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.

We present a new top‐down approach that spatially constrains the amount of aerosol emissions using satellite (Moderate Resolution Imaging Spectroradiometer (MODIS)) observed radiances with the adjoint of a chemistry transport model (GEOS‐Chem). This paper aims to demonstrate the approach through applying it to a case study that yields the following emission estimates over China for April 2008: 1.73 Tg for SO₂, 0.72 Tg for NH₃, 1.38 Tg for NO_x, 0.10 Tg for black carbon, and 0.18 Tg for organic carbon from anthropogenic sources, which reflects, respectively, a reduction of 33.5%, 34.5%, 18.8%, 9.1%, and 15% in comparison to the prior bottom‐up inventories of INTEX‐B 2006. The mineral dust emission from the online dust entrainment and mobilization module is reduced by 56.4% of 19.02 to 8.30 Tg. Compared to the prior simulation, the posterior simulation shows a much better agreement with the following independent measurements: aerosol optical depth (AOD) measured by AERONET sun‐spectrophotometers and retrieved from Multi‐angle Imaging SpectroRadiometer (MISR), atmospheric NO₂ and SO₂ columnar amount retrieved from Ozone Monitoring Instrument (OMI), and in situ data of sulfate‐nitrate‐ammonium and PM₁₀ (particular matter with aerodynamic diameter less than 10 µm) mass concentrations over both anthropogenic pollution and dust source regions. Assuming the bottom‐up (prior) anthropogenic emissions are the best estimates for their base year of 2006, the overwhelming reduction in the posterior (top‐down) estimate indicates less emission in April 2008 especially for the SO₂ tracer in the central and eastern parts of China, and/or an overestimation in the prior emission. The former is supported by the AOD change detected by MODIS and MISR sensors, while the latter is likely the case for NO_x and NH₃ emissions because no evidence shows that their atmospheric concentration has declined over China. With the promising results shown in this study, continuous efforts are needed toward a holistic and comprehensive inversion of emission using multisensor remote sensing data (of trace gases and aerosols) for constraining aerosol primary and precursor emissions at various temporal and spatial scales.

NASA's Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission, scheduled for launch in the timeframe of 2023, will carry a hyperspectral scanning radiometer named the Ocean Color Instrument (OCI) and two multi-angle polarimeters (MAPs): the UMBC Hyper-Angular Rainbow Polarimeter (HARP2) and the SRON Spectro-Polarimeter for Planetary EXploration one (SPEXone). The MAP measurements contain rich information on the microphysical properties of aerosols and hydrosols and therefore can be used to retrieve accurate aerosol properties for complex atmosphere and ocean systems. Most polarimetric aerosol retrieval algorithms utilize vector radiative transfer models iteratively in an optimization approach, which leads to high computational costs that limit their usage in the operational processing of large data volumes acquired by the MAP imagers. In this work, we propose a deep neural network (NN) forward model to represent the radiative transfer simulation of coupled atmosphere and ocean systems for applications to the HARP2 instrument and its predecessors. Through the evaluation of synthetic datasets for AirHARP (airborne version of HARP2), the NN model achieves a numerical accuracy smaller than the instrument uncertainties, with a running time of 0.01 s in a single CPU core or 1 ms in a GPU. Using the NN as a forward model, we built an efficient joint aerosol and ocean color retrieval algorithm called FastMAPOL, evolved from the well-validated Multi-Angular Polarimetric Ocean coLor (MAPOL) algorithm. Retrievals of aerosol properties and water-leaving signals were conducted on both the synthetic data and the AirHARP field measurements from the Aerosol Characterization from Polarimeter and Lidar (ACEPOL) campaign in 2017. From the validation with the synthetic data and the collocated High Spectral Resolution Lidar (HSRL) aerosol products, we demonstrated that the aerosol microphysical properties and water-leaving signals can be retrieved efficiently and within acceptable error. Comparing to the retrieval speed using a conventional radiative transfer forward model, the computational acceleration is 10³ times faster with CPU or 10⁴ times with GPU processors. The FastMAPOL algorithm can be used to operationally process the large volume of polarimetric data acquired by PACE and other future Earth-observing satellite missions with similar capabilities.