• Journal of Food Hygiene and Safety
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• v.38 no.6
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• pp.489-495
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• 2023

In this study, we detected the presence of residual pesticides in 341 agricultural products collected from local food outlets in western Gyeonggi Province. Residual pesticides were detected in 105 (30.8%) samples. Six samples exceeded the legal limits for residual pesticides, resulting in a non-compliance rate of 1.8%, which was slightly higher than the average non-compliance rate of 1.4% in the last three years. Among the tested agricultural products, only fruits and vegetables were found to have pesticide residues, with 24 of 34 fruits (a detection rate of 70.6%) and 81 of 277 vegetables (a detection rate of 29.2%) testing positive. In total, 59 types of pesticides, including acetamiprid, which was detected 208 times, were detected and had a detection range of 0.01-2.38 mg/kg. Among the 105 agricultural products containing pesticide residues, a single pesticide was detected in 62 samples (59%) and two or more pesticides were detected in 43 samples (41%). In particular, 14 pesticides were detected in the same sample of peaches; dinotefuran was detected 21 times. Upon examining the toxicity of the detected pesticides, Class III pesticides (moderate toxicity) were detected 44 times (21.2%) and Class IV pesticides (low toxicity) were detected 164 times (78.8%). Class I, II, and III pesticides with fish toxicity were detected 68 (32.7%), 14 (6.7%), and 126 times (60.6%), respectively. Upon examining the exposure to high-frequency pesticide components detected five or more times, the hazard index was found to be ≤2.8%. Accordingly, the hazard of residual pesticides based on dietary intake was deemed insignificant.

• Economic and Environmental Geology
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• v.56 no.6
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• pp.871-885
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• 2023

In 2022, the total of 129 million m³ of aggregate was produced in Korea, a slightly decrease from the total production of 2021. Of these, about 44 million m³ of sand and about 84 million m³ of gravel were produced. About 41% of total quantity of aggregates were produced by permission and the rest were produced after declaration. It estimated that of the 129 million m³ of aggregates in Korea in 2022, about 54.9% was produced by screening crushed aggregate, by 32.8% by forest aggregate, 2.2% by land aggregate, 6.2% by marine aggregate and 3.1% by washing aggregate, and 0.3% by river aggregate. This indicates that screening crushed and forest aggregate are the main producers of domestic aggregate in 2022. Leading producing metropolitan governments were Gyeonggi-do, Gyeongsangnam-do, Chungcheongnam-do, Incheon, Jeollanam-do, Chungcheongbuk-do, Gangwon-do, Gyeongsangbuk-do in order decreasing volume. In 2022, aggregates were produced in 147 local governments, and the 10 leading producing local governments were, in descending order of volume, Hwaseong, Pocheon, Paju, Ongjin, Youngin, Gwangju, west EEZ, Incheon Seo-gu, Namyangju, Asan. The combined production of the 10 leading local governments accounted for 31% of the national total. And 44 local governments have produced aggregates of more than 1 million m³ each other. In 148 local governments that produced aggregate, a total of 800 active operations produced aggregate with 350 operations by river, land and forest aggregate, 450 operations by selective crushed and washing aggregate.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.563-576
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• 2023

In this study nitrogen dioxide (NO₂), formaldehyde (HCHO) from the Ozone Monitoring Instrument (OMI) and TROPOspheric Monitoring Instrument (TROPOMI), OMI/ Microwave Limb Sounder (MLS) tropospheric column ozone (TCO), and Airkorea ground-based O₃ data were analyzed to examine the photochemical reaction relationship between tropospheric ozone and its precursors nitrogen oxides (NOx) and volatile organic compounds (VOCs). As a result of analyzing the trend of long-term changes from 2006 to 2020 using OMI satellite data, TCO showed an increasing trend, NO₂ steadily decreased, and HCHO continued to increase in Northeast Asia. In addition, formaldehyde nitrogen dioxide ratio (FNR; HCHO/NO₂ ratio), an indicator of ozone sensitivity, is gradually increasing, which means that the VOC-limited regime is decreasing. This study conducted a sensitivity analysis of ozone generation using TROPOMI FNR and ground-based ozone (O₃) over the recent years (2019~2022) to identify the possible cause for the continuous increase of ozone in Korea. Similar to the previous studies, VOC-limited and transitional regimes appeared in megacities, and VOC-limited regimes also appeared in areas where major power plants were located. In VOC-limited regimes, in other words, areas where NOx is excessively saturated, the reduction in NOx emissions may have weakened the ozone titration and thus led to the increase of ozone. Therefore, VOC emissions should be reduced in the short term rather than NOx emissions to reduce ozone concentrations under the VOC-limited regime.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.715-727
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• 2023

To provide detailed and appropriate meteorological information in mountainous areas, the Korea Forest Service has established an Automatic Mountain Meteorology Observation Station (AMOS) network in major mountainous regions since 2012, and 464 stations are currently operated. In this study, we proposed an optimal kriging technique with lapse rate correction to produce gridded temperature data suitable for Korean forests using AMOS point observations. First, the outliers of the AMOS temperature data were removed through statistical processing. Then, an optimized theoretical variogram, which best approximates the empirical variogram, was derived to perform the optimal kriging with lapse rate correction. A 500-meter resolution Kriging map for temperature was created to reflect the elevation variations in Korean mountainous terrain. A blind evaluation of the method using a spatially unbiased validation sample showed a correlation coefficient of 0.899 to 0.953 and an error of 0.933 to 1.230℃, indicating a slight accuracy improvement compared to regular kriging without lapse rate correction. However, the critical advantage of the proposed method is that it can appropriately represent the complex terrain of Korean forests, such as local variations in mountainous areas and coastal forests in Gangwon province and topographical differences in Jirisan and Naejangsan and their surrounding forests.

• Korean Journal of Plant Resources
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• v.36 no.5
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• pp.496-507
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• 2023

The in vitro organogenesis is one of important issues in plant embryology, and somaclonal variations are existing in calli and/or regenerants induced from a process of the organogenesis with in vitro circumstances. In this study, expressions of organogenesis-related genes were evaluated and genetic stability of regenerants derived from the process of in vitro organogenesis were measured using ISSR markers in Imperata cylindrica 'Rubra', Poaceae. The expressions of organogenesis-related genes were detected all of regenerants at the process of the organogenesis. All ISSR markers produced with an average of 71 bands per in vitro-cultured regenerants, and the scorable bands were varied from two to eight with an average of 5.14 bands per a primer. The polymorphism rates of the in vitro regenerants were higher than that of mother plants (1.4%), showing 4.1% (pot-cultured regenerants), 4.3% (field-cultured regenerants), 4.2% (in vitro-cultured regenerants), 5.6% (calli with green shoots) and 1.4% (calli), respectively. The genetic similarity matrix (GSM) among all accessions ranged from 0.747 to 1.0 with a mean of 0.868. GSM of the regenerants showed differences (from 0.972 to 1.00) compared with that of mother plants (0.991). According to the clustering analysis, two independent groups were divided into; the one is mother plants and regenerants cultured at room and open field, the other is regenerants cultured in vitro. The results give a new insight for understanding the dynamics of organogenesis in monocot plant.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.1031-1042
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• 2023

In this study, a deep learning model was developed to predict the yield of cabbage and radish, one of the five major supply and demand management vegetables, using satellite images of Landsat 8. To predict the yield of cabbage and radish in Gangwon-do from 2015 to 2020, satellite images from June to September, the growing period of cabbage and radish, were used. Normalized difference vegetation index, enhanced vegetation index, lead area index, and land surface temperature were employed in this study as input data for the yield model. Crop yields can be effectively predicted using satellite images because satellites collect continuous spatiotemporal data on the global environment. Based on the model developed previous study, a model designed for input data was proposed in this study. Using time series satellite images, convolutional neural network, a deep learning model, was used to predict crop yield. Landsat 8 provides images every 16 days, but it is difficult to acquire images especially in summer due to the influence of weather such as clouds. As a result, yield prediction was conducted by splitting June to July into one part and August to September into two. Yield prediction was performed using a machine learning approach and reference models , and modeling performance was compared. The model's performance and early predictability were assessed using year-by-year cross-validation and early prediction. The findings of this study could be applied as basic studies to predict the yield of field crops in Korea.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.481-493
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• 2023

In high-density urban areas, the urban heat island effect increases urban temperatures, leading to negative impacts such as worsened air pollution, increased cooling energy consumption, and increased greenhouse gas emissions. In urban environments where it is difficult to secure additional green spaces, rooftop greening is an efficient greenhouse gas reduction strategy. In this study, we not only analyzed the current status of the urban heat island effect but also utilized high-resolution satellite data and spatial information to estimate the available rooftop greening area within the study area. We evaluated the mitigation effect of the urban heat island phenomenon and carbon sequestration capacity through temperature predictions resulting from rooftop greening. To achieve this, we utilized WorldView-2 satellite data to classify land cover in the urban heat island areas of Busan city. We developed a prediction model for temperature changes before and after rooftop greening using machine learning techniques. To assess the degree of urban heat island mitigation due to changes in rooftop greening areas, we constructed a temperature change prediction model with temperature as the dependent variable using the random forest technique. In this process, we built a multiple regression model to derive high-resolution land surface temperatures for training data using Google Earth Engine, combining Landsat-8 and Sentinel-2 satellite data. Additionally, we evaluated carbon sequestration based on rooftop greening areas using a carbon absorption capacity per plant. The results of this study suggest that the developed satellite-based urban heat island assessment and temperature change prediction technology using Random Forest models can be applied to urban heat island-vulnerable areas with potential for expansion.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.655-667
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• 2023

Algal bloom outbreaks are frequently reported around the world, and serious water pollution problems arise every year in Korea. It is necessary to protect the aquatic ecosystem through continuous management and rapid response. Many studies using satellite images are being conducted to estimate the concentration of chlorophyll-a (Chl-a), an indicator of algal bloom occurrence. However, machine learning models have recently been used because it is difficult to accurately calculate Chl-a due to the spectral characteristics and atmospheric correction errors that change depending on the water system. It is necessary to consider the factors affecting algal bloom as well as the satellite spectral index. Therefore, this study constructed a dataset by considering water quality, hydrological and meteorological factors, and sentinel-2 images in combination. Representative ensemble models random forest and extreme gradient boosting (XGBoost) were used to predict the concentration of Chl-a in eight weirs located on the Nakdong river over the past five years. R-squared score (R²), root mean square errors (RMSE), and mean absolute errors (MAE) were used as model evaluation indicators, and it was confirmed that R² of XGBoost was 0.80, RMSE was 6.612, and MAE was 4.457. Shapley additive expansion analysis showed that water quality factors, suspended solids, biochemical oxygen demand, dissolved oxygen, and the band ratio using red edge bands were of high importance in both models. Various input data were confirmed to help improve model performance, and it seems that it can be applied to domestic and international algal bloom detection.

• Korean Journal of Heritage: History & Science
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• v.56 no.4
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• pp.54-70
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• 2023

Surveys and studies on cultural assets using LiDAR measurement are already active overseas. Recently, awareness of the advantages and availability of LiDAR measurement has increased in Korea, and cases of using it for surveys of cultural assets are gradually increasing. However, it is usually restricted to surveys of mountain fortresses and is not actively used for surveys of ancient tombs yet. Therefore, this study intends to emphasize the need to secure fundamental data from LiDAR measurement for the era from the Three Kingdoms to Unified Silla in which recovery, maintenance, etc., in addition to the actual surveys, are unfulfilled due to the sites being mainly distributed in mountainous areas. For this, LiDAR measurement was executed for the area of Jangsan Ancient Tombs and Chunghyo-dong Ancient Tombs in Seoak-dong, Gyeongju, to review the distribution and geographical conditions of ancient tombs. As a result, in the Jangsan Ancient Tombs, in which a precision archaeological (measurement) survey was already executed, detailed geographic information and distribution conditions could be additionally identified, which could not be known only with the layout indicated by the topographic map of the existing report. Also, in the Chunghyo-dong Ancient Tombs, in which an additional survey was not conducted after 10 tombs were found during the Japanese colonial period, the location of the ancient tombs initially excavated was accurately identified, and the status and additional information was acquired, such as on the conditions of ancient tombs not surveyed. Such information may also be used as fundamental data for the preservation and maintenance of future ancient tombs in addition to the survey and study of the ancient tombs themselves. LiDAR measurement is most effective for identifying the condition of ancient tombs in mountainous areas where observation is difficult or access is limited due to the forest zone. It may be executed before on-site surveys, such as archaeological surveys, to secure data with high availability as prior surveys or pre-surveys. Therefore, it is necessary to secure fundamental data from LiDAR measurement in future surveys of ancient tombs and to establish a survey and maintenance/utilization plan based on this. To establish survey/study and preservation/maintenance measures for ancient tombs located in mountainous areas, a precision archaeological survey is currently executed to draw up a distribution chart of ancient tombs. If LiDAR measurement data is secured before this and used, a more effective and accurate distribution chart can be drawn up, and the actual conditions can be identified. Also, most omissions or errors in information can be prevented in on-site surveys of large regions. Therefore, it is necessary to accumulate fundamental data by actively using LiDAR measurement in future surveys of ancient tombs.

• Journal of Marine Life Science
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• v.8 no.2
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• pp.104-114
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• 2023

As plastic usage increases globally, the amount of plastic waste entering the marine environment is steadily rising. Microplastics, in particular, can be ingested by marine organisms and accumulated in their digestive tracts, causing harmful effects on their growth and reproduction. Cytochrome P450 (CYP) enzymes are known to metabolize various environmental pollutants as detoxification enzymes, but their role in crustaceans is not well understood. In this study, sequences of nine CYP genes (CYP370A4, CYP370C5 from clan 2; CYP350A1, CYP350C5, CYP361A1 from clan 3; CYP4AN-like, CYP4AP2, CYP4AP3, CYP4C33-like1 from clan 4) were analyzed using conserved domains in the brackish water flea Diaphanosoma celebensis. Additionally, after exposure to three different sizes of polystyrene beads (0.05-, 0.5-, 6-㎛ PS beads; 0.1, 1, and 10 mg/L) for 48 hours, the expression of these nine CYP genes were investigated using real-time reverse transcription polymerase chain reaction (RT-PCR). The results showed that all CYP genes possessed conserved motifs, indicating that D. celebensis CYP has evolutionarily conserved functions. Among these CYP genes, the expression of CYP370C5, CYP360A1, and CYP4C122 showed a significant increase after exposure to 0.05-㎛ PS beads, suggesting their involvement in PS metabolism. This research will contribute to understanding the molecular mode of actions of microplastics on marine invertebrates.