To prevent severe air pollution, it is important to analyze time-series air quality data, but this is often challenging as the time-series data is usually partially missing, especially when it is collected from multiple locations simultaneously. To solve this problem, various deep-learning-based missing value imputation models have been proposed. However, often they are barely interpretable, which makes it difficult to analyze the imputed data. Thus, we propose a novel deep learning-based imputation model that achieves high interpretability as well as shows great performance in missing value imputation for spatio-temporal data. We verify the effectiveness of our method through quantitative and qualitative results on a publicly available air-quality dataset.

This research was to conduct a pilot study for two consecutive days in order to assess fine particulate matter (PM_2.5) exposure of an entire population in a community. We aimed to construct a surveillance system by analyzing the observed spatio-temporal variation of exposure. Guro-gu in Seoul, South Korea, was divided into 2,204 scale grids of 100 m each. Hourly exposure concentrations of PM_2.5 were modeled by the inverse distance weighted method, using 24 sensor-based air monitoring instruments and the indoor-to-outdoor concentration ratio. Population distribution was assessed using mobile phone network data and indoor residential rates, according to sex and age over time. Exposure concentration, population distribution, and population exposure were visualized to present spatio-temporal variation. The PM_2.5 exposure of the entire population of Guro-gu was calculated by population-weighted average exposure concentration. The average concentration of outdoor PM_2.5 was 42.1 µg/m³, which was lower than the value of the beta attenuation monitor measured by fixed monitoring station. Indoor concentration was estimated using an indoor-to-outdoor PM_2.5 concentration ratio of 0.747. The population-weighted average exposure concentration of PM_2.5 was 32.4 µg/m³. Thirty-one percent of the population exceeded the Korean Atmospheric Environmental Standard for PM_2.5 over a 24 h average period. The results of this study can be used in a long-term aggregate and cumulative PM_2.5 exposure assessment, and as a basis for policy decisions on public health management among policymakers and stakeholders.

Climate change has been considered as a main threat for food safety by influencing on crop production and food supply chain through the change in temperature and humidity. To prevent risks of mycotoxins from climate change, it is important to predict mycotoxin risks with statistical approaches and stepwise process to compile large volume of datasets, such as climate change, contamination level, and cultivation area in specific regions. This paper aims at prioritization of vulnerable mycotoxins related to climate change in Korea. In addition, this paper focuses on prioritization of vulnerable raw materials for specific mycotoxins and prediction of vulnerable regions for vulnerable raw materials in Korea. Among six target mycotoxins (deoxynivalenol, fumonisin (B1 and B2), ochratoxin A, patulin, total aflatoxin (B1, B2, G1, and G2), and zearalenone), ochratoxin A (OTA) and total aflatoxin (TA) were identified as specific vulnerable mycotoxins. In addition, 4 raw materials (chestnut, dried red pepper, perilla seed, and soy bean) were identified as vulnerable raw materials for OTA and TA and vulnerable regions were predicted to be moved to the northward areas in Korea. These results can be utilized to design long-term national sampling plan for mycotoxins in food considering climate change in Korea.

Veterinary drugs are widely used to protect production-related diseases and promote the growth of farmed fish. The use of large amounts of veterinary drugs may have potential risk and cause adverse effects on both humans and the environment. In this study, we developed risk-based ranking based on a scoring system to be applied in the national residue program. In this approach, the following three factors of veterinary drugs that may occur as residues in fishery products were considered: potency (acceptable daily intake), usage (number of dose and withdrawal period), and residue occurrence. The overall ranking score was calculated using the following equation: potency × usage (sum of the number of sales and withdrawal period) × residue occurrence. The veterinary drugs that were assigned high score by applying this approach were enrofloxacin, amoxicillin, oxolinic acid, erythromycin, and trimethoprim. The risk-based approach for monitoring veterinary drugs can provide a reliable inspection priority in fishery products. The developed ranking system can be applied in web-based systems and residue-monitoring programs and to ensure safe management of fishery products in Korea.

Iodine is an essential component of thyroid hormones, but excessive iodine intake can lead to thyroid dysfunction. Traditionally, Korean mothers consume brown seaweed soup (miyeokguk), a high source of iodine, after childbirth. There is controversy regarding the effects of excessive postpartum iodine intake on the health of mothers and infants. Thus far, there have been no nationwide large-scale surveys regarding the status of iodine intake among postpartum women in Korea. Therefore, we conducted a nationwide survey of postpartum dietary iodine intake among Korean women. In total, 1054 Korean women aged ≥19 years, at less than 8 weeks postpartum, participated in this survey. Dietary data were collected using self-reported 2-day dietary records, along with before-and-after meal photos. To evaluate the correlation between dietary iodine and urinary iodine excretion (UIE), spot urine, and 24 h urine samples were collected from 98 and 29 participants, respectively. The mean daily iodine intake among all participants was 2945.6 μg, and it gradually decreased over time after childbirth. Dietary iodine intake was significantly correlated with 24 h UIE (r = 0.396, p < 0.05) and spot urine UIE (r = 0.312, p < 0.05). Follow-up studies are required to examine the influence of excessive postpartum iodine intake on thyroid health in mothers and their infants.