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We aim to reduce uncertainties in CH2O and other volatile organic carbon (VOC) emissions through assimilation of remote sensing data. We first update a three‐dimensional (3D) chemical transport model, GEOS‐Chem with the KORUSv5 anthropogenic emission inventory and inclusion of chemistry for aromatics and C2H4, leading to modest improvements in simulation of CH2O (normalized mean bias (NMB): −0.57 to −0.51) and O3 (NMB: −0.25 to −0.19) compared against DC‐8 aircraft measurements during KORUS‐AQ; the mixing ratio of most VOC species are still underestimated. We next constrain VOC emissions using CH2O observations from two satellites (OMI and OMPS) and the DC‐8 aircraft during KORUS‐AQ. To utilize data from multiple platforms in a consistent manner, we develop a two‐step Hybrid Iterative Finite Difference Mass Balance and four‐dimensional variational inversion system (Hybrid IFDMB‐4DVar). The total VOC emissions throughout the domain increase by 47%. The a posteriori simulation reduces the low biases of simulated CH2O (NMB: −0.51 to −0.15), O3 (NMB: −0.19 to −0.06), and VOCs. Alterations to the VOC speciation from the 4D‐Var inversion include increases of biogenic isoprene emissions in Korea and anthropogenic emissions in Eastern China. We find that the IFDMB method alone is adequate for reducing the low biases of VOCs in general; however, 4D‐Var provides additional refinement of high‐resolution emissions and their speciation. Defining reasonable emission errors and choosing optimal regularization parameters are crucial parts of the inversion system. Our new hybrid inversion framework can be applied for future air quality campaigns, maximizing the value of integrating measurements from current and upcoming geostationary satellite instruments. Key Points: A two step Hybrid IFDMB‐4DVar inversion systemVOC DC‐8 emissions in Northeast Asia were constrained using CH2O concentrations observed by Ozone Monitoring Instrument, Ozone Mapping and Profiler Suite, and DC‐8 aircraft during KORUS‐AQVOC emissions were increased by 47% leading to improved performance in simulation of O3 and speciated VOCs [ABSTRACT FROM AUTHOR]

Particulate matter with an aerodynamic diameter of equal to or less than 2.5 μm (PM 2.5) has been found to have a serious adverse effect on human health and the environment. While the importance of measuring PM 2.5 has been demonstrated, doing so remotely remains challenging. In this study, methodologies for the assessment of aerosol PM 2.5 and chemical composition based on a combination of regional and global models and active remote sensing were evaluated against surface observations from the KORUS-AQ campaign. The model outputs from the Community Multiscale Air Quality (CMAQ) and GEOS-Chem were used and were available at the KORUS-AQ campaign data archive. For remote sensing, aerosol extinction and derived aerosol types available from NASA Langley Airborne Differential Absorption Lidar (DIAL)/High Spectral Resolution Lidar (HSRL) flying onboard DC-8 aircraft were used. A revised version of the algorithm, which incorporates size-specific aerosol dry mass extinction efficiencies for sulfate, nitrate, and ammonia as well as organic matter, is also presented. The PM 2.5 concentration estimates were compared with measurements taken at the ground stations. The estimated mean absolute error between the ground station measurements and the remote-sensing-based methodologies was significantly lower compared to the models. The data analysis has shown that uncertainties in relative humidity values, the presence of particles larger than 2.5 μm in diameter, and the abundance of black carbon and organic matter in Asian aerosol were unlikely to explain the differences between measured and predicted surface PM 2.5. Local meteorology was found to play a key role influencing the spatiotemporal variability of aerosols and the most important factor determining the agreement between the estimated and ground site-measured PM 2.5. The lowest mean absolute error was found for the May 1–16 period, when aerosols were well mixed within the mixing layer and homogeneous across the temporal (1 h) and spatial (8 km) scales used in this study. Under these conditions, the methodologies presented here could give reasonable estimates of PM 2.5 concentration and derived chemical composition over South Korea when HSRL data are available. • New methods for estimating surface PM 2.5 are applied to Asian aerosols. • PM 2.5 and speciation are derived using HSRL-retrieved extinction and aerosol type. • The methods improve regional and global model-predicted surface PM 2.5 [ABSTRACT FROM AUTHOR]