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Probabilistic Exposure Assessment of Pesticide Residues in Agricultural Products in Gyeonggi-do

경기도내 유통 농산물 중 잔류농약의 확률론적 노출평가 연구

  • Do, Young-Sook (Health Research & Planning Team, Gyeonggi-do Institute of Health & Environment) ;
  • Kim, Jung-Boem (Health Research & Planning Team, Gyeonggi-do Institute of Health & Environment) ;
  • Kang, Suk-Ho (Health Research & Planning Team, Gyeonggi-do Institute of Health & Environment) ;
  • Kim, Nan-Young (Health Research & Planning Team, Gyeonggi-do Institute of Health & Environment) ;
  • Eom, Mi-Na (Health Research & Planning Team, Gyeonggi-do Institute of Health & Environment) ;
  • Yoon, Mi-Hye (Health Research & Planning Team, Gyeonggi-do Institute of Health & Environment)
  • 도영숙 (경기도보건환경연구원 보건연구기획팀) ;
  • 김중범 (경기도보건환경연구원 보건연구기획팀) ;
  • 강석호 (경기도보건환경연구원 보건연구기획팀) ;
  • 김난영 (경기도보건환경연구원 보건연구기획팀) ;
  • 엄미나 (경기도보건환경연구원 보건연구기획팀) ;
  • 윤미혜 (경기도보건환경연구원 보건연구기획팀)
  • Received : 2013.04.18
  • Accepted : 2013.05.21
  • Published : 2013.08.30

Abstract

A probabilistic exposure assessment was performed on the monitoring data of pesticides were assessed in agricultural products in Gyeonggi-do from 2006 to 2010. Chlorothalonil, chlorpyrifos, dicofol, endosulfan, EPN, ethoprophos, fenitrothion, methidathion, phenthoate and tebupirimfos were assessed. For this assessment, we used Monte Carlo simulation software and the distribution of concentration and intake were assumed to lognormal distribution by inputting mean and standard deviation. The hazard index (HI, %ADI) of average value and the $95^{th}$ percentile based on a probabilistic method were usually lower than those by a deterministic one. For the whole population, when non-detects data were assigned 0 mg/kg, HI of the average value and the $95^{th}$ percentile showed 0.05~0.70% and 0.11~1.94%, respectively. When nondetects data were assigned 0.005 mg/kg, HI of the average value and the $95^{th}$ percentile were 0.41~4.42% and 0.98~13.81%. For only consumers, when non-detects data were assigned 0 mg/kg, HI of the average value and the $95^{th}$ percentile were 1.24~10.16% and 3.72~33.81%, respectively. When non-detects data were assigned 0.005 mg/kg, HI of the average value and the $95^{th}$ percentile were 3.43~18.26% and 9.45~54.99%, respectively. Methidathion had highest values when both of 0 and 0.005 were assigned to non-detecs data for consumers only. This study showed that agricultural products in Gyeonggi-do were safe because they had less than 100 of HI (%ADI) based on probabilistic exposure assessment.

References

  1. Agrochemical use guide book (2011) 478. KCPA.
  2. Choi, H., S. K. Park and M. H. Kim (2012) Risk Assessment of Mercury through Food Intake for Korean Population. Korean J. Food Sci. Technol. 44(1):106-113. https://doi.org/10.9721/KJFST.2012.44.1.106
  3. Claeys, W. L., S. De Voghel, J. F. Schmit and V. V. Pussemier (2007) Exposure assessment of the Belgian population to pesticide residues through fruit and vegetable consumption. Food Addit. Contam. 25(7):851-863.
  4. Do, J. A., H. J. Lee, Y. W. Shin, W. J. Choe, K. R. Chae, K. C. Soon and W. S. Kim (2010) Monitoring of Pesticide Residues in Domestic Agricultural Products, J. Korean Soc. Food Sci. Nutr., 39(6):902-908. https://doi.org/10.3746/jkfn.2010.39.6.902
  5. Do, Y. S., Y. B. Park and M. H. Yoon (2012) Risk assessment for pesticide residues of agricultural products in Gyeonggido. GIHE.
  6. EFSA (2011) Overview of the procedures currently used at EFSA for the assessment of dietary exposure to different chemical substances. EFSA J 9(12):2490. https://doi.org/10.2903/j.efsa.2011.2490
  7. FAO/WHO (2006) Food safety risk anaysis - A guide for national food safety authorities pp11.
  8. FAO/WHO (2009) ICPS EHC 240 Principle and methods for the risk assessment of chemicals in food, 6-45.
  9. Ferrier, H. M. Nieuwenhuijsen, A. Boobis and P. Elliott (2002) Current Knowledge and recent developments in consumer exposure assessment of pesticides: A UK perspective. Food Addit. Contam. 19(9):837-852. https://doi.org/10.1080/02652030210156322
  10. Ferrier, H., G. Shaw, D. M. Nieuwenhuijsen, M. B. Alan and E. Paul (2006) Assessment of uncertainty in a probabilistic model of consumer exposure to pesticide residues in food. Food Addit. Contam. 23(6):601-615. https://doi.org/10.1080/02652030600573244
  11. Flynn, M. R. (2004) The beta distribution-a physically consistent model for human exposure to air borne contaminants. Stoch Envir Res and Risk Ass. 18:306-308. https://doi.org/10.1007/s00477-004-0180-x
  12. Gilsenan, M. B., J. Lambe and M. J. Gibney(2003) Assessment of food intake input distributions for use in probabilistic exposure assessments of food additives. Food Addit. Contam. 20(11):1023-1033.
  13. Hamilton, D., A. Ambrus, R. Dieterle, A. Felsot, C. Harris, B. Petersen, K. Racke, S. S. Wong, R. Gonzalez, K. Tanaka, M. Earl, G. Roberts and R. Bhula (2004) Pesticide residues in food - acute dietary exposure - Pest Manag. Sci., 60: 311-339. https://doi.org/10.1002/ps.865
  14. Hamilton, D. (2000) Making the best use of available residue data for acute intake assessment. Food Addit. Contam. 17:563-8. https://doi.org/10.1080/026520300412465
  15. Han, K. T., K. S. Lee, E. K. Lee, K. Y. Ko, D. J. Won, J. W. Lee and S. D. Kwon (2003) Pesticide Residue Survey and Estimate lntake Amount of Vegetables in Noeun Wholesale Market, Daejeon. Korean J. Environmental Agriculture 22(3):210-214. J. Korean Soc Food Sci Nutr., 38(12): 1779-1784. https://doi.org/10.5338/KJEA.2003.22.3.210
  16. http://www.rda.go.kr/board/
  17. http://fse.foodnara.go.kr/residue/.
  18. Jang, M. R., H. K. Moon, T. R. Kim, D. H. Yuk, J. H. Kim and S. G. Park (2010) Dietary Risk Assessment for Pesticide Residues of Vegetables in Seoul, Korea, Korean J. Nutr, 43(4):404-412. https://doi.org/10.4163/kjn.2010.43.4.404
  19. Jung, J. Y., M. S. Hwang, G. G. Jung and H. J. Yoon (2011) Study for developing integrated risk assessmnet technology of heavy metal. 39-52. KFDA.
  20. Lee, M. G., J. H. Shim, S. H. Ko, H. R. Chung (2010) Research Trends on the Development of Scientific Evidence on the domestic Maximum Residue Limits of Pesticides. Food Sci. indus. 43(2):41-66.
  21. Kim, C. J., J. H. Jung, S. J. Lee, Y. S. Park and S. H. Ko (2010) Calculation of food commodity intake for safety control of pesticide residues. Food Sci. indus. 43(2):67-78
  22. KFDA (2011) Guidelines for risk assessment.
  23. Korea centers for disease control and prevention (2009) The fourth korea national and nutrition examination survey.
  24. Lee, M. G. (2002) Cumulative risk assessment and predictive modeling of pesticide residues in foods. Korea Sci. & Engin. Foundation. R05-2000-000-00206-0, pp 18-20.
  25. Lee, H. J., W. J. Choe, J. Y. Lee, D. H. Cho, C. S. Kang and W. S. Kim (2009) Monitoring of Ergosterol Biosynthesis Inhibitor (EBI) Pesticide Residues in Commercial Agricultural Products and Risk Assessment. J. Korean Soc. Food Sci. Nutr. 38(12):1779-1784. https://doi.org/10.3746/jkfn.2009.38.12.1779
  26. Paik, M. K., B. J. Park, K. A. Son, J. B. Kim, S. M. Hong, W. I. Kim, G. J. Im and M. K. Hong (2010) Probabilistic Approach on Dietary Exposure Assessment of Neonicotinoid Pesticide Residues in Fruit Vegetables, Korean J. Pest. Sci. 14(2):110-115.
  27. Voet, H., P. E. Boon and J. D. van Klaveren (2003) Validation of monte carlo models for estimating pesticide intake of Dutch infants. EC QLRT-1999-00155, Institute of Food Safety, Netherlands, pp8.

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