Identifying pollution sources of sediment in Lake Jangseong, Republic of Korea, through an extensive survey: Internal disturbances of past aquaculture sedimentation.

Lake sediments are important sinks of various pollutants and preserve historical pollution records caused by anthropogenic activities. Recently, the sediments of Lake Jangseong, South Korea were first detected with high concentrations of organic matter (ignition loss [IL]; total organic carbon [TOC]), nutrients (total nitrogen [TN]; total phosphorus [TP]), and some heavy metals (Zn, Cu, Cd, and Hg). Here, we identified the origins of these concentrations accumulated in the sediments using extensive surveys and various assessments. Sediment pollution assessed by sediment quality guidelines, pollution load index, and potential ecological risk index was found to be of serious concern for IL, TN, TP, and Cd. Thus, we assessed pollution sources through spatial, grid, and vertical distributions and found that the high pollutant concentrations detected in 2020 were confirmed only at a certain location in the lake. Additionally, similar results were detected in the sedimentary layer below a sediment core at a depth of 15.0 cm. The high pollutant concentrations locally occurred around a "hotspot" site that was previously frequently used for aquaculture activities, indicating that the pollutants were accumulated in sediments owing to past cage fish farming rather than from influx of externally sourced pollution. Furthermore, chemical fractionation of phosphorus and heavy metals and assessment of stable isotopes (13C and 15N) of organic matter suggested that the pollutants in the sediments at the "hotspot" sites had different origins than those found at other sites. Accordingly, the by-products discharged after cage fish farming, such as residual feed, fish meal, and waste, accumulated in the sediments and were then exposed to natural internal disturbances caused by the effects of climate change-induced drought. This local distribution and the phosphorus and heavy metal chemical fraction results with low elution potential indicated that the pollutants in the sediments of Lake Jangseong had negligible impact on water quality.

Tracking nitrate sources in agricultural-urban watershed using dual stable isotope and Bayesian mixing model approach: Considering N transformation by Lagrangian sampling.

A dual isotopes approach and the Bayesian isotope mixing model were applied to trace nitrogen pollution sources and to quantify their relative contribution to river water quality. We focused on two points to enhance the applicability of the method: 1) Direct measurement on the end-members to distinguish "sewage" and "manure" which used to be grouped in one pollution source as their isotope ranges overlap; 2) The Lagrangian sampling method was applied to consider the transport of nitrogen pollutants in a long river so that any fractionation process can be dealt with in the given Bayesian modeling framework. The results of the analysis confirmed the NO3- isotope composition in the river of interest to be within the range of NO3- with origins in "NH4+ in fertilizer", "Soil N", and "Manure and sewage" pollution. This suggests that nitrogen pollution is mostly attributed to anthropogenic sources. The δ18O NO3 value follows the range +2.5∼+15.0‰, implying that NO3- in the river is mainly derived from nitrification, and possible nitrification in groundwater or waterfront other than surface water. The ratio of the concentration of δ15N NO3 to that of δ18O NO3, and the corresponding regression equation indicates that the denitrification effect in surface water was insignificant during the study period. From the results of the contribution ratio of each source, improving the water quality of the discharge from the sewage treatment plants was proved to be the key factor to reduce nitrogen pollution in the river.

Assessing heavy metals in surface sediments of the Seomjin River Basin, South Korea, by statistical and geochemical analysis.

We investigated particle size distribution and heavy metal concentrations in surface sediments of streams and lakes in the Seomjin River Basin by comparison with Sediment Quality Guidelines (SQGs). Origins were identified using statistical and geochemical approaches. Sand was prevalent in mean particle size of surface sediments (except lakes). Mean concentrations of Pb, Zn, Cd, and Hg were similar for the Seomjin and Boseong rivers, while those of Cu, As, Cr, and Ni were approximately 1.5-2.0 times higher in the Boseong. SQGs revealed no serious pollution in the basin's site concentrations, although As and Ni levels in the Boseong had some potential for benthos toxicity. Correlation and principal component/factor analysis showed that concentrations of Cu, As, Cr, and Ni were dominant from geological origins rather than anthropogenic. The reducible fraction bound to Fe and Mn-oxides was prevalent in Pb, while the water- and acid-soluble fractions were easily exchangeable or bound to high Cd carbonates. The fraction bound to the highest lattice in residual prevailed in Zn, Cu, Cr, and Ni, accounting for 64%, 65%, 87%, and 86%, respectively. Similarly, results indicated geological origins. Risk assessment to benthos based on labile fractions (F1 + F2 + F3) were Cd (72%) < Pb (66%) < Zn (36%) ≈ Cu (35%) < Ni (14%) ≈ Cr (13%). While Cd and Pb showed the highest risk, their concentrations were relatively lower. However, Cr and Ni showed the highest concentrations but low risk levels, suggesting their pollution is unlikely to have adverse effects on benthos.

Organic matter and heavy metal in river sediments of southwestern coastal Korea: Spatial distributions, pollution, and ecological risk assessment.

This study identifies the impact of river sediments on coastal ecosystems in the southwestern coastal region of Korea. Surface sediments were analyzed for their spatial distributions of organic matter, nutrients, and heavy metal concentrations. Furthermore, pollutants were identified according to the pollution load index (PLI) and potential ecological risk index (RI). Concentrations did not show serious pollution levels compared to generalized guidelines; however, some sites exceeded the PLI pollution standard, and were also identified as potential ecological risks. Through cluster analyses the sediment sites were classified into three groups: rivers with relatively high concentrations of organic matter and nutrients, rivers affected largely by artificial heavy metal pollution, and rivers with low levels of pollution by organic matter, nutrients, and heavy metals. It is evident that continuous monitoring and management are required to prevent major pollution from industrial complexes, agriculture, and commercial activities in the regions near these rivers.

Analysis of spatiotemporal variation in river water quality using clustering techniques: a case study in the Yeongsan River, Republic of Korea.

Herein, cluster analysis was applied to evaluate the spatiotemporal variations in water quality variables of a river. The analysis was performed using the data obtained from 15 monitoring stations during 2007-2018 in the Yeongsan River, Republic of Korea. The spatiotemporal analysis successfully clustered the annual water quality variables temporally into years of poor water quality (2007-2012) and good water quality (2013-2018), and spatially into stations observing bad water quality (midstream) and good water quality (upstream and downstream). For the spatial cluster analysis results before and after a large river engineering project, the water quality was grouped into four clusters according to regional effects and water pollutant sources. The clustering analysis results clearly reflected changes in the water quality along the river due to the project. Overall, this study demonstrates that cluster analysis can be effectively used for evaluating spatiotemporal variations in river water quality.

Distribution and ecological risk of pharmaceuticals in surface water of the Yeongsan river, Republic of Korea.

This study examined the distribution of pharmaceuticals in Yeongsan River and at point sources (PSs) in the associated water system, and performed a risk assessment based on our findings. The samples included effluents collected from three sewage treatment plants (PS1, PS2, and PS3) and two industrial complexes (PS4 and PS5) as well as surface water collected from seven mainstreams and 11 tributaries of the river. The target pharmaceuticals were acetylsalicylic acid, carbamazepine, clarithromycin, naproxen, sulfamethazine, sulfamethoxazole, sulfathiazole, and trimethoprim, which were detected by liquid chromatography-tandem mass spectrometry. All pharmaceuticals except acetylsalicylic acid and sulfathiazole were found in PS1, PS2, and PS3 samples, whereas acetylsalicylic acid, carbamazepine, sulfamethazine, and sulfamethoxazole were found in PS4, most of the pharmaceuticals were not present in PS5. The rank order of pharmaceutical concentration in surface water was carbamazepine (97.2%, 0.2067 µg/L) > sulfamethoxazole (88.9%, 0.1132 µg/L) > naproxen (51.4%, 0.0516 µg/L) > clarithromycin (43.1%, 0.0427 µg/L). The distribution of pharmaceuticals in the Yeongsan River at PSs and non-PSs differed, and higher concentrations of human pharmaceuticals were detected in upstream and midstream areas whereas higher concentrations of animal pharmaceuticals were found downstream. Hazard quotients (HQs) evaluated at each sites based on mean concentration and 95% upper confidence limits (95% UCLs) were all less than one, indicating a low risk of toxicity. The findings of this study are expected to be useful for risk assessment of aquatic ecosystems.