We develop an approach combining mass balance and four‐dimensional variational (4D‐Var) methods to facilitate inversion of decadal‐scale total nitrogen oxides (NO_x = NO + NO₂) emissions. In 7 year pseudo‐observation tests, hybrid posterior emissions have smaller normalized mean square error (NMSE) than that of mass balance when compared to true emissions in most cases and perform slightly better in detecting NO_x emission magnitudes and trends. Using this hybrid method, OMI NO₂ satellite observations and the GEOS‐Chem chemical transport model, we find more than 30% increases of emissions over most of East China at the 0.5° × 0.667° grid cell level, leading to a 16% growth of emissions over all of China from 2005 to 2012, whereas emissions in several urban centers have decreased by 10–26% in the same period. From 2010 to 2012, a decline is found in the North China Plain, Hubei Province, and Pearl River Delta area, coinciding with China's enforcement of its twelfth “Five Year Plan.” Changes in individual grid cell may be different from changes over the entire city or province, as exemplified by opposite trends in Beijing versus the Mentougou district of Beijing from 2005 to 2012. Also, NO₂ columns do not necessarily have the same trend as NO_x emissions due to their nonlinear response to emissions and the influence of meteorology, the latter alone which can cause up to 30% interannual changes in NO₂ columns. Compared to recent bottom‐up inventories, hybrid posterior emissions have the same seasonality, smaller emissions, and emission growth rate at the national scale.

EPA reports a steady decline of US anthropogenic NO _x emissions in 2005–2019 summers, while NO₂ vertical column densities (VCDs) from the OMI satellite over large spatial domains have flattened since 2009. To better understand the contributing factors to a flattening of the OMI NO₂ trends, we investigate the role of soil and lightning NO_x emissions on this apparent disagreement. We improve soil NO _x emissions estimates using a new observation-based temperature response, which increases the linear correlation coefficient between GEOS-Chem simulated and OMI NO₂ VCDs by 0.05–0.2 over the Central US. Multivariate trend analysis reveals that soil and lightning NO _x combined emissions trends change from −3.95% a⁻¹ during 2005–2009 to 0.60% a⁻¹ from 2009 to 2019, thereby rendering the abrupt slowdown of total NO _x emissions reduction. Non-linear inter-annual variations explain 6.6% of the variance of total NO _x emissions. As background emissions become relatively larger with uncertain inter-annual variations, the NO₂ VCDs alone at the national scale, especially in the regions with vast rural areas, will be insufficient to discern the trend of anthropogenic emissions.

SO₂ and NO₂ observations from the Ozone Mapping and Profiler Suite (OMPS) sensor are used for the first time in conjunction with the GEOS-Chem adjoint model to optimize both SO₂ and NO_x emission estimates over China for October 2013. Separate and joint (simultaneous) optimizations of SO₂ and NO₂ emissions are both conducted and compared. Posterior emissions, compared to the prior, yield improvements in simulating columnar SO₂ and NO₂, in comparison to measurements from the Ozone Monitoring Instrument (OMI) and OMPS. The posterior SO₂ and NO_x emissions from separate inversions are 748 Gg S and 672 Gg N, which are 36 % and 6 % smaller than prior MIX emissions (valid for 2010), respectively. In spite of the large reduction of SO₂ emissions over the North China Plain, the simulated sulfate–nitrate–ammonium aerosol optical depth (AOD) only decrease slightly, which can be attributed to (a) nitrate rather than sulfate as the dominant contributor to AOD and (b) replacement of ammonium sulfate with ammonium nitrate as SO₂ emissions are reduced. For joint inversions, both data quality control and the weight given to SO₂ relative to NO₂ observations can affect the spatial distributions of the posterior emissions. When the latter is properly balanced, the posterior emissions from assimilating OMPS SO₂ and NO₂ jointly yield a difference of −3 % to 15 % with respect to the separate assimilations for total anthropogenic SO₂ emissions and ±2 % for total anthropogenic NO_x emissions; but the differences can be up to 100 % for SO₂ and 40 % for NO₂ in some grid cells. Improvements on SO₂ and NO₂ simulations from the joint inversions are overall consistent with those from separate inversions. Moreover, the joint assimilations save ∼ 50 % of the computational time compared to assimilating SO₂ and NO₂ separately in a sequential manner of computation. The sensitivity analysis shows that a perturbation of NH₃ to 50 % (20 %) of the prior emission inventory can (a) have a negligible impact on the separate SO₂ inversion but can lead to a decrease in posterior SO₂ emissions over China by −2.4 % (−7.0 %) in total and up to −9.0 % (−27.7 %) in some grid cells in the joint inversion with NO₂ and (b) yield posterior NO_x emission decreases over China by −0.7 % (−2.8 %) for the separate NO₂ inversion and by −2.7 % (−5.3 %) in total and up to −15.2 % (−29.4 %) in some grid cells for the joint inversion. The large reduction of SO₂ between 2010 and 2013, however, only leads to ∼ 10 % decrease in AOD regionally; reducing surface aerosol concentration requires the reduction of emissions of NH₃ as well.

Largely used in several independent estimates of fire emissions, fire products based on MODIS sensors aboard the Terra and Aqua polar‐orbiting satellites have a number of inherent limitations, including (a) inability to detect fires below clouds, (b) significant decrease of detection sensitivity at the edge of scan where pixel sizes are much larger than at nadir, and (c) gaps between adjacent swaths in tropical regions. To remedy these limitations, an empirical method is developed here and applied to correct fire emission estimates based on MODIS pixel level fire radiative power measurements and emission coefficients from the Fire Energetics and Emissions Research (FEER) biomass burning emission inventory. The analysis was performed for January 2010 over the northern sub‐Saharan African region. Simulations from WRF‐Chem model using original and adjusted emissions are compared with the aerosol optical depth (AOD) products from MODIS and AERONET as well as aerosol vertical profile from CALIOP data. The comparison confirmed an 30–50% improvement in the model simulation performance (in terms of correlation, bias, and spatial pattern of AOD with respect to observations) by the adjusted emissions that not only increases the original emission amount by a factor of two but also results in the spatially continuous estimates of instantaneous fire emissions at daily time scales. Such improvement cannot be achieved by simply scaling the original emission across the study domain. Even with this improvement, a factor of two underestimations still exists in the modeled AOD, which is within the current global fire emissions uncertainty envelope.