Principal Investigator (PI): Lok Lamsal, Universities Space Research Association, Columbia, MD

Nitrogen oxides (NO_x=NO+NO₂), produced during combustion processes, are designated as criteria pollutants by the U.S. Environmental Protection Agency (EPA) due to their negative effects on public health and the environment. They are precursors of ozone and particulate matter, both of which are also criteria pollutants that have important implications for air quality, crop yields, and climate. While several space-based instruments have made NO₂ observations over the past 20+ years, the satellite-based NO₂ datasets have rarely been analyzed together in a systematic way due to algorithmic, instrumental, and observational differences.

We are developing consistent long-term global data records of tropospheric and stratospheric NO₂ columns as well as value-added surface NO₂ concentrations and anthropogenic NO_x emissions. We will achieve this by applying our mature NO₂ algorithms developed for the NASA Earth Observing System (EOS) Aura Ozone Monitoring Instrument (OMI) to similar satellite spectrometers including heritage, concurrent, and upcoming instruments that observe at different times of day.

Over the past 12 years, our NASA OMI Science team has developed, implemented, and maintained the official NASA OMI NO₂ product. Our OMI NO₂ product, archived at the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), has been widely used to quantify tropospheric pollution levels, study decadal world-wide changes in NO₂, evaluate chemical transport models, infer NO_x emissions, and study NO_x chemistry and lifetime. OMI NO₂ is one of the most widely utilized Aura datasets with over 400 research articles. The paper describing our version 2 NO₂ data set (A new stratospheric and tropospheric NO₂ retrieval algorithm for nadir-viewing satellite instruments: applications to OMI, Bucsela et al., 2013) is the second most downloaded paper in the history of the journal Atmospheric Measurement Techniques. The number of users, science applications, and publications from these data continues to grow.

Objective 1 Adapt OMI operational algorithms to other satellite instruments and create and archive consistent multi-satellite Level 2 and Level 3 NO₂ products. We will adapt our well-validated OMI NO₂, cloud, and geometry-dependent surface reflectivity retrieval algorithms to prior and contemporaneous satellite instruments that include Global Ozone Monitoring Experiment (GOME), 1996-2003; SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY), 2002-2012; Global Ozone Monitoring Experiment 2 (GOME-2), 2007-present; and TROPOspheric Monitoring Instrument (TROPOMI), launched September 2017. The proposed adaptation of the OMI Level 2 algorithms to these instruments will provide a self-consistent, long-term records ideally suited for analysis of global trends, diurnal changes in NO₂ columns, and NO_x emissions.

Objective 2 Evaluate data sets developed in Objective 1 for consistency. We will assess multi-satellite data from Objective 1 using independent observations from ground-based and in-situ sensors, and characterize multi-satellite consistency, accounting for changes in satellite footprint sizes and NO₂ diurnal cycles. We will conduct multi-sensor, cross-calibration analyses by

1. Determining vicarious calibration adjustment factors,
2. systematically evaluating the temporal stability of the satellite spectrometers, and
3. assessing the accuracy of derived products and their consistency.

Objective 3 Generate and archive higher level (Level 4) products. Using the outcomes from Objectives 1 and 2 and recent advances in NASA’s modeling capabilities, we will generate Level 4 products to enable new science and applied projects: surface NO₂ concentrations and NO_x emissions.