Exposure assessment for pesticide residues in consumed agricultural products in the Republic of Korea

Exposure assessment for pesticide residues in consumed agricultural products in the Republic of Korea | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Exposure assessment for pesticide residues in consumed agricultural products in the Republic of Korea Tae-Hun Kim, Su Chin Park, Ji Eun Kim, Hyun Jun Yeon, Ju Ho Kim, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1490058/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract Pesticide residues in food are intentional pollutants such as insecticides, fungicides, herbicides, miticides, and plant activators. The insecticides diazinon and malathion are classified as probably carcinogenic to humans (Group 2A) by the International Agency for Research on Cancer under the World Health Organization, and the fungicides chlorothalonil and hexachlorobenzene are classified as possibly carcinogenic to humans (Group 2B). In this study, gas chromatography and gas chromatography–tandem mass spectrometry analyses were used to identify the concentrations of pesticide residues in agricultural products and to assess the effects of chronic human exposure to pesticide residues via agricultural consumption. Food consumption data were obtained from the Korea National Health and Nutrition Examination Survey 2016–2018. Chronic exposures using mean consumption data for the whole population, with mean concentration of pesticide residues, were 5.15E-11 ~ 2.08E-05 (LB) and 2.41E-07 ~ 4.69E-05 mg/kg bw/day (UB), corresponding to 0.00012 ~ 2.16% of hazard index (HA). Exposures to pesticide residues using the 95th percentile of the consumption data were 0 ~ 8.76E-05 (LB) and 9.26E-07 ~ 1.56E-04 mg/kg bw/day (UB), corresponding to 0.00045 ~ 9.41% of HA. Insecticides Fungicides Herbicides Miticides Plant activators Agricultural product consumption Exposure assessment Hazard index Figures Figure 1 Figure 2 1. Introduction Pesticides, including insecticides, fungicides, herbicides, miticides, and plant activators, refer to drugs used to control pests, bacteria, weeds, and mites that harm agricultural products or to enhance or suppress the physiological functions of agricultural products. Pesticide residues refer to the small amounts of pesticides that remain in agricultural products. Diazinon is an insecticide and a pesticide that binds with cholinesterase, an enzyme present in the nervous system and blood of the human body, to form a complex, thereby, inhibiting the function of cholinesterase, which is to decompose acetylcholine into acetic acid and choline (Rosenberg, 1990 ). In terms of human toxicity, plasma cholinesterase activity decreased by an average of 48% when diazinon was administered at 0.03 mg/kg bw/day for 20 days to four men (Beilstein, 1998 ). Chlorothalonil, a fungicide, acts as an alkylating agent and reacts with sulfhydryl compounds in cells (NLM, 1990). Within 15 to 30 minutes of inhalation exposure to chlorothalonil, patients experienced severe facial edema, nasal congestion, chest tightness, laryngeal spasms, dysphagia, dyspnea, and wheezing, along with itching and general edema (Dannaker et al., 1993 ). The herbicide, atrazine, has been shown to increase the risk of ovarian tumors in women exposed to it in an Italian study. When 400 mg/kg was orally administered to livestock, there was a proliferation of subcutaneous hemolysis, liver necrosis, ataxia, black stools, and eventually, death (NLM, 1997). The Korea Food and Drug Administration (KFDA) regulation of pesticide residues in agricultural products is set to 0.005 to 400 mg/kg, depending on the levels of intake and contamination (KFDA, 2021). The use of pesticides is indispensable as a means of improving crop productivity; however, if the pesticides are abused or misused, they remain in agricultural products and can cause toxicity to the human body when ingested, and therefore, safety management and monitoring are continuously required. In this study, pesticide residue exposure was assessed from the domestic consumption of agricultural products using the concentration data of 158 pesticide residues collected from 2016 to 2020 and consumption data obtained from the Korea National Health and Nutrition Examination Survey (KNHANES) 2016–2018. 2. Materials And Methods 2.1. Samples From January 2016 to December 2020, 11,776 agricultural products were collected from the Noeun Agricultural and Marine Products Wholesale Market in Daejeon, Korea, including cereal grains, potatoes, pulses, peanut or nuts, oilseeds, pome fruits, citrus fruits, stone fruits, berries and other small fruits, assorted tropical and sub-tropical fruits, flowerhead brassicas, leafy vegetables, stalk and stem vegetables, root and tuber vegetables, fruiting vegetables, cucurbits, fruiting vegetables other than cucurbits, and mushrooms. These samples were used to monitor items corresponding to 98.6 % of the total agricultural products consumed by Koreans between 2016 and 2018 (Kang et al., 2019). The samples were composed of 97.3 % domestic and 2.7 % imported products. 2.2. Reagent and solutions The standards for pesticide residues (insecticide, fungicide, herbicide, miticide, and plant activator) were purchased from AccuStandard (New Haven, Connecticut, USA). Acetonitrile, methanol, and dichloromethane were purchased from Merck (Darmstadt, Germany). Sodium chloride, anhydrous sodium sulfate, acetone, and hexane were purchased from Wako Pure Chemicals (Osaka, Japan). Water was obtained from a Barnstead NANOpure Diamond™ water purification system (Asheville, NC, USA). 2.3. Sample pretreatment One kilogram of the sample was put into a cutter mixer and 50 g of the pulverized sample was weighed into an Omni mixer bottle, and to this 100 mL of acetonitrile was added. It was then homogenized for 2–3 minutes with a mixer extractor. Following homogenization, it was filtered under reduced pressure with a Buchner funnel lined with filter paper. The filtrate was transferred to a 500 mL separatory funnel containing 15 g of sodium chloride, after which the stopper was closed, and it was shaken vigorously and allowed to stand until the layers were completely separated. After dehydrating it by passing the acetonitrile layer through anhydrous sodium sulfate, separate acetonitrile was added to make up the final volume to 100 mL. Each acetonitrile layer (20 mL) was taken and concentrated under reduced pressure on a water bath at 40 °C or lower to blow off the solvent. The residue was dissolved in 4 mL of 20 % acetone/hexane. The solution dissolved in 4 mL of 20 % acetone/hexane is eluted in a Florisil cartridge previously activated with 5 mL of hexane and 5 mL of 20 % acetone/hexane and collected in a test tube. Further, it was eluted with 5 mL of 20 % acetone/hexane and collected in the same test tube. The eluate was used as the test solution by blowing off the solvent while passing air in a water bath below 40 °C and then dissolving it in 3 mL of 20 % acetone/hexane. 2.4. Quantification of pesticide residues 158 pesticide residue monitoring items with high detection frequency were selected among all pesticide residue monitoring items in the Korean Food Code. An Agilent Technologies 7890 A (Santa Clara, USA) gas chromatograph with a nitrogen phosphorous detector and an electron capture detector controlled by Open LAB CDS C.01.07 software was used to determine the pesticide residues (Table 1). The following conditions were applied unless stated otherwise: DB-17 column (30 m × 0.25 mm, 0.25 μm); carrier gas N 2 , gas flow, 1.0 mL/min; inlet split mode, 20:1; and detector temperature, 280 °C. The oven temperature was 80 °C (2 min) → 7 °C /min → 250 °C → 5 °C /min → 280 °C (20 min). The pesticides detected via gas chromatography (GC) were confirmed by a Thermo Scientific Trace 1310 TSQ 9000 (Waltham, USA) gas chromatography–tandem mass spectrometer. The operating conditions were as follows: DB-5MS column (30 m × 0.25 mm, 0.25 μm); carrier gas He, gas flow, 1.2 mL/min; inlet splitless; inlet temperature, 280 °C; source temperature, 230 °C; and electron ionization, 70 eV. The oven temperature was 80 °C (5 min) → 10 °C /min → 300 °C (3 min). 2.5. Method validation The validation of the analytical methods was carried out in accordance with the KFDA guidance document on residue analytical methods (KFDA, 2017). The analytical methods were verified with performance parameters, including the limit of detection (LOD), the limit of quantification (LOQ), and the linearity of the calibration curves. LOD and LOQ were calculated by multiplying the standard deviation by 3 and 10, respectively, and the standard deviation was derived from seven measurements of blank samples spiked at a concentration near the LOQ. The linearity of the calibration curve was evaluated by the coefficient of correlation from a regression equation. 2.6. Exposure assessment The exposure assessment was conducted by combining the pesticide residues contamination values with the agricultural product consumption data (described below), divided by the body weight (USEPA, 2000; WHO, 2009). The means and 95 th percentiles of the daily consumption data were multiplied by the corresponding concentrations of the pesticide residues for each sample. Exposure assessment was also performed for different age groups (EFSA, 2017). 2.6.1. Consumption data Consumption data was extracted from the Korea National Health and Nutrition Examination Survey (KNHANES 2016 – 2018), which surveys the current status and trends of health and nutrition in the Korean population. This survey serves to highlight health-vulnerable groups and calculates the statistics for the effective delivery of health policies and projects. Each year, 25 households in 192 areas are randomly surveyed, totaling approximately 10,000 individuals over 1 year old. The data is divided into age groups for children (1 - 11 years old), adolescents (12 - 18 years old), and adults (19 years or older). Daily food consumption was analyzed according to the different food groups (KNHANES VII, 2016 – 2018). 2.6.2. Contamination data Contamination data were obtained from the analyses using GC (electron capture detector, nitrogen phosphorous detector) and gas chromatography–tandem mass spectrometry in this study. A substitution method was applied to correct the left-censored data (EFSA, 2010; GEMS/Food-EURO, 1995). Because the rate of pesticide residues not detected was over 80 % was applied exposure assessment Zero (Lower Bound, LB) and LOD (Upper Bound, UB). 3. Results And Discussion 3.1. Method validation Table 2 shows the performance parameters used to verify the analytical methods. The LODs for the pesticide residues ranged from 0.00002 to 0.00375 mg/kg, and the LOQs ranged from 0.00008 to 0.01249 mg/kg. The linear regression analysis showed that the calibration curves had consistent linear relationships between the peak areas and concentrations; the regression coefficients were 0.99118 to 0.99998. 3.2. Concentrations of pesticide residues in agricultural product samples The concentrations of pesticide residues in agricultural product samples are summarized in Table 3. The mean concentrations of fludioxonil, pencycuron, and tolylfluanid were high in agricultural product samples. 59 types of residues were found, with 23 pesticide residues exceeding their maximum residue limits (MRLs). The rate of violation of MRLs to the number of detected pesticide residues is 3.7 %. Ethoprophos, tebupirimfos, and diazinon had higher rates of exceeding their MRLs compared to the number of detected pesticide residues. 3.3. Distribution of pesticide residues in agricultural product samples Pesticides were detected in 72 out of 138 types of agricultural products. Meanwhile, 27 (out of 76) types of agricultural product samples exceeded the residue limit (Table 4). No pesticides were detected in cereal grains, peanuts or nuts, and oilseeds. Leafy vegetables have a larger surface area to weight ratio compared to other agricultural products; therefore, pesticides easily get attached to them during spraying, and it is thought that the detection amount is relatively high due to a large amount of adhesion. This result is consistent with the results of domestic studies (Kim et al., 2010). The rates of violation of MRLs were high in flowerhead brassicas, leafy vegetables, stalk and stem vegetables, and root and tuber vegetables. 3.4. Consumption of agricultural products Based on the KNHANES (2016 – 2018), the mean long-term intake of agricultural products was 553.3 g/day for the entire Korean population. The 95 th percentile intake of agricultural products was 2,076.4 g/day for the entire Korean population. 3.5. Exposure to pesticide residues The exposures to pesticide residues using the mean consumption data for whole population were 5.15E-11 ~ 2.08E-05 (LB) and 2.41E-07 ~ 4.69E-05 mg/kg bw/day (UB). The exposures to pesticide residues using the 95 th percentile consumption data for whole population were 0 ~ 8.76E-05 (LB) and 9.26E-07 ~ 1.56E-04 mg/kg bw/day (UB) (see Table 5). Exposure values in the mean and 95 th percentile intake groups of 1 % or greater are summarized in Fig. 1. For the detected pesticides, an acceptable daily intake value was set by the KFDA as the human exposure safety standard (EFSA, 2021). To assess exposure, deterministic estimates of dietary exposure to pesticide residues have to be compared to the human exposure safety standard. Agricultural product consumption resulted in hazard index (HA, % acceptable daily intake) to diazinon that was 0.94 ~ 2.16 %. The HAs of piperophos, tebupirimfos, and methidathion were 1.16, 0.31 ~ 1.12, and 0.17 ~ 1.05 %, respectively. The HAs of diazinon, piperophos, tebupirimfos, and methidathion were at 13 – 30 % (UB) levels in consumers only. Notably, in the high consumers (those on the 95 th ) percentile, HA of diazinon was 57.07 ~ 101.38 % (see Fig. 1A). The exposures across different age groups were estimated as 0 ~ 5.03E-05 (LB) and 1.77E-07 ~ 1.25E-04 mg/kg bw/day (UB). For the 95 th percentile, the exposures across different age groups were estimated as 0 ~ 1.89E-04 (LB) and 6.07E-07 ~ 4.83E-04 mg/kg bw/day (UB). The HA of dimethoate, diniconazole, and edifenphos was 5 to 9 % (UB), which was slightly higher than that of other pesticides. Diazinon, ethoprophos, and methidathion showed higher HA in all age groups, but within 19 % (see Fig. 1B). For diazinon, pesticide residue with high HA value, exposure was also estimated for the individual agricultural product species according to entire Korean population consumption data (see Fig. 2A). For all consumption P95 (consumers only) consumption, radish leaf was the leading diazinon contributor (6.22E-05 mg/kg bw/day, 54.5 %), followed by young radish (2.88E-05 mg/kg bw/day, 25.2 %). Within ≥ 65 Consumption P95 consumption data, radish leaf was the leading diazinon contributor (2.10E-05 mg/kg bw/day, 81.5 %), followed by Korean cabbage (3.78E-06 mg/kg bw/day, 14.7 %). The residual tolerance standard for diazinon radish leaves and young radish was 0.05 mg/kg until 2018, and from 2019, the MRL was changed to non-detection. The number of cases of diazinon detected in radish leaves and young radish was 17 out of a total of 76 cases (detection rate 22.4 %) from 2016 to 2018 and three out of a total of 37 cases (detection rate 8.1 %) from 2019 to 2020. As a result of risk assessment using the contamination level of radish leaves and young radish diazinon from 2019 to 2020, the HA value in consumers of only P95 decreased from 57 (LB) ~ 101 % (UB) to 27 (LB) ~ 71 % (UB) (see Fig. 2B). It is noteworthy that one out of three cases of diazinon detected between 2019 and 2020 was detected at a high concentration (0.535 mg/kg) as nonconforming, and the average contamination value of diazinon used for risk assessment was overestimated. Thus, as a result of performing risk assessment again with the average value excluding nonconformity, the HA value in consumers of only P95 decreased to 13 (LB) ~ 57 % (UB). Therefore, it is expected that the risk for diazinon will be lowered in the future. 4. Conclusions In this study, pesticide residue exposure via agricultural consumption was assessed. It is estimated that Koreans are not at risk of pesticide residue (insecticides, fungicides, herbicides miticides, and plant activators) poisoning. Exposures using mean consumption data pesticide residues were 5.15E-11 ~ 2.08E-05 (LB) and 2.41E-07 ~ 4.69E-05 mg/kg bw/day (UB), corresponding to 0.00012 ~ 2.16% of HA. These exposure assessments indicate that the pesticide residues in agricultural products are adequately controlled by the regulatory authorities. Declarations Corresponding author Correspondence to Tae-Hun Kim. Author contribution Tae-Hun Kim: planning the whole work, writing—original draft. Soo-Hwaun Kim: extracted the agricultural product consumption data. Su Chin Park, Ji Eun Kim, Hyun Jun Yeon, Ju Ho Kim, and Young Soek Park: performed the pesticide residues analysis. Yoon-Hee Oh, Gune-Hee Jo: review and editing. Funding This study was financially supported by a research fund from the Daejeon Metropolitan City Institute of Health and Environment in 2021. Data Availability The authors confirm that all data supporting the study’s findings are included in the article. Ethics approval and consent to participate Not applicable. Consent for publication All authors consent for publication. Conflict of interest The authors declare that they have no conflict of interest. Acknowledgements Thanks to the editors and anonymous reviewers for their valuable suggestions. References Beilstein P (1998) Tolerance study in Novartis managers upon repeated oral administration of diazion Unpublished report No. 972019. Huntingdon Research Centre Ltd, Cambridgeshire Dannaker CJ, Maibach HI, O'Malley M (1993) Contact urticaria and anaphylaxis to the fungicide chlorothalonil. Cutis 52:312–315 European Food Safety Authority (EFSA) (2010) Management of left-censored data in dietary exposure assessment of chemical substances. EFSA J 8:1557. https://doi.org/10.2903/j.efsa.2010.1557 European Food Safety Authority (EFSA) (2017) Human and animal dietary exposure to ergot alkaloids. EFSA J 15:1–53. https://doi.org/10.2903/j.efsa.2017.4902 Global Environment Monitoring System - Food Contamination Monitoring and Assessment Programme (GEMS/Food-EURO) (1995) Reliable evaluation of low-level contamination of food. Report on a workshop in the frame of GEMS/Food-EURO. 26–27 May 1995, Kulmbach, Germany. World Health Organization Regional Office for Europe, Geneva Kang GJ, Choi JD, Kwon JW, Shin MS, Shin YY, Chun SY, Kim SH (2019) Hazardous Pollutants Risk Assessment Practice Standards Manual. National Food and Drug Safety Evaluation, Ministry of Food and Drug Safety, Cheongju. Chap. 3 Kim MO, Hwang HS, Lim MS, Hong JE, Kim SS, Do JA, Choi DM, Cho DH (2010) Monitoring of Residual Pesticides in Agricultural Products by LC/MS/MS. KOREAN J. FOOD SCI. TECHNOL. Vol. 42, No. 6, pp. 664 ~ 675 Korea Food and Drug Administration (KFDA) (2017) Practical Guide to Food Standards Residual Pesticide Analysis Method. National Food and Drug Safety Evaluation, Ministry of Food and Drug Safety, Cheongju. Chap. 7 Korea Food and Drug Administration (KFDA) (2021) The Korean Food Code. Ministry of Food and Drug Safety, Cheongju National Library of Medicine (NLM) (1990) Hazardous Substances Data Bank (HSDB) Toxicology Data Network. http://toxnet.nlm.nih.gov National Library of Medicine (NLM) (1997) Hazardous Substances Data Bank (HSDB) Toxicology Data Network. http://toxnet.nlm.nih.gov Rosenberg J (1990) Occupational medicine, Section â…£ occupational exposure (pesticides) Connecticut Prentice Hall publishing division, pp401-402, 408–417 United States Environmental Protection Agency (USEPA) (2000) Guidance for assessing chemical contaminant data for use. Fish advisories-fish sampling and analysis, Vol. 1, third edition. United States Environmental Protection Agency, Washington, Office of Water383, Chap. 4 World Health Organization (WHO), Geneva (2009) Environmental Health Criteria 240. Principles and methods for the risk assessment of chemicals in food. FAO/WHO. Chap. 6 Tables Table 1-5 are available in the Supplementary Files section. Supplementary Files Table20220325final.doc Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Major Revision 14 May, 2022 Reviews received at journal 15 Apr, 2022 Reviewers invited by journal 15 Apr, 2022 Editor invited by journal 13 Apr, 2022 Editor assigned by journal 06 Apr, 2022 First submitted to journal 25 Mar, 2022 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-1490058","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":98877647,"identity":"91826e36-fb98-4dc2-8623-3755222ec26e","order_by":0,"name":"Tae-Hun 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exposures for the entire Korean population\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-1490058/v1/4cd6ad659aae9ae1dc9aa1e0.png"},{"id":20505163,"identity":"e33cc71d-f917-48a6-a136-11e9f28e6fd7","added_by":"auto","created_at":"2022-04-19 14:32:48","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1092734,"visible":true,"origin":"","legend":"\u003cp\u003eDietary exposure to diazinon via each agricultural product\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-1490058/v1/d38cae5ae7264112eec502f4.png"},{"id":20505165,"identity":"940caa71-473d-4447-a0c6-7e4f9399a4c1","added_by":"auto","created_at":"2022-04-19 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Introduction","content":"\u003cp\u003ePesticides, including insecticides, fungicides, herbicides, miticides, and plant activators, refer to drugs used to control pests, bacteria, weeds, and mites that harm agricultural products or to enhance or suppress the physiological functions of agricultural products. Pesticide residues refer to the small amounts of pesticides that remain in agricultural products.\u003c/p\u003e \u003cp\u003eDiazinon is an insecticide and a pesticide that binds with cholinesterase, an enzyme present in the nervous system and blood of the human body, to form a complex, thereby, inhibiting the function of cholinesterase, which is to decompose acetylcholine into acetic acid and choline (Rosenberg, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e1990\u003c/span\u003e). In terms of human toxicity, plasma cholinesterase activity decreased by an average of 48% when diazinon was administered at 0.03 mg/kg bw/day for 20 days to four men (Beilstein, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). Chlorothalonil, a fungicide, acts as an alkylating agent and reacts with sulfhydryl compounds in cells (NLM, 1990). Within 15 to 30 minutes of inhalation exposure to chlorothalonil, patients experienced severe facial edema, nasal congestion, chest tightness, laryngeal spasms, dysphagia, dyspnea, and wheezing, along with itching and general edema (Dannaker et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e1993\u003c/span\u003e). The herbicide, atrazine, has been shown to increase the risk of ovarian tumors in women exposed to it in an Italian study. When 400 mg/kg was orally administered to livestock, there was a proliferation of subcutaneous hemolysis, liver necrosis, ataxia, black stools, and eventually, death (NLM, 1997).\u003c/p\u003e \u003cp\u003eThe Korea Food and Drug Administration (KFDA) regulation of pesticide residues in agricultural products is set to 0.005 to 400 mg/kg, depending on the levels of intake and contamination (KFDA, 2021). The use of pesticides is indispensable as a means of improving crop productivity; however, if the pesticides are abused or misused, they remain in agricultural products and can cause toxicity to the human body when ingested, and therefore, safety management and monitoring are continuously required. In this study, pesticide residue exposure was assessed from the domestic consumption of agricultural products using the concentration data of 158 pesticide residues collected from 2016 to 2020 and consumption data obtained from the Korea National Health and Nutrition Examination Survey (KNHANES) 2016\u0026ndash;2018.\u003c/p\u003e"},{"header":"2. Materials And Methods","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003e2.1. Samples\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFrom January 2016 to December 2020, 11,776 agricultural products were collected from the Noeun Agricultural and Marine Products Wholesale Market in Daejeon, Korea, including cereal grains, potatoes, pulses, peanut or nuts, oilseeds, pome fruits, citrus fruits, stone fruits, berries and other small fruits, assorted tropical and sub-tropical fruits, flowerhead brassicas, leafy vegetables, stalk and stem vegetables, root and tuber vegetables, fruiting vegetables, cucurbits, fruiting vegetables other than cucurbits, and mushrooms. These samples were used to monitor items corresponding to 98.6 % of the total agricultural products consumed by Koreans between 2016 and 2018 (Kang et al., 2019). The samples were composed of 97.3 % domestic and 2.7 % imported products.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e2.2. Reagent and solutions\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe standards for pesticide residues (insecticide, fungicide, herbicide, miticide, and plant activator) were purchased from AccuStandard (New Haven, Connecticut, USA). Acetonitrile, methanol, and dichloromethane were purchased from Merck (Darmstadt, Germany). Sodium chloride, anhydrous sodium sulfate,\u0026nbsp;acetone, and hexane were purchased from Wako Pure Chemicals (Osaka, Japan). Water was obtained from a Barnstead NANOpure Diamond™ water purification system (Asheville, NC, USA).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e2.3. Sample pretreatment\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOne kilogram of the sample was put into a cutter mixer and 50 g of the pulverized sample was weighed into an Omni mixer bottle, and to this 100 mL of acetonitrile was added. It was then homogenized for 2–3 minutes with a mixer extractor. Following homogenization, it was filtered under reduced pressure with a Buchner funnel lined with filter paper. The filtrate was transferred to a 500 mL separatory funnel containing 15 g of sodium chloride, after which the stopper was closed, and it was shaken vigorously and allowed to stand until the layers were completely separated. After dehydrating it by passing the acetonitrile layer through anhydrous sodium sulfate, separate acetonitrile was added to make up the final volume to 100 mL. Each acetonitrile layer (20 mL) was taken and concentrated under reduced pressure on a water bath at 40 °C or lower to blow off the solvent. The residue was dissolved in 4 mL of 20 % acetone/hexane. The solution dissolved in 4 mL of 20 % acetone/hexane is eluted in a Florisil cartridge previously activated with 5 mL of hexane and 5 mL of 20 % acetone/hexane and collected in a test tube. Further, it was eluted with 5 mL of 20 % acetone/hexane and collected in the same test tube. The eluate was used as the test solution by blowing off the solvent while passing air in a water bath below 40 °C and then dissolving it in 3 mL of 20 % acetone/hexane.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e2.4. Quantification of pesticide residues\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e158 pesticide residue\u0026nbsp;monitoring\u0026nbsp;items with high detection frequency were selected among all pesticide residue\u0026nbsp;monitoring\u0026nbsp;items in the Korean Food Code. An Agilent Technologies 7890 A\u0026nbsp;(Santa Clara, USA)\u0026nbsp;gas chromatograph\u0026nbsp;with a\u0026nbsp;nitrogen phosphorous detector and an electron capture detector controlled by\u0026nbsp;Open LAB CDS C.01.07\u0026nbsp;software\u0026nbsp;was used to determine the pesticide residues (Table 1).\u0026nbsp;The following conditions were applied unless stated otherwise:\u0026nbsp;DB-17 column (30 m × 0.25 mm, 0.25 μm); carrier gas N\u003csub\u003e2\u003c/sub\u003e, gas flow, 1.0 mL/min; inlet split mode, 20:1; and detector temperature, 280\u0026nbsp;°C. The oven temperature was 80\u0026nbsp;°C\u0026nbsp;(2 min)\u0026nbsp;→\u0026nbsp;7\u0026nbsp;°C\u0026nbsp;/min\u0026nbsp;→\u0026nbsp;250\u0026nbsp;°C\u0026nbsp;→\u0026nbsp;5\u0026nbsp;°C\u0026nbsp;/min\u0026nbsp;→\u0026nbsp;280\u0026nbsp;°C\u0026nbsp;(20 min). The pesticides detected via gas chromatography\u0026nbsp;(GC) were confirmed by a Thermo Scientific Trace 1310 TSQ 9000 (Waltham, USA) gas chromatography–tandem mass spectrometer. The operating conditions were as follows: DB-5MS\u0026nbsp;column (30 m × 0.25 mm, 0.25 μm); carrier gas He, gas flow, 1.2 mL/min; inlet splitless; inlet temperature, 280\u0026nbsp;°C; source temperature, 230 °C; and electron ionization, 70 eV. The oven temperature was 80\u0026nbsp;°C\u0026nbsp;(5 min)\u0026nbsp;→\u0026nbsp;10\u0026nbsp;°C\u0026nbsp;/min\u0026nbsp;→\u0026nbsp;300\u0026nbsp;°C\u0026nbsp;(3 min).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e2.5. Method validation\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe validation of the analytical methods was carried out in accordance with the KFDA guidance document on residue analytical methods (KFDA, 2017). The analytical methods were verified with performance parameters, including the limit of detection (LOD), the limit of quantification (LOQ), and the linearity of the calibration curves. LOD and LOQ were calculated by multiplying the standard deviation by 3 and 10, respectively, and the standard deviation was derived from seven measurements of blank samples spiked at a concentration near the LOQ. The linearity of the calibration curve was evaluated by the coefficient of correlation from a regression equation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e2.6. Exposure assessment\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe exposure assessment was conducted by combining the pesticide residues contamination values with the agricultural product consumption data (described below), divided by the body weight (USEPA, 2000; WHO, 2009). The means and 95\u003csup\u003eth\u003c/sup\u003e percentiles of the daily consumption data were multiplied by the corresponding concentrations of the pesticide residues for each sample. Exposure assessment was also performed for different age groups (EFSA, 2017).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e2.6.1. Consumption data\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConsumption data was extracted from the Korea National Health and Nutrition Examination Survey (KNHANES 2016 – 2018), which surveys the current status and trends of health and nutrition in the Korean population. This survey serves to highlight health-vulnerable groups and calculates the statistics for the effective delivery of health policies and projects. Each year, 25 households in 192 areas are randomly surveyed, totaling approximately 10,000 individuals over 1 year old. The data is divided into age groups for children (1 - 11 years old), adolescents (12 - 18 years old), and adults (19 years or older). Daily food consumption was analyzed according to the different food groups (KNHANES VII, 2016 – 2018).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e2.6.2. Contamination data\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eContamination data were obtained from the analyses using GC (electron capture detector, nitrogen phosphorous detector) and gas chromatography–tandem mass spectrometry in this study. A substitution method was applied to correct the left-censored data (EFSA, 2010; GEMS/Food-EURO, 1995). Because the rate of pesticide residues not detected was over 80 % was applied exposure assessment Zero (Lower Bound, LB) and LOD (Upper Bound, UB).\u003c/p\u003e"},{"header":"3. Results And Discussion","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003e3.1. Method validation\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 2 shows the performance parameters used to verify the analytical methods. The LODs for the pesticide residues ranged from 0.00002 to 0.00375 mg/kg, and the LOQs ranged from 0.00008 to 0.01249 mg/kg. The linear regression analysis showed that the calibration curves had consistent linear relationships between the peak areas and concentrations; the regression coefficients were 0.99118 to 0.99998.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e3.2. Concentrations of pesticide residues in agricultural product samples\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe concentrations of pesticide residues in agricultural product samples are summarized in Table 3. The mean concentrations of fludioxonil, pencycuron, and tolylfluanid were high in agricultural product samples. 59 types of residues were found, with 23 pesticide residues exceeding their maximum residue limits (MRLs).\u0026nbsp;The rate of violation of MRLs to the number of detected pesticide residues is 3.7 %. Ethoprophos, tebupirimfos, and diazinon had higher rates of exceeding their MRLs compared to the number of detected pesticide residues.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e3.3. Distribution of pesticide residues in agricultural product samples\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePesticides were detected in 72 out of 138 types of agricultural products. Meanwhile, 27 (out of 76) types of agricultural product samples exceeded the residue limit (Table 4). No pesticides were detected in cereal grains, peanuts or nuts, and oilseeds. Leafy vegetables have a larger surface area to weight ratio compared to other agricultural products; therefore, pesticides easily get attached to them during spraying, and it is thought that the detection amount is relatively high due to a large amount of adhesion. This result is consistent with the results of domestic studies (Kim et al., 2010). The rates of violation of MRLs were high in flowerhead brassicas, leafy vegetables, stalk and stem vegetables, and root and tuber vegetables.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e3.4. Consumption of agricultural products\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBased on the KNHANES (2016 – 2018), the mean long-term intake of agricultural products was 553.3 g/day for the entire Korean population. The 95\u003csup\u003eth\u003c/sup\u003e percentile intake of agricultural products was 2,076.4 g/day for the entire Korean population.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e3.5. Exposure to pesticide residues\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe exposures to pesticide residues using the mean consumption data for whole population were 5.15E-11 ~ 2.08E-05 (LB) and 2.41E-07 ~ 4.69E-05 mg/kg bw/day (UB). The exposures to pesticide residues using the 95\u003csup\u003eth\u003c/sup\u003e percentile consumption data for whole population were 0 ~ 8.76E-05 (LB) and 9.26E-07 ~ 1.56E-04 mg/kg bw/day (UB) (see Table 5). Exposure values in the mean and 95\u003csup\u003eth\u003c/sup\u003e percentile intake groups of 1 % or greater are summarized in Fig. 1. For the detected pesticides, an acceptable daily intake value was set by the KFDA as the human exposure safety standard (EFSA, 2021). To assess exposure, deterministic estimates of dietary exposure to pesticide residues have to be compared to the human exposure safety standard.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAgricultural product consumption resulted in hazard index (HA, % acceptable daily intake) to diazinon that was 0.94 ~ 2.16 %. The HAs of piperophos, tebupirimfos, and methidathion were 1.16, 0.31 ~ 1.12, and 0.17 ~ 1.05 %, respectively. The HAs of diazinon, piperophos, tebupirimfos, and methidathion were at 13 – 30 % (UB) levels in consumers only. Notably, in the high consumers (those on the 95\u003csup\u003eth\u003c/sup\u003e) percentile, HA of diazinon was 57.07 ~ 101.38 % (see Fig. 1A).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe exposures across different age groups were estimated as 0 ~ 5.03E-05 (LB) and 1.77E-07 ~ 1.25E-04 mg/kg bw/day (UB). For the 95\u003csup\u003eth\u003c/sup\u003e percentile, the exposures across different age groups were estimated as 0 ~ 1.89E-04 (LB) and 6.07E-07 ~ 4.83E-04 mg/kg bw/day (UB). The HA of dimethoate, diniconazole, and edifenphos was 5 to 9 % (UB), which was slightly higher than that of other pesticides. Diazinon, ethoprophos, and methidathion showed higher HA in all age groups, but within 19 % (see Fig. 1B).\u003c/p\u003e\n\u003cp\u003eFor diazinon, pesticide residue with high HA value, exposure was also estimated for the individual agricultural product species according to entire Korean population consumption data (see Fig. 2A). For all consumption P95 (consumers only) consumption, radish leaf was the leading diazinon contributor (6.22E-05 mg/kg bw/day, 54.5 %), followed by young radish (2.88E-05 mg/kg bw/day, 25.2 %). Within\u0026nbsp;≥\u0026nbsp;65 Consumption P95 consumption data, radish leaf was the leading diazinon contributor (2.10E-05 mg/kg bw/day, 81.5 %), followed by Korean cabbage (3.78E-06 mg/kg bw/day, 14.7 %).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe residual tolerance standard for diazinon radish leaves and young radish was 0.05 mg/kg until 2018, and from 2019, the MRL was changed to non-detection. The number of cases of diazinon detected in radish leaves and young radish was 17 out of a total of 76 cases (detection rate 22.4 %) from 2016 to 2018 and three out of a total of 37 cases (detection rate 8.1 %) from 2019 to 2020. As a result of risk assessment using the contamination level of radish leaves and young radish diazinon from 2019 to 2020, the HA value in consumers of only P95 decreased from 57 (LB) ~ 101 % (UB) to 27 (LB) ~ 71 % (UB) (see Fig. 2B). It is noteworthy that one out of three cases of diazinon detected between 2019 and 2020 was detected at a high concentration (0.535 mg/kg) as nonconforming, and the average contamination value of diazinon used for risk assessment was overestimated. Thus, as a result of performing risk assessment again with the average value excluding nonconformity, the HA value in consumers of only P95 decreased to 13 (LB) ~ 57 % (UB). Therefore, it is expected that the risk for diazinon will be lowered in the future.\u003c/p\u003e"},{"header":"4. Conclusions","content":"\u003cp\u003eIn this study, pesticide residue exposure via agricultural consumption was assessed. It is estimated that Koreans are not at risk of pesticide residue (insecticides, fungicides, herbicides miticides, and plant activators) poisoning. Exposures using mean consumption data pesticide residues were 5.15E-11\u0026thinsp;~\u0026thinsp;2.08E-05 (LB) and 2.41E-07\u0026thinsp;~\u0026thinsp;4.69E-05 mg/kg bw/day (UB), corresponding to 0.00012\u0026thinsp;~\u0026thinsp;2.16% of HA. These exposure assessments indicate that the pesticide residues in agricultural products are adequately controlled by the regulatory authorities.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCorresponding author \u0026nbsp; \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCorrespondence to Tae-Hun Kim.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTae-Hun Kim: planning the whole work, writing\u0026mdash;original draft. Soo-Hwaun Kim: extracted the agricultural product consumption data. Su Chin Park, Ji Eun Kim, Hyun Jun Yeon, Ju Ho Kim, and Young Soek Park: performed the pesticide residues analysis. Yoon-Hee Oh, Gune-Hee Jo: review and editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was financially supported by a research fund from the Daejeon Metropolitan City Institute of Health and Environment in 2021.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors confirm that all data supporting the study\u0026rsquo;s findings are included in the article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors consent for publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest \u0026nbsp; \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements \u0026nbsp; \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThanks to the editors and anonymous reviewers for their valuable suggestions.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBeilstein P (1998) Tolerance study in Novartis managers upon repeated oral administration of diazion Unpublished report No. 972019. Huntingdon Research Centre Ltd, Cambridgeshire\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDannaker CJ, Maibach HI, O'Malley M (1993) Contact urticaria and anaphylaxis to the fungicide chlorothalonil. Cutis 52:312\u0026ndash;315\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEuropean Food Safety Authority (EFSA) (2010) Management of left-censored data in dietary exposure assessment of chemical substances. EFSA J 8:1557. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.2903/j.efsa.2010.1557\u003c/span\u003e\u003cspan address=\"10.2903/j.efsa.2010.1557\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEuropean Food Safety Authority (EFSA) (2017) Human and animal dietary exposure to ergot alkaloids. EFSA J 15:1\u0026ndash;53. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.2903/j.efsa.2017.4902\u003c/span\u003e\u003cspan address=\"10.2903/j.efsa.2017.4902\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGlobal Environment Monitoring System - Food Contamination Monitoring and Assessment Programme (GEMS/Food-EURO) (1995) Reliable evaluation of low-level contamination of food. Report on a workshop in the frame of GEMS/Food-EURO. 26\u0026ndash;27 May 1995, Kulmbach, Germany. World Health Organization Regional Office for Europe, Geneva\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKang GJ, Choi JD, Kwon JW, Shin MS, Shin YY, Chun SY, Kim SH (2019) Hazardous Pollutants Risk Assessment Practice Standards Manual. National Food and Drug Safety Evaluation, Ministry of Food and Drug Safety, Cheongju. Chap. 3\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKim MO, Hwang HS, Lim MS, Hong JE, Kim SS, Do JA, Choi DM, Cho DH (2010) Monitoring of Residual Pesticides in Agricultural Products by LC/MS/MS. KOREAN J. FOOD SCI. TECHNOL. Vol.\u0026nbsp;42, No. 6, pp.\u0026nbsp;664 ~ 675\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKorea Food and Drug Administration (KFDA) (2017) Practical Guide to Food Standards Residual Pesticide Analysis Method. National Food and Drug Safety Evaluation, Ministry of Food and Drug Safety, Cheongju. Chap. 7\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKorea Food and Drug Administration (KFDA) (2021) The Korean Food Code. Ministry of Food and Drug Safety, Cheongju\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNational Library of Medicine (NLM) (1990) Hazardous Substances Data Bank (HSDB) Toxicology Data Network. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://toxnet.nlm.nih.gov\u003c/span\u003e\u003cspan address=\"http://toxnet.nlm.nih.gov\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNational Library of Medicine (NLM) (1997) Hazardous Substances Data Bank (HSDB) Toxicology Data Network. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://toxnet.nlm.nih.gov\u003c/span\u003e\u003cspan address=\"http://toxnet.nlm.nih.gov\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRosenberg J (1990) Occupational medicine, Section \u0026acirc;\u0026#133;\u0026pound; occupational exposure (pesticides)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eConnecticut Prentice Hall publishing division, pp401-402, 408\u0026ndash;417\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUnited States Environmental Protection Agency (USEPA) (2000) Guidance for assessing chemical contaminant data for use. Fish advisories-fish sampling and analysis, Vol.\u0026nbsp;1, third edition. United States Environmental Protection Agency, Washington, Office of Water383, Chap. 4\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Health Organization (WHO), Geneva (2009) Environmental Health Criteria 240. Principles and methods for the risk assessment of chemicals in food. FAO/WHO. Chap. 6\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1-5 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"environmental-science-and-pollution-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"espr","sideBox":"Learn more about [Environmental Science and Pollution Research](https://www.springer.com/journal/11356)","snPcode":"11356","submissionUrl":"https://submission.nature.com/new-submission/11356/3","title":"Environmental Science and Pollution Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Insecticides, Fungicides, Herbicides, Miticides, Plant activators , Agricultural product consumption, Exposure assessment, Hazard index","lastPublishedDoi":"10.21203/rs.3.rs-1490058/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1490058/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePesticide residues in food are intentional pollutants such as insecticides, fungicides, herbicides, miticides, and plant activators. The insecticides diazinon and malathion are classified as probably carcinogenic to humans (Group 2A) by the International Agency for Research on Cancer under the World Health Organization, and the fungicides chlorothalonil and hexachlorobenzene are classified as possibly carcinogenic to humans (Group 2B). In this study, gas chromatography and gas chromatography\u0026ndash;tandem mass spectrometry analyses were used to identify the concentrations of pesticide residues in agricultural products and to assess the effects of chronic human exposure to pesticide residues via agricultural consumption. Food consumption data were obtained from the Korea National Health and Nutrition Examination Survey 2016\u0026ndash;2018. Chronic exposures using mean consumption data for the whole population, with mean concentration of pesticide residues, were 5.15E-11\u0026thinsp;~\u0026thinsp;2.08E-05 (LB) and 2.41E-07\u0026thinsp;~\u0026thinsp;4.69E-05 mg/kg bw/day (UB), corresponding to 0.00012\u0026thinsp;~\u0026thinsp;2.16% of hazard index (HA). Exposures to pesticide residues using the 95th percentile of the consumption data were 0\u0026thinsp;~\u0026thinsp;8.76E-05 (LB) and 9.26E-07\u0026thinsp;~\u0026thinsp;1.56E-04 mg/kg bw/day (UB), corresponding to 0.00045\u0026thinsp;~\u0026thinsp;9.41% of HA.\u003c/p\u003e","manuscriptTitle":"Exposure assessment for pesticide residues in consumed agricultural products in the Republic of Korea","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-04-19 14:32:46","doi":"10.21203/rs.3.rs-1490058/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major Revision","date":"2022-05-14T04:28:35+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2022-04-15T09:18:15+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2022-04-15T08:44:43+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"Environmental Science and Pollution Research","date":"2022-04-13T14:05:01+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2022-04-06T05:31:00+00:00","index":"","fulltext":""},{"type":"submitted","content":"Environmental Science and Pollution Research","date":"2022-03-25T12:57:28+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"environmental-science-and-pollution-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"espr","sideBox":"Learn more about [Environmental Science and Pollution Research](https://www.springer.com/journal/11356)","snPcode":"11356","submissionUrl":"https://submission.nature.com/new-submission/11356/3","title":"Environmental Science and Pollution Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"44bc597a-673a-4c56-9b7b-0f18bc781893","owner":[],"postedDate":"April 19th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2022-07-07T16:18:34+00:00","versionOfRecord":[],"versionCreatedAt":"2022-04-19 14:32:46","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-1490058","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1490058","identity":"rs-1490058","version":["v1"]},"buildId":"_2-kVJe1T_tPrBINL-cwx","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}