scholarly journals Comparison of TROPOMI/Sentinel-5 Precursor NO<sub>2</sub> observations with ground-based measurements in Helsinki

2020 ◽  
Vol 13 (1) ◽  
pp. 205-218 ◽  
Author(s):  
Iolanda Ialongo ◽  
Henrik Virta ◽  
Henk Eskes ◽  
Jari Hovila ◽  
John Douros
Keyword(s):  
Air Quality ◽  
Transport Model ◽  
A Priori ◽  
Quality Data ◽  
High Temporal Resolution ◽  
Chemical Transport Model ◽  
Early Evaluation ◽  
The Mean ◽  
Urban Sites

Abstract. We present a comparison between satellite-based TROPOMI (TROPOspheric Monitoring Instrument) NO2 products and ground-based observations in Helsinki (Finland). TROPOMI NO2 total (summed) columns are compared with the measurements performed by the Pandora spectrometer between April and September 2018. The mean relative and absolute bias between the TROPOMI and Pandora NO2 total columns is about 10 % and 0.12×1015 molec. cm−2 respectively. The dispersion of these differences (estimated as their standard deviation) is 2.2×1015 molec. cm−2. We find high correlation (r = 0.68) between satellite- and ground-based data, but also that TROPOMI total columns underestimate ground-based observations for relatively large Pandora NO2 total columns, corresponding to episodes of relatively elevated pollution. This is expected because of the relatively large size of the TROPOMI ground pixel (3.5×7 km) and the a priori used in the retrieval compared to the relatively small field-of-view of the Pandora instrument. On the other hand, TROPOMI slightly overestimates (within the retrieval uncertainties) relatively small NO2 total columns. Replacing the coarse a priori NO2 profiles with high-resolution profiles from the CAMS chemical transport model improves the agreement between TROPOMI and Pandora total columns for episodes of NO2 enhancement. When only the low values of NO2 total columns or the whole dataset are taken into account, the mean bias slightly increases. The change in bias remains mostly within the uncertainties. We also analyse the consistency between satellite-based data and in situ NO2 surface concentrations measured at the Helsinki–Kumpula air quality station (located a few metres from the Pandora spectrometer). We find similar day-to-day variability between TROPOMI, Pandora and in situ measurements, with NO2 enhancements observed during the same days. Both satellite- and ground-based data show a similar weekly cycle, with lower NO2 levels during the weekend compared to the weekdays as a result of reduced emissions from traffic and industrial activities (as expected in urban sites). The TROPOMI NO2 maps reveal also spatial features, such as the main traffic ways and the airport area, as well as the effect of the prevailing south-west wind patterns. This is one of the first works in which TROPOMI NO2 retrievals are validated against ground-based observations and the results provide an early evaluation of their applicability for monitoring pollution levels in urban sites. Overall, TROPOMI retrievals are valuable to complement the ground-based air quality data (available with high temporal resolution) for describing the spatio-temporal variability of NO2, even in a relatively small city like Helsinki.

scholarly journals Comparison of TROPOMI/Sentinel 5 Precursor NO<sub>2</sub> observations with ground-based measurements in Helsinki

2019 ◽  
Author(s):  
Iolanda Ialongo ◽  
Henrik Virta ◽  
Henk Eskes ◽  
Jari Hovila ◽  
John Douros
Keyword(s):  
Air Quality ◽  
Transport Model ◽  
A Priori ◽  
Quality Data ◽  
High Temporal Resolution ◽  
Chemical Transport Model ◽  
Early Evaluation ◽  
Weekly Cycle ◽  
Urban Sites

Abstract. We present a comparison between satellite-based TROPOMI (TROPOspheric Monitoring Instrument) NO2 products and ground-based observations in Helsinki (Finland). TROPOMI NO2 total (summed) columns are compared with the measurements performed by the Pandora spectrometer during April–September 2018. We find a high correlation (r = 0.68) between satellite- and ground-based data, but also that TROPOMI total columns underestimate ground-based observations for relatively large Pandora NO2 total columns, corresponding to episodes of relatively elevated pollution. This is expected because of the relatively large size of the TROPOMI ground pixel (3.5 km x 7 km) and the a-priori used in the retrieval compared to the relatively small field-of-view of the Pandora instrument. Replacing the coarse a-priori NO2 profiles with high-resolution profiles from the CAMS chemical transport model improves the agreement between TROPOMI and Pandora total columns for episodes of NO2 enhancement. We also analyse the consistency between satellite-based data and in situ NO2 surface concentrations measured at the Helsinki-Kumpula air quality station (located a few metres from the Pandora spectrometer). We find similar day-to-day variability between TROPOMI, Pandora and in situ measurements, with NO2 enhancements observed during the same days. Both satellite- and ground-based data show a similar weekly cycle, with lower NO2 levels during the weekend compared to the weekdays as a result of reduced emissions from traffic and industrial activities (as expected in urban sites). The TROPOMI NO2 maps reveal also spatial features, such as the main traffic ways and the airport area, as well as the effect of the prevailing south-west wind patterns. This is one of the first works in which TROPOMI NO2 retrievals are validated against ground-based observations and the results provide an early evaluation of their applicability for monitoring pollution levels in urban sites. Overall, TROPOMI retrievals are valuable to complement the ground-based air quality data (available with high temporal resolution) for describing the spatio-temporal variability of NO2, even in a relatively small city like Helsinki.

Comparison of TROPOMI/Sentinel-5 Precursor NO2 product with ground-based observations in Helsinki and first societal applications

2020 ◽  
Author(s):  
Iolanda Ialongo ◽  
Henrik Virta ◽  
Henk Eskes ◽  
Jari Hovila ◽  
John Douros
Keyword(s):  
Air Quality ◽  
Transport Model ◽  
A Priori ◽  
Urban Air Quality ◽  
Oil Refinery ◽  
Urban Air ◽  
Chemical Transport Model ◽  
Weekly Cycle ◽  
Oil Refineries

&lt;p&gt;We evaluate the satellite-based TROPOMI (TROPOspheric Monitoring Instrument) NO2 products against ground-based observations in Helsinki (Finland). TROPOMI NO2 total (summed) columns are compared with the measurements performed by the Pandora spectrometer during April&amp;#8211;September 2018. The mean relative and absolute bias between the TROPOMI and Pandora NO2 total columns is about 10 % and 0.12 &amp;#215; 10&lt;sup&gt;15&lt;/sup&gt; molec. cm&lt;sup&gt;-2&lt;/sup&gt; respectively.&lt;span&gt;&amp;#160;&lt;/span&gt;&lt;/p&gt;&lt;p&gt;We find high correlation (r = 0.68) between satellite- and ground-based data, but also that TROPOMI total columns underestimate ground-based observations for relatively large Pandora NO2 total columns, corresponding to episodes of relatively elevated pollution. This is expected because of the relatively large size of the TROPOMI ground pixel (3.5 &amp;#215; 7 km) and the a priori used in the retrieval compared to the relatively small field-of-view of the Pandora instrument. On the other hand, TROPOMI slightly overestimates relatively small NO2 total columns. Replacing the coarse a priori NO2 profiles with high-resolution profiles from the CAMS chemical transport model improves the agreement between TROPOMI and Pandora total columns for episodes of NO2 enhancement.&lt;span&gt;&amp;#160;&lt;/span&gt;&lt;/p&gt;&lt;p&gt;In order to evaluate the capability of TROPOMI observation for monitoring urban air quality, we also analyse the consistency between satellite-based data and NO2 surface concentrations from the local air quality station. We find similar day-to-day variability between TROPOMI and in situ measurements, with NO2 enhancements observed during the same days. Both satellite- and ground-based data show a similar weekly cycle, with lower NO2 levels during the weekend compared to the weekdays as a result of reduced emissions from traffic and industrial activities (as expected in urban sites). The TROPOMI NO2 maps reveal also spatial features, such as the main traffic ways, the airport and other industrial areas, as well as the effect of the prevailing south-west wind patterns.&lt;span&gt;&amp;#160;&lt;/span&gt;&lt;/p&gt;&lt;p&gt;These first results confirm that TROPOMI NO2 products are valuable to complement the traditional ground-based in situ data for monitoring urban air quality and are already tested by local and national authorities as well as private companies to monitor pollution sources in the Helsinki region (e.g., emissions from traffic, energy production or oil refineries). For example, TROPOMI NO2 products are already used by the oil refinery company NESTE in their sustainability report and by the Finnish Ministry of Environment to map the air pollution levels in Finland.&lt;/p&gt;&lt;p&gt;Ialongo, I., Virta, H., Eskes, H., Hovila, J., and Douros, J.: Comparison of TROPOMI/Sentinel 5 Precursor NO2 observations with ground-based measurements in Helsinki, Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2019-329, accepted for publication, 2020.&lt;/p&gt;

scholarly journals The added value of a visible channel to a geostationary thermal infrared instrument to monitor ozone for air quality

2014 ◽  
Vol 7 (2) ◽  
pp. 1645-1689
Author(s):  
E. Hache ◽  
J.-L. Attié ◽  
C. Tourneur ◽  
P. Ricaud ◽  
L. Coret ◽  
...  
Keyword(s):  
Air Quality ◽  
Transport Model ◽  
Statistical Tests ◽  
Surface Ozone ◽  
A Priori ◽  
Thermal Infrared ◽  
Added Value ◽  
Chemical Transport Model ◽  
Geo Satellite ◽  
Sky Conditions

Abstract. Ozone is a tropospheric pollutant and plays a key role in determining the air quality that affects human wellbeing. In this study, we compare the capability of two hypothetical grating spectrometers onboard a geostationary (GEO) satellite to sense ozone in the lowermost troposphere (surface and the 0–1 km column). We consider one week during the Northern Hemisphere summer simulated by a chemical transport model, and use the two GEO instrument configurations to measure ozone concentration (1) in the thermal infrared (GEO TIR) and (2) in the thermal infrared and the visible (GEO TIR+VIS). These configurations are compared against each other, and also against an ozone reference state and a priori ozone information. In a first approximation, we assume clear sky conditions neglecting the influence of aerosols and clouds. A number of statistical tests are used to assess the performance of the two GEO configurations. We consider land and sea pixels and whether differences between the two in the performance are significant. Results show that the GEO TIR+VIS configuration provides a better representation of the ozone field both for surface ozone and the 0–1 km ozone column during the daytime especially over land.

scholarly journals Evaluation of potential sources of a priori ozone profiles for TEMPO tropospheric ozone retrievals

2018 ◽  
Vol 11 (6) ◽  
pp. 3457-3477 ◽  
Author(s):  
Matthew S. Johnson ◽  
Xiong Liu ◽  
Peter Zoogman ◽  
John Sullivan ◽  
Michael J. Newchurch ◽  
...  
Keyword(s):  
Air Quality ◽  
Tropospheric Ozone ◽  
Transport Model ◽  
A Priori ◽  
Retrieval Algorithm ◽  
Chemical Transport Model ◽  
Diurnal Variability ◽  
Potential Sources ◽  
Tropospheric O3 ◽  
Lidar Observations

Abstract. Potential sources of a priori ozone (O3) profiles for use in Tropospheric Emissions: Monitoring of Pollution (TEMPO) satellite tropospheric O3 retrievals are evaluated with observations from multiple Tropospheric Ozone Lidar Network (TOLNet) systems in North America. An O3 profile climatology (tropopause-based O3 climatology (TB-Clim), currently proposed for use in the TEMPO O3 retrieval algorithm) derived from ozonesonde observations and O3 profiles from three separate models (operational Goddard Earth Observing System (GEOS-5) Forward Processing (FP) product, reanalysis product from Modern-era Retrospective Analysis for Research and Applications version 2 (MERRA2), and the GEOS-Chem chemical transport model (CTM)) were: (1) evaluated with TOLNet measurements on various temporal scales (seasonally, daily, and hourly) and (2) implemented as a priori information in theoretical TEMPO tropospheric O3 retrievals in order to determine how each a priori impacts the accuracy of retrieved tropospheric (0–10 km) and lowermost tropospheric (LMT, 0–2 km) O3 columns. We found that all sources of a priori O3 profiles evaluated in this study generally reproduced the vertical structure of summer-averaged observations. However, larger differences between the a priori profiles and lidar observations were calculated when evaluating inter-daily and diurnal variability of tropospheric O3. The TB-Clim O3 profile climatology was unable to replicate observed inter-daily and diurnal variability of O3 while model products, in particular GEOS-Chem simulations, displayed more skill in reproducing these features. Due to the ability of models, primarily the CTM used in this study, on average to capture the inter-daily and diurnal variability of tropospheric and LMT O3 columns, using a priori profiles from CTM simulations resulted in TEMPO retrievals with the best statistical comparison with lidar observations. Furthermore, important from an air quality perspective, when high LMT O3 values were observed, using CTM a priori profiles resulted in TEMPO LMT O3 retrievals with the least bias. The application of near-real-time (non-climatological) hourly and daily model predictions as the a priori profile in TEMPO O3 retrievals will be best suited when applying this data to study air quality or event-based processes as the standard retrieval algorithm will still need to use a climatology product. Follow-on studies to this work are currently being conducted to investigate the application of different CTM-predicted O3 climatology products in the standard TEMPO retrieval algorithm. Finally, similar methods to those used in this study can be easily applied by TEMPO data users to recalculate tropospheric O3 profiles provided from the standard retrieval using a different source of a priori.

scholarly journals Validation of satellite formaldehyde (HCHO) retrievals using observations from 12 aircraft campaigns

2020 ◽  
Author(s):  
Lei Zhu ◽  
Gonzalo González Abad ◽  
Caroline R. Nowlan ◽  
Christopher Chan Miller ◽  
Kelly Chance ◽  
...  
Keyword(s):  
Transport Model ◽  
A Priori ◽  
Chemical Transport Model ◽  
Shape Factors ◽  
Atmospheric Lifetime ◽  
Volatile Organic ◽  
Satellite Sensors ◽  
Systematic Biases ◽  
In Situ Observations

Abstract. Formaldehyde (HCHO) has been measured from space for more than two decades. Owing to its short atmospheric lifetime, satellite HCHO data are used widely as a proxy of volatile organic compounds (VOCs; please refer to Appendix A for abbreviations and acronyms), providing constraints on underlying emissions and chemistry. However, satellite HCHO products from different satellite sensors using different algorithms have received little validation so far. The accuracy and consistency of HCHO retrievals remain largely unclear. Here we develop a global validation platform for satellite HCHO retrievals using in situ observations from 12 aircraft campaigns with a chemical transport model (GEOS-Chem) as the intercomparison method. Application to the NASA operational OMI HCHO product indicates slight biases (−30.9 % to +16.0 %) under high-HCHO conditions partially caused by a priori shape factors used in the retrievals, while high biases (+113.9 % to +194.6 %) under low-HCHO conditions due mainly to slant column fitting and radiance reference sector correction. By providing quick assessment to systematic biases in satellite products over large domains, the platform facilitates, in an iterative process, optimization of retrieval settings and the minimization of retrieval biases. It is also complementary to localized validation efforts based on ground observations and aircraft spirals.

scholarly journals Application of a Fusion Method for Gas and Particle Air Pollutants between Observational Data and Chemical Transport Model Simulations Over the Contiguous United States for 2005–2014

2019 ◽  
Vol 16 (18) ◽  
pp. 3314
Author(s):  
Niru Senthilkumar ◽  
Mark Gilfether ◽  
Francesca Metcalf ◽  
Armistead G. Russell ◽  
James A. Mulholland ◽  
...  
Keyword(s):  
United States ◽  
Air Quality ◽  
Spatial Variation ◽  
Temporal Variation ◽  
Observational Data ◽  
Transport Model ◽  
Chemical Transport ◽  
Daily Basis ◽  
Quality Data ◽  
Chemical Transport Model

Accurate spatiotemporal air quality data are critical for use in assessment of regulatory effectiveness and for exposure assessment in health studies. A number of data fusion methods have been developed to combine observational data and chemical transport model (CTM) results. Our approach focuses on preserving the temporal variation provided by observational data while deriving the spatial variation from the community multiscale air quality (CMAQ) simulations, a type of CTM. Here we show the results of fusing regulatory monitoring observational data with 12 km resolution CTM simulation results for 12 pollutants (CO, NOx, NO2, SO2, O3, PM2.5, PM10, NO3−, NH4+, EC, OC, SO42−) over the contiguous United States on a daily basis for a period of ten years (2005–2014). An annual mean regression between the CTM simulations and observational data is used to estimate the average spatial fields, and spatial interpolation of observations normalized by predicted annual average is used to provide the daily variation. Results match the temporal variation well (R2 values ranging from 0.84–0.98 across pollutants) and the spatial variation less well (R2 values 0.42–0.94). Ten-fold cross validation shows normalized root mean square error values of 60% or less and spatiotemporal R2 values of 0.4 or more for all pollutants except SO2.

scholarly journals The added value of a visible channel to a geostationary thermal infrared instrument to monitor ozone for air quality

2014 ◽  
Vol 7 (7) ◽  
pp. 2185-2201 ◽  
Author(s):  
E. Hache ◽  
J.-L. Attié ◽  
C. Tourneur ◽  
P. Ricaud ◽  
L. Coret ◽  
...  
Keyword(s):  
Air Quality ◽  
Transport Model ◽  
Statistical Tests ◽  
Surface Ozone ◽  
A Priori ◽  
Thermal Infrared ◽  
Added Value ◽  
Chemical Transport Model ◽  
Geo Satellite ◽  
Sky Conditions

Abstract. Ozone is a tropospheric pollutant and plays a key role in determining the air quality that affects human wellbeing. In this study, we compare the capability of two hypothetical grating spectrometers onboard a geostationary (GEO) satellite to sense ozone in the lowermost troposphere (surface and the 0–1 km column). We consider 1 week during the Northern Hemisphere summer simulated by a chemical transport model, and use the two GEO instrument configurations to measure ozone concentration (1) in the thermal infrared (GEO TIR) and (2) in the thermal infrared and the visible (GEO TIR+VIS). These configurations are compared against each other, and also against an ozone reference state and a priori ozone information. In a first approximation, we assume clear sky conditions neglecting the influence of aerosols and clouds. A number of statistical tests are used to assess the performance of the two GEO configurations. We consider land and sea pixels and whether differences between the two in the performance are significant. Results show that the GEO TIR+VIS configuration provides a better representation of the ozone field both for surface ozone and the 0–1 km ozone column during the daytime especially over land.

scholarly journals Validation of satellite formaldehyde (HCHO) retrievals using observations from 12 aircraft campaigns

2020 ◽  
Vol 20 (20) ◽  
pp. 12329-12345 ◽  
Author(s):  
Lei Zhu ◽  
Gonzalo González Abad ◽  
Caroline R. Nowlan ◽  
Christopher Chan Miller ◽  
Kelly Chance ◽  
...  
Keyword(s):  
Transport Model ◽  
A Priori ◽  
Chemical Transport Model ◽  
Atmospheric Lifetime ◽  
Volatile Organic ◽  
Main Driver ◽  
Satellite Sensors ◽  
Systematic Biases ◽  
In Situ Observations

Abstract. Formaldehyde (HCHO) has been measured from space for more than 2 decades. Owing to its short atmospheric lifetime, satellite HCHO data are used widely as a proxy of volatile organic compounds (VOCs; please refer to Appendix A for abbreviations and acronyms), providing constraints on underlying emissions and chemistry. However, satellite HCHO products from different satellite sensors using different algorithms have received little validation so far. The accuracy and consistency of HCHO retrievals remain largely unclear. Here we develop a validation platform for satellite HCHO retrievals using in situ observations from 12 aircraft campaigns with a chemical transport model (GEOS-Chem) as the intercomparison method. Application to the NASA operational OMI HCHO product indicates negative biases (−44.5 % to −21.7 %) under high-HCHO conditions, while it indicates high biases (+66.1 % to +112.1 %) under low-HCHO conditions. Under both conditions, HCHO a priori vertical profiles are likely not the main driver of the biases. By providing quick assessment of systematic biases in satellite products over large domains, the platform facilitates, in an iterative process, optimization of retrieval settings and the minimization of retrieval biases. It is also complementary to localized validation efforts based on ground observations and aircraft spirals.

scholarly journals Global and regional emissions estimates for N<sub>2</sub>O

2014 ◽  
Vol 14 (9) ◽  
pp. 4617-4641 ◽  
Author(s):  
E. Saikawa ◽  
R. G. Prinn ◽  
E. Dlugokencky ◽  
K. Ishijima ◽  
G. S. Dutton ◽  
...  
Keyword(s):  
Agricultural Sector ◽  
Transport Model ◽  
A Priori ◽  
Three Dimensional ◽  
American Samoa ◽  
N2o Emissions ◽  
Chemical Transport Model ◽  
Chemical Tracers ◽  
Multiple Networks

Abstract. We present a comprehensive estimate of nitrous oxide (N2O) emissions using observations and models from 1995 to 2008. High-frequency records of tropospheric N2O are available from measurements at Cape Grim, Tasmania; Cape Matatula, American Samoa; Ragged Point, Barbados; Mace Head, Ireland; and at Trinidad Head, California using the Advanced Global Atmospheric Gases Experiment (AGAGE) instrumentation and calibrations. The Global Monitoring Division of the National Oceanic and Atmospheric Administration/Earth System Research Laboratory (NOAA/ESRL) has also collected discrete air samples in flasks and in situ measurements from remote sites across the globe and analyzed them for a suite of species including N2O. In addition to these major networks, we include in situ and aircraft measurements from the National Institute of Environmental Studies (NIES) and flask measurements from the Tohoku University and Commonwealth Scientific and Industrial Research Organization (CSIRO) networks. All measurements show increasing atmospheric mole fractions of N2O, with a varying growth rate of 0.1–0.7% per year, resulting in a 7.4% increase in the background atmospheric mole fraction between 1979 and 2011. Using existing emission inventories as well as bottom-up process modeling results, we first create globally gridded a priori N2O emissions over the 37 years since 1975. We then use the three-dimensional chemical transport model, Model for Ozone and Related Chemical Tracers version 4 (MOZART v4), and a Bayesian inverse method to estimate global as well as regional annual emissions for five source sectors from 13 regions in the world. This is the first time that all of these measurements from multiple networks have been combined to determine emissions. Our inversion indicates that global and regional N2O emissions have an increasing trend between 1995 and 2008. Despite large uncertainties, a significant increase is seen from the Asian agricultural sector in recent years, most likely due to an increase in the use of nitrogenous fertilizers, as has been suggested by previous studies.

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