An improved tropospheric NO<sub>2</sub> column retrieval algorithm for the Ozone Monitoring Instrument

Abstract

We present an improved tropospheric nitrogen dioxide column retrieval algorithm (DOMINO v2.0) for OMI based on better air mass factors (AMFs) and a correction for across-track stripes resulting from calibration errors in the OMI backscattered reflectances. Since October 2004, NO₂ retrievals from the Ozone Monitoring Instrument (OMI), a UV/Vis nadir spectrometer onboard NASA's EOS-Aura satellite, have been used with success in several scientific studies focusing on air quality monitoring, detection of trends, and NO_x emission estimates. Dedicated evaluations of previous DOMINO tropospheric NO₂ retrievals indicated their good quality, but also suggested that the tropospheric columns were susceptible to high biases (by 0–40%), probably because of errors in the air mass factor calculations. Here we update the DOMINO air mass factor approach. We calculate a new look-up table (LUT) for altitude-dependent AMFs based on more realistic atmospheric profile parameters, and include more surface albedo and surface pressure reference points than before. We improve the sampling of the TM4 model, resulting in a priori NO₂ profiles that are better mixed throughout the boundary layer. We evaluate the NO₂ profiles simulated with the improved TM4 sampling as used in the AMF calculations and show that they are highly consistent with in situ NO₂ measurements from aircraft during the INTEX-A and INTEX-B campaigns in 2004 and 2006. Our air mass factor calculations are further updated by the implementation of a high-resolution terrain height and a high-resolution surface albedo climatology based on OMI measurements. Together with a correction for across-track stripes, the overall impact of the improved terrain height and albedo descriptions is modest (<5%) on average over large polluted areas, but still causes significant changes locally. The main changes in the DOMINO v2.0 algorithm follow from the new LUT and the improved TM4 sampling that results in more NO₂ simulated aloft, where sensitivity to NO₂ is higher, and amount to reductions in tropospheric NO₂ columns of up to 20% in winter, and 10% in summer over extended polluted areas. We investigate the impact of aerosols on the NO₂ retrieval, and based on a comparison of concurrent retrievals of clouds from OMI and aerosols from MODIS Aqua, we find empirical evidence that OMI cloud retrievals are sensitive to the presence of scattering aerosols. It follows that an implicit correction for the effects of aerosols occurs through the aerosol-induced cloud parameters in DOMINO, and we show that such a correction amounts to a 20% AMF reduction in summer and ±10% changes in winter over the eastern US

Satellite constraints of Nitrogen Oxide (NOX) emissions from India based on OMI observations and WRF-Chem simulations

“…Averaged over India, the magnitude of simulated NO 2 columns (with optimized inventory) is about 10% higher than observed by OMI. The overall error for individual retrieved tropospheric column NO 2 is reported as~25% plus 1.0×10 15 molecules/ cm 2 in DOMINO version 2.0 retrievals [Boersma et al, 2011]. Even though the usefulness of the optimized top-down estimate is limited by these uncertainties, it provides useful information about trends and spatial coverage to policymakers and air quality modelers.…”

“…In brief, tropospheric NO 2 column is derived in three main steps involving the calculation of (1) slant column (using Differential Optical Absorption Spectroscopy (DOAS) approach in the 405-465 nm spectral window), (2) tropospheric slant column (using modeling/ assimilation approach), and (3) tropospheric vertical column (using air mass factor-AMF). OMI retrieval errors have an absolute component of~1.0×10 15 molecules/cm 2 and a relative AMF component of 25% [Boersma et al, 2011]. More details on the retrievals and error budgets are discussed by Boersma et al [2011].…”

“…OMI retrieval errors have an absolute component of~1.0×10 15 molecules/cm 2 and a relative AMF component of 25% [Boersma et al, 2011]. More details on the retrievals and error budgets are discussed by Boersma et al [2011]. In this work, we use daily level-2 (Version 2.0) data from DOMINO with solar zenith angles <80º, cloud radiance fraction less than 50%, and cloud fraction less than 0.2.…”

“…However, it should be noted that the top-down estimate E is subject to various sources of uncertainty including uncertainties in OMI retrievals [Boersma et al, 2011] and the model simulations [Kumar et al, 2012], and nonlinearity between emission of NO x and column NO 2 due to NO x transport between the grid cells [Martin et al, 2003, Kuenen, 2006. Uncertainty due to transport between the grid cells is expected to be small because the iteration process compensates for transport to neighboring grid cells [Kuenen, 2006].…”

Inverse Modeling of Nitrogen Oxides Emissions from the 2010 Russian Wildfires by Using Satellite Measurements of Nitrogen Dioxide

“…We used tropospheric NO2 column amounts retrieved from measurements of visible and ultraviolet back scattered radiation by the Ozone Monitoring Instrument (OMI) [22] onboard the NASA EOS Aura satellite and provided by KNMI as the DOMINO version 2 data product [23,24]. OMI provides global coverage daily at the 13 × 24 km 2 nominal spatial resolution; the measurements are taken in the early afternoon, as the Aura satellite operates in a sun-synchronous polar orbit with an equator crossing at 13:45 LST.…”