Publications

Groundwater serves various purposes worldwide, including agricultural, drinking, domestic, and industrial uses. In the Republic of Korea, groundwater is used primarily for agricultural purpose. Understanding the quality of groundwater is crucial because microplastics (MPs) can enter groundwater through agricultural activities and potentially pose harm to humans. Therefore, groundwater sampling plays a vital role in determining the presence of MPs. However, the optimal volume of groundwater sampling required for accurate MP assessment remains uncertain. This study examined the optimal sample size for collecting MPs from groundwater in the heavy agricultural area of the Haean Basin, Korea. Groundwater sampling and MP analyses were conducted during the wet and dry seasons of 2022. A total of 500 L of groundwater was continuously sampled in increments of 100 L to 500 L (100, 200, 300, 400, and 500 L). Additionally, we investigated the land use surrounding the sampling wells and the predominant types of plastics used in agriculture. To ensure reliable MP analysis, precautions were taken to minimize plastic contact during sampling, pretreatment, and μ-FTIR analysis. The concentration of MPs in groundwater ranged from 0.04 to 17.77 particles/L during the wet season and from 0 to 0.56 particles/L during the dry season. The highest concentration of MPs was observed at the first 100 L sample volume, with concentrations decreasing as the sampling volume increased. Fragmented particles accounted for 86.3 % during the wet season and 91.5 % during the dry season, whereas fibers constituted 13.7 and 8.5 %, respectively. MPs in the size range of 20–100 μm were predominant in both seasons. The polymers identified in both seasons were polypropylene (PP), polyethylene (PE), polyvinyl chloride (PVC), and polyamide (PA). While some studies suggest that 500 L is the optimal sample volume for assessing MPs in groundwater, the findings of this study indicate that a larger sample volume may be necessary. This study was the first attempt to determine the optimum sample volume required to collect MPs from groundwater, emphasizing the importance of conducting further research to validate these findings.

Microplastic (MP) pollution in urban environments is a pervasive and complex problem with significant environmental and human health implications. Although studies have been conducted on MP pollution in urban environments, there are still research gaps in understanding the exact sources, regulation, and impact of urban MP on the environment and public health. Therefore, the goal of this study is to provide a comprehensive overview of the complex pathways, harmful effects, and regulatory efforts of urban MP pollution. It discusses the research challenges and suggests future directions for addressing MPs related to environmental issues in urban settings. In this study, original research papers published from 2010 to 2024 across ten database categories, including PubMed, Google Scholar, Scopus, and Web of Science, were selected and reviewed to improve our understanding of urban MP pollution. The analysis revealed multifaceted sources of MPs, including surface runoff, wastewater discharge, atmospheric deposition, and biological interactions, which contribute to the contamination of aquatic and terrestrial ecosystems. MPs pose a threat to marine and terrestrial life, freshwater organisms, soil health, plant communities, and human health through ingestion, inhalation, and dermal exposure. Current regulatory measures for MP pollution include improved waste management, upgraded wastewater treatment, stormwater management, product innovation, public awareness campaigns, and community engagement. Despite these regulatory measures, several challenges such as; the absence of standardized MPs testing methods, MPs enter into the environment through a multitude of sources and pathways, countries struggle in balancing trade interests with environmental concerns have hindered effective policy implementation and enforcement. Addressing MP pollution in urban environments is essential for preserving ecosystems, safeguarding public health, and advancing sustainable development. Interdisciplinary collaboration, innovative research, stringent regulations, and public participation are vital for mitigating this critical issue and ensuring a cleaner and healthier future for urban environments and the planet.

The 2010 Haiti earthquake displaced millions of people and induced numerous landslides. Migrants triggered staggering deforestation since new settlers need wooden resources. This deforestation caused soil degradation, erosion, flooding, and landslides. The purpose of this study is to explore the impact of human displacement on landslide distribution and its frequency changes by comparing land use and land cover (LULC) maps of pre- and post-earthquake landslide distributions in Port-au-Prince, Artibonite, and Grande Anse. To assess the impact of anthropogenic activities on landslides, we employed a maximum likelihood method to produce LULC maps from Landsat images from 2002 to 2015. Landslide inventory maps were created through visual detection from high resolution satellite imagery. LULC characteristics of new landslide areas were assessed to find land cover types experienced landslides and their distribution characteristics, along with the changes in human influx. The result shows that there was no obvious increase in the number of landslides in forested land after the earthquake while grassland and barren showed an increase in the number of landslides (22% in Port-au-Prince and 77.1% in Artibonite, respectively). Migrants had not explored the forest because there were not enough resources to access remote areas and cut down trees. Since the human migration are more likely to be occurred in grassland and barren, anthropogenic impacts were more evident.

The present study investigated the effect of biomass burning on the water cycle using a case study of the Chari–Logone Catchment of the Lake Chad Basin (LCB). The Chari–Logone catchment was selected because it supplies over 90% of the water input to the lake, which is the largest basin in central Africa. Two water balance simulations, one considering burning and one without, were compared from the years 2003 to 2011. For a more comprehensive assessment of the effects of burning, albedo change, which has been shown to have a significant impact on a number of environmental factors, was used as a model input for calculating potential evapotranspiration (ET). Analysis of the burning scenario showed that burning grassland, which comprises almost 75% of the total Chari–Logone land cover, causes increased ET and runoff during the dry season (November–March). Recent studies have demonstrated that there is an increasing trend in the LCB of converting shrubland, grassland, and wetlands to cropland. This change from grassland to cropland has the potential to decrease the amount of water available to water bodies during the winter. All vegetative classes in a burning scenario showed a decrease in ET during the wet season. Although a decrease in annual precipitation in global circulation processes such as the El Niño Southern Oscillation would cause droughts and induce wildfires in the Sahel, the present study shows that a decrease in ET by the human-induced burning would cause a severe decrease in precipitation as well.

Abstract The present study is to explore the feasibility of GRACE-based estimation of a groundwater storage change in a data-poor region using a case study of the Ngadda catchment in the Lake Chad Basin. Although the Ngadda catchment has only one set of in situ time series data of groundwater from 2006 to 2009 and a limited number of groundwater measurements in 2005 and 2009, GRACE-based groundwater storage change can be evaluated against the in situ groundwater measurements combined with specific yield data. The cross-correlation analysis in the Ngadda catchment shows that maximum rainfall reached in July and August, whereas both the maximum total water storage anomaly and the maximum groundwater storage anomaly occurred 2months later. Whereas the mean annual amplitude of total water storage anomaly is about 17cm from both the average total water storage anomaly from three mascon products and the one from three spherical harmonic products, the mean annual amplitude of soil moisture storage anomaly is substantially varied from 5.58cm for CLM to about 14cm for NOAH and Mosaic. The goodness-of-fit tests show that CLM soil moisture produces the closest estimation of groundwater storage anomaly to the in situ groundwater measurements. The present study shows that GRACE-based estimation for groundwater storage anomaly can be a cost-effective and alternative tool to observe how groundwater changes in a basin scale under the limitation of modelling and in situ data availability.

Abstract The scarcity of groundwater storage change data at the global scale hinders our ability to monitor groundwater resources effectively. In this study, we assimilate a state-of-the-art terrestrial water storage product derived from Gravity Recovery and Climate Experiment (GRACE) satellite observations into NASA s Catchment land surface model (CLSM) at the global scale, with the goal of generating groundwater storage time series that are useful for drought monitoring and other applications. Evaluation using in situ data from nearly 4,000 wells shows that GRACE data assimilation improves the simulation of groundwater, with estimation errors reduced by 36% and 10% and correlation improved by 16% and 22% at the regional and point scales, respectively. The biggest improvements are observed in regions with large interannual variability in precipitation, where simulated groundwater responds too strongly to changes in atmospheric forcing. The positive impacts of GRACE data assimilation are further demonstrated using observed low-flow data. CLSM and GRACE data assimilation performance is also examined across different permeability categories. The evaluation reveals that GRACE data assimilation fails to compensate for the lack of a groundwater withdrawal scheme in CLSM when it comes to simulating realistic groundwater variations in regions with intensive groundwater abstraction. CLSM-simulated groundwater correlates strongly with 12-month precipitation anomalies in low-latitude and midlatitude areas. A groundwater drought indicator based on GRACE data assimilation generally agrees with other regional-scale drought indicators, with discrepancies mainly in their estimated drought severity.