Improving algorithms and uncertainty estimates for satellite NO<sub>2</sub> retrievals: Results from the Quality Assurance for Essential Climate Variables (QA4ECV) project

Abstract

Abstract. Global observations of tropospheric nitrogen dioxide (NO2) columns have been shown to be feasible from space, but consistent multi-sensor records do not yet exist, nor are they covered by planned activities on the international level. Harmonised, multi-decadal records of NO2 columns and their associated uncertainties can provide crucial information how the emissions and concentrations of nitrogen oxides evolve over time. Here we describe the development of a new, community best practice NO2 retrieval algorithm based on a synthesis of existing approaches. Detailed comparisons of these approaches led us to implement an enhanced spectral fitting method for NO2, a 1° × 1° TM5-MP data assimilation scheme to estimate the stratospheric background, and improve air mass factor calculations. Guided by the needs expressed by data users, producers, and WMO GCOS guidelines, we incorporated detailed per-pixel uncertainty information in the data product, along with easily traceable information on the relevant quality aspects of the retrieval. We applied the improved QA4ECV NO2 algorithm on the most actual level-1 data sets to produce a complete 22-year data record that includes GOME (1995-2003), SCIAMACHY (2002–2012), GOME-2(A) (2007 onwards) and OMI (2004 onwards). The QA4ECV NO2 spectral fitting recommendations and TM5-MP stratospheric column and air mass factor approach are currently also applied to S5P-TROPOMI. The uncertainties in the QA4ECV tropospheric NO2 columns amount to typically 40 % over polluted scenes. First validation results of the QA4ECV OMI NO2 columns and their uncertainties over Tai’an, China in June 2006 suggests little bias (−27thinsp;%) and better precision than suggested by uncertainty propagation. We conclude that our improved QA4ECV NO2 long-term data record is providing valuable information to quantitatively constrain emissions, deposition, and trends in nitrogen oxides on a global scale.

Nitrogen Oxide Emissions from U.S. Oil and Gas Production: Recent Trends and Source Attribution

“…For this study, we use tropospheric vertical column densities (VCDs) of NO 2 , which signify the total number of molecules between the surface and the tropopause per surface area. The latest OMI NO 2 tropospheric VCD product (QA4ECV version 1.1, Boersma et al, ) was obtained from the Royal Dutch Meteorological Institute. To minimize bias in our multiyear trend analysis, we only use pixels from detector rows 5–25 to exclude rows with a large ground pixel size and to avoid row anomalies, a problem probably caused by an external blockage of the field of view (Schenkeveld et al, ).…”

Hybrid Mass Balance/4D‐Var Joint Inversion of NOx and SO2 Emissions in East Asia

“…There are three recent operational OMI NO 2 retrievals available over East Asia domain. The NASA standard product (Krotkov et al, ), Quality Assurance for Essential Climate Variables product (Boersma et al, ), and Peking University OMI NO 2 (POMINO) product (cover China and part of India; Liu et al, ). In this study, we assimilate the NASA standard product OMNO2 (Level 2, Version 3) tropospheric NO 2 slant column density (Krotkov et al, ).…”

“…However, the seasonalities of absolute NO 2 uncertainties in the product used in this study may be different from those of other products. For instance, Boersma et al () show a winter peak of OMI NO 2 uncertainties over China. Monthly variations in the magnitude of the cost function reduction for each species are related to balance of observation and parameter errors.…”

Balance of Emission and Dynamical Controls on Ozone During the Korea‐United States Air Quality Campaign From Multiconstituent Satellite Data Assimilation

“…Uncertainties in the retrieval a priori do not play a role because the averaging kernels are used. The detailed error characteristics and validation results of the OMI NO 2 product is described by Boersma et al (, ). MLS ozone and HNO 3 …”