Stations In Korea Research Articles

Nationwide distribution and factors related to indoor fine particulate matter concentrations in subway stations in Korea: Results of first-year measurement

This study assessed the seasonal distribution and factors associated with PM2.5 in nationwide subway stations in Korea. A total of 229,644 data points collected over one year were used to determine one-day PM2.5 concentrations from 642 subway stations. The geometric mean of indoor PM2.5 concentrations was 26.6 µg/m3. PM2.5 concentrations were higher in the Seoul metropolitan area (SMA) compared to non-Seoul metropolitan areas (NSMA), with the highest level occurring in winter, followed by spring, fall, and summer, similar to the trend observed for outdoor PM2.5 concentrations. In SMA, PM2.5 concentrations were significantly associated with the operation year, number of air cleaners on platforms, and number of passengers. These findings may help in the development of national strategies for managing indoor PM2.5 concentrations in subway stations, taking into account spatial and temporal factors.

Assessing the impact of green infrastructure on thermal comfort in relation to humidity: A case study in Korea

Problems arising from heatwaves and urban heat islands (UHIs) exacerbated by climate change have prompted diverse adaptation strategies. Although green infrastructure, which positively affects climate change adaptation, has been extensively evaluated, global-scale assessments of UHIs indicate that green infrastructure may not be sufficient to mitigate UHIs in humid regions with annual precipitation exceeding 1000 mm or summer precipitation exceeding 570 mm. However, these assessments primarily focused on UHIs; different results may be obtained for individual heat comfort. As relative humidity increases, the cooling effect of green areas potentially decreases. This suggests the need for additional studies on the impact of short-term precipitation, which increases relative humidity and induces cooling effects on green infrastructure. Korea experiences a humid summer due to the concentration of precipitation (approximately 711 mm of summer precipitation); thus, the contribution of green infrastructure to improving heat comfort might be limited. Therefore, this study investigated the impact of green infrastructure on thermal comfort in relation to precipitation levels using the Wet-Bulb Globe Temperature (WBGT) index and data from weather stations in Korea. Precipitation intensity was categorized into 2-day periods and 10 mm/day. Subsequently, thermal comfort was compared for summers from 1993 to 2022 according to the green infrastructure ratio around the stations. The results indicated that green infrastructure had a cooling effect on clear days but only had a cooling effect on precipitation days when the level of green infrastructure was above the critical ratio. Additionally, green infrastructure reduced the WBGT index if minimal precipitation occurred during the five-day cooling period following precipitation. While green infrastructure remains crucial for climate change adaptation, other strategies must be implemented to improve the thermal environment, particularly in areas with frequent precipitation.

Particle removal performance of a novel ESP type air cleaning system for indoor air quality in a subway station

A novel electrostatic precipitation type air cleaning technology with near zero ozone emission for indoor air quality of a subway station was developed. To minimize ozone emission and achieve high particle removal performance against ultrafine particulate matters (PMs), a multi-channel charging method using soft ionization by micrometre carbon fibers and a narrow gap collection method using high electric field by thin conductive plastic sheets as a high voltage electrode were used. In this study, the novel electrostatic charging and collection technologies were applied to a real scale air cleaning system in an Air Handling Unit (AHU) with air flow rate of 950 m3/min in Yuseong Oncheon subway station with an area of 3000 m2 in Daejeon, South Korea. The particle removal performance of the demonstration system was evaluated with real suspended particles in the subway station during test period with high PM concentrations in Korea over 40 μg/m3. Particle collection efficiency, pressure drop and ozone emission were evaluated, and compared to those of the a minimum efficiency reporting value (MERV) 10 and 14 filters used in the typical subway stations in Korea. In the field researches, the developed ESP achieved over 80% of the PM collection efficiency higher than those of the filters with MERV-10 and -14, and even 10% higher efficiency against PM1.0, while generating only 10% of pressure drop and also emitting nearly zero ozone. It is concluded that a novel ESP type air cleaning system with near zero ozone emission could be a promising air cleaning method for a large indoor environment such as a subway station where polluted air with ultrafine particles flowed in with a very high flow rate.

Ecohydrologic model with satellite-based data for predicting streamflow in ungauged basins

Information on water availability in basins can be crucial for making decisions for effective water resource management in basins. As the operation of hydrometric stations in Korea is mainly focused on flood season and large rivers, most basins have lack or no observed data. Consequently, this complicates water resource planning and management. Remote sensing data is emerging as a powerful alternative to hydrological information in ungauged basins. This study investigated the applicability of Satellite-Remote Sensed Data (SRSD) as a source for model calibration in Prediction in Ungauged Basins (PUB) through modeling. Remote sensed leaf area index (LAI), actual evapotranspiration, and soil moisture data were used. Each SRSD was used alone to calibrate a hydrologic model to predict the daily streamflow for 28 basins in Korea. A vegetation module was added to the existing hydrologic model to use LAI. Among the SRSDs tested, the model calibrated with LAI had the most robust performance, predicting streamflow with acceptable accuracy compared to the traditional calibration based on streamflow. In particular, since the model account for vegetation actively interacting with evapotranspiration and soil moisture in the season of low flow, the LAI-calibrated model showed an advantage in improving the flow prediction performance. Although further research is required to utilize evapotranspiration and soil moisture data, the overall results of the LAI-based calibration were promising for predicting streamflow in ungauged basins where observations are scarce or absent, given that the satellite-derived LAI data were used alone without any preprocessing such as a bias correction. However, the prediction performance of the LAI-calibrated model was found to have a statistically significant relationship with local conditions. Therefore, by evaluating and improving the potential of SRSD in different region and climatic conditions, it is expected that the application of the SRSD-only calibration method can be extended to various ungauged basins.

Seismic Acceleration Estimation Method at Arbitrary Position Using Observations and Machine Learning

This study proposes a method of estimating the measurement data of nearby seismic stations by training an artificial neural network (ANN) through machine learning to understand the seismic acceleration time history at an arbitrary location where seismic acceleration time history is unknown. The ANN is trained using the observation data of 6 earthquakes at 10 ground seismic stations in Korea and 12 earthquakes at 212 underground seismic stations from the Korea Meteorological Administration. The location of the seismic station is assumed to be arbitrary in the untrained observation data to verify the validity of the trained ANN, and the measured and estimated data are compared. It is confirmed that the estimation accuracy of the ANN trained with the observation data of the underground seismic station is higher than that of the ANN trained with the observation data of the ground seismic station. The accuracy of the seismic acceleration estimation method proposed in this study is improved according to the level of learning data. It can also be applied as seismic acceleration to evaluate seismic damage or behavior of structures or facilities, even in places without seismic acceleration.

Comparison of the sources and oxidative potential of PM2.5 during winter time in large cities in China and South Korea

Regional air pollution is rising in Northeast Asia due to increasing energy consumption resulting from a growing population and intensifying industrialization. This study analyzes the sources of air pollution using fine particulate matter (PM2.5) sampling from the atmosphere over Korea and China. We then use this analysis to further investigate the relationship between organic compounds (source tracers) and the oxidative potential of PM2.5. The PM2.5 concentration during winter measured at a measurement stations in Korea showed no significant variation year-to-year. The PM2.5 concentrations measured during winter at a site near Beijing, China were 62.45 μg/m3 in 2018 and 33.07 μg/m3 in 2020. The sources, as determined from PMF, were analyzed at a site in Korea, the sources as secondary nitrate (34.10 %), secondary sulfate (20.20 %), coal combustion (4.01 %), vehicle emission (8.55 %), cooking and biomass burning (18.39 %), dust (8.45 %), and SOA (6.29 %) were identified. At a site in China, secondary nitrate (17.54 %), secondary sulfate (12.03 %), coal combustion (15.53 %), vehicle emission (12.43 %), cooking and biomass burning (9.25 %), dust (26.40 %), secondary organic aerosol (6.82 %) were identified. Our results show secondary organic carbon had a positive association with oxidative potential in Korea while primary organic carbon presented higher correlation with oxidative potential in China. Further, the ECMWF Reanalysis v5 (ERA5) wind field during the high PM2.5 events demonstrated airflow from the west coast of China resulting in high polar organic compounds at the Korean monitoring site. The results further support that aged PM2.5, which contains secondary products, leads to increased oxidative potential. The results presented explain the high concentrations of secondary products and the impact on the biological activities of PM2.5, supporting additional actions to address the impacts of long-range transport of PM2.5.

Site flatfile of Korea meteorological administration’s seismic stations in Korea

Site flatfile of Korea meteorological administration’s seismic stations in Korea

수소자동차 충전소 및 공급망 배치 최적화: 현황 및 연구 제언

Hydrogen infrastructure consisting of hydrogen refueling stations and supply chain network is critical in the hydrogen mobility economy. This paper overviews the important key concepts of the hydrogen mobility economy and investigates the status of hydrogen vehicles and refueling stations in Korea and other countries. It also reviews the methodologies for hydrogen station and supply chain network optimization and suggests research agenda for the hydrogen mobility economy.

Case Study: Development of the CNN Model Considering Teleconnection for Spatial Downscaling of Precipitation in a Climate Change Scenario

Global climate models (GCMs) are used to analyze future climate change. However, the observed data of a specified region may differ significantly from the model since the GCM data are simulated on a global scale. To solve this problem, previous studies have used downscaling methods such as quantile mapping (QM) to correct bias in GCM precipitation. However, this method cannot be considered when certain variables affect the observation data. Therefore, the aim of this study is to propose a novel method that uses a convolution neural network (CNN) considering teleconnection. This new method considers how the global climate phenomena affect the precipitation data of a target area. In addition, various meteorological variables related to precipitation were used as explanatory variables for the CNN model. In this study, QM and the CNN models were applied to calibrate the spatial bias of GCM data for three precipitation stations in Korea (Incheon, Seoul, and Suwon), and the results were compared. According to the results, the QM method effectively corrected the range of precipitation, but the pattern of precipitation was the same at the three stations. Meanwhile, for the CNN model, the range and pattern of precipitation were corrected better than the QM method. The quantitative evaluation selected the optimal downscaling model, and the CNN model had the best performance (correlation coefficient (CC): 69% on average, root mean squared error (RMSE): 117 mm on average). Therefore, the new method suggested in this study is expected to have high utility in forecasting climate change. Finally, as a result of forecasting for future precipitation in 2100 via the CNN model, the average annual rainfall increased by 17% on average compared to the reference data.

Development of a Tsunami-tide Interaction Model with Simulation of Tsunami Wave Propagation to Korea Coasts

Kim, K.O.; Jung, K.T., and Ha, T.M., 2021. Development of a tsunami-tide interaction model with simulation of tsunami wave propagation to Korea coasts. In: Lee, J.L.; Suh, K.-S.; Lee, B.; Shin, S., and Lee, J. (eds.), Crisis and Integrated Management for Coastal and Marine Safety. Journal of Coastal Research, Special Issue No. 114, pp. 91–95. Coconut Creek (Florida), ISSN 0749-0208. Simulation studies of historic and prognostic tsunamis have been performed with a focus on tsunami-tide interactions. A modeling system based on the 3D POM (Princeton Ocean Model) has been developed that is composed of a global tsunami model and a regional multinesting tide/tsunami/tsunami-tide interaction model covering the Northwest Pacific region. Propagations of two historic tsunamis, the 2010 Chilean and 2011 Tohoku tsunamis, were simulated to estimate the effects of tsunami-tide interactions by comparing the results from tsunami-only and tsunami simulations with tide simulations. Calculations show that tsunami waves are significantly transformed after traveling a long distance and subsequently affected by the tidal phase. As prognostic tsunami propagation, the Nankai Trough earthquake-induced tsunami wave in Japan was investigated. A series of calculations were performed with a systematic shift of the tsunami occurrence time. The effects of tsunami-tide interactions were examined in terms of local tidal phase changes, focusing on the changes in the first tsunami heights and occurrence times arriving at the selected tidal stations in Korea. The tsunami-tide interaction mostly results in a positive change in the tsunami first peak heights with a maximum change near low tide probably due to the interaction between the tsunami-induced current and tidal current. The water depth increase near high tide advances the arrival of the tsunami first peaks, whereas the water depth decrease near low tide delays the arrival of the tsunami first peaks.

The Role of the Pacific‐Japan Pattern in Extreme Heatwaves Over Korea and Japan

AbstractIn the Northwestern Pacific, the meridionally propagating Rossby waves, known as the Pacific‐Japan (PJ) pattern, is the dominant teleconnection pattern and is considered as a source of heatwaves in East Asia. In this study, the circulation and thermodynamic characteristics of these patterns were investigated based on daily timescale to evaluate their relationship with the likelihood of heatwaves in Korea and Japan. The investigations reveal that stations in Korea and Japan record approximately 90% increase in extremely hot days (Tmax > 35°C) during the positive PJ pattern events. According to thermodynamic budget, horizontal heat advection is a key factor for the observed near‐surface warming during the positive PJ. The circulation pattern during the positive PJ largely explains the enhanced warm advection and physical heating due to the increased insolation and adiabatic heating are secondary factors for near‐surface warming. This phenomenon is robustly observed regardless of the definition.

Consumer Search and Price Dispersion: A Comparison of Gas Station Prices Before and After COVID-19

탐색이론모형은 동질적인 재화에 대해 두 개 혹은 그 이상의 가격이 존재하는 가격분산을 소비자의 가격탐색에 따른 편익과 비용으로 설명한다. 우리나라 주유소에서 판매되는 운송용 유류는 품질과 서비스의 높은 동질성에도 불구하고 동일한 지역 내에서 다양한 가격에 판매되고 있다. 본 연구는 코로나19가 보통휘발유와 경유의 가격분산 변화에 미친 영향을 실증적으로 분석하고자 한다. 탐색이론모형에 따르면, 코로나19의 확산으로 감염 위험이 증가하여 운전자의 유류소비가 감소하거나 소비자의 가격탐색에 따른 편익이 감소하여 보통휘발유와 경유 소매가격의 분산이 증가할 것이라고 추론할 수 있다. 2019~2020년 서울특별시와 6대 광역시 주유소의 일별보통휘발유와 경유 가격 자료를 패널 고정효과 모형을 이용해 분석한 결과에 따르면, 코로나19 이후 보통휘발유와 경유 가격의 도시 수준 분산이 약 16.5%와 23.4% 증가하였다. 또한 코로나19 누적 확진자수가 증가할수록 보통휘발유와 경유 가격의 도시 내 격차는 확대되었으며, 이러한 효과는 코로나19 확산 초기 누적 확진자수가 적을수록 크게 나타났다. 한편 다른 조건이 일정할 경우, 유류 가격상승 지속기간이 증가할수록 해당 유류의 가격분산은 감소하였지만 가격하락 지속기간은 가격분산에 유의미한 영향을 주지 않았다.The search-theoretic model attibutes the price dispersion, variation in prices across sellers of the homogeneous goods, to the differences in benefits and costs of consumer search for lower price. Transportation oil at gas stations in Korea is sold at various prices even within the same region despite its homogeneity in quality and services. This study analyzed the effect of Covid-19 on the price dispersion of regular gasoline and diesel. According to the search-theoretic model, the spread of Corona 19 is expected to increase the risk of infection such that reduced transportation oil consumption or lowered benefits of price search will result in an increase in the dispersion of regular gasoline and diesel prices. Using daily regular gasoline and diesel price data at Seoul and six metropolitan cities in Korea between 2019 and 2020. we find that the city-level dispersion of regualar gasoline and diesel prices increased by about 16.5% and 23.4% after the spread of COVID-19. Our results also suggest that, as the cumulative number of confirmed cases of Corona 19 increases, the price dispersion of regular gasoline or diesel widens, and this effect is shown to be stronger at earlier days of COVID-19 era. Finally the price dispersion of transportation oil decreases more as the duration of oil price rise lasts longer, but the duration of oil price decline has no statistically significant effect on oil price dispersion.

Association between case volume of ambulance stations and clinical outcomes of out-of-hospital cardiac arrest: A nationwide multilevel analysis

ObjectivesThe case volume effects of ambulance stations on the survival of out-of-hospital cardiac arrest (OHCA) patients are uncertain. This study was conducted to evaluate the association between the case volume of ambulance stations and clinical outcomes in OHCAs by the number of emergency medical services (EMS) providers at the scene. MethodsAdult cardiac EMS-treated OHCAs between 2015 and 2018 were enrolled. The main exposure was the annual OHCA case volumes of 204 ambulance stations in Korea, which were categorized into three groups; low-volume (<100), moderate-volume (100–159) and high-volume (≥160). The primary and secondary outcomes were good neurological recovery and survival to discharge. Multilevel multivariable logistic regression analysis was conducted to calculate adjusted odds ratios (AORs). Interaction analysis between the number of EMS providers at the scene and the exposure variable was performed. ResultsA total of 92,534 patients were enrolled. OHCAs in the low-volume group tended to be arrest in a public place or a non-metropolitan area, less prehospital administration of an advanced airway and intravenous management. Significant differences were found the main analysis: AORs (95% CIs) compared to the low-volume group were 1.15 (1.03–1.29) and 1.14 (1.03–1.27) in the high-volume and moderate-volume groups for good neurological recovery and 1.19 (1.07–1.33) and 1.14 (1.04–1.25) in the high-volume and moderate-volume groups for survival to discharge. Significant interaction effects between the number of EMS providers at the scene and case volume on clinical outcomes were found. ConclusionOHCA case volumes of ambulance stations are associated with clinical outcomes after cardiac arrest.

Comparative sustainability assessment of a hydrogen supply network for hydrogen refueling stations in Korea – a techno-economic and lifecycle assessment perspective

Economical and environmental sustainability of hydrogen supply routes is evaluated for hydrogen refueling stations.

Shear Wave Velocity Estimation in Korea Using P-Wave Seismograms

The average shear wave velocity for a soil depth of 30 m (VS30) is crucial for seismic hazard assessments. However, VS30 measurements are not available at most recording stations in Korea. The P-wave seismogram method is an efficient way to estimate VS30 because it only utilizes P-wave seismograms recorded on the ground surface without boring process. VS30 measurements for 51 recording stations are acquired from previous literature, and downhole tests were performed at 10 stations for additional VS30 measurements. The P-wave seismogram method is validated for 50 stations using 359 seismograms recorded during 66 earthquake events with local magnitudes greater than 3.0. The average shear wave velocity for a certain depth (VSZ) can be estimated using the ratio of radial to vertical components in the initial P-wave velocity seismograms, which can be converted to VS30 using an empirical relationship. The residuals between the measured and estimated VS30 are divided into the overall bias, between-site residuals, and within-site residuals. The standard deviation for between-site residuals is 0.37, which is comparable with the values of previous studies for other countries. After bias correction, 70% of measured VS30 and estimated VS30 are within ±50% of each other. This study estimates VS30 values for 118 stations where VS30 is not available.

Seismic moment tensors from synthetic rotational and translational ground motion: Green’s functions in 1-D versus 3-D

SUMMARY Seismic moment tensors are an important tool and input variable for many studies in the geosciences. The theory behind the determination of moment tensors is well established. They are routinely and (semi-) automatically calculated on a global scale. However, on regional and local scales, there are still several difficulties hampering the reliable retrieval of the full seismic moment tensor. In an earlier study, we showed that the waveform inversion for seismic moment tensors can benefit significantly when incorporating rotational ground motion in addition to the commonly used translational ground motion. In this study, we test, what is the best processing strategy with respect to the resolvability of the seismic moment tensor components: inverting three-component data with Green’s functions (GFs) based on a 3-D structural model, six-component data with GFs based on a 1-D model, or unleashing the full force of six-component data and GFs based on a 3-D model? As a reference case, we use the inversion based on three-component data and 1-D structure, which has been the most common practice in waveform inversion for moment tensors so far. Building on the same Bayesian approach as in our previous study, we invert synthetic waveforms for two test cases from the Korean Peninsula: one is the 2013 nuclear test of the Democratic People’s Republic of Korea and the other is an Mw 5.4 tectonic event of 2016 in the Republic of Korea using waveform data recorded on stations in Korea, China and Japan. For the Korean Peninsula, a very detailed 3-D velocity model is available. We show that for the tectonic event both, the 3-D structural model and the rotational ground motion, contribute strongly to the improved resolution of the seismic moment tensor. The higher the frequencies used for inversion, the higher is the influence of rotational ground motions. This is an important effect to consider when inverting waveforms from smaller magnitude events. The explosive source benefits more from the 3-D structural model than from the rotational ground motion. Nevertheless, the rotational ground motion can help to better constraint the isotropic part of the source in the higher frequency range.

Correlation Structures of PM2.5 Concentration Series in the Korean Peninsula

In this paper, the authors investigate the idiosyncratic features of auto- and cross-correlation structures of PM2.5 (particulate matter of diameter less than 2.5 μ m ) mass concentrations using DFA (detrended fluctuation analysis) methodologies. Since air pollutant mass concentrations are greatly affected by geographical, topographical, and meteorological conditions, their correlation structures can have non-universal properties. To this end, the authors firstly examine the spatio-temporal statistics of PM2.5 daily average concentrations collected from 18 monitoring stations in Korea, and then select five sites from those stations with overall lower and higher concentration levels in order to make up two groups, namely, G1 and G2, respectively. Firstly, to compare characteristic behaviors of the auto-correlation structures of the two groups, we performed DFA and MFDFA (multifractal DFA) analyses on both and then confirmed that the G2 group shows a clear crossover behavior in DFA and MFDFA analyses, while G1 shows no crossover. This finding implies that there are possibly two different scale-dependent underlying dynamics in G2. Furthermore, in order to confirm that different underlying dynamics govern G1 and G2, the authors conducted DCCA (detrended cross-correlation analysis) analysis on the same and different groups. As a result, in the same group, coupling behavior became more prominent between two series as the scale increased, while, in the different group, decoupling behavior was observed. This result also implies that different dynamics govern G1 and G2. Lastly, we presented a stochastic model, namely, ARFIMA (auto-regressive fractionally integrated moving average) with periodic trends, to reproduce behaviors of correlation structures from real PM2.5 concentration time series. Although those models succeeded in reproducing crossover behaviors in the auto-correlation structure, they yielded no valid results in decoupling behavior among heterogeneous groups.

A Study of the Rainfall in Korea Using Outlier Detections

The outliers in annual maximum rainfall can play an important role in the frequency analysis that estimates the probability rainfall. To ensure reliability of the frequency analysis, this study detects the outliers and conducts a qualitative analysis to investigate the causes of rainfall based on selected outliers. The outliers in annual maximum 24-hr rainfalls at 57 stations in Korea were analyzed by four different methods, such as Grubbs and Beck method, IACWD method, modified z-score method and box-plot method. The causes of the selected rainfall events as high outliers were classified into changma, typhoon, severe rain storm and frontal rainfall. The comparison of the methods shows that less outliers were found with Grubbs and Beck method than the other methods. It is found that 51.0% of the outliers occurred due to typhoon, followed by severe rain storm (35.7%), frontal storm (7.2%) and changma (6.1%). Rainfall events as outliers were mostly caused by severe rain storm in inland regions while they were caused by typhoon in coastal regions. The probability rainfall calculated without outliers from the test was compared with that before the test.

Inhalation cancer risk from PM10 in the metropolitan subway stations in Korea

IntroductionAlthough subways have many advantages as a transport system, passengers may be exposed to indoor air pollution. In such cases, the dominant risk factors are associated with particulate matter (PM) bound metals and polycyclic aromatic hydrocarbons (PAHs). In this study, inhalation cancer risks (ICR) were assessed at Seoul metro subway stations (SMS), South Korea, in 2014–2015. MethodsThe mass fractions of PAHs and metals in PM10 were calculated from the previous studies. The PM10 exposure and mass deposition in various sections of the human respiratory tract (HRT) was calculated using mass deposition technique. In addition, ICR via exposure of PM10 in HRT and incremental lifetime cancer risk (ILCR) were estimated for the teen and adult groups of commuters at SMS. Moreover, ICR levels have been compared with incremental lifetime cancer risk (ILCR) levels for SMS commuters. ResultsThe PM10 pollution levels at SMS were found within the acceptable range for the subway platforms in Korean (150 μg/m3). In addition, the maximum amounts of total deposition (TD) and head deposition (HD) in HRT were estimated for the adult group. Hence, tracheobronchial (TB) and alveoli (A) depositions were calculated height for the teen. For the adult and teen groups, ICR(TD) level found significant (>1 × 10−6) for Cr and PAHs. But, among both age groups, significant values of total ICR(TBD + AD) were estimated for the teen (1.40 × 10−06). In addition, the ICR(TD) and ILCR have estimated the same order of inhalation cancer risk for both groups. ConclusionIn the SMS, cancer risk levels were estimated in the acceptable range (1 × 10−06 - 1 × 10−05) of life carcinogenic risk for the commuters, provided by the World Health Organization (WHO). Furthermore, Cr and Ni were identified as significant contributors to inhalation cancer risks with 58% and 39% of total risk level, respectively for teen and adult.

Seasonal and spatial variations of tritium in precipitation in Northeast Asia (Korea) over the last 20 years

Several studies have documented the characteristics of seasonal, decadal, and spatial variations of tritium in different regions including North America, Australia, and Europe. However, long-term data such as these studies were not yet reported for Northeast Asia. In this study, we document the extensive spatial-temporal monitoring data of tritium levels in precipitation measured at 16 stations in Korea over the last 20 years, including the long-term trend since 1961 by using measured and estimated data. The long-term variation of tritium concentrations in the Korean precipitation follows the global trend, reaching the maximum in 1963 owing to nuclear bomb testing, followed by a consistent level since the late 1990s. Tritium concentrations in precipitation from 1998 to 2017 were maximum in spring (April) due to tropopause folding and minimum in summer (July) due to the dominant inflows of marine air. The tritium concentrations in precipitation were lower toward the coastal stations, due to the influence of marine moisture for all seasons. Our results characterize the differences in tritium levels in groundwater recharging areas for different periods in this region. These results will serve as important tritium reference data for hydrology studies in Northeast Asia, which is an important region for understanding global hydrological cycles.