U.S. NO2 trends (2005e2013): EPA Air Quality System (AQS) data versus improved...

The core information for this publication's citation.: 
Lamsal, L. N., B. Duncan, Y. Yoshida, N. Krotkov, K. E. Pickering, D. Streets, and Z. Lu (2015), U.S. NO2 trends (2005e2013): EPA Air Quality System (AQS) data versus improved observations from the Ozone Monitoring Instrument (OMI), Atmos. Environ., 110, 130-143, doi:10.1016/j.atmosenv.2015.03.055.
Abstract: 

Emissions of nitrogen oxides (NOx) and, subsequently, atmospheric levels of nitrogen dioxide (NO2) have decreased over the U.S. due to a combination of environmental policies and technological change. Consequently, NO2 levels have decreased by 30e40% in the last decade. We quantify NO2 trends (2005 e2013) over the U.S. using surface measurements from the U.S. Environmental Protection Agency (EPA) Air Quality System (AQS) and an improved tropospheric NO2 vertical column density (VCD) data product from the Ozone Monitoring Instrument (OMI) on the Aura satellite. We demonstrate that the current OMI NO2 algorithm is of sufficient maturity to allow a favorable correspondence of trends and variations in OMI and AQS data. Our trend model accounts for the non-linear dependence of NO2 concentration on emissions associated with the seasonal variation of the chemical lifetime, including the change in the amplitude of the seasonal cycle associated with the significant change in NOx emissions that occurred over the last decade. The direct relationship between observations and emissions becomes more robust when one accounts for these non-linear dependencies. We improve the OMI NO2 standard retrieval algorithm and, subsequently, the data product by using monthly vertical concentration profiles, a required algorithm input, from a high-resolution chemistry and transport model (CTM) simulation with varying emissions (2005e2013). The impact of neglecting the time-dependence of the profiles leads to errors in trend estimation, particularly in regions where emissions have changed substantially. For example, trends calculated from retrievals based on time-dependent profiles offer 18% more instances of significant trends and up to 15% larger total NO2 reduction versus the results based on profiles for 2005. Using a CTM, we explore the theoretical relation of the trends estimated from NO2 VCDs to those estimated from ground-level concentrations. The model-simulated trends in VCDs strongly correlate with those estimated from surface concentrations (r = 0.83, N = 355). We then explore the observed correspondence of trends estimated from OMI and AQS data. We find a significant, but slightly weaker, correspondence (i.e., r = 0.68, N = 208) than predicted by the model and discuss some of the important factors affecting the relationship, including known problems (e.g., NOz interferents) associated with the

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Research Program: 
Applied Sciences Program (ASP)