Air Mass Factor Research Articles

Effects of a priori profile shape assumptions on comparisons between satellite NO<sub>2</sub> columns and model simulations

Abstract. A critical step in satellite retrievals of trace gas columns is the calculation of the air mass factor (AMF) used to convert observed slant columns to vertical columns. This calculation requires a priori information on the shape of the vertical profile. As a result, comparisons between satellite-retrieved and model-simulated column abundances are influenced by the a priori profile shape. We examine how differences between the shape of the simulated and a priori profiles can impact the interpretation of satellite retrievals by performing an adjoint-based four-dimensional variational (4D-Var) assimilation of synthetic NO2 observations for constraining NOx emissions. We use the GEOS-Chem adjoint model to perform assimilations using a variety of AMFs to examine how a posteriori emission estimates are affected if the AMF is calculated using an a priori shape factor that is inconsistent with the simulated profile. In these tests, an inconsistent a priori shape factor increased root mean square errors in a posteriori emission estimates by up to 30 % for realistic conditions over polluted regions. As the difference between the simulated profile shape and the a priori profile shape increases, so do the corresponding assimilated emission errors. This reveals the importance of using simulated profile information for AMF calculations when comparing that simulated output to satellite-retrieved columns.

Comparison and Validation of TROPOMI and OMI NO2 Observations over China

The new-generation sensor TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel 5 precursor (S5P) satellite is promising for monitoring air pollutants with greater spatial resolution, especially for China, which suffers from severe pollution. As tropospheric NO2 vertical column densities (VCDs) from TROPOMI have become available since February 2018, this study presents the comparisons of NO2 data measured by TROPOMI and its predecessor Ozone Monitoring Instrument (OMI) over China, together with validation against ground Multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements. At the nationwide scale, we used two different filters performed for the TROPOMI data (named TROPOMI50 and TROPOMI75), and the TROPOMI50 yielded larger values than TROPOMI75. The TROPOMI NO2 datasets from different filters show consistent spatial patterns with OMI, and the correlation coefficient values were both above 0.93. However, linear regression indicates that NO2 loadings in TROPOMI is about 2/3 to 4/5 of those in OMI, which is presumably due to a different cloud mask and uncertainties of air mass factors. The absolute difference is prominent over the high pollution areas such as Jing-Jin-Ji region and during winter and autumn, exceeding 0.6 × 1016 molecules cm−2 (molec cm−2). However, the NO2 concentrations retrieved from TROPOMI50 in the southern China may be somewhat higher than OMI. When it comes to the local-scale Jing-Jin-Ji hotspot, the analysis focuses on a comparison to TROPOMI75. TROPOMI manifests high quality and exhibits a significantly better performance of representing spatial variability. In contrast, OMI shows fewer effective pixels and does a poor job of capturing local details due to its row anomaly and low resolution. The absolute difference between two datasets shows the same seasonal behavior with NO2 variation, which is most striking in the winter (0.31 × 1016 molec cm−2) and is lowest in the summer (0.05 × 1016 molec cm−2). Furthermore, the ground MAX-DOAS instrument in Xianghe station, the representative site in Jing-Jin-Ji, is used to assess the skill of satellite retrievals. It turns out that both OMI and TROPOMI underestimate the observations, ranging from 30% to 50%, with OMI being less biased. In spite of the negative drift, the temporal structures of changes derived from OMI and TROPOMI closely match the ground-based records, since the correlation coefficients are above 0.8 and 0.95 for daily and monthly scales, respectively. Overall, TROPOMI NO2 retrievals are better suited for applications in China as well as the Jing-Jin-Ji hotspot due to its higher spatial resolution, although some improvements are also needed in the near future.

Investigation of O 4 Air Mass Factor Sensitivity to Aerosol Peak Height Using UV-VIS Hyperspectral Synthetic Radiance in Various Measurement Conditions

Investigation of O 4 Air Mass Factor Sensitivity to Aerosol Peak Height Using UV-VIS Hyperspectral Synthetic Radiance in Various Measurement Conditions

Investigation of Aerosol Peak Height Effect on PBL and Volcanic Air Mass Factors for SO2 Column Retrieval from Space-Borne Hyperspectral UV Sensors

We investigate the effects of aerosol peak height (APH) and various parameters on the air mass factor (AMF) for SO2 retrieval. Increasing aerosol optical depth (AOD) leads to multiple scattering within the planetary boundary layer (PBL) and an increase in PBL SO2 AMF. However, under high AOD conditions, aerosol shielding effects dominate, which causes the PBL SO2 AMF to decrease with increasing AOD. The height of the SO2 layer and the APH are found to significantly influence the PBL SO2 AMF under high AOD conditions. When the SO2 and aerosol layers are of the same height, aerosol multiple scattering occurs dominantly within the PBL, which leads to an increase in the PBL SO2 AMF. When the APH is greater than the SO2 layer height, aerosol shielding effects dominate, which decreases the PBL SO2 AMF. When the SO2 and aerosol layers are of the same height under low AOD and solar zenith angle (SZA) conditions, increased surface reflectance is found to significantly increase the PBL SO2 AMF. However, high AOD dominates the surface reflectance contribution to PBL SO2 AMF. Under high SZA conditions, Rayleigh scattering contributes to a reduction in the light path length and PBL SO2 AMF. For volcanic SO2 AMF, high SZA enhances the light path length within the volcanic SO2 layer, as well as the volcanic SO2 AMF, because of the negligible photon loss by Rayleigh scattering at high altitudes. High aerosol loading and an APH that is greater than the SO2 peak height lead to aerosol shielding effects, which reduce the volcanic SO2 AMF. The SO2 AMF errors are also quantified as a function of uncertainty in the input data of AOD, APH, and surface reflectance. The SO2 AMF sensitivities and error analysis provided here can be used to develop effective error reduction strategies for satellite-based SO2 retrievals.

First observation of tropospheric nitrogen dioxide from the Environmental Trace Gases Monitoring Instrument onboard the GaoFen-5 satellite

The Environmental Trace Gases Monitoring Instrument (EMI) is the first Chinese satellite-borne UV–Vis spectrometer aiming to measure the distribution of atmospheric trace gases on a global scale. The EMI instrument onboard the GaoFen-5 satellite was launched on 9 May 2018. In this paper, we present the tropospheric nitrogen dioxide (NO2) vertical column density (VCD) retrieval algorithm dedicated to EMI measurement. We report the first successful retrieval of tropospheric NO2 VCD from the EMI instrument. Our retrieval improved the original EMI NO2 prototype algorithm by modifying the settings of the spectral fit and air mass factor calculations to account for the on-orbit instrumental performance changes. The retrieved EMI NO2 VCDs generally show good spatiotemporal agreement with the satellite-borne Ozone Monitoring Instrument and TROPOspheric Monitoring Instrument (correlation coefficient R of ~0.9, bias < 50%). A comparison with ground-based MAX-DOAS (Multi-Axis Differential Optical Absorption Spectroscopy) observations also shows good correlation with an R of 0.82. The results indicate that the EMI NO2 retrieval algorithm derives reliable and precise results, and this algorithm can feasibly produce stable operational products that can contribute to global air pollution monitoring.

Identification of ambient SO2 sources in industrial areas in the lower Athabasca oil sands region of Alberta, Canada

Abstract With ongoing interest in sulfur dioxide (SO2) levels approaching a new Canadian Ambient Air Quality Standards (CAAQS) in the Athabasca Oil Sands Region (AOSR), an exploratory study was undertaken to identify potential local emission sources that influence ambient SO2 concentrations. The approach used in this study was to apply the receptor model positive matrix factorization (PMF) using ambient measurement data of PM10 components (metals and ion species), gaseous pollutants and volatile organic compound (VOC) species from two industrial air monitoring stations (i.e., AMS13-Fort McKay South and AMS15-CNRL Horizon) over a 3-year period (2015–2017). Results were then used to examine receptor model-defined sources for which SO2 was a statistically strong predictor. Eleven sources were tentatively identified: a mixed oil sands, stack emissions & fugitive dust factor, a haul road dust factor, an aged air mass & biogenic factor, secondary inorganic aerosol, a W–Co–Bi–SO2-rich factor, oil sands mixed fugitives and a mixed industrial and off-road traffic factor. No significant variation was observed in inferred contributions of major SO2-related sources among the two air monitoring stations investigated. These preliminary findings offer insights about different source emissions that influence ambient SO2 concentrations in the AOSR. We suggest there may be potential application of this approach to other settings where similar datasets are available and there is interest in understanding sources affecting ambient SO2 levels.

An improved air mass factor calculation for nitrogen dioxide measurements from the Global Ozone Monitoring Experiment-2 (GOME-2)

Abstract. An improved tropospheric nitrogen dioxide (NO2) retrieval algorithm from the Global Ozone Monitoring Experiment-2 (GOME-2) instrument based on air mass factor (AMF) calculations performed with more realistic model parameters is presented. The viewing angle dependency of surface albedo is taken into account by improving the GOME-2 Lambertian-equivalent reflectivity (LER) climatology with a directionally dependent LER (DLER) dataset over land and an ocean surface albedo parameterisation over water. A priori NO2 profiles with higher spatial and temporal resolutions are obtained from the IFS (CB05BASCOE) chemistry transport model based on recent emission inventories. A more realistic cloud treatment is provided by a clouds-as-layers (CAL) approach, which treats the clouds as uniform layers of water droplets, instead of the current clouds-as-reflecting-boundaries (CRB) model, which assumes that the clouds are Lambertian reflectors. On average, improvements in the AMF calculation affect the tropospheric NO2 columns by ±15 % in winter and ±5 % in summer over largely polluted regions. In addition, the impact of aerosols on our tropospheric NO2 retrieval is investigated by comparing the concurrent retrievals based on ground-based aerosol measurements (explicit aerosol correction) and the aerosol-induced cloud parameters (implicit aerosol correction). Compared with the implicit aerosol correction utilising the CRB cloud parameters, the use of the CAL approach reduces the AMF errors by more than 10 %. Finally, to evaluate the improved GOME-2 tropospheric NO2 columns, a validation is performed using ground-based multi-axis differential optical absorption spectroscopy (MAXDOAS) measurements at different BIRA-IASB stations. At the suburban Xianghe station, the improved tropospheric NO2 dataset shows better agreement with coincident ground-based measurements with a correlation coefficient of 0.94.

Impact of natural gas production on nitrogen dioxide and sulphur dioxide over Northeast British Columbia, Canada

Northeast British Columbia (BC) Canada, is a region in which natural gas production has undergone rapid development since 2007. We used nitrogen dioxide (NO2) and sulphur dioxide (SO2) data products of the Ozone Monitoring Instrument (OMI) to assess the impact of natural gas development activity on air quality in this region from 2005 to 2018. We noticed that values of both pollutants were elevated in the immediate vicinity of large emission sources within the Montney formation and Horn River Basin – regions, which have experienced an increase in unconventional natural gas activities. Places with elevated NO2 Vertical Column Densities (VCDs) are Fort St. John, Taylor, and Dawson Creek located in the Montney formation, and higher SO2 VCDs are found near the Fort Nelson gas plant situated in the Horn River and Liard Basin areas. Although all the OMI data products consistently reported relatively high NO2 VCDs in the same areas, VCD values vary substantially with data products largely due to differences in Air Mass Factor (AMF) calculations. The rate of increase in NO2 VCDs and mass between 2005 and 2018 in the Dawson Creek area was assessed at 2.34% yr−1 and 4.32% yr−1, respectively, and these rates of change are statistically significant. Although we obtained an overall increasing trend for NO2 in Northeast BC, we also noticed a decreasing trend in the period of 2011–2013, which may be attributed, in part, to compliance and enforcement of regulations concerning flaring activities from oil and gas activities in Northeast BC, or due to less development activities. From our analysis, we suggest that the current air quality monitoring network in Northeast BC should be expanded to capture the spatial distribution of SO2 by deploying one additional station near Fort Nelson equipped with meteorology and SO2 monitoring systems.

Lightning NOx Production in the Tropics as Determined Using OMI NO2 Retrievals and WWLLN Stroke Data

AbstractNitrogen oxide (NOx) production by lightning in the tropics is estimated using tropospheric NOx amounts (LNOx*) over deep convective grid boxes derived from Ozone Monitoring Instrument (OMI) nitrogen dioxide (NO2) slant columns and detection‐efficiency–adjusted World Wide Lightning Location Network (WWLLN) flashes. The lightning NOx production efficiency (LNOx PE) in the tropics is determined for the austral and boreal summers of 2007 to 2011 by regressing regional mean daily values of LNOx* for individual seasons against daily flash totals during flash windows prior to the OMI overpass. LNOx PE is determined to be approximately two times larger over marine locations than over continental locations possibly because marine flashes are more energetic. Overall, the mean LNOx PE for the tropics is calculated to be 170 ± 100 mol per flash with values over the tropical Pacific (low flash rate region) being largest. The main contributors to uncertainties in PE are uncertainties in WWLLN flash detection efficiency, upper tropospheric NOx lifetime in the near field of convection, and air mass factor biases.

Evaluating the impact of spatial resolution on tropospheric NO2 column comparisons within urban areas using high-resolution airborne data.

NASA deployed the GeoTASO airborne UV-Visible spectrometer in May-June 2017 to produce high resolution (approximately 250 × 250 m) gapless NO2 datasets over the western shore of Lake Michigan and over the Los Angeles Basin. The results collected show that the airborne tropospheric vertical column retrievals compare well with ground-based Pandora spectrometer column NO2 observations (r2=0.91 and slope of 1.03). Apparent disagreements between the two measurements can be sensitive to the coincidence criteria and are often associated with large local variability, including rapid temporal changes and spatial heterogeneity that may be observed differently by the sunward viewing Pandora observations. The gapless mapping strategy executed during the 2017 GeoTASO flights provides data suitable for averaging to coarser areal resolutions to simulate satellite retrievals. As simulated satellite pixel area increases to values typical of TEMPO, TROPOMI, and OMI, the agreement with Pandora measurements degraded, particularly for the most polluted columns as localized large pollution enhancements observed by Pandora and GeoTASO are spatially averaged with nearby less-polluted locations within the larger area representative of the satellite spatial resolutions (aircraft-to-Pandora slope: TEMPO scale=0.88; TROPOMI scale=0.77; OMI scale=0.57). In these two regions, Pandora and TEMPO or TROPOMI have the potential to compare well at least up to pollution scales of 30×1015 molecules cm-2. Two publicly available OMI tropospheric NO2 retrievals are both found to be biased low with respect to these Pandora observations. However, the agreement improves when higher resolution a priori inputs are used for the tropospheric air mass factor calculation (NASA V3 Standard Product slope = 0.18 and Berkeley High Resolution Product slope=0.30). Overall, this work explores best practices for satellite validation strategies with Pandora direct-sun observations by showing the sensitivity to product spatial resolution and demonstrating how the high spatial resolution NO2 data retrieved from airborne spectrometers, such as GeoTASO, can be used with high temporal resolution ground-based column observations to evaluate the influence of spatial heterogeneity on validation results.

Explicit Aerosol Correction of OMI Formaldehyde Retrievals

Atmospheric aerosols are significant sources of uncertainty in air mass factor (AMF) calculations for trace gas retrievals using ultraviolet measurements from space. Current trace gas retrievals typically do not consider aerosols explicitly as cloud products partially account for aerosol effects. Here, we propose a new measurement‐based approach to correct for aerosols explicitly in the AMF calculation, apply it to Ozone Monitoring Instrument (OMI) formaldehyde (HCHO) retrievals and quantify the aerosol‐induced HCHO vertical column density difference for three aerosol types (smoke, dust, and sulfate) during 2006–2007. We use OMI aerosol retrievals for aerosol optical properties and vertical profiles to construct lookup tables of scattering weights as functions of geometry, surface pressure, surface albedo, and aerosol information. The average difference between the National Aeronautics and Space Administration operational OMI HCHO product (not considering aerosols) and the results obtained in this study on a global scale are 27%, 6%, and −0.3% for smoke, dust, and sulfate aerosols, respectively. The region with the largest aerosol effects is East China, where the explicit smoke aerosol correction enhances mean HCHO vertical column densities by 35%, with corrections to individual observations sometimes larger than 100%. The quantified aerosol effects are applicable under clear‐sky conditions. This study highlights the need to implement aerosol corrections in the AMF calculation for HCHO retrievals. This is particularly relevant in regions with high levels of pollution where aerosols interfere the most with formaldehyde satellite observations.

Lightning NO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; simulation over the contiguous US and its effects on satellite NO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; retrievals

Abstract. Lightning is an important NOx source representing ∼10 % of the global source of odd N and a much larger percentage in the upper troposphere. The poor understanding of spatial and temporal patterns of lightning contributes to a large uncertainty in understanding upper tropospheric chemistry. We implement a lightning parameterization using the product of convective available potential energy (CAPE) and convective precipitation rate (PR) coupled with the Kain–Fritsch convective scheme (KF/CAPE-PR) into the Weather Research and Forecasting-Chemistry (WRF-Chem) model. Compared to the cloud-top height (CTH) lightning parameterization combined with the Grell 3-D convective scheme (G3/CTH), we show that the switch of convective scheme improves the correlation of lightning flash density in the southeastern US from 0.30 to 0.67 when comparing against the Earth Networks Total Lightning Network; the switch of lightning parameterization contributes to the improvement of the correlation from 0.48 to 0.62 elsewhere in the US. The simulated NO2 profiles using the KF/CAPE-PR parameterization exhibit better agreement with aircraft observations in the middle and upper troposphere. Using a lightning NOx production rate of 500 mol NO flash−1, the a priori NO2 profile generated by the simulation with the KF/CAPE-PR parameterization reduces the air mass factor for NO2 retrievals by 16 % on average in the southeastern US in the late spring and early summer compared to simulations using the G3/CTH parameterization. This causes an average change in NO2 vertical column density 4 times higher than the average uncertainty.

Underestimation of column NO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; amounts from the OMI satellite compared to diurnally varying ground-based retrievals from multiple PANDORA spectrometer instruments

Abstract. Retrievals of total column NO2 (TCNO2) are compared for 14 sites from the Ozone Measuring Instrument (OMI using OMNO2-NASA v3.1) on the AURA satellite and from multiple ground-based PANDORA spectrometer instruments making direct-sun measurements. While OMI accurately provides the daily global distribution of retrieved TCNO2, OMI almost always underestimates the local amount of TCNO2 by 50 % to 100 % in polluted areas, while occasionally the daily OMI value exceeds that measured by PANDORA at very clean sites. Compared to local ground-based or aircraft measurements, OMI cannot resolve spatially variable TCNO2 pollution within a city or urban areas, which makes it less suitable for air quality assessments related to human health. In addition to systematic underestimates in polluted areas, OMI's selected 13:30 Equator crossing time polar orbit causes it to miss the frequently much higher values of TCNO2 that occur before or after the OMI overpass time. Six discussed Northern Hemisphere PANDORA sites have multi-year data records (Busan, Seoul, Washington DC, Waterflow, New Mexico, Boulder, Colorado, and Mauna Loa), and one site in the Southern Hemisphere (Buenos Aires, Argentina). The first four of these sites and Buenos Aires frequently have high TCNO2 (TCNO2 &gt; 0.5 DU). Eight additional sites have shorter-term data records in the US and South Korea. One of these is a 1-year data record from a highly polluted site at City College in New York City with pollution levels comparable to Seoul, South Korea. OMI-estimated air mass factor, surface reflectivity, and the OMI 24 km × 13 km FOV (field of view) are three factors that can cause OMI to underestimate TCNO2. Because of the local inhomogeneity of NOx emissions, the large OMI FOV is the most likely factor for consistent underestimates when comparing OMI TCNO2 to retrievals from the small PANDORA effective FOV (measured in m2) calculated from the solar diameter of 0.5∘.

Enhanced Capabilities of TROPOMI NO2: Estimating NOX from North American Cities and Power Plants.

The TROPOspheric Monitoring Instrument (TROPOMI) is used to derive top-down NOX emissions for two large power plants and three megacities in North America. We first re-process the vertical column NO2 with an improved air mass factor to correct for a known systematic low bias in the operational retrieval near urban centers. For the two power plants, top-down NOX emissions agree to within 10% of the emissions reported by the power plants. We then derive top-down NOX emissions rates for New York City, Chicago, and Toronto, and compare them to projected bottom-up emissions inventories. In this analysis of 2018 NOX emissions, we find a +22% overestimate for New York City, a -21% underestimate in Toronto, and good agreement in Chicago in the projected bottom-up inventories when compared to the top-down emissions. Top-down NOX emissions also capture intraseasonal variability, such as the weekday versus weekend effect (emissions are +45% larger on weekdays versus weekends in Chicago). Finally, we demonstrate the enhanced capabilities of TROPOMI, which allow us to derive a NOX emissions rate for Chicago using a single overpass on July 7, 2018. The large signal-to-noise ratio of TROPOMI is well-suited for estimating NOX emissions from relatively small sources and for sub-seasonal timeframes.

Retrieval of total column and surface NO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; from Pandora zenith-sky measurements

Abstract. Pandora spectrometers can retrieve nitrogen dioxide (NO2) vertical column densities (VCDs) via two viewing geometries: direct Sun and zenith sky. The direct-Sun NO2 VCD measurements have high quality (0.1 DU accuracy in clear-sky conditions) and do not rely on any radiative transfer model to calculate air mass factors (AMFs); however, they are not available when the Sun is obscured by clouds. To perform NO2 measurements in cloudy conditions, a simple but robust NO2 retrieval algorithm is developed for Pandora zenith-sky measurements. This algorithm derives empirical zenith-sky NO2 AMFs from coincident high-quality direct-Sun NO2 observations. Moreover, the retrieved Pandora zenith-sky NO2 VCD data are converted to surface NO2 concentrations with a scaling algorithm that uses chemical-transport-model predictions and satellite measurements as inputs. NO2 VCDs and surface concentrations are retrieved from Pandora zenith-sky measurements made in Toronto, Canada, from 2015 to 2017. The retrieved Pandora zenith-sky NO2 data (VCD and surface concentration) show good agreement with both satellite and in situ measurements. The diurnal and seasonal variations of derived Pandora zenith-sky surface NO2 data also agree well with in situ measurements (diurnal difference within ±2 ppbv). Overall, this work shows that the new Pandora zenith-sky NO2 products have the potential to be used in various applications such as future satellite validation in moderate cloudy scenes and air quality monitoring.

An Observation‐Based Correction for Aerosol Effects on Nitrogen Dioxide Column Retrievals Using the Absorbing Aerosol Index

AbstractRetrievals of nitrogen dioxide (NO2) and other trace gases from satellite measurements rely on accurate calculation of an air mass factor (AMF) to account for the atmospheric light path. Scattering and absorption of sunlight by aerosols affects AMFs by impacting the sensitivity of satellite‐observed radiances to NO2 at different altitudes. Current NO2 retrievals either do not explicitly account for these effects or rely on aerosol information from an external source. Here we investigate a method for quantifying the impact of aerosols on NO2 AMFs using the Absorbing Aerosol Index, a satellite‐based measure of light absorption and scattering by aerosols. We find a robust relationship between the Absorbing Aerosol Index and the aerosol correction to NO2 AMFs using the GEOS‐Chem chemical transport model and the LIDORT radiative transfer model. This relationship enables estimating the impact of aerosols on AMFs using observed Absorbing Aerosol Index values, thus yielding an observation‐based aerosol correction for NO2 retrievals.

Vertical profile of aerosol extinction based on the measurement of O4 of multi-elevation angles with MAX-DOAS**Project supported by the National Natural Science Foundation of China (Grant Nos. 41875040, 41705012, and 1605013).

A method for aerosol extinction profile retrieval using ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) is studied, which is based on a look-up table algorithm. The algorithm uses parametric method to represent aerosol extinction profiles and simulate different atmospheric aerosol states through atmospheric radiation transfer model. Based on the method, aerosol extinction profile was obtained during six cloud-free days. The O4 differential air mass factor (dAMF) measured by MAX-DOAS is compared with the corresponding model results under different atmospheric conditions (). The aerosol optical thickness, aerosol weight factor in boundary layer, and the height of the boundary layer are obtained after the process of minimization and look-up table method. The retrieved aerosol extinction in boundary layer is compared with PM2.5 data measured by ground point instrument. The diurnal variation trends of the two methods are in good agreement. The correlation coefficients of the two methods are 0.71 when the aerosol optical thickness is smaller than 0.5. The results show that the look-up table method can obtain the aerosol state of the troposphere and provide validation for other instrument data.

Description of a formaldehyde retrieval algorithm for the Geostationary Environment Monitoring Spectrometer (GEMS)

Abstract. We describe a formaldehyde (HCHO) retrieval algorithm for the Geostationary Environment Monitoring Spectrometer (GEMS) that will be launched by the Korean Ministry of Environment in 2019. The algorithm comprises three steps: preprocesses, radiance fitting, and postprocesses. The preprocesses include a wavelength calibration, as well as interpolation and convolution of absorption cross sections; radiance fitting is conducted using a nonlinear fitting method referred to as basic optical absorption spectroscopy (BOAS); and postprocesses include air mass factor calculations and bias corrections. In this study, several sensitivity tests are conducted to examine the retrieval uncertainties using the GEMS HCHO algorithm. We evaluate the algorithm with the Ozone Monitoring Instrument (OMI) Level 1B irradiance/radiance data by comparing our retrieved HCHO column densities with OMI HCHO products of the Smithsonian Astrophysical Observatory (OMHCHO) and of the Quality Assurance for Essential Climate Variables project (OMI QA4ECV). Results show that OMI HCHO slant columns retrieved using the GEMS algorithm are in good agreement with OMHCHO, with correlation coefficients of 0.77–0.91 and regression slopes of 0.94–1.04 for March, June, September, and December 2005. Spatial distributions of HCHO slant columns from the GEMS algorithm are consistent with the OMI QA4ECV products, but relatively poorer correlation coefficients of 0.52–0.76 are found compared to those against the OMHCHO products. Also, we compare the satellite results with ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) observations. OMI GEMS HCHO vertical columns are 9 %–25 % lower than those of MAX-DOAS at Haute-Provence Observatory (OHP) in France, Bremen in Germany, and Xianghe in China. We find that the OMI GEMS retrievals have less bias than the OMHCHO and OMI QA4ECV products at OHP and Bremen in comparison with MAX-DOAS.

A scanning strategy optimized for signal-to-noise ratio for the Geostationary Carbon Cycle Observatory (GeoCarb) instrument

Abstract. The Geostationary Carbon Cycle Observatory (GeoCarb) will make measurements of greenhouse gases over the contiguous North and South American landmasses at daily temporal resolution. The extreme flexibility of observing from geostationary orbit induces an optimization problem, as operators must choose what to observe and when. The proposed scanning strategy for the GeoCarb mission tracks the sun's path from east to west and covers the entire area of interest in five coherent regions in the order of tropical South America east, tropical South America west, temperate South America, tropical North America, and temperate North America. We express this problem in terms of a geometric set cover problem, and use an incremental optimization (IO) algorithm to create a scanning strategy that minimizes expected error as a function of the signal-to-noise ratio (SNR). The IO algorithm used in this studied is a modified greedy algorithm that selects, incrementally at 5 min intervals, the scanning areas with the highest predicted SNR with respect to air mass factor (AF) and solar zenith angle (SZA) while also considering operational constraints to minimize overlapping scans and observations over water. As a proof of concept, two experiments are performed applying the IO algorithm offline to create an SNR-optimized strategy and compare it to the proposed strategy. The first experiment considers all landmasses with equal importance and the second experiment illustrates a temporary campaign mode that gives major urban areas greater importance weighting. Using a simple instrument model, we found that there is a significant performance increase with respect to overall predicted error when comparing the algorithm-selected scanning strategies to the proposed scanning strategy.

Effects of spatiotemporal O4 column densities and temperature-dependent O4 absorption cross-section on an aerosol effective height retrieval algorithm using the O4 air mass factor from the ozone monitoring instrument

In this present study, an aerosol effective height (AEH) retrieval algorithm has been developed using the O4 air mass factor (AMF) at 477 nm from the hyperspectral Ozone Monitoring Instrument (OMI). We investigated the magnitude of change in topographical and seasonal O4 vertical column density (VCD) in Northeast Asia and evaluated its effect on AEH retrieval accuracy using our AEH retrieval algorithm. In addition, the effect of a temperature-dependent cross-section for O4 (TDCS) on Look Up Table (LUT)-based AEH retrieval accuracy was quantified. A comparison between the retrieved AEH and those from the NIES lidar network for the period from January 2005 to June 2009, applying both the TDCS and the seasonal and topographical O4 VCDs, resulted in a root mean square error (RMSE) of 0.44 km for both smoke and dust aerosols. However, when both a TDCS (an O4 absorption cross-section at a single temperature of 293 K; SCS) and a single O4 VCD value were applied to the LUT, the RMSE for both aerosol types was calculated to be 0.52 km (0.51 km), which implies that TDCS contributes most to AEH retrieval accuracy when accurate O4 VCDs are applied to the LUT. For smoke aerosols only, both TDCS and multiple O4 VCD (SCS and single O4 VCD) applications had RMSE values of 0.46 km (0.66 km). The retrieved AEHs were additionally compared with satellite-based lidar measurements. We also investigated the effects of uncertainties in our algorithm input data (e.g., O4 VCD, TDCS, AOD, and surface reflectance) on AEH retrieval error using synthetic radiances. Large errors can be caused by uncertainties in O4 VCD and AOD. In particular (0.4 ≤ AOD < 1.0), O4 VCD uncertainty led to AEH errors 0.96 km. However, the effect of uncertainty of TDCS on AEH retrieval is much smaller than that of O4 VCD, which agrees with a small contribution of TDCS to an improvement of AEH retrieval accuracy found in the comparison between the lidar data and the retrieved AEH with the TDCS LUT.