scholarly journals Comparison of Total Column and Surface Mixing Ratio of Carbon Monoxide Derived from the TROPOMI/Sentinel-5 Precursor with In-Situ Measurements from Extensive Ground-Based Network over South Korea

2021 ◽  
Vol 13 (19) ◽  
pp. 3987
Author(s):  
Ukkyo Jeong ◽  
Hyunkee Hong
Keyword(s):  
Carbon Monoxide ◽  
Air Quality ◽  
South Korea ◽  
Winter Season ◽  
In Situ Measurements ◽  
Spatiotemporal Variability ◽  
Spatial Coverage ◽  
Surface Mixing ◽  
Total Column

Atmospheric carbon monoxide (CO) significantly impacts climate change and human health, and has become the focus of increased air quality and climate research. Since 2018, the Troposphere Monitoring Instrument (TROPOMI) has provided total column amounts of CO (CTROPOMI) with a high spatial resolution to monitor atmospheric CO. This study compared and assessed the accuracy of CTROPOMI measurements using surface in-situ measurements (SKME) obtained from an extensive ground-based network over South Korea, where CO level is persistently affected by both local emissions and trans-boundary transport. Our analysis reveals that the TROPOMI effectively detected major emission sources of CO over South Korea and efficiently complemented the spatial coverage of the ground-based network. In general, the correlations between CTROPOMI and SKME were lower than those for NO2 reported in a previous study, and this discrepancy was partly attributed to the lower spatiotemporal variability. Moreover, vertical CO profiles were sampled from the ECMWF CAMS reanalysis data (EAC4) to convert CTROPOMI to surface mixing ratios (STROPOMI). STROPOMI showed a significant underestimation compared with SKME by approximately 40%, with a moderate correlation of approximately 0.51. The low biases of STROPOMI were more significant during the winter season, which was mainly attributed to the underestimation of the EAC4 CO at the surface. This study can contribute to the assessment of satellite and model data for monitoring surface air quality and greenhouse gas emissions.

scholarly journals Multiscale observations of NH<sub>3</sub> around Toronto, Canada

2021 ◽  
Vol 14 (2) ◽  
pp. 905-921
Author(s):  
Shoma Yamanouchi ◽  
Camille Viatte ◽  
Kimberly Strong ◽  
Erik Lutsch ◽  
Dylan B. A. Jones ◽  
...  
Keyword(s):  
Temporal Variability ◽  
Grid Point ◽  
Regional Scale ◽  
Model Performance ◽  
In Situ Measurements ◽  
Coefficient Of Determination ◽  
Spatial And Temporal Variability ◽  
Predictive Capacity ◽  
Total Column

Abstract. Ammonia (NH3) is a major source of nitrates in the atmosphere and a major source of fine particulate matter. As such, there have been increasing efforts to measure the atmospheric abundance of NH3 and its spatial and temporal variability. In this study, long-term measurements of NH3 derived from multiscale datasets are examined. These NH3 datasets include 16 years of total column measurements using Fourier transform infrared (FTIR) spectroscopy, 3 years of surface in situ measurements, and 10 years of total column measurements from the Infrared Atmospheric Sounding Interferometer (IASI). The datasets were used to quantify NH3 temporal variability over Toronto, Canada. The multiscale datasets were also compared to assess the representativeness of the FTIR measurements. All three time series showed positive trends in NH3 over Toronto: 3.34 ± 0.89 %/yr from 2002 to 2018 in the FTIR columns, 8.88 ± 5.08 %/yr from 2013 to 2017 in the surface in situ data, and 8.38 ± 1.54 %/yr from 2008 to 2018 in the IASI columns. To assess the representative scale of the FTIR NH3 columns, correlations between the datasets were examined. The best correlation between FTIR and IASI was obtained with coincidence criteria of ≤25 km and ≤20 min, with r=0.73 and a slope of 1.14 ± 0.06. Additionally, FTIR column and in situ measurements were standardized and correlated. Comparison of 24 d averages and monthly averages resulted in correlation coefficients of r=0.72 and r=0.75, respectively, although correlation without averaging to reduce high-frequency variability led to a poorer correlation, with r=0.39. The GEOS-Chem model, run at 2∘ × 2.5∘ resolution, was compared to FTIR and IASI to assess model performance and investigate the correlation of observational data and model output, both with local column measurements (FTIR) and measurements on a regional scale (IASI). Comparisons on a regional scale (a domain spanning 35 to 53∘ N and 93.75 to 63.75∘ W) resulted in r=0.57 and thus a coefficient of determination, which is indicative of the predictive capacity of the model, of r2=0.33, but comparing a single model grid point against the FTIR resulted in a poorer correlation, with r2=0.13, indicating that a finer spatial resolution is needed for modeling NH3.

scholarly journals A statistical approach to quantify uncertainty in carbon monoxide measurements at the Izaña global GAW station: 2008–2011

2012 ◽  
Vol 5 (5) ◽  
pp. 6949-6989 ◽  
Author(s):  
A. J. Gomez-Pelaez ◽  
R. Ramos ◽  
V. Gomez-Trueba ◽  
P. C. Novelli ◽  
R. Campo-Hernandez
Keyword(s):  
Carbon Monoxide ◽  
Response Function ◽  
Measurement System ◽  
Minimum Variance ◽  
Standard Uncertainty ◽  
In Situ Measurements ◽  
North East ◽  
The Mean ◽  
Mean Differences

Abstract. Atmospheric CO in-situ measurements are carried out at the Izaña (Tenerife) global GAW mountain station using a RGA (Reduction Gas Analyser). In-situ measurements at Izaña are representative of the subtropical North-East Atlantic free troposphere, specially during the night period. We present the measurement system configuration, the response function, the calibration scheme, the data processing, the Izaña's 2008–2011 CO nocturnal time series, and the mean diurnal cycle by months. We have developed a rigorous uncertainty analysis for carbon monoxide measurements carried out at the Izaña station which could be applied to other GAW stations. We determine the combined standard uncertainty from four components of the measurement: uncertainty of the WMO standard gases interpolated over the range of measurement, the uncertainty that takes into account the agreement between the standard gases and the response function used, the uncertainty due to the repeatability of the injections, and the propagated uncertainty related to the response function parameters uncertainties (which also takes into account the covariance between the parameters). The mean value of the combined standard uncertainty decreased significantly after March 2009, from 2.37 nmol mol−1 to 1.66 nmol mol−1, due to improvements in the measurement system. A fifth type of uncertainty we call representation uncertainty is considered when some of the data necessary to compute exactly the mean are absent. Any computed mean has also a propagated uncertainty arising from the uncertainties of the data used to compute the mean. The law of propagation depends on the type of uncertainty component (random or systematic). In-situ hourly means are compared with simultaneous and collocated NOAA flask samples. The uncertainty in the differences is determined and whether these are significant. For 2009–2011, only 24.5% of the differences are significant, and 68% of the differences are between −2.39 and 2.5 nmol mol−1. Total and annual mean differences are computed using conventional expressions but also expressions with weights based on the minimum variance method. The annual mean differences for 2009–2011 are well within the &amp;pm;2 nmol mol−1 compatibility goal of GAW.

scholarly journals Global carbon monoxide products from combined AIRS, TES and MLS measurements on A-train satellites

2013 ◽  
Vol 13 (6) ◽  
pp. 15409-15441
Author(s):  
J. X. Warner ◽  
R. Yang ◽  
Z. Wei ◽  
F. Carminati ◽  
A. Tangborn ◽  
...  
Keyword(s):  
Carbon Monoxide ◽  
Data Fusion ◽  
Lower Troposphere ◽  
Atmospheric Infrared Sounder ◽  
Upper Troposphere ◽  
In Situ Data ◽  
Diode Laser Spectrometer ◽  
Spatial Coverage ◽  
Transport Experiment

Abstract. This study tests a novel methodology to add value to satellite datasets. This methodology, data fusion, is similar to data assimilation, except that the background model-based field is replaced by a satellite dataset, in this case AIRS (Atmospheric Infrared Sounder) carbon monoxide (CO) measurements. The observational information comes from CO measurements with lower spatial coverage than AIRS, namely, from TES (Tropospheric Emission Spectrometer) and MLS (Microwave Limb Sounder). We show that combining these datasets with data fusion uses the higher spectral resolution of TES to extend AIRS CO observational sensitivity to the lower troposphere, a region especially important for air quality studies. We also show that combined CO measurements from AIRS and MLS provide enhanced information in the UTLS (upper troposphere/lower stratosphere) region compared to each product individually. The combined AIRS/TES and AIRS/MLS CO products are validated against DACOM (differential absorption mid-IR diode laser spectrometer) in situ CO measurements from the INTEX-B (Intercontinental Chemical Transport Experiment: MILAGRO and Pacific phases) field campaign and in situ data from HIPPO (HIAPER Pole-to-Pole Observations) flights. The data fusion results show improved sensitivities in the lower and upper troposphere (20–30% and above 20%, respectively) as compared with AIRS-only retrievals, and improved coverage compared with TES and MLS CO data.

scholarly journals Brick Sector and Air Quality: An Integrated Assessment towards 2020 Challenge of Environment Development

2021 ◽  
Vol 19 (2) ◽  
pp. 153-164
Author(s):  
Shazia Pervaiz ◽  
◽  
Muhammad Ameer Nawaz Akram ◽  
Filza Zafar Khan ◽  
Kanwal Javid ◽  
...  
Keyword(s):  
Carbon Monoxide ◽  
Air Quality ◽  
Winter Season ◽  
Environmental Parameters ◽  
Control Measures ◽  
Pollution Levels ◽  
Brick Kilns ◽  
Central Regions ◽  
The Government ◽  
Set Up

Brick sector is a mainstay of the urban economy of Punjab. The traditional technology of brick making emits a lot of toxic gases and smoke particulates into air. Hence, the Government of the Punjab, Pakistan announced a ban on low technology brick kiln operations during winter season by the end of December 2020. Initially, the existing set up of brick kilns and air pollution levels were evaluated before and during lockdown period using spatial application. Further, environmental parameters such as aerosols, carbon monoxide, ozone, sulfur dioxide and carbon dioxide were determined to analyze the air quality, including metrological factors. Results of the study exhibited that the upper and central regions of Punjab are the major hubs of brick kilns. So, the level of air quality was inconsistent in the study period due to the existence of large mushrooms of brick kilns. Further, despite lockdown the highest concentration of carbon monoxide was recorded in the eastern side of the province, such as Kasur, Lahore, and Sheikhupura. The level of aerosols also fluctuated and shifted its trends in the central and southern part of the province. While SO2 and CO2 level declined and revealed a satisfactory level of air quality during shutdown. On the other hand, no significant relation to metrological factors, such as rain, is involved in the pollution reduction. Conclusively, the findings of the present study encourage the government agencies to realign the stringent control measures to improve the quality of air in the winter months using the experience of quarantine in 2020.

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;

Towards the removal of model bias from ESA CCI SM by using an L-band scaling reference

2021 ◽  
Author(s):  
Rémi Madelon ◽  
Nemesio Rodriguez-Fernandez ◽  
Robin Van Der Shalie ◽  
Yann Kerr ◽  
Tracy Scalon ◽  
...  
Keyword(s):  
Time Series ◽  
Soil Moisture ◽  
Climate Models ◽  
In Situ Measurements ◽  
Time Data ◽  
Data Set ◽  
Spatial Coverage ◽  
L Band ◽  
Better Than

&lt;p&gt;Merging data from different instruments is required to construct long time data records of soil moisture (SM). This is the goal of projects such as the ESA Climate Change Initiative (CCI) for SM (Gruber et al., 2019), which uses both active and passive microwave sensors. Currently, the GLDAS v2.1 model is used as reference to re-scale active and passive time series by matching their Cumulative Density Function (CDF) to that of the model. Removing the dependency on models is important, in particular for data assimilation applications into hydrological or climate models, and it has been proposed (Van der Schalie et al., 2018) to use L-band data from one of the two instruments specifically designed to measure SM, ESA Soil Moisture and Ocean Salinity (SMOS) and NASA Soil Moisture Active Passive (SMAP) satellites, as reference to re-scale other time series.&lt;br&gt;To investigate this approach, AMSR-2 SM time series obtained from C1-, C2- and X-band observations using LPRM (Land Parameter Retrieval Model) were re-scaled by CDF-matching (Brocca et al., 2011) using different SMAP and SMOS official (SMAP L2 V005, SMOS L3 V300, SMOS NRT V100&amp;V200) and research (SMOS IC V103) SM products as well as the SMAP and SMOS LPRM v6 SM data used by the ESA CCI. The time series re-scaled using L-band remote sensing data were compared to those re-scaled using GLDAS and were evaluated against in situ measurements at several hundred sites retrieved from the International Soil Moisture Network (Dorigo et al., 2011). The results were analyzed as a function of the land cover class and the Koppen-Geiger climate classification.&lt;br&gt;Overall, AMSR-2 time series re-scaled using SMAP L2, SMAP LPRM and SMOS IC data sets as reference gave the best correlations with respect to in situ measurements, similar to those obtained by the time series re-scaled using GLDAS and slightly better than those of the original AMSR-2 time series. These results imply that different SMAP and SMOS products could actually be used to replace GLDAS as reference for the re-scaling of other sensors time series within the ESA CCI. However, one must bear in mind that this study is limited to the re-scaling of AMSR-2 data at a few hundred sites.&lt;br&gt;For a more detailed assessment of the L-band data set to be used for a global re-scaling, it is necessary to investigate other effects such as the spatial coverage or the time series length. SMAP spatial coverage is better than that of SMOS in regions affected by radio frequency interference. In contrast, the length of SMAP time series can be too short to capture the long term SM variability for climate applications in some regions. The CDF of SMOS time series computed from the date of SMAP launch is significantly different to those of the full length SMOS time series in some regions of the Globe. Possible ways of using a coherent SMAP/SMOS L-band data set will be discussed.&lt;/p&gt;

scholarly journals Contributions of the troposphere and stratosphere to CH<sub>4</sub> model biases

2017 ◽  
Vol 17 (21) ◽  
pp. 13283-13295 ◽  
Author(s):  
Zhiting Wang ◽  
Thorsten Warneke ◽  
Nicholas M. Deutscher ◽  
Justus Notholt ◽  
Ute Karstens ◽  
...  
Keyword(s):  
Latitudinal Gradient ◽  
Transport Model ◽  
In Situ Measurements ◽  
Model Bias ◽  
Chemical Transport Model ◽  
Fourier Transform Spectrometry ◽  
Model Biases ◽  
Inverse Models ◽  
Total Column

Abstract. Inverse modelling is a useful tool for retrieving CH4 fluxes; however, evaluation of the applied chemical transport model is an important step before using the inverted emissions. For inversions using column data one concern is how well the model represents stratospheric and tropospheric CH4 when assimilating total column measurements. In this study atmospheric CH4 from three inverse models is compared to FTS (Fourier transform spectrometry), satellite and in situ measurements. Using the FTS measurements the model biases are separated into stratospheric and tropospheric contributions. When averaged over all FTS sites the model bias amplitudes (absolute model to FTS differences) are 7.4 ± 5.1, 6.7 ± 4.8, and 8.1 ± 5.5 ppb in the tropospheric partial column (the column from the surface to the tropopause) for the models TM3, TM5-4DVAR, and LMDz-PYVAR, respectively, and 4.3 ± 9.9, 4.7 ± 9.9, and 6.2 ± 11.2 ppb in the stratospheric partial column (the column from the tropopause to the top of the atmosphere). The model biases in the tropospheric partial column show a latitudinal gradient for all models; however there are no clear latitudinal dependencies for the model biases in the stratospheric partial column visible except with the LMDz-PYVAR model. Comparing modelled and FTS-measured tropospheric column-averaged mole fractions reveals a similar latitudinal gradient in the model biases but comparison with in situ measured mole fractions in the troposphere does not show a latitudinal gradient, which is attributed to the different longitudinal coverage of FTS and in situ measurements. Similarly, a latitudinal pattern exists in model biases in vertical CH4 gradients in the troposphere, which indicates that vertical transport of tropospheric CH4 is not represented correctly in the models.

scholarly journals OMI satellite observations of decadal changes in ground-level sulfur dioxide over North America

2017 ◽  
Vol 17 (9) ◽  
pp. 5921-5929 ◽  
Author(s):  
Shailesh K. Kharol ◽  
Chris A. McLinden ◽  
Christopher E. Sioris ◽  
Mark W. Shephard ◽  
Vitali Fioletov ◽  
...  
Keyword(s):  
Air Quality ◽  
North America ◽  
Sulfur Dioxide ◽  
Power Plants ◽  
Ground Level ◽  
In Situ Measurements ◽  
Ozone Monitoring Instrument ◽  
Control Laws ◽  
The Impact

Abstract. Sulfur dioxide (SO2) has a significant impact on the environment and human health. We estimated ground-level sulfur dioxide (SO2) concentrations from the Ozone Monitoring Instrument (OMI) using SO2 profiles from the Global Environmental Multi-scale – Modelling Air quality and CHemistry (GEM-MACH) model over North America for the period of 2005–2015. OMI-derived ground-level SO2 concentrations (r = 0. 61) and trends (r = 0. 74) correlated well with coincident in situ measurements from air quality networks over North America. We found a strong decreasing trend in coincidently sampled ground-level SO2 from OMI (−81 ± 19 %) and in situ measurements (−86 ± 13 %) over the eastern US for the period of 2005–2015, which reflects the implementation of stricter pollution control laws, including flue-gas desulfurization (FGD) devices in power plants. The spatially and temporally contiguous OMI-derived ground-level SO2 concentrations can be used to assess the impact of long-term exposure to SO2 on the health of humans and the environment.

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