U . S . NO 2 trends ( 2005 – 2013 ) : EPA Air Quality System 1 ( AQS ) data versus improved observations from the 2 Ozone Monitoring Instrument ( OMI ) 3

Content Provider	Semantic Scholar
Author	Lamsal, Lok N. Duncan, Bryan Neal Yoshida, Yasuko Pickering, K. E. Streets, D. G. Lu, Zifeng
Copyright Year	2015
Abstract	12 Emissions of nitrogen oxides (NOx) and, subsequently, atmospheric levels 13 of nitrogen dioxide (NO2) have decreased over the U.S. due to a combination 14 of environmental policies and technological change. Consequently, NO2 levels 15 have decreased by 30–40% in the last decade. We quantify NO2 trends (2005– 16 2013) over the U.S. using surface measurements from the U.S. Environmental 17 Protection Agency (EPA) Air Quality System (AQS) and an improved tro18 pospheric NO2 vertical column density (VCD) data product from the Ozone 19 Monitoring Instrument (OMI) on the Aura satellite. We demonstrate that 20 the current OMI NO2 algorithm is of sufficient maturity to allow a favorable 21 correspondence of trends and variations in OMI and AQS data. Our trend 22 model accounts for the non-linear dependence of the NO2 concentration on 23 emissions associated with the seasonal variation of the chemical lifetime, in24 cluding the change in the amplitude of the seasonal cycle associated with 25 ∗Corresponding author Email address: lok.lamsal@nasa.gov (Lok N. Lamsal) Preprint submitted to Atmospheric Environment February 2, 2015 the significant change in NOx emissions that occurred over the last decade. 26 The direct relationship between observations and emissions becomes more 27 robust when one accounts for these non-linear dependencies. We improve 28 the OMI NO2 standard retrieval algorithm and, subsequently, the data prod29 uct by using monthly vertical concentration profiles, a required algorithm 30 input, from a high-resolution chemistry and transport model (CTM) sim31 ulation with varying emissions (2005–2013). The impact of neglecting the 32 time-dependence of the profiles leads to errors in trend estimation, particu33 larly in regions where emissions have changed substantially. For example, we 34 find that by including the time-dependency there are 18% more instances of 35 significant trends and up to 15% larger total NO2 reduction. Using a CTM, 36 we explore the theoretical relation of the trends estimated from NO2 VCDs 37 to those estimated from ground-level concentrations. The model-simulated 38 trends in VCDs strongly correlate with those estimated from surface concen39 trations (r = 0.83, N = 355). We then explore the observed correspondence 40 of trends estimated from OMI and AQS data. We find a significant, but 41 slightly weaker, correspondence (i.e., r = 0.68, N = 208) than predicted by 42 the model and discuss some of the important factors affecting the relation43 ship, including known problems (e.g., NOz interferents) associated with the 44 AQS data. This significant correspondence gives confidence in trend and 45 surface concentration estimates from OMI VCDs for locations, such as the 46 majority of the U.S. and globe, that are not covered by surface monitoring 47 networks. Using our improved trend model and our enhanced OMI data 48 product, we find that both OMI and AQS data show substantial downward 49 trends from 2005 to 2013, with an average reduction of 38 % for each over 50
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Language	English
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Resource Type	Article