Improving NO 2 and ozone simulations through global NO x emission inversions

Atmospheric Chemistry and Physics(2020)

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摘要
Abstract. Tropospheric ozone simulations have large uncertainties, but their biases, seasonality and trends can be improved with more accurate estimates of precursor gas emissions. We perform global top-down estimates of monthly NOx emissions using two OMI NO2 retrievals (NASAv3 and DOMINOv2) from 2005 to 2016 through a hybrid 4D-Var/mass balance inversion. The 12-year averages of regional NOx budgets from the NASA posterior emissions are 37 % to 53 % smaller than the DOMINO posterior. Compared to surface NO2 measurements, GEOS-Chem adjoint NO2 simulations using the DOMINO posterior NOx emissions have smaller biases in China (by 15 %) and the US (by 22 %), but NO2 trends have more consistent decreases (by 26 %) with the measurements (by 32 %) in the US from 2006 to 2016 when using the NASA posterior. The two posterior NOx emissions datasets have different strengths with respect to simulation of ozone concentrations. Simulations using NASA-based emissions provide better agreement for polluted conditions. Ozone from these shows the highest correlation (R2 = 0.88) with annual MDA8 ozone trends and alleviates the double peak in the prior simulation of global ozone seasonality. The DOMINO-based emissions, on the other hand, are better for simulating ozone at remote sites, making them well-suited to generation of boundary conditions for regional models, and in capturing the interannual variability of daytime-average (R2 = 0.72–0.81) and 24-hour average (R2 = 0.88–0.96) surface ozone. We recommend using NOx emission datasets that have the best performance in the corresponding spatial domain and temporal focus to improve ozone simulations.
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