| Occurrence of Pesticides in the Nakdong River Basin and Risk Assessment |
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Hee-Young Kim1, Hee-Jin Jung1, Jae-Jung Yoo2, Tae-Hyo Lim3, Young-Kyong Lim2, Jeong-Eun Oh1 |
1Department of Civil and Environmental Engineering, Pusan National University, Busan 46241, Korea
2Nakdong River Environment Research Center, National Institute of Environmental Research, Goryeong, 40103, Korea |
| 낙동강 수계에서의 농약류 발생 및 위해성 평가 |
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김희영1, 정희진1, 유재정2, 임태효3, 임영경2, 오정은1 |
1부산대학교 사회환경시스템공학부 환경공학전공
2국립환경과학원 낙동강물환경연구소 |
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| Abstract |
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In this study, eight pesticides belonging to the groups of carbamates, phenoxy-acids, heterocyclics were analyzed to identify their concentrations and distribution patterns at various sampling locations (20 sites) in the Nakdong River basin during various sampling periods (May, July, September, and November 2012). Among the eight pesticides, carbofuran showed the highest mean concentration (0.0335 μg/L), followed by methomyl (0.0138 μg/L) and quinoline (0.0070 μg/L), while aldicarb and molinate were observed below the method detection limit (MDL). Quinoline was the most frequently detected pesticide with a detection frequency of 85- 100% in all the sampling periods. The concentration levels and the detection frequencies of the pesticides seemed to be related with the pesticides’ shipment/production. Among the four sampling periods, September showed the highest mean and median concentrations, although the differences were not statistically significant.
The concentration levels were higher in the midstream area than the up and downstream areas of the Nakdong River, because a number of potential contamination pathways such as wastewater treatment plants, industrial facilities and agricultural fields were located in this zone. All these non-cancer-causing pesticides, except quinolone, showed no risk value (risk assessment value < 1). This study could be used as basic data for risk assessment and analysis procedures for quality assurance and quality control of pesticides in Korea. |
| Key Words:
Pesticide, Nakdong River, Risk assessment, Monte-Carlo simulation |
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