1Belgian Institute for Space Aeronomy, Avenue Circulaire 3, 1180, Brussels, Belgium
2Royal Netherlands Meteorological Institute (KNMI), Wilhelminalaan 10, De Bilt, the Netherlands
3Eindhoven University of Technology, Fluid Dynamics Lab, Eindhoven, the Netherlands
4Asia Center for Air Pollution Research, Niigata, Japan
5National Institute for Environmental Studies, Tsukuba, Ibaraki, Japan
6Center for Earth System Science, Tsinghua University, Beijing, China
Abstract. Triggered by recent developments from laboratory and field studies regarding major NOx sink pathways in the troposphere, this study evaluates the influence of chemical uncertainties in NOx sinks for global NOx distributions calculated by the IMAGESv2 chemistry-transport model, and quantifies their significance for top-down NOx emission estimates. Our study focuses on four key chemical parameters believed to be of primary importance, more specifically, the rate of the reaction of NO2 with OH radicals, the newly-identified HNO3-forming channel in the reaction of NO with HO2, the reactive uptake of N2O5 on aerosols, and the regeneration of OH in the oxidation of isoprene. Sensitivity simulations are performed to estimate the impact of each source of uncertainty. The model calculations show that, although the NO2 + OH reaction is the largest NOx sink globally accounting for 50–70% of the total sink, the reaction contributing the most to the overall uncertainty is the formation of HNO3 in NO + HO2, leading to NOx column changes reaching a~factor of two over tropical regions, and to a 35% decrease in the global tropospheric NOx lifetime.
Emission inversion experiments are carried out using model settings which either miminize (MINLOSS) or maximize (MAXLOSS) the total NOx sink, both constrained by one year of OMI NO2 column data from the DOMINO v2 KNMI algorithm. The choice of the model setup is found to have a major impact on the top-down flux estimates, with 50% higher emissions for MAXLOSS compared to the MINLOSS inversion globally. Even larger departures are found for soil NO (factor of 2) and lightning (70%), whereas the global anthropogenic source is comparatively better constrained, especially in China.
Evaluation of the emission optimization is performed against independent satellite observations from the SCIAMACHY sensor, airborne NO2 measurements, observed NOx lifetimes at megacities, as well as with two new bottom-up inventories of anthropogenic emissions in Asia (REASv2) and China (MEIC). Neither the MINLOSS nor the MAXLOSS setup succeeds in providing the best possible match with all independent datasets. Whereas the minimum sink assumption leads to better agreement with aircraft NO2 profile measurements, comforting the results of a previous analysis (Henderson et al., 2012), the same assumption leads to unrealistic features in the inferred distribution of emissions over China. Clearly, although our study addresses an important issue which was largely overlooked in previous inversion exercises, and demonstrates the strong influence of NOx loss uncertainties on top-down emission fluxes, additional processes need to be considered which could also influence the inferred source.