Korea-United States Air Quality Research Articles

Using observed urban NOx sinks to constrain VOC reactivity and the ozone and radical budget in the Seoul Metropolitan Area

Abstract. Ozone (O3) is an important secondary pollutant that impacts air quality and human health. Eastern Asia has high regional O3 background due to the numerous sources and increasing and rapid industrial growth, which also impacts the Seoul Metropolitan Area (SMA). However, the SMA has also been experiencing increasing O3 driven by decreasing NOx emissions, highlighting the role of the local in situ O3 production on the SMA. Here, comprehensive gas-phase measurements collected on the NASA DC-8 during the National Institute of Environmental Research (NIER)/NASA Korea–United States Air Quality (KORUS-AQ) study are used to constrain the instantaneous O3 production rate over the SMA. The observed NOx oxidized products support the importance of non-measured peroxy nitrates (PNs) in the O3 chemistry in the SMA, as they accounted for ∼49 % of the total PNs. Using the total measured PNs (ΣPNs) and alkyl and multifunctional nitrates (ΣANs), unmeasured volatile organic compound (VOC) reactivity (R(VOC)) is constrained and found to range from 1.4–2.1 s−1. Combining the observationally constrained R(VOC) with the other measurements on the DC-8, the instantaneous net O3 production rate, which is as high as ∼10 ppbv h−1, along with the important sinks of O3 and radical chemistry, is constrained. This analysis shows that ΣPNs play an important role in both the sinks of O3 and radical chemistry. Since ΣPNs are assumed to be in a steady state, the results here highlight the role that ΣPNs play in urban environments in altering the net O3 production, but ΣPNs can potentially lead to increased net O3 production downwind due to their short lifetime (∼1 h). The results provide guidance for future measurements to identify the missing R(VOCs) and ΣPN production.

Ozone, nitrogen dioxide, and PM2.5 estimation from observation-model machine learning fusion over S. Korea: Influence of observation density, chemical transport model resolution, and geostationary remotely sensed AOD

High-resolution multi-component estimates of ground-level air pollutants are necessary for assessing their impacts to human health, agriculture, and ecosystems. We demonstrate a high-resolution fusion and downscaling approach over South Korea for May 2016 and May 2021. Daily 1 km fine particulate matter (PM2.5), ozone (O3), and nitrogen dioxide (NO2) concentrations are calculated at ground level using a random forest machine learning (ML) algorithm, with predictors including reanalysis meteorology, satellite aerosol optical depth (AOD), and gridded surface fields from chemical transport models (CTM). The ML model is tested for May 2016, coinciding with the Korea-United States Air Quality Study (KORUS-AQ) intensive field campaign, and for May 2021, to allow incorporation of observations from the Geostationary Environment Monitoring Spectrometer (GEMS). In the tests for May 2016, the correlation coefficients (R) and root mean squared errors (RMSE) relative to withheld observations of daily-averaged pollutants in 10-fold cross-validation are promising: 0.93 (5.5 μg/m3), 0.90 (5.5 ppbv), and 0.95 (4.7 ppbv) for PM2.5, O3, and NO2, respectively. Relative performance is assessed for alternate choices of predictors: (a) 80-km global reanalysis Copernicus Atmosphere Monitoring Service (CAMS) vs. 4-km regional Weather Research and Forecasting model coupled with Chemistry (WRF-Chem); (b) AOD polar-orbiting Moderate Resolution Image Spectroradiometer (MODIS) Multi-Angle Implementation of Atmospheric Correction (MAIAC) vs. geostationary GEMS; and (c) variations in surface observation density. This study is among the very first to incorporate both CTM and GEMS AOD for building surface high resolution multiple air pollution predictions over South Korea.

Sensitivity of the WRF-Chem v4.4 simulations of ozone and formaldehyde and their precursors to multiple bottom-up emission inventories over East Asia during the KORUS-AQ 2016 field campaign

Abstract. In this study, the WRF-Chem v4.4 model was utilized to evaluate the sensitivity of O3 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 O3 and its main precursor NO2 as compared to the surface monitor data. However, the spatial distributions of the daily maximum 8 h 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 and 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 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 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.

Assessing the impact of shipping emissions on ozone concentrations in East Asia: Insights from KORUS-AQ and SIJAQ 2021 campaign periods

This study analyzed the impact of shipping emissions on ozone (O3) concentrations in East Asia during the Korea-United States Air Quality (KORUS-AQ) and the Satellite Integrated Joint monitoring for Air Quality (SIJAQ) 2021 campaign period. Numerical simulations were performed during the KORUS-AQ (May 2016, the KORUS case) and the SIJAQ 2021 (October–November 2021, the SIJAQ case) using Community Multi-scale Air Quality (CMAQ), the three-dimensional chemical transport model. We additionally simulated an experiment without shipping emissions to compare the impact with and without shipping emissions. Using the validated simulation results, the average O3 concentrations in inland regions were found to be 35.63 ppb and 20.62 ppb in the KORUS and SIJAQ cases, respectively. The average O3 concentrations were higher in the KORUS case owing to the difference in weather conditions between the two cases in various seasons. The results of examining the impact of shipping emissions on O3 concentrations in the ocean area indicate that both the KORUS and SIJAQ cases resulted in a decrease in O3 concentrations in the Yellow Sea region, while the O3 concentrations increased in the East Sea and North Pacific regions. In particular, in the Yellow Sea and East China Sea, where the O3 concentrations decreased in the KORUS case, O3 sensitivity results showed volatile organic compounds (VOC)-sensitive regime when the shipping emissions were removed but changed to nitrogen oxide (NOx)-sensitive regime when the shipping emissions were added. Meanwhile, in the inland regions, the SIJAQ case decreased O3 concentrations in most areas, whereas the KORUS case showed an increase in O3 concentrations in the Korean Peninsula and Japan. Analysis of O3 sensitivity revealed that the regions of the Korean Peninsula and Japan, where O3 concentrations increased, exhibited a NOx-sensitive regime. Particularly, in the case of the Korean Peninsula, the initial transport of shipping emissions in the western part led to a decrease in O3 concentrations. However, as shipping emissions were further transported from west to east, they became more diluted, and additional NOx generated by O3 titration reactions was also transported, gradually increasing O3 concentrations. Furthermore, we found that during seasons with abundant BVOC emissions, the transport of shipping emissions could contribute to additional O3 production. These results confirmed that shipping emissions in East Asia primarily reduce O3 concentrations, however, differences in seasonal and regional O3 sensitivity and transportation patterns can contribute to O3 production.

Effect of nitryl chloride chemistry on air quality in South Korea during the KORUS-AQ campaign

Nitryl chloride (ClNO2) can play an important role in determining ozone and particulate matter (PM) chemistry as a nighttime reservoir of NOX and a source of chlorine radical (Cl•) in the daytime in polluted environments. We present a quantitative evaluation of the impact of tropospheric ClNO2 chemistry on air quality in South Korea using extensive observations during the Korea-United States Air Quality (KORUS-AQ) field study and a 3-D chemical transport model (CTM). We first estimated anthropogenic emissions of reactive chlorine in South Korea to implement it along with the latest Chinese emissions in the model. A comparison between the simulated and observed ClNO2 concentrations during the KORUS-AQ campaign shows that the model captures the observed spatial and temporal variations, including local and transboundary transport of ClNO2 and its precursors. The model simulation highlights that ClNO2 plays a significant role in nighttime NOX chemistry by efficiently converting NO to NO2. In addition, it causes a noticeable acceleration of the NOX-O3 cycle. When averaged over the campaign, adding ClNO2 chemistry into the model leads to an increase of O3 (1.1%), NOX (3.1%), •OH (2.0%), HO2• (0.8%), and Cl• (507.8%) and a decrease of TNO3 (HNO3 + aerosol nitrate, 1.7%).

Direct aerosol optical depth retrievals using MODIS reflectance data and machine learning over East Asia

Anthropogenic aerosols have rapidly increased since the industrial revolution and are harmful to human health. Moderate Resolution Imaging Spectroradiometer (MODIS) data are critical for retrieving aerosol properties worldwide. However, current MODIS aerosol optical depth (AOD) products require extensive computations and a precalculated lookup table. This study proposes assumption-free high-resolution AOD retrieval models based on the light gradient boosting machine method using MODIS data and ground-based observations over East Asia. The models were developed with three spatial resolutions: 250 m, 500 m, and 1 km. The results showed that 77.8% of the 250 m AOD values were within the MODIS expected error (EE) range, while 76.5%, 76.3%, and 70.08% of the 500 m, 1 km, and Multi-Angle Implementation of Atmospheric Correction (MAIAC) AOD values were within the EE range, respectively. Furthermore, an analysis of the time series and detailed spatial distribution of the proposed model-derived AOD based on data from the Korea–United States Air Quality campaign demonstrated the excellent quality of the 250 m AOD via further validation using a spatially independent dataset. The Shapley Additive exPlanations analysis identified the sensor zenith angle and top-of-atmosphere reflectance of the blue band as the key contributors to the models. In addition, while MAIAC has limited spatial coverage, the spatial frequency of the proposed direct AOD retrieval was nearly 1.5-times higher than that of the MAIAC AOD. Our findings confirmed that machine learning-based high-resolution AOD estimates can be obtained using only satellite data.

Adjusting elemental carbon emissions in Northeast Asia using observed surface concentrations of downwind area and simulated contributions

In this study, we developed a practical approach to augment elemental carbon (EC) emissions to improve the reproducibility of the most recent air quality with photochemical grid modeling in support of source-receptor relationship analysis. We demonstrated the usefulness of this approach with a series of simulations for EC concentrations over Northeast Asia during the 2016 Korea-United States Air Quality study. Considering the difficulty of acquiring EC observational data in foreign countries, our approach takes two steps: (1) augmenting upwind EC emissions based on simulated upwind contributions and observational data at a downwind EC monitor considered as the most representative monitor for upwind influences and (2) adjusting downwind EC emissions based on simulated downwind contributions, including the effects of updated upwind emissions from the first step and observational data at the downwind EC monitors. The emission adjustment approach resulted in EC emissions 2.5 times higher than the original emissions in the modeling domain. The EC concentration in the downwind area was observed to be 1.0 μg m−3 during the study period, while the simulated EC concentration was 0.5 μg m−3 before the emission adjustment. After the adjustment, the normalized mean error of the daily mean EC concentration decreased from 48 % to 22 % at ground monitor locations. We found that the EC simulation results were improved at high altitudes, and the contribution of the upwind areas was greater than that of the downwind areas for EC concentrations downwind with or without emission adjustment. This implies that collaborating with upwind regions is essential to alleviate high EC concentrations in downwind areas. The developed emission adjustment approach can be used for any upwind or downwind area when transboundary air pollution mitigation is needed because it provides better reproducibility of the most recent air quality through modeling with improved emission data.

Interpretation of the effects of anthropogenic chlorine on nitrate formation over northeast Asia during KORUS-AQ 2016

The Weather Research and Forecasting–Community Multiscale Air Quality (WRF-CMAQ) model, implemented with anthropogenic chlorine (Cl) emissions, was evaluated against ground and NASA DC-8 aircraft measurements during the Korea-United States Air Quality (KORUS-AQ) 2016 campaign. The latest anthropogenic Cl emissions, including gaseous HCl and particulate chloride (pCl−) emissions from the Anthropogenic Chlorine Emissions Inventory of China (ACEIC-2014) (over China) and a global emissions inventory (Zhang et al., 2022) (over outer China), were used to examine the impacts of Cl emissions and the role of nitryl chloride (ClNO2) chemistry in N2O5 heterogeneous reactions on secondary nitrate (NO3−) formation across the Korean Peninsula. The model results against aircraft measurements clearly showed significant Cl- underestimations due mainly to the high gas-particle (G/P) partitioning ratios at aircraft measurement altitudes such as 700–850 hPa, but the ClNO2 simulations were reasonable. Several simulations of CMAQ-based sensitivity experiments against ground measurements indicated that although addition of Cl emission did not significantly alter NO3− formation, the activated ClNO2 chemistry with Cl emissions showed the best model performance with the reduced normalized mean bias (NMB) of 18.7 % compared to a value of 21.1 % for the Cl emissions-free case. In our model evaluation, ClNO2 accumulated during the night but quickly produced Cl radical due to ClNO2 photolysis at sunrise, which modulated other oxidation radicals (e.g., ozone [O3] and hydrogen oxide radicals [HOx]) in the early morning. In the morning hours (0800–1000 LST), the HOx were the dominant oxidants, contributing 86.6 % of the total oxidation capacity (sum of major oxidants such as O3 and HOx species), while oxidability was enhanced by up to ∼6.4 % (increase in 1 h HOx average of 2.89 × 106 molecules·cm−3) in the early morning mainly due to the changes in OH (+7.2 %), hydroperoxyl radical (HO2)(+10.0 %), and O3 (+4.2 %) over the Seoul Metropolitan Area, during the KORUS-AQ campaign. Our results improve understanding of the atmospheric changes in the PM2.5 formation pathway caused by ClNO2 chemistry and Cl emissions over northeast Asia.

Coarse particulate matter air quality in East Asia: implications for fine particulate nitrate

Abstract. Air quality network data in China and South Korea show very high year-round mass concentrations of coarse particulate matter (PM), as inferred by the difference between PM10 and PM2.5. Coarse PM concentrations in 2015 averaged 52 µg m−3 in the North China Plain (NCP) and 23 µg m−3 in the Seoul Metropolitan Area (SMA), contributing nearly half of PM10. Strong daily correlations between coarse PM and carbon monoxide imply a dominant source from anthropogenic fugitive dust. Coarse PM concentrations in the NCP and the SMA decreased by 21 % from 2015 to 2019 and further dropped abruptly in 2020 due to COVID-19 reductions in construction and vehicle traffic. Anthropogenic coarse PM is generally not included in air quality models but scavenges nitric acid to suppress the formation of fine particulate nitrate, a major contributor to PM2.5 pollution. GEOS-Chem model simulation of surface and aircraft observations from the Korea–United States Air Quality (KORUS-AQ) campaign over the SMA in May–June 2016 shows that consideration of anthropogenic coarse PM largely resolves the previous model overestimate of fine particulate nitrate. The effect is smaller in the NCP which has a larger excess of ammonia. Model sensitivity simulations for 2015–2019 show that decreasing anthropogenic coarse PM directly increases PM2.5 nitrate in summer, offsetting 80 % the effect of nitrogen oxide and ammonia emission controls, while in winter the presence of coarse PM increases the sensitivity of PM2.5 nitrate to ammonia and sulfur dioxide emissions. Decreasing coarse PM helps to explain the lack of decrease in wintertime PM2.5 nitrate observed in the NCP and the SMA over the 2015–2021 period despite decreases in nitrogen oxide and ammonia emissions. Continuing decrease of fugitive dust pollution means that more stringent nitrogen oxide and ammonia emission controls will be required to successfully decrease PM2.5 nitrate.

Tropospheric NO2 vertical profiles over South Korea and their relation to oxidant chemistry: implications for geostationary satellite retrievals and the observation of NO2 diurnal variation from space

Abstract. Nitrogen oxides (NOx≡ NO + NO2) are of central importance for air quality, climate forcing, and nitrogen deposition to ecosystems. The Geostationary Environment Monitoring Spectrometer (GEMS) is now providing hourly NO2 satellite observations over East Asia, offering the first direct measurements of NO2 diurnal variation from space to guide understanding of NOx emissions and chemistry. The NO2 retrieval requires independent vertical profile information from a chemical transport model (CTM) to compute the air mass factor (AMF) that relates the NO2 column measured along the line of sight to the NO2 vertical column. Here, we use aircraft observations from the Korea-United States Air Quality (KORUS-AQ) campaign over the Seoul metropolitan area (SMA) and around the Korean Peninsula in May–June 2016 to better understand the factors controlling the NO2 vertical profile, its diurnal variation, the implications for the AMFs, and the ability of the GEOS-Chem CTM to compute the NO2 vertical profiles used for AMFs. Proper representation of oxidant chemistry is critical for the CTM simulation of NO2 vertical profiles and is achieved in GEOS-Chem through new model developments, including aerosol nitrate photolysis, reduced uptake of hydroperoxy (HO2) radicals by aerosols, and accounting for atmospheric oxidation of volatile chemical products (VCPs). We find that the tropospheric NO2 columns measured from space in the SMA are mainly contributed by the planetary boundary layer (PBL) below 2 km altitude, reflecting the highly polluted conditions. Repeated measurements of NO2 vertical profiles over the SMA at different times of day show that diurnal change in mixing depth affecting the NO2 vertical profile induces a diurnal variation in AMFs of comparable magnitude to the diurnal variation in the NO2 column. GEOS-Chem captures this diurnal variation in AMFs and more generally the variability in the AMFs for the KORUS-AQ NO2 vertical profiles (2.7 % mean bias, 7.6 % precision), with some outliers in the morning due to errors in the timing of mixed-layer growth.

Highly resolved mapping of NO2 vertical column densities from GeoTASO measurements over a megacity and industrial area during the KORUS-AQ campaign

Abstract. The Korea–United States Air Quality (KORUS-AQ) campaign is a joint study between the United States National Aeronautics and Space Administration (NASA) and the South Korea National Institute of Environmental Research (NIER) to monitor megacity and transboundary air pollution around the Korean Peninsula using airborne and ground-based measurements. Here, tropospheric nitrogen dioxide (NO2) slant column density (SCD) measurements were retrieved from Geostationary Trace and Aerosol Sensor Optimization (GeoTASO) L1B data during the KORUS-AQ campaign (2 May to 10 June 2016). The retrieved SCDs were converted to tropospheric vertical column densities using the air mass factor (AMF) obtained from a radiative transfer calculation with trace gas profiles and aerosol property inputs simulated with the Community Multiscale Air Quality (CMAQ) model and surface reflectance data obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS). For the first time, we examine highly resolved (250 m × 250 m resolution) tropospheric NO2 over the Seoul and Busan metropolitan regions and the industrial region of Anmyeon. We reveal that the maximum NO2 vertical column densities (VCDs) were 4.94×1016 and 1.46×1017 molec. cm−2 at 09:00 and 15:00 LT over Seoul, respectively, 6.86×1016 and 4.89×1016 molec. cm−2 in the morning and afternoon over Busan, respectively, and 1.64×1016 molec. cm−2 over Anmyeon. The VCDs retrieved from the GeoTASO airborne instrument were correlated with those obtained from the Ozone Monitoring Instrument (OMI) (r=0.48), NASA's Pandora Spectrometer System (r=0.91), and NO2 mixing ratios obtained from in situ measurements (r=0.07 in the morning, r=0.26 in the afternoon over the Seoul, and r>0.56 over Busan). Based on our results, GeoTASO is useful for identifying NO2 hotspots and their spatial distribution in highly populated cities and industrial areas.

Evaluation of biogenic emissions from three different vegetation distributions in South Korea

Map of plant functional type (PFT) is one of key information in estimating the bottom-up biogenic emissions. This study investigated the performance of three different maps of PFT on biogenic emissions in South Korea: i) PFT map from the MODerate resolution Imaging Spectroradiometer (MODIS) satellite sensor onboard Terra-/Aqua-satellites (MPFT); ii) PFT map from the Environmental Geographic Information System (EGIS) provided by the Korean Ministry of Environment (EPFT); and iii) PFT map from the Forest Geographic Information System (FGIS) established by the Korea Forest Service (FPFT). These three different vegetation distributions were used as input information into the Model of Emissions of Gases and Aerosols from Nature (MEGAN) model. The biogenic emissions estimated by the MEGAN model simulations were then evaluated by comparisons between the Community Multi-scale Air Quality (CMAQ) simulated mixing ratios of biogenic species with ground- and aircraft-borne mixing ratios during the period of the Korea–United States Air Quality (KORUS-AQ) campaign. The analyses found that the simulation using the FPFT map, which has been regarded as ‘ground truth’, produced the best results in terms of several statistical metrics. For example, among the three experiments, the simulation with the FPFT map produced the best index of agreement (IOA) of 0.76 and the lowest normalized mean bias (NMB) of 5.61%, in comparison with ground-based isoprene observations. The simulations with the MPFT map also performed reasonably, showing low NMBs of −42.13% and −14.87% for the isoprene and the first-generation products of isoprene, respectively, in comparison with the DC-8 airborne observations. In addition, the applications of the MPFT map to the MEGAN modeling showed significant overestimations in the mixing ratios of biogenic species over the SoBaek (SB) mountain ranges. It was believed that this was due to the overestimated density of broadleaf deciduous temperate trees over the SB mountain ranges in the MPFT map. On the other hand, the EPFT map showed the worst performances, which might be related to crude classification of vegetation. This study also suggests two important possibilities. First, the current isoprene-related photochemistry appears to be highly uncertain, based on large underestimations of the first-generation products of isoprene, in comparison with observations. Second, the emission factors of monoterpenes in the MEGAN model may be too small, based on large underestimations of monoterpenes, in comparison with observations.

Nocturnal Boundary Layer Height Uncertainty in Particulate Matter Simulations during the KORUS-AQ Campaign

Vertical mixing in the planetary boundary layer (PBL) is an important factor in the prediction of particulate matter (PM) concentrations; however, PBL height (PBLH) in the stable atmosphere remains poorly understood. In particular, the assessment of uncertainties related to nocturnal PBLH (nPBLH) is challenging due to the absence of stable atmosphere observations. In this study, we explored nPBLH–PM2.5 interactions by comparing model results and observations during the Korea–United States Air Quality Study (KORUS-AQ) campaign (1–31 May 2016). Remote sensing measurements (e.g., aerosol and wind Doppler lidar) and on-line WRF-Chem modeling results were used by applying three different PBL parameterizations: Yonsei University (YSU), Mellor–Yamada–Janjic (MYJ), and Asymmetrical Convective Model v2 (ACM2). Our results indicated that the uncertainties of PBLH–PM interactions were not large in daytime, whereas the uncertainties of nPBLH–PM2.5 interactions were significant. All WRF-Chem experiments showed a clear tendency to underestimate nighttime nPBLH by a factor of ~3 compared with observations, and shallow nPBLH clearly led to extremely high PM2.5 peaks during the night. These uncertainties associated with nPBLH and nPBLH–PM2.5 simulations suggest that PM2.5 peaks predicted from nighttime or next-morning nPBLH simulations should be interpreted with caution. Additionally, we discuss uncertainties among PBL parameterization schemes in relation to PM2.5 simulations.

Aerosol Layer Height Retrieval Over Ocean From the Advanced Himawari Imager Using Spectral Reflectance Sensitivity

Aerosol layer height (ALH) has been retrieved using multi-angle observations or the O2–O2 and O2–A/B absorption bands. This study attempted to retrieve ALH using the Advanced Himawari Imager (AHI), a single passive imager onboard Himawari-8 and -9. ALH retrieval using geostationary Earth orbit (GEO) satellites is advantageous for monitoring diurnal changes in ALH and understanding long-range transport. Before retrieving the ALH, the aerosol optical properties (AOPs) are retrieved using the green-near infrared (NIR) band, which is relatively insensitive to aerosol height. The retrieved AOPs are used as input to the radiative transfer calculation to compute the top-of-atmosphere (TOA) reflectance of a highly sensitive band (the blue band in this study). Then, the ALH is retrieved using the observed and calculated TOA reflectances. Since the retrieval accuracy of the aerosol optical depth (AOD) is better over the ocean, the retrieval was performed only over the ocean during the Korea–United States Air Quality Study (KORUS-AQ) campaign period. The retrieved ALH was validated using the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and high-spectral-resolution Lidar (HSRL).

An investigation of petrochemical emissions during KORUS-AQ: Ozone production, reactive nitrogen evolution, and aerosol production

Emissions and secondary photochemical products from the Daesan petrochemical complex (DPCC), on the west coast of South Korea, were measured from the NASA DC-8 research aircraft during the Korea-United States Air Quality campaign in 2016. The chemical evolution of petrochemical emissions was examined utilizing near-source and downwind plume transects. Small alkenes, such as ethene (C2H4), propene (C3H6), and 1,3-butadiene (C4H6), dominated the hydroxyl (OH) radical reactivity near the source region. The oxidation of these alkenes in the petrochemical plumes led to efficient conversion of nitrogen oxides (NOx) to nitric acid (HNO3), peroxycarboxylic nitric anhydrides (PANs), and alkyl nitrates (ANs), where the sum of the speciated reactive nitrogen contributes more than 80% of NOy within a few hours. Large enhancements of short-lived NOx oxidation products, such as hydroxy nitrates (HNs) and peroxyacrylic nitric anhydride, were observed, in conjunction with high ozone levels of up to 250 ppb, which are attributed to oxidation of alkenes such as 1,3-butadiene. Instantaneous ozone production rates, P(O3), near and downwind of the DPCC ranged from 9 to 24 ppb h−1, which were higher than those over Seoul. Ozone production efficiencies ranged from 6 to 10 downwind of the DPCC and were lower than 10 over Seoul. The contributions of alkenes to the instantaneous secondary organic aerosol (SOA) production rate, P(SOA), were estimated to be comparable to those of more common SOA precursors such as aromatics at intermediate distances from the DPCC. A model case study constrained to an extensive set of observations provided a diagnostic of petrochemical plume chemistry. The simulated plume chemistry reproduced the observed evolution of ozone and short-lived reactive nitrogen compounds, such as PANs and HNs as well as the rate and efficiency of ozone production. The simulated peroxy nitrates (PNs) budget included large contributions (approximately 30%) from unmeasured PNs including peroxyhydroxyacetic nitric anhydride and peroxybenzoic nitric anhydride. The large, predicted levels of these PAN compounds suggest their potential importance in chemical evolution of petrochemical plumes. One unique feature of the DPCC plumes is the substantial contribution of 1,3-butadiene to ozone and potentially SOA production. This work suggests that reductions in small alkene, especially 1,3-butadiene, emissions from the DPCC should be a priority for reducing downwind ozone.

A Box-Model Simulation of the Formation of Inorganic Ionic Particulate Species and Their Air Quality Implications in Republic of Korea

The Observation-Constrained Atmospheric BOX model (OCABOX) was used to analyze the formation of secondary inorganic PM species in the Seoul Metropolitan Area (SMA), South Korea. The measurement data of the ionic components of PM2.5 and their gaseous precursors made at the Olympic Park ground site (37.53°N, 127.12°E) during the Korea-United States Air Quality field campaign were used to run OCABOX in observation-based mode and compare the simulation results. The use of the HNO3 concentrations measured at a marine background site as the boundary conditions appeared to increase the accuracy of the model prediction of HNO3 and particulate NO3− concentrations. For the primary precursors emitted considerably throughout the SMA, such as NOx and NH3, using the data measured inside the SMA as the boundary conditions could lead to more accurate predictions. OCABOX was shown to be a reliable tool to analyze the formation of secondary inorganic aerosol in the SMA if used with appropriate regional background concentrations and observation-based constraints

Observed versus simulated OH reactivity during KORUS-AQ campaign: Implications for emission inventory and chemical environment in East Asia

We present a holistic examination of tropospheric OH reactivity (OHR) in South Korea using comprehensive NASA DC-8 airborne measurements collected during the Korea–United States Air Quality field study and chemical transport models. The observed total OHR (tOHR) averaged in the planetary boundary layer (PBL, <2.0 km) and free troposphere was 5.2 s−1 and 2.0 s−1 during the campaign, respectively. These values were higher than the calculated OHR (cOHR, 3.4 s−1, 1.0 s−1) derived from trace-gas observations, indicating missing OHR fractions in the PBL and free troposphere of 35% and 50%, respectively. Incorporating nonobserved secondary species from the observationally constrained box model increased cOHR to 4.0 s−1 in the PBL and 1.3 s−1 in the free troposphere. Simulated OHR (sOHR, 2.7 s−1, 0.8 s−1) was substantially lower than both tOHR and cOHR by as much as 60%. This underestimate was substantial in the free troposphere and marine boundary layer of the marginal sea (Yellow Sea). We then discuss the potential causes of unaccounted OHR. First, we suggest improving the accuracy of tropospheric reaction kinetics, which vary significantly in the available literature. Second, underestimated emissions of anthropogenic CO and oxygenated volatile organic compounds in East Asia contributed to the discrepancy between tOHR and sOHR. In addition, oxygenated and biogenic volatile organic compounds emitted from the marginal sea may contribute substantially to the regional OHR. Typical chemical transport models underestimate these sources, leading to a large missing OHR fraction. Despite this discrepancy, we found that simulated OH concentrations were comparable with those observed during the campaign because of slow OH recycling rates in the models; therefore, the models predicted less formation of photochemical oxidation products such as ozone.

Implementation of aerosol data assimilation in WRFDA (v4.0.3) for WRF-Chem (v3.9.1) using the RACM/MADE-VBS scheme

Abstract. The Weather Research and Forecasting model data assimilation (WRFDA) system, initially designed for meteorological data assimilation, is extended for aerosol data assimilation for the WRF model coupled with chemistry (WRF-Chem). An interface between WRF-Chem and WRFDA is built for the Regional Atmospheric Chemistry Mechanism (RACM) chemistry and the Modal Aerosol Dynamics Model for Europe (MADE) coupled with the Volatility Basis Set (VBS) aerosol schemes. This article describes the implementation of the new interface for assimilating PM2.5 and PM10 as well as four gas species (SO2, NO2, O3, and CO) on the ground. The effects of aerosol data assimilation are briefly examined through a month-long case study during the Korea–United States Air Quality (KORUS-AQ) period. It is demonstrated that the improved chemical initial conditions through the 3D-Var analysis can lead to consistent forecast improvements up to 26 %, reducing systematic bias errors in surface PM2.5 (PM10) concentrations to 0.0 (−1.9) µg m−3 over South Korea for 24 h.

Role of Upwind Precipitation in Transboundary Pollution and Secondary Aerosol Formation: A Case Study during the KORUS-AQ Field Campaign

Abstract Clouds and precipitation play critical roles in wet removal of aerosols and soluble gases in the atmosphere, and hence their accurate prediction largely influences accurate prediction of air pollutants. In this study, the impacts of clouds and precipitation on wet scavenging and long-range transboundary transport of pollutants are examined during the 2016 Korea–United States Air Quality (KORUS-AQ) field campaign using the Weather Research and Forecasting Model coupled with chemistry. Two simulations—one in which atmospheric moisture is constrained and one in which it is not—are performed and evaluated against surface and airborne observations. The simulation with moisture constraints is found to better reproduce precipitation as well as surface PM2.5, whereas the areal extent and amount of precipitation are overpredicted in the simulation without moisture constraints. As a results of overpredicted clouds and precipitation and consequently overpredicted wet scavenging, PM2.5 concentration is generally underpredicted across the model domain in the simulation without moisture constraints. The effects are significant not only in the precipitating region (upwind region, southern China in this study) but also in the downwind region (South Korea) where no precipitation is observed. The difference in upwind precipitation by 77% on average between the two simulations leads to the difference in PM2.5 by ∼39% both in the upwind and downwind regions. The transboundary transport of aerosol precursors, especially nitric acid, has a considerable impact on ammonium-nitrate aerosol formation in the ammonia-rich downwind region. This study highlights that skillful prediction of atmospheric moisture can have ultimate potential to skillful prediction of aerosols across regions.

Impacts of uncertainties in emissions on aerosol data assimilation and short-term PM2.5 predictions over Northeast Asia

To improve PM2.5 predictions in Northeast Asia, we estimated a new background error covariance matrix (BEC) for aerosol data assimilation using surface PM2.5 observations. In contrast to the conventional method of BEC estimation that uses perturbations in meteorological data, this method additionally considered the perturbations using two different emission inventories. By taking the emission uncertainty into account, we found that the standard deviations in the BEC were significantly increased. The standard deviations became around three times larger than those in the conventional method at the surface. The impacts of the new BEC were then tested for the prediction of surface PM2.5 over Northeast Asia using the Community Multiscale Air Quality (CMAQ) model initialized by three-dimensional variational method (3D-VAR). The surface PM2.5 data measured at 154 sites in South Korea and 1535 sites in China were assimilated every 6 h during the campaign period of the Korea-United States Air Quality Study (KORUS-AQ) (1 May–14 June 2016). The data assimilation with the new BEC showed better agreement with the surface PM2.5 observations than with the BEC from the conventional method. Our method was also more consistent with the observations in 24-h PM2.5 predictions than the conventional method (specifically, with a ∼44% reduction of negative biases). We concluded that increased standard deviations, together with updated horizontal and vertical length scales in the new BEC, improved the data assimilation and short-term predictions of the surface PM2.5. This paper also suggests several research efforts to further improve the BEC for better short-term PM2.5 predictions in Northeast Asia.