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 five 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 and HO2 by 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 ca. 60% of the total sink, the reactions contributing the most to the overall uncertainty are the formation of HNO3 in NO+HO2, leading to NOx column changes exceeding a factor of two over tropical regions, and the uptake of HO2 by aqueous aerosols, in particular over East and South Asia. Emission inversion experiments are carried out using model settings which either minimise (MINLOSS) or maximise (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 75% higher emissions for MAXLOSS compared to the MINLOSS inversion globally. Even larger departures are found for soil NO (factor of 2) and lightning (1.8). The global anthropogenic source is better constrained (factor of 1.57) than the natural sources, except over South Asia where the combined uncertainty primarily associated to the NO+HO2 reaction in summer and HO2 uptake by aerosol in winter lead to top-down emission differences exceeding a factor of 2. Evaluation of the emission optimisation is performed against independent satellite observations from the SCIAMACHY sensor, with airborne NO2 measurements of the INTEX-A and INTEX-B campaigns, 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, consistent with 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.

Abstract. Due to changing economic activity, emissions of air pollutants in East Asia are changing rapidly in space and time. Monthly emission estimates of nitrogen oxides derived from satellite observations provide valuable insight into the evolution of anthropogenic activity on a regional scale. We present the first results of a new emission estimation algorithm, specifically designed to use daily satellite observations of column concentrations for fast updates of emissions of short-lived atmospheric constituents on a mesoscopic scale (∼ 0.25The algorithm is used to construct a monthly NO x emission time series for the period 2007-2011 from tropospheric NO 2 observations of GOME-2 for East Chinese provinces and surrounding countries. The new emission estimates correspond well with the bottom-up inventory of EDGAR v4.2, but are smaller than the inventories of INTEX-B and MEIC. They reveal a strong positive trend during 2007-2011 for almost all Chinese provinces, related to the country's economic development. We find a 41 % increment of NO x emissions in East China during this period, which shows the need to update emission inventories in this region on a regular basis. Negative emission trends are found in Japan and South Korea, which can be attributed to a combined effect of local environmental policy and global economic crises. Analysis of seasonal variation distinguishes between regions with dominant anthropogenic or biogenic emissions. For regions with a mixed anthropogenic and biogenic signature, the opposite seasonality can be used for an estimation of the separate emission contributions. Finally, the non-local concentration/emission relationships calculated by the algorithm are used to quantify the direct effect of regional NO x emissions on tropospheric NO 2 concentrations outside the region. For regions such as North Korea and the Beijing municipality, a substantial part of the tropospheric NO 2 originates from emissions elsewhere.

Triggered by recent developments from laboratory and field studies regarding major NO_x sink pathways in the troposphere, this study evaluates the influence of chemical uncertainties in NO_x sinks for global NO_x distributions calculated by the IMAGESv2 chemistry-transport model, and quantifies their significance for top-down NO_x 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 NO_x 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 NO_x column changes reaching a~factor of two over tropical regions, and to a 35% decrease in the global tropospheric NO_x lifetime.

Emission inversion experiments are carried out using model settings which either miminize (MINLOSS) or maximize (MAXLOSS) the total NO_x 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 NO_x 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 NO_x loss uncertainties on top-down emission fluxes, additional processes need to be considered which could also influence the inferred source

Due to changing economic activity, emissions of air pollutants in East Asia change rapidly in space and time. Monthly emission estimates of nitrogen oxides derived from satellite observations provide valuable insight in the evolution of anthropogenic activity on a regional scale. We present the first results of a new emission estimation algorithm, specifically designed to use daily satellite observations of column concentrations for fast updates of emissions of short-lived atmospheric constituents on a~mesoscopic scale (~ 0.25° × 0.25°). The algorithm is used to construct a monthly NO_x emission time series for 2007–2011 from tropospheric NO₂ observations of GOME-2 for East Chinese provinces and surrounding countries. The new emission estimates correspond well with the bottom-up inventory of EDGAR v4.2, but are smaller than the inventories of INTEX-B and MEIC. They reveal a strong positive trend during 2007–2011 for almost all Chinese provinces, related to the country's economic development. We find a 41% increment of NO_x emissions in East China during this period, which shows the need to update emission inventories in this region on a regular basis. Negative emission trends are found in Japan and South Korea, which can be attributed to a combined effect of local environmental policy and global economic crises. Analysis of seasonal variation distinguishes between regions with dominant anthropogenic or biogenic emissions. For regions with a mixed anthropogenic and biogenic signature, the opposite seasonality can be used for an estimation of the separate emission contributions. Finally, the non-local concentration/emission relationships calculated by the algorithm are used to quantify the direct effect of regional NO_x emissions on tropospheric NO₂ concentrations outside the region. For regions such as North Korea and Beijing province, a substantial part of the tropospheric NO₂ originates from emissions elsewhere