of quality and has a negative effect on the durability of the concrete. Usually, the effects are not noticed until years later, when the first damage to the structure occurs because of the poor concrete quality. This paper presents a non-destructive measurement method for the determination of the curing quality of young concrete. Hyperspectral imaging in the near infrared is a contactless method that provides information about material properties in an electromagnetic wavelength range that cannot be seen with the human eye. Laboratory tests were carried out with samples with three different curing types at the age of 1, 7, and 27 days. The results showed that differences in the near infrared spectral signatures can be determined depending on the age of the concrete and the type of curing. The data was classified and analyzed by evaluating the results using k-means clustering. This method showed a high level of reliability for the differentiation between the different curing types and concrete ages. A recommendation for hyperspectral measurement and the evaluation of the curing quality of concrete could be made.

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