Exposure, Risk Assessment and Predictive Exposure Model Development for Agricultural Operator in Representative Crop Fields

DC Field Value Language
dc.description학위논문 (박사)-- 서울대학교 대학원 : 농생명공학부, 2017. 2. 김정한.-
dc.description.abstractKorea predictive model for the estimation of agricultural operator exposure has been developed on the basis of new exposure data to improve the current agricultural operator exposure and risk assessment in the Korea. The new operator exposure model represents current application techniques (speed sprayer and power sprayer) and practices in representative crop fields (apple orchard and rice field). 30 replicate exposure studies conducted between 2010 and 2012 were evaluated for the new model. Exposure and risk assessment were conducted for agricultural applicators during preparation of spray suspension and application with speed sprayer and power sprayer on crop fields. Several exposure matrices, including patches, cotton gloves, socks, masks and XAD-2 resin were used to measure the potential exposure for workers. The analytical methods were fully validated to guarantee the precision and accuracy of analysis. As a major factor contributing to the exposure of operators, the amount of active ingredient used per day was identified. Other parameters such as formulation type, density of the canopy were selected as factors for sub-scenarios. Accordingly, 75 percentile of exposure dose was calculated for mixing / loading and application according to scenario, and it was derived as exposure factor of Korean model. In vitro metabolism of kresoxim-methyl was conducted with human liver microsome. Two metabolites were identified. The screening test for identifying which recombinant CYP involved with metabolism of kresoxim-methyl was conducted with 10 human cDNA-expressed CYP isoforms. Eight rCYPs (except 2A6, 2E1) contributed to metabolism of kresoxim-methyl.-
dc.description.tableofcontentsChapter I: Exposure of Operators, Risk Assessment, and Model Development 1
Introduction 1
Occupational exposure study 1
Methodology of agricultural worker exposure to pesticides 5
Dermal exposure 5
Risk assessment 6
Predictive model 8
Korea predictive operator exposure model 10

Part 1 : Probabilistic Exposure Assessment for Applicators during Treatment of the Fungicide Kresoxim-methyl on Apple Orchard by Speed Sprayer 13
Introduction 15
Materials and Methods 17
Reagents and materials 17
Dermal exposure matrices 17
Inhalation exposure matrices 17
Experimental sites and field trial 18
Exposure matrices sampling 20
Extraction of kresoxim-methyl from exposure matrices 20
Instrumental conditions 20
Method validation 21
Exposure assessment 22
Exposure estimation using Monte Carlo simulation for kresoxim-methyl 23
Risk assessment 24
Results and Discussion 25
Selection of crops and pesticide 25
Method validation 25
Determination of the number of iterations 26
Dermal exposure assessment 33
Inhalation exposure assessment 34
Exposure database for predictive model 34
Risk assessment 39

Part 2 : Exposure and Risk Assessment of Operators to Insecticide Acetamiprid during Treatment on Apple Orchard 45
Introduction 47
Materials and Methods 49
Reagents and materials 49
Exposure matrices 49
Experimental sites 50
Chromatographic condition 50
Limit of detection (LOD), limit of quantitation (LOQ), reproducibility and linearity of calibration curve 52
Trapping efficiency and breakthrough tests 52
Recovery (Matrix extraction efficiency) test 52
Extraction of acetamiprid from exposure matrices 53
Field trials and sampling procedure 53
Calculation of potential dermal and inhalation exposure 54
Risk assessment 54
Results and Discussion 56
Method validation 56
PDE and PIE 60
MOS and Risk Assessment 67
Database for model 67

Part 3 : Comparative Exposure of Operators to Fenthion during Treatment in Paddy Field 73
Introduction 75
Materials and Methods 77
Reagents and materials 77
Sampling methodology 77
Calculation of dermal and inhalation exposure 77
Analytical condition 77
Method validation 78
Sampling and field experiment 78
Results and Discussion 80
Method validation 80
Potential dermal exposure and inhalation exposure 80
Risk Assessment 87
Database for model 87

Part 4 : Operator Exposure to Indoxacarb Wettable Powder and Water Dispersible Granule during Mixing/loading and Risk Assessment 93
Materials and Methods 95
Experimental materials 95
Exposure study samples and analytical conditions 95
Extraction of exposure matrices 95
LOD, LOQ, and reproducibility 96
Recovery (Matrix extraction efficiency) test 96
Trapping efficiency and breakthrough tests 96
Field study, calculation of exposure, and risk assessment 97
Results and Discussion 98
Method Validation 98
Hand exposure, inhalation exposure and MOS 99

Part 5 : Hand Exposure of Operator to Chlorpyrifos during Mixing/loading and Risk Assessment 107
Materials and Methods 109
Reagents and materials 109
Analytical method validation 109
Measurement of hand exposure and risk assessment 109
Results and Discussion 111
Method validation 111
Hand exposure and risk assessment 111

Chapter II: In vitro metabolism of kresoxim-methyl by human liver microsomes 117
Introduction 119
In vitro human metabolism studies of pesticides 119
Human liver microsomal CYP450 122
Enzyme kinetics in metabolism 125
Materials and Methods 128
Chemicals and reagents 128
Analytical instruments and conditions 128
Metabolism of kresoxim-methyl in HLMs (Phase I reaction) 130
Metabolite identification 130
Optimization of metabolic conditions and kinetic studies 130
Metabolism of kresoxim-methyl by cDNA-expressed CYP450 isoforms 131
Determination of crystal structure 131
Results and discussion 132
Formation of the kresoxim-methyl metabolite by HLMs 132
Optimization of metabolic conditions and kinetic studies 132
Metabolism of kresoxim-methyl in cDNA-expressed CYP450 isoforms 133
Determination of crystal structure for kresoxim-methyl 142

Supplementary Materials 146
References 169
Abstract in Korean 179
dc.format.extent1979655 bytes-
dc.publisher서울대학교 대학원-
dc.subjectdermal exposure-
dc.subjectexposure model-
dc.subjecthuman liver microsome-
dc.subjectinhalation exposure-
dc.subjectrisk assessment-
dc.titleExposure, Risk Assessment and Predictive Exposure Model Development for Agricultural Operator in Representative Crop Fields-
dc.contributor.affiliation농업생명과학대학 농생명공학부-
Appears in Collections:
College of Agriculture and Life Sciences (농업생명과학대학)Dept. of Agricultural Biotechnology (농생명공학부)Theses (Ph.D. / Sc.D._농생명공학부)
Files in This Item:
  • mendeley

Items in S-Space are protected by copyright, with all rights reserved, unless otherwise indicated.