ALBERT

Description: KORUS-AQ was an international cooperative air quality field study in South Korea that measured local and remote sources of air pollution affecting the Korean Peninsula during May–June 2016. Some of the largest aerosol mass concentrations were measured during a Chinese haze transport event (24 May). Air quality forecasts using the WRF-Chem model with aerosol optical depth (AOD) data assimilation captured AOD during this pollution episode but overpredicted surface particulate matter concentrations in South Korea, especially PM2.5, often by a factor of 2 or larger. Analysis revealed multiple sources of model deficiency related to the calculation of optical properties from aerosol mass that explain these discrepancies. Using in situ observations of aerosol size and composition as inputs to the optical properties calculations showed that using a low-resolution size bin representation (four bins) underestimates the efficiency with which aerosols scatter and absorb light (mass extinction efficiency). Besides using finer-resolution size bins (8–16 bins), it was also necessary to increase the refractive indices and hygroscopicity of select aerosol species within the range of values reported in the literature to achieve better consistency with measured values of the mass extinction efficiency (6.7 m2 g−1 observed average) and light-scattering enhancement factor (f(RH)) due to aerosol hygroscopic growth (2.2 observed average). Furthermore, an evaluation of the optical properties obtained using modeled aerosol properties revealed the inability of sectional and modal aerosol representations in WRF-Chem to properly reproduce the observed size distribution, with the models displaying a much wider accumulation mode. Other model deficiencies included an underestimate of organic aerosol density (1.0 g cm−3 in the model vs. observed average of 1.5 g cm−3) and an overprediction of the fractional contribution of submicron inorganic aerosols other than sulfate, ammonium, nitrate, chloride, and sodium corresponding to mostly dust (17 %–28 % modeled vs. 12 % estimated from observations). These results illustrate the complexity of achieving an accurate model representation of optical properties and provide potential solutions that are relevant to multiple disciplines and applications such as air quality forecasts, health impact assessments, climate projections, solar power forecasts, and aerosol data assimilation.

Description: Atmospheric nitrogen deposition in China has attracted public attention in recent years due to the increasing anthropogenic emission of reactive nitrogen (Nr) and its impacts on the terrestrial and aquatic ecosystems. However, limited long-term and multisite measurements have restrained the understanding of the mechanism of the Nr deposition and the chemical transport model (CTM) improvement. In this study, the performance of the simulated wet and dry deposition for different Nr species, i.e., particulate NO3- and NH4+, gaseous NOx, HNO3 and NH3 have been conducted using the framework of Model Inter-Comparison Study for Asia (MICS-Asia) phase III. A total of nine models, including five Weather Research and Forecasting models coupled with the Community Multiscale Air Quality (WRF-CMAQ) models, two self-developed regional models, a global model and a Regional Atmospheric Modeling System coupled with the Community Multiscale Air Quality (RAMS-CMAQ) model have been selected for the comparison. For wet deposition, observation data from 83 measurement sites from the East Asia Acid Deposition Monitoring Network (EANET), Chinese Ecosystem Research Network (CERN), China Agricultural University Deposition Network (CAUDN), National Acid Deposition Monitoring Network (NADMN) and Department of Ecological Environment (DEE) of China have been collected and normalized for comparison with model results. In general, most models show the consistent spatial and temporal variation of both oxidized N (Nox) and reduced N (Nrd) wet deposition in China, with the normalized mean error (NME) at around 50 %, which is lower than the value of 70 % based on EANET observation over Asia. Both the ratio of wet or dry deposition to the total inorganic N (TIN) deposition and the ratios of TIN to their emissions have shown consistent results with the Nationwide Nitrogen Deposition Monitoring Network (NNDMN) estimates. The performance of ensemble results (ENMs) was further assessed with satellite measurements. In different regions of China, the results show that the simulated Nox wet deposition was overestimated in northeastern China (NE) but underestimated in the south of China, namely southeastern (SE) and southwestern (SW) China, while the Nrd wet deposition was underestimated in all regions by all models. The deposition of Nox has larger uncertainties than the Nrd, especially in northern China (NC), indicating the chemical reaction process is one of the most important factors affecting the model performance. Compared to the critical load (CL) value, the Nr deposition in NC, SE and SW reached or exceeded reported CL values and resulted in serious ecological impacts. The control of Nrd in NC and SW and Nox in SE would be an effective mitigation measure for TIN deposition in these regions. The Nr deposition in the Tibetan Plateau (TP) with a high ratio of TIN ∕ emission (∼3.0), indicates a significant transmission from outside. Efforts to reduce these transmissions ought to be paramount due the climatic importance of the Tibetan region to the sensitive ecosystems throughout China.

Description: 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.

Description: Organic aerosol (OA) is an important fraction of submicron aerosols. However, it is challenging to predict and attribute the specific organic compounds and sources that lead to observed OA loadings, largely due to contributions from secondary production. This is especially true for megacities surrounded by numerous regional sources that create an OA background. Here, we utilize in situ gas and aerosol observations collected on board the NASA DC-8 during the NASA–NIER KORUS-AQ (Korea–United States Air Quality) campaign to investigate the sources and hydrocarbon precursors that led to the secondary OA (SOA) production observed over Seoul. First, we investigate the contribution of transported OA to total loadings observed over Seoul by using observations over the Yellow Sea coupled to FLEXPART Lagrangian simulations. During KORUS-AQ, the average OA loading advected into Seoul was ∼1–3 µg sm−3. Second, taking this background into account, the dilution-corrected SOA concentration observed over Seoul was ∼140 µgsm-3ppmv-1 at 0.5 equivalent photochemical days. This value is at the high end of what has been observed in other megacities around the world (20–70 µgsm-3ppmv-1 at 0.5 equivalent days). For the average OA concentration observed over Seoul (13 µg sm−3), it is clear that production of SOA from locally emitted precursors is the major source in the region. The importance of local SOA production was supported by the following observations. (1) FLEXPART source contribution calculations indicate any hydrocarbons with a lifetime of less than 1 day, which are shown to dominate the observed SOA production, mainly originate from South Korea. (2) SOA correlated strongly with other secondary photochemical species, including short-lived species (formaldehyde, peroxy acetyl nitrate, sum of acyl peroxy nitrates, dihydroxytoluene, and nitrate aerosol). (3) Results from an airborne oxidation flow reactor (OFR), flown for the first time, show a factor of 4.5 increase in potential SOA concentrations over Seoul versus over the Yellow Sea, a region where background air masses that are advected into Seoul can be measured. (4) Box model simulations reproduce SOA observed over Seoul within 11 % on average and suggest that short-lived hydrocarbons (i.e., xylenes, trimethylbenzenes, and semi-volatile and intermediate-volatility compounds) were the main SOA precursors over Seoul. Toluene alone contributes 9 % of the modeled SOA over Seoul. Finally, along with these results, we use the metric ΔOA/ΔCO2 to examine the amount of OA produced per fuel consumed in a megacity, which shows less variability across the world than ΔOA∕ΔCO.

Description: Topic 3 of the Model Inter-Comparison Study for Asia (MICS-Asia) Phase III examines how online coupled air quality models perform in simulating high aerosol pollution in the North China Plain region during wintertime haze events and evaluates the importance of aerosol radiative and microphysical feedbacks. A comprehensive overview of the MICS-Asia III Topic 3 study design, including descriptions of participating models and model inputs, the experimental designs, and results of model evaluation, are presented. Six modeling groups from China, Korea and the United States submitted results from seven applications of online coupled chemistry–meteorology models. Results are compared to meteorology and air quality measurements, including data from the Campaign on Atmospheric Aerosol Research Network of China (CARE-China) and the Acid Deposition Monitoring Network in East Asia (EANET). The correlation coefficients between the multi-model ensemble mean and the CARE-China observed near-surface air pollutants range from 0.51 to 0.94 (0.51 for ozone and 0.94 for PM2.5) for January 2010. However, large discrepancies exist between simulated aerosol chemical compositions from different models. The coefficient of variation (SD divided by the mean) can reach above 1.3 for sulfate in Beijing and above 1.6 for nitrate and organic aerosols in coastal regions, indicating that these compositions are less consistent from different models. During clean periods, simulated aerosol optical depths (AODs) from different models are similar, but peak values differ during severe haze events, which can be explained by the differences in simulated inorganic aerosol concentrations and the hygroscopic growth efficiency (affected by varied relative humidity). These differences in composition and AOD suggest that future models can be improved by including new heterogeneous or aqueous pathways for sulfate and nitrate formation under hazy conditions, a secondary organic aerosol (SOA) formation chemical mechanism with new volatile organic compound (VOCs) precursors, yield data and approaches, and a more detailed evaluation of the dependence of aerosol optical properties on size distribution and mixing state. It was also found that using the ensemble mean of the models produced the best prediction skill. While this has been shown for other conditions (for example, the prediction of high-ozone events in the US (McKeen et al., 2005)), this is to our knowledge the first time it has been shown for heavy haze events.

Description: Accurate and consistent monitoring of anthropogenic combustion is imperative because of its significant health and environmental impacts, especially at city-to-regional scale. Here, we assess the performance of the Copernicus Atmosphere Monitoring Service (CAMS) global prediction system using measurements from aircraft, ground sites, and ships during the Korea-United States Air Quality (KORUS-AQ) field study in May to June 2016. Our evaluation focuses on CAMS CO and CO2 analyses as well as two higher-resolution forecasts (16 and 9 km horizontal resolution) to assess their capability in predicting combustion signatures over east Asia. Our results show a slight overestimation of CAMS CO2 with a mean bias against airborne CO2 measurements of 2.2, 0.7, and 0.3 ppmv for 16 and 9 km CO2 forecasts, and analyses, respectively. The positive CO2 mean bias in the 16 km forecast appears to be consistent across the vertical profile of the measurements. In contrast, we find a moderate underestimation of CAMS CO with an overall bias against airborne CO measurements of −19.2 (16 km), −16.7 (9 km), and −20.7 ppbv (analysis). This negative CO mean bias is mostly seen below 750 hPa for all three forecast/analysis configurations. Despite these biases, CAMS shows a remarkable agreement with observed enhancement ratios of CO with CO2 over the Seoul metropolitan area and over the West (Yellow) Sea, where east Asian outflows were sampled during the study period. More efficient combustion is observed over Seoul (dCO/dCO2=9 ppbv ppmv−1) compared to the West Sea (dCO/dCO2=28 ppbv ppmv−1). This “combustion signature contrast” is consistent with previous studies in these two regions. CAMS captured this difference in enhancement ratios (Seoul: 8–12 ppbv ppmv−1, the West Sea: ∼30 ppbv ppmv−1) regardless of forecast/analysis configurations. The correlation of CAMS CO bias with CO2 bias is relatively high over these two regions (Seoul: 0.64–0.90, the West Sea: ∼0.80) suggesting that the contrast captured by CAMS may be dominated by anthropogenic emission ratios used in CAMS. However, CAMS shows poorer performance in terms of capturing local-to-urban CO and CO2 variability. Along with measurements at ground sites over the Korean Peninsula, CAMS produces too high CO and CO2 concentrations at the surface with steeper vertical gradients (∼0.4 ppmv hPa−1 for CO2 and 3.5 ppbv hPa−1 for CO) in the morning samples than observed (∼0.25 ppmv hPa−1 for CO2 and 1.7 ppbv hPa−1 for CO), suggesting weaker boundary layer mixing in the model. Lastly, we find that the combination of CO analyses (i.e., improved initial condition) and use of finer resolution (9 km vs. 16 km) generally produces better forecasts.

Description: In this work, we investigate the NOx emissions inventory in Seoul, South Korea, using a regional ozone monitoring instrument (OMI) NO2 product derived from the standard NASA product. We first develop a regional OMI NO2 product by recalculating the air mass factors using a high-resolution (4 km × 4 km) WRF-Chem model simulation, which better captures the NO2 profile shapes in urban regions. We then apply a model-derived spatial averaging kernel to further downscale the retrieval and account for the subpixel variability. These two modifications yield OMI NO2 values in the regional product that are 1.37 times larger in the Seoul metropolitan region and 〉2 times larger near substantial point sources. These two modifications also yield an OMI NO2 product that is in better agreement with the Pandora NO2 spectrometer measurements acquired during the South Korea–United States Air Quality (KORUS-AQ) field campaign. NOx emissions are then derived for the Seoul metropolitan area during the KORUS-AQ field campaign using a top-down approach with the standard and regional NASA OMI NO2 products. We first apply the top-down approach to a model simulation to ensure that the method is appropriate: the WRF-Chem simulation utilizing the bottom-up emissions inventory yields a NOx emissions rate of 227±94 kt yr−1, while the bottom-up inventory itself within a 40 km radius of Seoul yields a NOx emissions rate of 198 kt yr−1. Using the top-down approach on the regional OMI NO2 product, we derive the NOx emissions rate from Seoul to be 484±201 kt yr−1, and a 353±146 kt yr−1 NOx emissions rate using the standard NASA OMI NO2 product. This suggests an underestimate of 53 % and 36 % in the bottom-up inventory using the regional and standard NASA OMI NO2 products respectively. To supplement this finding, we compare the NO2 and NOy simulated by WRF-Chem to observations of the same quantity acquired by aircraft and find a model underestimate. When NOx emissions in the WRF-Chem model are increased by a factor of 2.13 in the Seoul metropolitan area, there is better agreement with KORUS-AQ aircraft observations and the recalculated OMI NO2 tropospheric columns. Finally, we show that by using a WRF-Chem simulation with an updated emissions inventory to recalculate the air mass factor (AMF), there are small differences (∼8 %) in OMI NO2 compared to using the original WRF-Chem simulation to derive the AMF. This suggests that changes in model resolution have a larger effect on the AMF calculation than modifications to the South Korean emissions inventory. Although the current work is focused on South Korea using OMI, the methodology developed in this work can be applied to other world regions using TROPOMI and future satellite datasets (e.g., GEMS and TEMPO) to produce high-quality region-specific top-down NOx emissions estimates.

Description: The MIX inventory is developed for the years 2008 and 2010 to support the Model Inter-Comparison Study for Asia (MICS-Asia) and the Task Force on Hemispheric Transport of Air Pollution (TF HTAP) by a mosaic of up-to-date regional emission inventories. Emissions are estimated for all major anthropogenic sources in 29 countries and regions in Asia. We conducted detailed comparisons of different regional emission inventories and incorporated the best available ones for each region into the mosaic inventory at a uniform spatial and temporal resolution. Emissions are aggregated to five anthropogenic sectors: power, industry, residential, transportation, and agriculture. We estimate the total Asian emissions of 10 species in 2010 as follows: 51.3 Tg SO2, 52.1 Tg NOx, 336.6 Tg CO, 67.0 Tg NMVOC (non-methane volatile organic compounds), 28.8 Tg NH3, 31.7 Tg PM10, 22.7 Tg PM2.5, 3.5 Tg BC, 8.3 Tg OC, and 17.3 Pg CO2. Emissions from China and India dominate the emissions of Asia for most of the species. We also estimated Asian emissions in 2006 using the same methodology of MIX. The relative change rates of Asian emissions for the period of 2006–2010 are estimated as follows: −8.1 % for SO2, +19.2 % for NOx, +3.9 % for CO, +15.5 % for NMVOC, +1.7 % for NH3, −3.4 % for PM10, −1.6 % for PM2.5, +5.5 % for BC, +1.8 % for OC, and +19.9 % for CO2. Model-ready speciated NMVOC emissions for SAPRC-99 and CB05 mechanisms were developed following a profile-assignment approach. Monthly gridded emissions at a spatial resolution of 0.25°  ×  0.25° are developed and can be accessed from http://www.meicmodel.org/dataset-mix.

Description: Topic 3 of the Model Inter-Comparison Study for Asia (MICS-Asia) Phase III examines how online coupled air quality models perform in simulating wintertime haze events in the North China Plain region and evaluates the importance of aerosol radiative feedbacks. This paper discusses the estimates of aerosol radiative forcing, aerosol feedbacks, and possible causes for the differences among the participating models. Over the Beijing–Tianjin–Hebei (BTH) region, the ensemble mean of estimated aerosol direct radiative forcing (ADRF) at the top of atmosphere, inside the atmosphere, and at the surface are −1.1, 7.7, and −8.8 W m−2 during January 2010, respectively. Subdivisions of direct and indirect aerosol radiative forcing confirm the dominant role of direct forcing. During severe haze days (17–19 January 2010), the averaged reduction in near-surface temperature for the BTH region can reach 0.3–1.6 ∘C. The responses of wind speeds at 10 m (WS10) inferred from different models show consistent declines in eastern China. For the BTH region, aerosol–radiation feedback-induced daytime changes in PM2.5 concentrations during severe haze days range from 6.0 to 12.9 µg m−3 (

Description: In this work, we investigate the NOx emissions inventory in Seoul, South Korea using a regional NASA Ozone Monitoring Instrument (OMI) NO2 product. We first develop a regional OMI NO2 product by re-calculating the air mass factors using a high-resolution (4×4km2) WRF-Chem model simulation, which better captures the NO2 shape profiles in urban regions. We then apply a model-derived spatial averaging kernel to further downscale the retrieval and account for the sub-pixel variability. These two modifications yield OMI NO2 values in the regional product that are 1.37 larger in the Seoul metropolitan region and 〉2 times larger near large industrial sources. These two modifications also yield an OMI NO2 product that is in better agreement with the Pandora NO2 spectrometer measurements acquired during the Korea U.S.-Air Quality (KORUS-AQ) field campaign. NOx emissions are then derived for the Seoul metropolitan area during the KORUS-AQ field campaign using a top-down approach with the standard and regional NASA OMI NO2 products. We first apply the top-down approach to a model simulation to ensure that the method is appropriate: the WRF-Chem simulation utilizing the bottom-up emission inventory yields a NOx emission rate of 227±94kton/yr, while the bottom-up inventory itself yields a NOx emission rate of 198kton/yr. Using the top-down approach on the regional OM NO2 product, we derive the NOx emissions rate from Seoul to be 484±201kton/yr, and a 353±146kton/yr NOx emissions rate using the standard NASA OMI NO2 product. This suggests an underestimate of 53% and 36% using the regional and standard NASA OMI NO2 products respectively. To supplement this finding, we compare the NO2 simulated by WRF-Chem to observations of the same quantity acquired by aircraft and find a model underestimate. When NOx emissions in the WRF-Chem model are doubled, there is better agreement with KORUS-AQ aircraft observations. Although the current work is focused on South Korea using OMI, the methodology developed in this work can be applied to other world regions using TROPOMI and future satellite datasets (e.g., GEMS and TEMPO) to produce high-quality region-specific top-down NOx emission estimates.