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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]

The availability of formaldehyde (HCHO) (a proxy for volatile organic compound reactivity) and nitrogen dioxide (NO 2) (a proxy for nitrogen oxides) tropospheric columns from ultraviolet–visible (UV–Vis) satellites has motivated many to use their ratios to gain some insights into the near-surface ozone sensitivity. Strong emphasis has been placed on the challenges that come with transforming what is being observed in the tropospheric column to what is actually in the planetary boundary layer (PBL) and near the surface; however, little attention has been paid to other sources of error such as chemistry, spatial representation, and retrieval uncertainties. Here we leverage a wide spectrum of tools and data to quantify those errors carefully. Concerning the chemistry error, a well-characterized box model constrained by more than 500 h of aircraft data from NASA's air quality campaigns is used to simulate the ratio of the chemical loss of HO 2 + RO 2 (LROx) to the chemical loss of NO x (LNOx). Subsequently, we challenge the predictive power of HCHO/NO2 ratios (FNRs), which are commonly applied in current research, in detecting the underlying ozone regimes by comparing them to LROx/LNOx. FNRs show a strongly linear (R2=0.94) relationship with LROx/LNOx , but only on the logarithmic scale. Following the baseline (i.e., ln(LROx/LNOx) = - 1.0 ± 0.2) with the model and mechanism (CB06, r2) used for segregating NOx -sensitive from VOC-sensitive regimes, we observe a broad range of FNR thresholds ranging from 1 to 4. The transitioning ratios strictly follow a Gaussian distribution with a mean and standard deviation of 1.8 and 0.4, respectively. This implies that the FNR has an inherent 20 % standard error (1σ) resulting from not accurately describing the ROx – HOx cycle. We calculate high ozone production rates (PO 3) dominated by large HCHO × NO 2 concentration levels, a new proxy for the abundance of ozone precursors. The relationship between PO 3 and HCHO × NO 2 becomes more pronounced when moving towards NOx -sensitive regions due to nonlinear chemistry; our results indicate that there is fruitful information in the HCHO × NO 2 metric that has not been utilized in ozone studies. The vast amount of vertical information on HCHO and NO 2 concentrations from the air quality campaigns enables us to parameterize the vertical shapes of FNRs using a second-order rational function permitting an analytical solution for an altitude adjustment factor to partition the tropospheric columns into the PBL region. We propose a mathematical solution to the spatial representation error based on modeling isotropic semivariograms. Based on summertime-averaged data, the Ozone Monitoring Instrument (OMI) loses 12 % of its spatial information at its native resolution with respect to a high-resolution sensor like the TROPOspheric Monitoring Instrument (TROPOMI) (> 5.5 × 3.5 km 2). A pixel with a grid size of 216 km 2 fails at capturing ∼ 65 % of the spatial information in FNRs at a 50 km length scale comparable to the size of a large urban center (e.g., Los Angeles). We ultimately leverage a large suite of in situ and ground-based remote sensing measurements to draw the error distributions of daily TROPOMI and OMI tropospheric NO 2 and HCHO columns. At a 68 % confidence interval (1σ), errors pertaining to daily TROPOMI observations, either HCHO or tropospheric NO 2 columns, should be above 1.2–1.5 × 10 16 molec. cm -2 to attain a 20 %–30 % standard error in the ratio. This level of error is almost non-achievable with the OMI given its large error in HCHO. The satellite column retrieval error is the largest contributor to the total error (40 %–90 %) in the FNRs. Due to a stronger signal in cities, the total relative error (< 50 %) tends to be mild, whereas areas with low vegetation and anthropogenic sources (e.g., the Rocky Mountains) are markedly uncertain (> 100 %). Our study suggests that continuing development in the retrieval algorithm and sensor design and calibration is essential to be able to advance the application of FNRs beyond a qualitative metric. [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]

The absence of up-to-date emissions has been a major impediment to accurately simulating aspects of atmospheric chemistry and to precisely quantifying the impact of changes in emissions on air pollution. Hence, a nonlinear joint analytical inversion (Gauss–Newton method) of both volatile organic compounds (VOCs) and nitrogen oxide (NOx) emissions is made by exploiting the Smithsonian Astrophysical Observatory (SAO) Ozone Mapping and Profiler Suite Nadir Mapper (OMPS-NM) formaldehyde (HCHO) and the National Aeronautics and Space Administration (NASA) Ozone Monitoring Instrument (OMI) tropospheric nitrogen dioxide (NO2) columns during the Korea–United States Air Quality (KORUS-AQ) campaign over East Asia in May–June 2016. Effects of the chemical feedback of NOx and VOCs on both NO2 and HCHO are implicitly included by iteratively optimizing the inversion. Emission uncertainties are greatly narrowed (averaging kernels >0.8 , which is the mathematical presentation of the partition of information gained from the satellite observations with respect to the prior knowledge) over medium- to high-emitting areas such as cities and dense vegetation. The prior amount of total NOx emissions is mainly dictated by values reported in the MIX-Asia 2010 inventory. After the inversion we conclude that there is a decline in emissions (before, after, change) for China (87.94±44.09 Gg d -1 , 68.00±15.94 Gg d -1 , -23 %), North China Plain (NCP) (27.96±13.49 Gg d -1 , 19.05±2.50 Gg d -1 , -32 %), Pearl River Delta (PRD) (4.23±1.78 Gg d -1 , 2.70±0.32 Gg d -1 , -36 %), Yangtze River Delta (YRD) (9.84±4.68 Gg d -1 , 5.77±0.51 Gg d -1 , -41 %), Taiwan (1.26±0.57 Gg d -1 , 0.97±0.33 Gg d -1 , -23 %), and Malaysia (2.89±2.77 Gg d -1 , 2.25±1.34 Gg d -1 , -22 %), all of which have effectively implemented various stringent regulations. In contrast, South Korea (2.71±1.34 Gg d -1 , 2.95±0.58 Gg d -1 , + 9 %) and Japan (3.53±1.71 Gg d -1 , 3.96±1.04 Gg d -1 , +12 %) are experiencing an increase in NOx emissions, potentially due to an increased number of diesel vehicles and new thermal power plants. We revisit the well-documented positive bias (by a factor of 2 to 3) of MEGAN v2.1 (Model of Emissions of Gases and Aerosols from Nature) in terms of biogenic VOC emissions in the tropics. The inversion, however, suggests a larger growth of VOCs (mainly anthropogenic) over NCP (25 %) than previously reported (6 %) relative to 2010. The spatial variation in both the magnitude and sign of NOx and VOC emissions results in nonlinear responses of ozone production and loss. Due to a simultaneous decrease and increase in NOx/VOC over NCP and YRD, we observe a ∼53 % reduction in the ratio of the chemical loss of NOx (LNOx) to the chemical loss of ROx (RO2+HO2) over the surface transitioning toward NOx -sensitive regimes, which in turn reduces and increases the afternoon chemical loss and production of ozone through NO2+OH (-0.42 ppbv h -1) /HO2 (and RO2) +NO (+0.31 ppbv h -1). Conversely, a combined decrease in NOx and VOC emissions in Taiwan, Malaysia, and southern China suppresses the formation of ozone. Simulations using the updated emissions indicate increases in maximum daily 8 h average (MDA8) surface ozone over China (0.62 ppbv), NCP (4.56 ppbv), and YRD (5.25 ppbv), suggesting that emission control strategies on VOCs should be prioritized to curb ozone production rates in these regions. Taiwan, Malaysia, and PRD stand out as regions undergoing lower MDA8 ozone levels resulting from the NOx reductions occurring predominantly in NOx -sensitive regimes. [ABSTRACT FROM AUTHOR]

Nitryl chloride (ClNO2) plays an important role in the budget and distribution of tropospheric oxidants, halogens, and reactive nitrogen species. ClNO2 is formed from the heterogeneous uptake and reaction of dinitrogen pentoxide (N2O5) on chloride‐containing aerosol, with a production yield, ϕ(ClNO2), defined as the moles of ClNO2 produced relative to N2O5 lost. The ϕ(ClNO2) has been increasingly incorporated into 3‐D chemical models where it is parameterized based on laboratory‐derived kinetics and currently accepted aqueous‐phase formation mechanism. This parameterization models ϕ(ClNO2) as a function of the aerosol chloride to water molar ratio. Box model simulations of night flights during the 2015 Wintertime INvestigation of Transport, Emissions, and Reactivity (WINTER) aircraft campaign derived 3,425 individual ϕ(ClNO2) values with a median of 0.138 and range of 0.003 to 1. Comparison of the box model median to those predicted by two other field‐based ϕ(ClNO2) derivation methods agreed within a factor of 1.3, within the uncertainties of each method. In contrast, the box model median was 75–84% lower than predictions from the laboratory‐based parameterization (i.e., [parameterization − box model]/parameterization). An evaluation of factors influencing this difference reveals a positive dependence of ϕ(ClNO2) on aerosol water, opposite to the currently parameterized trend. Additional factors may include aqueous‐phase competition reactions for the nitronium ion intermediate and/or direct ClNO2 loss mechanisms. Further laboratory studies of ClNO2 formation and the impacts of aerosol water, sulfate, organics, and ClNO2 aqueous‐phase reactions are required to elucidate and quantify these processes on ambient aerosol, critical for the development of a robust ϕ(ClNO2) parameterization. Key Points: Box modeling of wintertime measurements over the eastern United States provides the first determinations of ClNO2 yields (ϕ(ClNO2)) from aircraftThe median ϕ(ClNO2) value derived from the box model is overpredicted by 75‐84% by the current laboratory‐based ϕ(ClNO2) parameterizationModeled and parameterized ϕ(ClNO2) values show opposite trends with aerosol water, suggesting an incorrectly parameterized dependence [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]