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.

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.

Comparative assessment of net CO2 exchange across an urbanization gradient in Korea based on eddy covariance measurements.

BACKGROUND: It is important to quantify changes in CO2 sources and sinks with land use and land cover change. In the last several decades, carbon sources and sinks in East Asia have been altered by intensive land cover changes due to rapid economic growth and related urbanization. To understand impact of urbanization on carbon cycle in the monsoon Asia, we analyze net CO2 exchanges for various land cover types across an urbanization gradient in Korea covering high-rise high-density residential, suburban, cropland, and subtropical forest areas. RESULTS: Our analysis demonstrates that the urban residential and suburban areas are constant CO2 sources throughout the year (2.75 and 1.02 kg C m-2 year-1 at the urban and suburban sites), and the net CO2 emission indicate impacts of urban vegetation that responds to the seasonal progression of the monsoon. However, the total random uncertainties of measurement are much larger in the urban and suburban areas than at the nonurban sites, which can make it challenging to obtain accurate urban flux measurements. The cropland and forest sites are strong carbon sinks because of a double-cropping system and favorable climate conditions during the study period, respectively (- 0.73 and - 0.60 kg C m-2 year-1 at the cropland and forest sites, respectively). The urban area of high population density (15,000 persons km-2) shows a relatively weak CO2 emission rate per capita (0.7 t CO2 year-1 person-1), especially in winter because of a district heating system and smaller traffic volume. The suburban area shows larger net CO2 emissions per capita (4.9 t CO2 year-1 person-1) because of a high traffic volume, despite a smaller building fraction and population density (770 persons km-2). CONCLUSIONS: We show that in situ flux observation is challenging because of its larger random uncertainty and this larger uncertainty should be carefully considered in urban studies. Our findings indicate the important role of urban vegetation in the carbon balance and its interaction with the monsoon activity in East Asia. Urban planning in the monsoon Asia must consider interaction on change in the monsoon activity and urban structure and function for sustainable city in a changing climate.

Evaluating the predictability of PM10 grades in Seoul, Korea using a neural network model based on synoptic patterns.

As of November 2014, the Korean Ministry of Environment (KME) has been forecasting the concentration of particulate matter with diameters ≤ 10 µm (PM10) classified into four grades: low (PM10 ≤ 30 µg m-3), moderate (30 < PM10 ≤ 80 µg m-3), high (80 < PM10 ≤ 150 µg m-3), and very high (PM10 > 150 µg m-3). The KME operational center generates PM10 forecasts using statistical and chemistry-transport models, but the overall performance and the hit rate for the four PM10 grades has not previously been evaluated. To provide a statistical reference for the current air quality forecasting system, we have developed a neural network model based on the synoptic patterns of several meteorological fields such as geopotential height, air temperature, relative humidity, and wind. Hindcast of the four PM10 grades in Seoul, Korea was performed for the cold seasons (October-March) of 2001-2014 when the high and very high PM10 grades are frequently observed. Because synoptic patterns of the meteorological fields are distinctive for each PM10 grade, these fields were adopted and quantified as predictors in the form of cosine similarities to train the neural network model. Using these predictors in conjunction with the PM10 concentration in Seoul from the day before prediction as an additional predictor, an overall hit rate of 69% was achieved; the hit rates for the low, moderate, high, and very high PM10 grades were 33%, 83%, 45%, and 33%, respectively. Our findings also suggest that the synoptic patterns of meteorological variables are reliable predictors for the identification of the favorable conditions for each PM10 grade, as well as for the transboundary transport of PM10 from China. This evaluation of PM10 predictability can be reliably used as a statistical reference and further, complement to the current air quality forecasting system.

Human-model hybrid Korean air quality forecasting system.

UNLABELLED: The Korean national air quality forecasting system, consisting of the Weather Research and Forecasting, the Sparse Matrix Operator Kernel Emissions, and the Community Modeling and Analysis (CMAQ), commenced from August 31, 2013 with target pollutants of particulate matters (PM) and ozone. Factors contributing to PM forecasting accuracy include CMAQ inputs of meteorological field and emissions, forecasters' capacity, and inherent CMAQ limit. Four numerical experiments were conducted including two global meteorological inputs from the Global Forecast System (GFS) and the Unified Model (UM), two emissions from the Model Intercomparison Study Asia (MICS-Asia) and the Intercontinental Chemical Transport Experiment (INTEX-B) for the Northeast Asia with Clear Air Policy Support System (CAPSS) for South Korea, and data assimilation of the Monitoring Atmospheric Composition and Climate (MACC). Significant PM underpredictions by using both emissions were found for PM mass and major components (sulfate and organic carbon). CMAQ predicts PM2.5 much better than PM10 (NMB of PM2.5: -20~-25%, PM10: -43~-47%). Forecasters' error usually occurred at the next day of high PM event. Once CMAQ fails to predict high PM event the day before, forecasters are likely to dismiss the model predictions on the next day which turns out to be true. The best combination of CMAQ inputs is the set of UM global meteorological field, MICS-Asia and CAPSS 2010 emissions with the NMB of -12.3%, the RMSE of 16.6µ/m(3) and the R(2) of 0.68. By using MACC data as an initial and boundary condition, the performance skill of CMAQ would be improved, especially in the case of undefined coarse emission. A variety of methods such as ensemble and data assimilation are considered to improve further the accuracy of air quality forecasting, especially for high PM events to be comparable to for all cases. IMPLICATIONS: The growing utilization of the air quality forecast induced the public strongly to demand that the accuracy of the national forecasting be improved. In this study, we investigated the problems in the current forecasting as well as various alternatives to solve the problems. Such efforts to improve the accuracy of the forecast are expected to contribute to the protection of public health by increasing the availability of the forecast system.

Chemical characteristics of long-range-transported fine particulate matter at Gosan, Jeju Island, in the spring and fall of 2008, 2009, 2011, and 2012.

UNLABELLED: Carbonaceous species (organic carbon [OC] and elemental carbon [EC]) and inorganic ions of particulate matter less than 2.5 µm (PM2.5) were measured to investigate the chemical characteristics of long-range-transported (LTP) PM2.5 at Gosan, Jeju Island, in Korea in the spring and fall of 2008-2012 (excluding 2010). On average, the non-sea-salt (nss) sulfate (4.2 µg/m3) was the most dominant species in the spring, followed by OC (2.6 µg/m3), nitrate (2.1 µg/m3), ammonium (1.7 µg/m3), and EC (0.6 µg/m3). In the fall, the nss-sulfate (4.7 µg/m3) was also the most dominant species, followed by OC (4.0 µg/m3), ammonium (1.7 µg/m3), nitrate (1.1 µg/m3), and EC (0.7 µg/m3). Both sulfate and OC were higher in the fall than in the spring, possibly due to more common northwest air masses (i.e., coming from China and Korea polluted areas) and more frequent biomass burnings in the fall. There was no clear difference in the EC between the spring and fall. The correlation between OC and EC was not strong; thus, the OC measured at Gosan was likely transported across a long distance and was not necessarily produced in a manner similar to the EC. Distinct types of LTP events (i.e., sulfate-dominant LTP versus OC-dominant LTP) were observed. In the sulfate-dominant LTP events, air masses directly arrived at Gosan without passing over the Korean Peninsula from the industrial area of China within 48 hr. During these events, the aerosol optical depth (AOD) increased to 1.63. Ionic balance data suggest that the long-range transported aerosols are acidic. In the OC-dominant LTP event, a higher residence time of air masses in Korea was observed (the air masses departing from the mainland of China arrived at the sampling site after passing Korea within 60-80 hr). IMPLICATIONS: In Northeast Asia, various natural and anthropogenic sources contribute to the complex chemical components and affect local/regional air quality and climate change. Chemical characteristics of long-range-transported (LTP) PM2.5 were investigated during spring and fall of 2008, 2009, 2011, and 2012. Based on air mass types, sulfate-dominant LTP and OC-dominant LTP were observed. A long-term variation and chemical characteristics of PM2.5 along with air mass and satellite data are required to better understand long-range-transported aerosols.

Identifying airborne fungi in Seoul, Korea using metagenomics.

Fungal spores are widespread and common in the atmosphere. In this study, we use a metagenomic approach to study the fungal diversity in six total air samples collected from April to May 2012 in Seoul, Korea. This springtime period is important in Korea because of the peak in fungal spore concentration and Asian dust storms, although the year of this study (2012) was unique in that were no major Asian dust events. Clustering sequences for operational taxonomic unit (OTU) identification recovered 1,266 unique OTUs in the combined dataset, with between 223᾿96 OTUs present in individual samples. OTUs from three fungal phyla were identified. For Ascomycota, Davidiella (anamorph: Cladosporium) was the most common genus in all samples, often accounting for more than 50% of all sequences in a sample. Other common Ascomycota genera identified were Alternaria, Didymella, Khuskia, Geosmitha, Penicillium, and Aspergillus. While several Basidiomycota genera were observed, Chytridiomycota OTUs were only present in one sample. Consistency was observed within sampling days, but there was a large shift in species composition from Ascomycota dominant to Basidiomycota dominant in the middle of the sampling period. This marked change may have been caused by meteorological events. A potential set of 40 allergy-inducing genera were identified, accounting for a large proportion of the diversity present (22.5᾿7.2%). Our study identifies high fungal diversity and potentially high levels of fungal allergens in springtime air of Korea, and provides a good baseline for future comparisons with Asian dust storms.

Sulfur deposition simulations over China, Japan, and Korea: a model intercomparison study for abating sulfur emission.

In response to increasing trends in sulfur deposition in Northeast Asia, three countries in the region (China, Japan, and Korea) agreed to devise abatement strategies. The concepts of critical loads and source-receptor (S-R) relationships provide guidance for formulating such strategies. Based on the Long-range Transboundary Air Pollutants in Northeast Asia (LTP) project, this study analyzes sulfur deposition data in order to optimize acidic loads over the three countries. The three groups involved in this study carried out a full year (2002) of sulfur deposition modeling over the geographic region spanning the three countries, using three air quality models: MM5-CMAQ, MM5-RAQM, and RAMS-CADM, employed by Chinese, Japanese, and Korean modeling groups, respectively. Each model employed its own meteorological numerical model and model parameters. Only the emission rates for SO(2) and NO(x) obtained from the LTP project were the common parameter used in the three models. Three models revealed some bias from dry to wet deposition, particularly the latter because of the bias in annual precipitation. This finding points to the need for further sensitivity tests of the wet removal rates in association with underlying cloud-precipitation physics and parameterizations. Despite this bias, the annual total (dry plus wet) sulfur deposition predicted by the models were surprisingly very similar. The ensemble average annual total deposition was 7,203.6 ± 370 kt S with a minimal mean fractional error (MFE) of 8.95 ± 5.24 % and a pattern correlation (PC) of 0.89-0.93 between the models. This exercise revealed that despite rather poor error scores in comparison with observations, these consistent total deposition values across the three models, based on LTP group's input data assumptions, suggest a plausible S-R relationship that can be applied to the next task of designing cost-effective emission abatement strategies.