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In this study, the WRF-Chem v4.4 model was utilized to evaluate the sensitivity of O 3 simulations with three bottom-up emission inventories (EDGAR-HTAP v2 and v3 and KORUS v5) using surface and aircraft data in East Asia during the Korea-United States Air Quality (KORUS-AQ) campaign period in 2016. All emission inventories were found to reproduce the diurnal variations of O 3 and its main precursor NO 2 as compared to the surface monitor data. However, the spatial distributions of the daily maximum 8 h average (MDA8) O 3 in the model do not completely align with the observations. The model MDA8 O 3 had a negative (positive) bias north (south) of 30° N over China. All simulations underestimated the observed CO by 50 %–60 % over China and South Korea. In the Seoul Metropolitan Area (SMA), EDGAR-HTAP v2 and v3 and KORUS v5 simulated the vertical shapes and diurnal patterns of O 3 and other precursors effectively, but the model underestimated the observed O 3 , CO, and HCHO concentrations. Notably, the model aromatic volatile organic compounds (VOCs) were significantly underestimated with the three bottom-up emission inventories, although the KORUS v5 shows improvements. The model isoprene estimations had a positive bias relative to the observations, suggesting that the Model of Emissions of Gases and Aerosols from Nature (MEGAN) version 2.04 overestimated isoprene emissions. Additional model simulations were conducted by doubling CO and VOC emissions over China and South Korea to investigate the causes of the model O 3 biases and the effects of the long-range transport on the O 3 over South Korea. The doubled CO and VOC emission simulations improved the model O 3 simulations for the local-emission-dominant case but led to the model O 3 overestimations for the transport-dominant case, which emphasizes the need for accurate representations of the local VOC emissions over South Korea. [ABSTRACT FROM AUTHOR]

In this study, the WRF-Chem v4.4 model was utilized to evaluate three bottom-up emission inventories (EDGAR-HTAP v2, v3, and KORUS v5) using surface and aircraft data in East Asia during the Korea-United States Air Quality (KORUS-AQ) campaign period in 2016. All emission inventories were found to reproduce the diurnal variations of O3 and NO2 as compared to the surface monitor data. However, the spatial distributions of the daily maximum 8-hour average (MDA8) O3 in the model do not completely align with the observations. The model MDA8 O3 had a negative (positive) bias north (south) of 30°N over China. All simulations underestimated the observed CO by 50-60% over China and South Korea. In the Seoul Metropolitan Area (SMA), EDGAR-HTAP v2, v3, and KORUS v5 simulated the vertical shapes and diurnal patterns of O3 and other precursors effectively, but the model underestimated the observed O3, CO and HCHO concentrations. Notably, the model aromatic VOCs were significantly underestimated with the three bottom-up emission inventories, although the KORUS v5 shows improvements. The model isoprene estimations had a positive bias relative to the observations, suggesting that the Model of Emissions of Gases and Aerosols from Nature (MEGAN) version 2.04 overestimated isoprene emissions. Additional model simulations were conducted by doubling CO and VOC emissions over China and South Korea to investigate the causes of the model O3 biases and the effects of the long-range transport on the O3 over South Korea. The doubled CO and VOC emission simulations improved the model O3 simulations for the local emission dominant case, but led to the model O3 overestimations for the transport dominant case, which emphasizes the need for accurate representations of the local VOC emissions over South Korea. [ABSTRACT FROM AUTHOR]

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]

Abstract: Strong correlations of O3‐CH2O, O3‐CO and CO‐CH2O were observed during the Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER‐AQ) aircraft experiment in July 2011 over the Washington‐Baltimore area. The linear regression slopes of observed O3‐CH2O, O3‐CO, and CO‐CH2O do not vary significantly with time (11 a.m. to 4 p.m.) or altitude in the boundary layer. These observed relationships are simulated well by a regional chemical transport model. Using tagged‐tracer simulations, we find that biogenic isoprene oxidation makes the largest contribution to the regression slope of O3‐CH2O across much of the eastern United States, providing a good indicator for O3 enhanced by biogenic isoprene oxidation. In contrast, the regression slope of O3‐CO is controlled by both anthropogenic and biogenic emissions. Therefore, we use the CO‐CH2O relationship to separate biogenic from anthropogenic contributions to CO. By combining these regressions, we can track the contributions to surface O3 by anthropogenic and biogenic factors and build a fast‐response ozone estimator using near‐surface CH2O and CO concentrations as inputs. We examine the quality of O3 estimator by increasing or decreasing anthropogenic emissions by up to 50%. The estimated O3 distribution is in reasonably good agreement with the full‐model simulations (R2 > 0.77 in the range of −30% to +50% of anthropogenic emissions). The analysis provides the basis for using high‐quality geostationary satellites with UV, thermal infrared, or near‐infrared instruments for observing CH2O and CO to improve surface O3 distribution monitoring. The estimation model can also be applied to derive observation‐derived regional metrics to evaluate and improve full‐fledged 3‐D air quality models. [ABSTRACT FROM AUTHOR]

The GEOstationary Coastal and Air Pollution Events (GEO-CAPE) Airborne Simulator (GCAS) was developed in support of NASA's decadal survey GEO-CAPE geostationary satellite mission. GCAS is an airborne pushbroom remote sensing instrument, consisting of two channels which make hyperspectral measurements in the ultraviolet/visible (optimized for air quality observations) and the visible/near-infrared (optimized for ocean color observations). The GCAS instrument participated in its first intensive field campaign during the Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) in Texas in September 2013. During this campaign, the instrument flew on a King Air B-200 aircraft during 21 flights on 11 days to make air quality observations over Houston, Texas. We present GCAS trace gas retrievals of nitrogen dioxide (NO2) and formaldehyde (CH2O), and compare these results with trace gas columns derived from coincident in situ profile measurements of NO2 and CH2O made by instruments on a P-3B aircraft, and with NO2 observations from ground-based Pandora spectrometers operating in direct sun and scattered light modes. GCAS tropospheric column measurements correlate well spatially and temporally with columns estimated from the P-3B measurements for both NO2 (r2=0.89) and CH2O (r2=0.54) and with Pandora direct sun (r2=0.85) and scattered light (r2=0.94) observed NO2 columns. Coincident GCAS columns agree in magnitude with NO2 and CH2O P-3B-observed columns to within 10%, but are larger than scattered light Pandora tropospheric NO2 columns by 33% and direct sun Pandora NO2 columns by 50%. [ABSTRACT FROM AUTHOR]

The nonlinear chemical processes involved in ozone production (P(O 3)) have necessitated using proxy indicators to convey information about the primary dependence of P(O 3) on volatile organic compounds (VOCs) or nitrogen oxides (NO x). In particular, the ratio of remotely sensed columns of formaldehyde (HCHO) to nitrogen dioxide (NO 2) has been widely used for studying O 3 sensitivity. Previous studies found that the errors in retrievals and the incoherent relationship between the column and the near-surface concentrations are a barrier in applying the ratio in a robust way. In addition to these obstacles, we provide calculational-observational evidence, using an ensemble of 0-D photochemical box models constrained by DC-8 aircraft measurements on an ozone event during the Korea-United States Air Quality (KORUS-AQ) campaign over Seoul, to demonstrate the chemical feedback of NO 2 on the formation of HCHO is a controlling factor for the transition line between NO x -sensitive and NO x -saturated regimes. A fixed value (~2.7) of the ratio of the chemical loss of NO x (LNO x) to the chemical loss of HO 2 +RO 2 (LRO x) perceptibly differentiates the regimes. Following this value, data points with a ratio of HCHO/NO 2 less than 1 can be safely classified as NO x -saturated regime, whereas points with ratios between 1 and 4 fall into one or the other regime. We attribute this mainly to the HCHO-NO 2 chemical relationship causing the transition line to occur at larger (smaller) HCHO/NO 2 ratios in VOC-rich (VOC-poor) environments. We then redefine the transition line to LNO x /LRO x ~2.7 that accounts for the HCHO-NO 2 chemical relationship leading to HCHO = 3.7 × (NO 2 – 1.14 × 1016 molec.cm-2). Although the revised formula is locally calibrated (i.e., requires for readjustment for other regions), its mathematical format removes the need for having a wide range of thresholds used in HCHO/NO 2 ratios that is a result of the chemical feedback. Therefore, to be able to properly take the chemical feedback into consideration, the use of HCHO = a × (NO 2 – b) formula should be preferred to the ratio in future works. We then use the Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) airborne instrument to study O 3 sensitivity in Seoul. The unprecedented spatial (250 × 250 m2) and temporal (~every 2 h) resolutions of HCHO and NO 2 observations form the sensor enhance our understanding of P(O 3) in Seoul; rather than providing a crude label for the entire city, more in-depth variabilities in chemical regimes are observed that should be able to inform mitigation strategies correspondingly. • Ozone sensitivity over Seoul on an exceptionally degraded air quality day. • Various thresholds for HCHO/NO 2 should be defined to label chemical regimes. • The inherent dependence of HCHO production on NO x levels complicates the ratio. • We redesign the formula to reflect the chemical feedback of NO x on HCHO. • GeoTASO provides in-depth variabilities in chemical regimes over Seoul. [ABSTRACT FROM AUTHOR]