Validation of OMI tropospheric NO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; column data using MAX-DOAS measurements deep inside the North China Plain in June 2006: Mount Tai Experiment 2006

Irie, Hitoshi; Kanaya, Yugo; Akimoto, Hajime; Tanimoto, Hiroshi; Wang, Z.; Gleason, J. F.; Bucsela, E. J.

doi:10.5194/acp-8-6577-2008

Cited by 107 publications

(95 citation statements)

References 25 publications

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“…These results are qualitatively similar to those obtained in previous validation exercises (e.g. Brinksma et al, 2008;Celarier et al, 2008;Irie et al, 2008). However, in our study a much longer comparison dataset is available (∼4 yr) and averaging can be performed, in order to limit the influence of temporal and spatial sensitivity differences on the comparison.…”

supporting

confidence: 79%

Operational total and tropospheric NO2 column retrieval for GOME-2

et al. 2011

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Abstract. This paper presents the algorithm for the operational near real time retrieval of total and tropospheric NO 2 columns from the Global Ozone Monitoring Experiment (GOME-2). The retrieval is performed with the GOME Data Processor (GDP) version 4.4 as used by the EUMETSAT Satellite Application Facility on Ozone and Atmospheric Chemistry Monitoring (O3M-SAF). The differential optical absorption spectroscopy (DOAS) method is used to determine NO 2 slant columns from GOME-2 (ir)radiance data in the 425-450 nm range. Initial total NO 2 columns are computed using stratospheric air mass factors, and GOME-2 derived cloud properties are used to calculate the air mass factors for scenarios in the presence of clouds. To obtain the stratospheric NO 2 component, a spatial filtering approach is used, which is shown to be an improvement on the Pacific reference sector method. Tropospheric air mass factors are computed using monthly averaged NO 2 profiles from the MOZART-2 chemistry transport model. An error analysis shows that the random error in the GOME-2 NO 2 slant columns is approximately 0.45 × 10 15 molec cm −2 . As a result of the improved quartz diffuser plate used in the GOME-2 instrument, the systematic error in the slant columns is strongly reduced compared to GOME/ERS-2. The estimated uncertainty in the GOME-2 tropospheric NO 2 column for polluted conditions ranges from 40 to 80 %. An end-toend ground-based validation approach for the GOME-2 NO 2 columns is illustrated based on multi-axis MAXDOAS measurements at the Observatoire de Haute Provence (OHP). The GOME-2 stratospheric NO 2 columns are found to be in Correspondence to: P. Valks (pieter.valks@dlr.de) good overall agreement with coincident ground-based measurements at OHP. A time series of the MAXDOAS and the GOME-2 tropospheric NO 2 columns shows that pollution episodes at OHP are well captured by GOME-2. Monthly mean tropospheric columns are in very good agreement, with differences generally within 0.5 × 10 15 molec cm −2 .

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confidence: 79%

Operational total and tropospheric NO2 column retrieval for GOME-2

et al. 2011

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“…The NO 2 slant column densities are converted to tropospheric vertical column density by using the AMF calculated with measured aerosol information and the vertical profile of NO 2 and a non-linear iterative inversion scheme . Additional details on the MAX-DOAS measurements, calibration, and retrieval procedures can be found in Irie et al (2008) and references therein. Overall errors in the tropospheric NO 2 vertical columns are < 14 %.…”

Section: Ground-based Max-doasmentioning

confidence: 99%

“…Tropospheric NO 2 column retrievals from satellites have been evaluated with in situ NO 2 profile measurements from aircraft (Heland et al, 2002;Martin et al, 2006;Boersma et al, 2008a;Bucsela et al, 2008Bucsela et al, , 2013Celarier et al, 2008;Hains et al, 2010), NO 2 column measurements from groundbased and airborne instruments Celarier et al, 2008;Brinksma et al, 2008;Kramer et al, 2008;Irie et al, 2008Irie et al, , 2012Wenig et al, 2008;Oetjen et al, 2013), in situ surface measurements (Schaub et al, 2006;Blond et al, 2007;Boersma et al, 2009;Lamsal et al, 2008Lamsal et al, , 2010, and a bottom-up NO x emission inventory (Lamsal et al, 2010). Aircraft offer precise in situ measurements within vertical spirals covering a spatial domain over a satellite field of view, but these are generally campaign-based experiments spanning only a few days to weeks and are limited by the need to extrapolate below the lowest measurement altitude (e.g.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of OMI operational standard NO2 column retrievals using in situ and surface-based NO2 observations

et al. 2014

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Abstract. We assess the standard operational nitrogen dioxide (NO 2 ) data product (OMNO2, version 2.1) retrieved from the Ozone Monitoring Instrument (OMI) onboard NASA's Aura satellite using a combination of aircraft and surface in situ measurements as well as ground-based column measurements at several locations and a bottom-up NO x emission inventory over the continental US. Despite considerable sampling differences, NO 2 vertical column densities from OMI are modestly correlated (r = 0.3-0.8) with in situ measurements of tropospheric NO 2 from aircraft, ground-based observations of NO 2 columns from MAX-DOAS and Pandora instruments, in situ surface NO 2 measurements from photolytic converter instruments, and a bottom-up NO x emission inventory. Overall, OMI retrievals tend to be lower in urban regions and higher in remote areas, but generally agree with other measurements to within ± 20 %. No consistent seasonal bias is evident. Contrasting results between different data sets reveal complexities behind NO 2 validation. Since validation data sets are scarce and are limited in space and time, validation of the global product is still limited in scope by spatial and temporal coverage and retrieval conditions. Monthly mean vertical NO 2 profile shapes from the Global Modeling Initiative (GMI) chemistry-transport model (CTM) used in the OMI retrievals are highly consistent with in situ aircraft measurements, but these measured profiles exhibit considerable day-to-day variation, affecting the retrieved daily NO 2 columns by up to 40 %. This assessment of OMI tropospheric NO 2 columns, together with the comparison of OMI-retrieved and model-simulated NO 2 columns, could offer diagnostic evaluation of the model.

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“…The spatial (<10 km) and temporal (hourly) requirements for air quality measurements have largely been determined by the desire to resolve the processes affecting the emissions, lifetime and transport of tropospheric NO 2 (e.g., Beirle et al, 2011;Valin et al, 2011bValin et al, , 2013de Foy et al, 2015) because of its fundamental role in the formation of tropospheric O 3 and particulate matter. There have been a variety of approaches for validating NO 2 products retrieved from LEO platforms (e.g., Bucsela et al, 2008Bucsela et al, , 2013Irie et al, 2008;Boersma et al, 2009;Lamsal et al, 2010;Russell et al, 2011;Travis et al, 2016). These works have identified and addressed gaps in the understanding of NO 2 retrievals, including methods for subtracting stratospheric NO 2 column contributions, a priori vertical profile deviations between urban and rural settings, and surface reflectance variations (e.g., Zhou et al, 2010;Russell et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

The Dawn of Geostationary Air Quality Monitoring: Case Studies From Seoul and Los Angeles

Judd

Al-Saadi

Valin

et al. 2018

Front. Environ. Sci.

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With the near-future launch of geostationary Earth orbit (GEO) pollution monitoring satellite instruments over North America, East Asia, and Europe, the air quality community is preparing for an integrated global atmospheric composition observing system at unprecedented spatial and temporal resolutions. One of the ways that NASA has supported this community preparation is through demonstration of future space-borne capabilities using the Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) airborne instrument. This paper integrates repeated high-resolution NO 2 maps from GeoTASO, ground-based Pandora spectrometers data, and low Earth orbit (LEO) measurements from the Ozone Mapping and Profiler Suite, for case studies over two regions: the Seoul Metropolitan Area, South Korea on June 9th, 2016 and Los Angeles Basin, California on June 27th, 2017. This dataset provides a unique opportunity to illustrate how GEO air quality monitoring platforms and ground-based remote sensing networks will close the current spatiotemporal observation gap. In both areas, the earliest morning maps exhibit spatial patterns similar to emission source areas (e.g., urbanized valleys, roadways, major airports) and change later in the day due to boundary layer dynamics, transport, and/or chemistry. On June 9th, 2016, GeoTASO observes NO 2 accumulating within the Seoul Metropolitan Area, while NO 2 peaks in the morning and decreases throughout the afternoon in the Los Angeles Basin on June 27th, 2017. The nominal resolution of GeoTASO is finer than will be obtained from GEO platforms, but when NO 2 data over Los Angeles are up-scaled to the expected resolution of TEMPO, spatial features discussed are preserved. Pandora instruments installed in both metropolitan areas capture the diurnal patterns observed by GeoTASO, continuously and over longer time periods and will play a critical role in validation of the next generation of satellite measurements. These case studies demonstrate the diversity of diurnal patterns in two urbanized regions and associates them with meteorology Judd et al.Dawn of Geostationary Air Quality Monitoring or anthropogenic patterns, hinting at the spatial and temporal richness of the upcoming GEO observations. LEO measurements, despite their inability to capture the diurnal patterns at fine spatial resolution, will be essential for intercalibrating the GEO radiances and cross-validating the GEO retrievals in an integrated global observing system.

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Validation of OMI tropospheric NO<sub>2</sub> column data using MAX-DOAS measurements deep inside the North China Plain in June 2006: Mount Tai Experiment 2006

Cited by 107 publications

References 25 publications

Operational total and tropospheric NO<sub>2</sub> column retrieval for GOME-2

Operational total and tropospheric NO<sub>2</sub> column retrieval for GOME-2

Evaluation of OMI operational standard NO<sub>2</sub> column retrievals using in situ and surface-based NO<sub>2</sub> observations

The Dawn of Geostationary Air Quality Monitoring: Case Studies From Seoul and Los Angeles

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Validation of OMI tropospheric NO&lt;sub&gt;2&lt;/sub&gt; column data using MAX-DOAS measurements deep inside the North China Plain in June 2006: Mount Tai Experiment 2006

Cited by 107 publications

References 25 publications

Operational total and tropospheric NO&lt;sub&gt;2&lt;/sub&gt; column retrieval for GOME-2

Operational total and tropospheric NO&lt;sub&gt;2&lt;/sub&gt; column retrieval for GOME-2

Evaluation of OMI operational standard NO&lt;sub&gt;2&lt;/sub&gt; column retrievals using in situ and surface-based NO&lt;sub&gt;2&lt;/sub&gt; observations

The Dawn of Geostationary Air Quality Monitoring: Case Studies From Seoul and Los Angeles

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Validation of OMI tropospheric NO<sub>2</sub> column data using MAX-DOAS measurements deep inside the North China Plain in June 2006: Mount Tai Experiment 2006

Operational total and tropospheric NO<sub>2</sub> column retrieval for GOME-2

Operational total and tropospheric NO<sub>2</sub> column retrieval for GOME-2

Evaluation of OMI operational standard NO<sub>2</sub> column retrievals using in situ and surface-based NO<sub>2</sub> observations