Boundary layer versus free tropospheric submicron particle formation: A case study from NASA DC-8 observations in the Asian continental outflow during the KORUS-AQ campaign.

In this study, we contrasted major secondary inorganic species and processes responsible for submicron particle formation (SPF) events in the boundary layer (BL) and free troposphere (FT) over the Korean Peninsula during Korea-United States Air Quality (KORUS-AQ) campaign (May-June, 2016) using aircraft observations. The number concentration of ultrafine particles with diameters between 3 nm and 10 nm (NCN3-10) during the entire KORUS-AQ period reached a peak (7,606 ± 12,003 cm -3) at below 1 km altitude, implying that the particle formation around the Korean Peninsula primarily occurred in the daytime BL. During the BL SPF case (7 May, 2016), the SPF over Seoul metropolitan area was more attributable to oxidation of NO2 rather than SO2-to-sulfate conversion. From the analysis of the relationship between nitrogen oxidation ratio (NOR) and temperature or relative humidity (RH), NOR showed a positive correlation only with temperature. This suggests that homogeneous gas-phase reactions of NO2 with OH or O3 contributed to nitrate formation. From the relationship between NCN3-10 (> 10,000 cm-3) and the NOR (or sulfur oxidation ratio) at Olympic Park in Seoul during the entire KORUS-AQ period, it was regarded that the relative importance of nitrogen oxidation was grown as the NCN3-10 increased. During the FT SPF case (31 May, 2016) over the yellow sea, the SO2-to-sulfate conversion seemed to influence SPF highly. The sulfate/CO ratio had a positive correlation with both the temperature and RH, suggesting that aqueous-phase pathways as well as gas-phase reactions might be attributable to sulfate formation in the FT. In particular, FT SPF event on 31 May was possibly caused by the direct transport of SO2 precursors from the continent above the shallow marine boundary layer under favorable conditions for FT SPF events, such as decreased aerosol surface area and increased solar radiation.

OH reactivity in urban and suburban regions in Seoul, South Korea - an East Asian megacity in a rapid transition.

South Korea has recently achieved developed country status with the second largest megacity in the world, the Seoul Metropolitan Area (SMA). This study provides insights into future changes in air quality for rapidly emerging megacities in the East Asian region. We present total OH reactivity observations in the SMA conducted at an urban Seoul site (May-June, 2015) and a suburban forest site (Sep, 2015). The total OH reactivity in an urban site during the daytime was observed at similar levels (∼15 s(-1)) to those previously reported from other East Asian megacity studies. Trace gas observations indicate that OH reactivity is largely accounted for by NOX (∼50%) followed by volatile organic compounds (VOCs) (∼35%). Isoprene accounts for a substantial fraction of OH reactivity among the comprehensive VOC observational dataset (25-47%). In general, observed total OH reactivity can be accounted for by the observed trace gas dataset. However, observed total OH reactivity in the suburban forest area cannot be largely accounted for (∼70%) by the trace gas measurements. The importance of biogenic VOC (BVOCs) emissions and oxidations used to evaluate the impacts of East Asian megacity outflows for the regional air quality and climate contexts are highlighted in this study.

Existence of typical winter atmospheric circulation patterns leading to high PM2.5 concentration days in East Asia.

Understanding the atmospheric circulation patterns responsible for severe air pollution events in East Asia is important because East Asia is one of the most polluted regions in the world, particularly during the boreal winter (December-January-February). Here, by conducting GEOS-Chem simulation with fixed anthropogenic emission sources, we found that there exist three typical atmospheric circulation patterns conducive to leading to high concentrations of particulate matter with a diameter less than or equal to 2.5 µm (PM2.5) in East Asia. These atmospheric circulation patterns are characterized by weakened horizontal winds, which allows PM2.5 to accumulate, and by enhanced relative humidity, which can favor secondary formation of PM2.5. The occurrence of these atmospheric circulation patterns is associated with increased sea ice cover over the Barents Sea and heavy precipitation over the tropical western Indian Ocean. The existence of these atmospheric circulation patterns among typical atmospheric circulation patterns indicates high PM2.5 days in East Asia are unavoidable given current level of anthropogenic emissions in the region. This conclusion indicates that sustained efforts to reduce anthropogenic emission sources in East Asia should be warranted to avoid high PM2.5 days.

Can climate indices forecast daily variations of wintertime PM2.5 concentrations in East Asia?

Synoptic meteorological variability plays an important role in determining air quality. In East Asia, the expansion and contraction of the Siberian high-pressure system is an essential mechanism for determining surface particulate matter concentrations (PM2.5) during the winter season. Here, we selected four climate indices that reflected the variability of the Siberian high-pressure system and analyzed their correlation with the daily variability of the observed winter PM2.5 concentrations in China and South Korea over the past six years (2014/15-2019/20). Siberian High Intensity (SHI) and East Asian Winter Monsoon (EAWM) indices were good indicators of daily PM2.5 concentration changes. Two to four days after the daily SHI and EAWM indices exceed the threshold (±1), the daily PM2.5 concentrations in East Asia significantly increased or decreased, up to 40 % compared to the mean winter PM2.5 concentrations. The climate indices associated with the Siberian high-pressure system thus potentially effectively forecast the daily PM2.5 concentrations in East Asia within a period of one week.

Future air quality and premature mortality in Korea.

We simulate air quality in Korea for the present, the near-term, and the long-term future conditions under the Shared Socioeconomic Pathways (SSP1: most sustainable pathway with strong emissions control, SSP3: most challenging pathway with mild emissions control) using a chemical transport model. Simulated future concentrations of NO2, SO2, and fine particulate matter (PM2.5), show, in general, lower values compared to the present with varying degrees depending on SSP scenarios. Significant reductions in precursor emissions result in a decrease in O3 concentrations under a NOx-limited environment in the long-term future under SSP1. Under SSP3, O3 increases in the future under a VOC-limited regime, driven by increased CH4 levels and biogenic VOC emissions under the warming climate. Concentrations of PM2.5 and its components, including sulfate, nitrate, ammonium, and organic aerosols (OA), generally decrease in the long-term future under both scenarios. However, the contribution of biogenic secondary OA (BSOA) to PM2.5 will increase in the future. Simulated results are used to estimate cardiorespiratory mortality changes with concentration-response factors from epidemiologic studies in Korea based on national health surveys and Korean cohorts, using projected population structures from the SSP database. The cardiorespiratory health burden of long-term exposure to O3, NO2, SO2, and PM2.5 is estimated to be 10,419 (95 % confidence interval: 1271-17,142), 8630 (0-18,713), 3958 (0-9272), and 10,431 (1411-20,643) deaths in 2019. We find that the total cardiorespiratory excess mortality due to air pollutants under SSP1 decreases by 8 % and 95 % in 2045 and 2095, respectively. Under SSP3, excess mortality increases by 80 % in 2045, and decreases by 22 % in 2095, resulting in a substantial difference in the health outcomes depending on the emission scenario. We also find that the BSOA contribution to total PM2.5 will differ by region, emphasizing the potential health impact of BSOA on a local scale in the future.

Intrinsic atmospheric circulation patterns associated with high PM2.5 concentration days in South Korea during the cold season.

Based on observation data and a novel K-mean clustering method, we investigated whether intrinsic atmospheric circulation patterns are related with the occurrence of high particulate matter (PM) concentration days (diameters less than or equal to 2.5 µm (PM2.5)), in Seoul, South Korea, during the cold season (December to March). A simple composite map shows that weak horizontal and vertical ventilation over the Korean Peninsula can cause high PM2.5 concentration (High_PM2.5) days. Also, atmospheric circulations are quite different between one day of High_PM2.5 and periods longer than two days. We also found that two intrinsic atmospheric circulation patterns in Asia, which were obtained by adopting K-mean clustering to the daily 850 hPa geopotential height anomalies for 2005-2020, were associated with High_PM2.5 days. These results indicate that High_PM2.5 days in Seoul, South Korea, occur as a result of intrinsic atmospheric circulation patterns, therefore, they are unavoidable unless the anthropogenic emission sources over the Korean Peninsula, East Asia, or both are reduced. In addition, these two intrinsic atmospheric circulation patterns are more prominent for periods longer than two days while there are no favorable intrinsic atmospheric circulation patterns to induce one day of High_PM2.5, which indicates that a single day of High_PM2.5 tends to occur by a stochastic atmospheric circulation rather than the intrinsic atmospheric circulation patterns.

Sulfur isotope-based source apportionment and control mechanisms of PM2.5 sulfate in Seoul, South Korea during winter and early spring (2017-2020).

High level of particulate matter (PM) concentrations are a major environmental concern in Seoul, South Korea, especially during winter and early spring. Sulfate is a major component of PM and induces severe environmental pollution, such as acid precipitation. Previous studies have used numerical models to constrain the relative contributions of domestic and trans-boundary sources to PM2.5 sulfate concentration in South Korea. Because of the scarce measurement result of δ34S for PM2.5 sulfate in South Korea, poorly defined δ34S value of domestic sulfur sources, and no application of sulfur isotope fractionation during sulfate formation in previous observation-based studies, source apportionment results conducted by model studies have not been corroborated from independent chemical observations. Here, we examined the δ34S of PM2.5 in Seoul and domestic sulfur sources, and considered the sulfur isotope fractionation for accurate source apportionment constraint. Accordingly, domestic and trans-boundary sulfur sources accounted for approximately (16-32) % and (68-84) % of the sulfate aerosols in Seoul, respectively, throughout the winter and early spring of 2017-2020. Air masses passing through north-eastern China had relatively low sulfate concentrations, enriched δ34S, and a low domestic source contribution. Those passing through south-eastern China had relatively a high sulfate concentrations, depleted δ34S, and high domestic source contribution. Furthermore, elevated PM2.5 sulfate concentrations (>10 µg m-3) were exclusively associated with a weak westerly wind speed of <3 m s-1. From December 2019 to March 2020, Seoul experienced relatively low levels of PM2.5 sulfate, which might be attributed to favorable weather conditions rather than the effects of COVID-19 containment measures. Our results demonstrate the potential use of δ34S for accurate source apportionment and for identifying the crucial role of regional air mass transport and meteorological conditions in PM2.5 sulfate concentration. Furthermore, the data provided can be essential for relevant studies and policy-making in East Asia.

Factors determining the seasonal variation of ozone air quality in South Korea: Regional background versus domestic emission contributions.

South Korea has experienced a rapid increase in ozone concentrations in surface air together with China for decades. Here we use a 3-D global chemical transport model, GEOS-Chem nested over East Asia (110 E - 140 E, 20 N-50 N) at 0.25° × 0.3125° resolution, to examine locally controllable (domestic anthropogenic) versus uncontrollable (background) contributions to ozone air quality at the national scale for 2016. We conducted model simulations for representative months of each season: January, April, July, and October for winter, spring, summer, and fall and performed extensive model evaluation by comparing simulated ozone with observations from satellite and surface networks. The model appears to reproduce observed spatial and temporal ozone variations, showing correlation coefficients (0.40-0.87) against each observation dataset. Seasonal mean ozone concentrations in the model are the highest in spring (39.3 ± 10.3 ppb), followed by summer (38.3 ± 14.4 ppb), fall (31.2 ± 9.8 ppb), and winter (24.5 ± 7.9 ppb), which is consistent with that of surface observations. Background ozone concentrations obtained from a sensitivity model simulation with no domestic anthropogenic emissions show a different seasonal variation in South Korea, showing the highest value in spring (46.9 ± 3.4 ppb) followed by fall (38.2 ± 3.7 ppb), winter (33.0 ± 1.9 ppb), and summer (32.1 ± 6.7 ppb). Except for summer, when the photochemical formation is dominant, the background ozone concentrations are higher than the seasonal ozone concentrations in the model, indicating that the domestic anthropogenic emissions play a role as ozone loss via NOx titration throughout the year. Ozone air quality in South Korea is determined mainly by year-round regional background contributions (peak in spring) with summertime domestic ozone formation by increased biogenic VOCs emissions with persistent NOx emissions throughout the year. The domestic NOx emissions reduce MDA8 ozone around large cities (Seoul and Busan) and hardly increase MDA8 in other regions in spring, but it increases MDA8 across the country in summer. Therefore, NOx reduction can be effective in control of MDA8 ozone in summer, but it can have rather countereffect in spring.

Ozone pollution threatens the production of major staple crops in East Asia.

East Asia is a hotspot of surface ozone (O3) pollution, which hinders crop growth and reduces yields. Here, we assess the relative yield loss in rice, wheat and maize due to O3 by combining O3 elevation experiments across Asia and air monitoring at about 3,000 locations in China, Japan and Korea. China shows the highest relative yield loss at 33%, 23% and 9% for wheat, rice and maize, respectively. The relative yield loss is much greater in hybrid than inbred rice, being close to that for wheat. Total O3-induced annual loss of crop production is estimated at US$63 billion. The large impact of O3 on crop production urges us to take mitigation action for O3 emission control and adaptive agronomic measures against the rising surface O3 levels across East Asia.

An Inversion Framework for Optimizing Non-Methane VOC Emissions Using Remote Sensing and Airborne Observations in Northeast Asia During the KORUS-AQ Field Campaign.

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.

Foraging trip duration of honeybee increases during a poor air quality episode and the increase persists thereafter.

Increased concentration of airborne particulate matter (PM) in the atmosphere alters the degree of polarization of skylight which is used by honeybees for navigation during their foraging trips. However, little has empirically shown whether poor air quality indeed affects foraging performance (foraging trip duration) of honeybee. Here, we show apparent increases in the average duration of honeybee foraging during and after a heavy air pollution event compared with that of the pre-event period. The average foraging duration of honeybees during the event increased by 32 min compared with the pre-event conditions, indicating that 71% more time was spent on foraging. Moreover, the average foraging duration measured after the event did not recover to its pre-event level. We further investigated whether an optical property (Depolarization Ratio, DR) of dominant PM in the atmosphere and level of air pollution (fine PM mass concentration) affect foraging trip duration. The result demonstrates the DR and fine PM mass concentration have significant effects on honeybee foraging trip duration. Foraging trip duration increases with decreasing DR while it increases with increasing fine PM mass concentration. In addition, the effects of fine PM mass concentration are synergistic with overcast skies. Our study implies that poor air quality could pose a new threat to bee foraging.

Light-absorption enhancement of black carbon in the Asian outflow inferred from airborne SP2 and in-situ measurements during KORUS-AQ.

We investigated the changes in the size distribution, coating thickness, and mass absorption cross-section (MAC) of black carbon (BC) with aging and estimated the light absorption enhancement (Eabs) in the Asian outflow from airborne in-situ measurements during 2016 KORUS-AQ campaign. The BC number concentration decreased, but mass mean diameter increased with increasing altitude in the West Coast (WC) and Seoul Metropolitan Area (SMA), reflecting the contrast between freshly emitted BC-containing particles at the surface and more aged aerosol associated with aggregation during vertical mixing and transport. Contradistinctively, BC number and mass size distributions were relatively invariant with altitude over the Yellow Sea (YS) because sufficiently aged BC from eastern China were horizontally transported to all altitudes over the YS, and there are no significant sources at the surface. The averaged inferred MAC of refractory BC in three regions reflecting differences in their size distributions increased to 9.8 ± 1.0 m2 g-1 (YS), 9.3 ± 0.9 m2 g-1 (WC), and 8.2 ± 0.9 m2 g-1 (SMA) as BC coating thickness increased from 20 nm to 120 nm. The absorption coefficient of BC calculated from the coating thickness and MAC were highly correlated with the filter-based absorption measurements with the slope of 1.16 and R2 of 0.96 at 550 nm, revealing that the thickly coated BC had a large MAC and absorption coefficient. The Eabs due to the inferred coatings was estimated as 1.0-1.6, which was about 30% lower than those from climate models and laboratory experiments, suggesting that the increase in the BC absorption by the coatings in the Asian outflow is not as large as calculated in the previous studies. Organics contributed to the largest Eabs accounting for 69% (YS), 61% (WC), and 64% (SMA). This implies that organics are largely responsible for the lensing effect of BC rather than sulfates in the Asian outflow.

The Korea-United States Air Quality (KORUS-AQ) field study.

The Korea-United States Air Quality (KORUS-AQ) field study was conducted during May-June 2016. The effort was jointly sponsored by the National Institute of Environmental Research of South Korea and the National Aeronautics and Space Administration of the United States. KORUS-AQ offered an unprecedented, multi-perspective view of air quality conditions in South Korea by employing observations from three aircraft, an extensive ground-based network, and three ships along with an array of air quality forecast models. Information gathered during the study is contributing to an improved understanding of the factors controlling air quality in South Korea. The study also provided a valuable test bed for future air quality-observing strategies involving geostationary satellite instruments being launched by both countries to examine air quality throughout the day over Asia and North America. This article presents details on the KORUS-AQ observational assets, study execution, data products, and air quality conditions observed during the study. High-level findings from companion papers in this special issue are also summarized and discussed in relation to the factors controlling fine particle and ozone pollution, current emissions and source apportionment, and expectations for the role of satellite observations in the future. Resulting policy recommendations and advice regarding plans going forward are summarized. These results provide an important update to early feedback previously provided in a Rapid Science Synthesis Report produced for South Korean policy makers in 2017 and form the basis for the Final Science Synthesis Report delivered in 2020.

Estimation of spatially continuous daytime particulate matter concentrations under all sky conditions through the synergistic use of satellite-based AOD and numerical models.

Satellite-derived aerosol optical depth (AOD) products are one of main predictors to estimate ground-level particulate matter (PM10 and PM2.5) concentrations. Since AOD products, however, are only provided under high-quality conditions, missing values usually exist in areas such as clouds, cloud shadows, and bright surfaces. In this study, spatially continuous AOD and subsequent PM10 and PM2.5 concentrations were estimated over East Asia using satellite- and model-based data and auxiliary data in a Random Forest (RF) approach. Data collected from the Geostationary Ocean Color Imager (GOCI; 8 times per day) in 2016 were used to develop AOD and PM models. Three schemes (i.e. G1, A1, and A2) were proposed for AOD modeling according to target AOD data (GOCI AOD and AERONET AOD) and the existence of satellite-derived AOD. The A2 scheme showed the best performance (validation R2 of 0.74 and prediction R2 of 0.73 when GOCI AOD did not exist) and the resultant AOD was used to estimate spatially continuous PM concentrations. The PM models with location information produced successful estimation results with R2 of 0.88 and 0.90, and rRMSE of 26.9 and 27.2% for PM10 and PM2.5, respectively. The spatial distribution maps of PM well captured the seasonal and spatial characteristics of PM reported in the literature, which implies the proposed approaches can be adopted for an operational estimation of spatially continuous AOD and PMs under all sky conditions.

Projections of excess mortality related to diurnal temperature range under climate change scenarios: a multi-country modelling study.

BACKGROUND: Various retrospective studies have reported on the increase of mortality risk due to higher diurnal temperature range (DTR). This study projects the effect of DTR on future mortality across 445 communities in 20 countries and regions. METHODS: DTR-related mortality risk was estimated on the basis of the historical daily time-series of mortality and weather factors from Jan 1, 1985, to Dec 31, 2015, with data for 445 communities across 20 countries and regions, from the Multi-Country Multi-City Collaborative Research Network. We obtained daily projected temperature series associated with four climate change scenarios, using the four representative concentration pathways (RCPs) described by the Intergovernmental Panel on Climate Change, from the lowest to the highest emission scenarios (RCP 2.6, RCP 4.5, RCP 6.0, and RCP 8.5). Excess deaths attributable to the DTR during the current (1985-2015) and future (2020-99) periods were projected using daily DTR series under the four scenarios. Future excess deaths were calculated on the basis of assumptions that warmer long-term average temperatures affect or do not affect the DTR-related mortality risk. FINDINGS: The time-series analyses results showed that DTR was associated with excess mortality. Under the unmitigated climate change scenario (RCP 8.5), the future average DTR is projected to increase in most countries and regions (by -0·4 to 1·6°C), particularly in the USA, south-central Europe, Mexico, and South Africa. The excess deaths currently attributable to DTR were estimated to be 0·2-7·4%. Furthermore, the DTR-related mortality risk increased as the long-term average temperature increased; in the linear mixed model with the assumption of an interactive effect with long-term average temperature, we estimated 0·05% additional DTR mortality risk per 1°C increase in average temperature. Based on the interaction with long-term average temperature, the DTR-related excess deaths are projected to increase in all countries or regions by 1·4-10·3% in 2090-99. INTERPRETATION: This study suggests that globally, DTR-related excess mortality might increase under climate change, and this increasing pattern is likely to vary between countries and regions. Considering climatic changes, our findings could contribute to public health interventions aimed at reducing the impact of DTR on human health. FUNDING: Korea Ministry of Environment.

Investigation of factors controlling PM2.5 variability across the South Korean Peninsula during KORUS-AQ.

The Korea - United States Air Quality Study (May - June 2016) deployed instrumented aircraft and ground-based measurements to elucidate causes of poor air quality related to high ozone and aerosol concentrations in South Korea. This work synthesizes data pertaining to aerosols (specifically, particulate matter with aerodynamic diameters <2.5 micrometers, PM2.5) and conditions leading to violations of South Korean air quality standards (24-hr mean PM2.5 < 35 µg m-3). PM2.5 variability from AirKorea monitors across South Korea is evaluated. Detailed data from the Seoul vicinity are used to interpret factors that contribute to elevated PM2.5. The interplay between meteorology and surface aerosols, contrasting synoptic-scale behavior vs. local influences, is presented. Transboundary transport from upwind sources, vertical mixing and containment of aerosols, and local production of secondary aerosols are discussed. Two meteorological periods are probed for drivers of elevated PM2.5. Clear, dry conditions, with limited transport (Stagnant period), promoted photochemical production of secondary organic aerosol from locally emitted precursors. Cloudy humid conditions fostered rapid heterogeneous secondary inorganic aerosol production from local and transported emissions (Transport/Haze period), likely driven by a positive feedback mechanism where water uptake by aerosols increased gas-to-particle partitioning that increased water uptake. Further, clouds reduced solar insolation, suppressing mixing, exacerbating PM2.5 accumulation in a shallow boundary layer. The combination of factors contributing to enhanced PM2.5 is challenging to model, complicating quantification of contributions to PM2.5 from local versus upwind precursors and production. We recommend co-locating additional continuous measurements at a few AirKorea sites across South Korea to help resolve this and other outstanding questions: carbon monoxide/carbon dioxide (transboundary transport tracer), boundary layer height (surface PM2.5 mixing depth), and aerosol composition with aerosol liquid water (meteorologically-dependent secondary production). These data would aid future research to refine emissions targets to further improve South Korean PM2.5 air quality.

Efficacy of dust aerosol forecasts for East Asia using the adjoint of GEOS-Chem with ground-based observations.

Asian dust storms occur often and have a great impact on East Asia and the western Pacific in spring. Early warnings based on reliable forecasts of dust storms thus are crucial for protecting human health and industry. Here we explore the efficacy of 4-D variational method-based data assimilation in a chemical transport model for dust storm forecasts in East Asia. We use a 3-D global chemical transport model (GEOS-Chem) and its adjoint model with surface PM10 mass concentration observations. We evaluate the model for several severe dust storm events, which occurred in May 2007 and March 2011 in East Asia. First of all, simulated the PM10 mass concentrations with the forward model showed large discrepancies compared with PM10 mass concentrations observed in China, Korea, and Japan, implying large uncertainties of simulated dust emission fluxes in the source regions. Based on our adjoint model constrained by observations for the whole period of each event, the reproduction of the spatial and temporal distributions of observations over East Asia was substantially improved (regression slopes from 0.15 to 2.81 to 0.85-1.02 and normalized mean biases from -74%-151% to -34%-1%). We then examine the efficacy of the data assimilation system for daily dust storm forecasts based on the adjoint model including previous day observations to update the initial condition of the forward model simulation for the next day. The forecast results successfully captured the spatial and temporal variations of ground-based observations in downwind regions, indicating that the data assimilation system with ground-based observations effectively forecasts dust storms, especially in downwind regions. However, the efficacy is limited in nearby the dust source regions, including Mongolia and North China, due to the lack of observations for constraining the model.

Dissimilar effects of two El Niño types on PM2.5 concentrations in East Asia.

We investigate the effects of natural variability of meteorological fields on surface PM2.5 concentration changes in East Asia during El Niño periods for the past three decades (1980-2014) through GEOS-Chem 3D global chemical transport model simulations. First, our evaluation of the model with anthropogenic emissions for 2006 and a comparison against observations show that the simulated results accurately reproduced the observed spatial distribution of annual mean aerosol concentrations for 2006-2007 including inorganic (sulfate, ammonium, and nitrate) and carbonaceous (organic and black carbon) aerosols in the surface air. Based on the Oceanic Niño Index, the assimilated meteorological data used in the model simulations indicate that 10 El Niño events occurred for the past three decades (1980-2014). We further classified the 10 El Niño events into 6 central Pacific El Niño (C-type) and 4 eastern Pacific El Niño (E-type) to examine the different roles of two El Niño types in determining seasonal surface PM2.5 concentrations in East Asia. We find opposite impacts on the seasonal surface PM2.5 concentrations depending on two El Niño types, such that the surface PM2.5 concentrations during the E-type period are higher than the climatological mean value, especially in northern East Asia. The peak increase of as much as 20% occurs in winter and is sustained until the following spring. However, the C-type period shows a decrease in seasonal PM2.5 concentrations in northern East Asia compare to the climatological mean, and the peak decrease of as much as 10% occurs in the following spring. The different of two El Niño types also have dissimilar impacts on surface PM2.5 concentrations in southeastern China. Natural variation of aerosol concentrations driven by the different of two El Niño types appears to be significant and would be an important factor in determining the inter-annual variation of aerosol concentrations in East Asia.

Impacts of different characterizations of large-scale background on simulated regional-scale ozone over the continental United States.

This study analyzes simulated regional-scale ozone burdens both near the surface and aloft, estimates process contributions to these burdens, and calculates the sensitivity of the simulated regional-scale ozone burden to several key model inputs with a particular emphasis on boundary conditions derived from hemispheric or global-scale models. The Community Multiscale Air Quality (CMAQ) model simulations supporting this analysis were performed over the continental US for the year 2010 within the context of the Air Quality Model Evaluation International Initiative (AQMEII) and Task Force on Hemispheric Transport of Air Pollution (TF-HTAP) activities. CMAQ process analysis (PA) results highlight the dominant role of horizontal and vertical advection on the ozone burden in the mid-to-upper troposphere and lower stratosphere. Vertical mixing, including mixing by convective clouds, couples fluctuations in free-tropospheric ozone to ozone in lower layers. Hypothetical bounding scenarios were performed to quantify the effects of emissions, boundary conditions, and ozone dry deposition on the simulated ozone burden. Analysis of these simulations confirms that the characterization of ozone outside the regional-scale modeling domain can have a profound impact on simulated regional-scale ozone. This was further investigated by using data from four hemispheric or global modeling systems (Chemistry - Integrated Forecasting Model (C-IFS), CMAQ extended for hemispheric applications (H-CMAQ), the Goddard Earth Observing System model coupled to chemistry (GEOS-Chem), and AM3) to derive alternate boundary conditions for the regional-scale CMAQ simulations. The regional-scale CMAQ simulations using these four different boundary conditions showed that the largest ozone abundance in the upper layers was simulated when using boundary conditions from GEOS-Chem, followed by the simulations using C-IFS, AM3, and H-CMAQ boundary conditions, consistent with the analysis of the ozone fields from the global models along the CMAQ boundaries. Using boundary conditions from AM3 yielded higher springtime ozone columns burdens in the middle and lower troposphere compared to boundary conditions from the other models. For surface ozone, the differences between the AM3-driven CMAQ simulations and the CMAQ simulations driven by other large-scale models are especially pronounced during spring and winter where they can reach more than 10 ppb for seasonal mean ozone mixing ratios and as much as 15 ppb for domain-averaged daily maximum 8 h average ozone on individual days. In contrast, the differences between the C-IFS-, GEOS-Chem-, and H-CMAQ-driven regional-scale CMAQ simulations are typically smaller. Comparing simulated sur face ozone mixing ratios to observations and computing seasonal and regional model performance statistics revealed that boundary conditions can have a substantial impact on model performance. Further analysis showed that boundary conditions can affect model performance across the entire range of the observed distribution, although the impacts tend to be lower during summer and for the very highest observed percentiles. The results are discussed in the context of future model development and analysis opportunities.

HTAP2 multi-model estimates of premature human mortality due to intercontinental transport of air pollution and emission sectors.

Ambient air pollution from ozone and fine particulate matter is associated with premature mortality. As emissions from one continent influence air quality over others, changes in emissions can also influence human health on other continents. We estimate global air pollution-related premature mortality from exposure to PM2.5 and ozone, and the avoided deaths from 20% anthropogenic emission reductions from six source regions, North America (NAM), Europe (EUR), South Asia (SAS), East Asia (EAS), Russia/Belarus/Ukraine (RBU) and the Middle East (MDE), three global emission sectors, Power and Industry (PIN), Ground Transportation (TRN) and Residential (RES) and one global domain (GLO), using an ensemble of global chemical transport model simulations coordinated by the second phase of the Task Force on Hemispheric Transport of Air Pollution (TF-HTAP2), and epidemiologically-derived concentration-response functions. We build on results from previous studies of the TF-HTAP by using improved atmospheric models driven by new estimates of 2010 anthropogenic emissions (excluding methane), with more source and receptor regions, new consideration of source sector impacts, and new epidemiological mortality functions. We estimate 290,000 (95% CI: 30,000, 600,000) premature O3-related deaths and 2.8 million (0.5 million, 4.6 million) PM2.5-related premature deaths globally for the baseline year 2010. While 20% emission reductions from one region generally lead to more avoided deaths within the source region than outside, reducing emissions from MDE and RBU can avoid more O3-related deaths outside of these regions than within, and reducing MDE emissions also avoids more PM2.5-related deaths outside of MDE than within. Our findings that most avoided O3-related deaths from emission reductions in NAM and EUR occur outside of those regions contrast with those of previous studies, while estimates of PM2.5-related deaths from NAM, EUR, SAS and EAS emission reductions agree well. In addition, EUR, MDE and RBU have more avoided O3-related deaths from reducing foreign emissions than from domestic reductions. For six regional emission reductions, the total avoided extra-regional mortality is estimated as 6,000 (-3,400, 15,500) deaths/year and 25,100 (8,200, 35,800) deaths/year through changes in O3 and PM2.5, respectively. Interregional transport of air pollutants leads to more deaths through changes in PM2.5 than in O3, even though O3 is transported more on interregional scales, since PM2.5 has a stronger influence on mortality. For NAM and EUR, our estimates of avoided mortality from regional and extra-regional emission reductions are comparable to those estimated by regional models for these same experiments. In sectoral emission reductions, TRN emissions account for the greatest fraction (26-53% of global emission reduction) of O3-related premature deaths in most regions, in agreement with previous studies, except for EAS (58%) and RBU (38%) where PIN emissions dominate. In contrast, PIN emission reductions have the greatest fraction (38-78% of global emission reduction) of PM2.5-related deaths in most regions, except for SAS (45%) where RES emission dominates, which differs with previous studies in which RES emissions dominate global health impacts. The spread of air pollutant concentration changes across models contributes most to the overall uncertainty in estimated avoided deaths, highlighting the uncertainty in results based on a single model. Despite uncertainties, the health benefits of reduced intercontinental air pollution transport suggest that international cooperation may be desirable to mitigate pollution transported over long distances.