Implied Maximum Dose Analysis of Standard Values of 25 Pesticides Based on Major Human Exposure Pathways

Zijian Li; Aaron A. Jennings

doi:10.3934/publichealth.2017.4.383

AIMS Public Health , 2017, 4(4): 383-398. doi: 10.3934/publichealth.2017.4.383. Research article

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Implied Maximum Dose Analysis of Standard Values of 25 Pesticides Based on Major Human Exposure Pathways

Zijian Li, Aaron A. Jennings

1 Department of Civil Engineering, Case Western Reserve University, Cleveland, OH 44106, USA
2 Present Address: Parsons Corporation, Chicago, IL 60606, USA

Received: , Accepted: , Published:

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Worldwide jurisdictions are making efforts to regulate pesticide standard values in residential soil, drinking water, air, and agricultural commodity to lower the risk of pesticide impacts on human health. Because human may exposure to pesticides from many ways, such as ingestion, inhalation, and dermal contact, it is important to examine pesticide standards by considering all major exposure pathways. Analysis of implied maximum dose limits for commonly historical and current used pesticides was adopted in this study to examine whether worldwide pesticide standard values are enough to prevent human health impact or not. Studies show that only U.S. has regulated pesticides standard in the air. Only 4% of the total number of implied maximum dose limits is based on three major exposures. For Chlorpyrifos, at least 77.5% of the total implied maximum dose limits are above the acceptable daily intake. It also shows that most jurisdictions haven’t provided pesticide standards in all major exposures yet, and some of the standards are not good enough to protect human health.

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Keywords: pesticide standard; implied maximum dose limits; human health risk; acceptable daily intake; human exposure

Citation: Zijian Li, Aaron A. Jennings. Implied Maximum Dose Analysis of Standard Values of 25 Pesticides Based on Major Human Exposure Pathways. AIMS Public Health , 2017, 4(4): 383-398. doi: 10.3934/publichealth.2017.4.383

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Copyright Info: 2017, Zijian Li, et al., licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution Licese (http://creativecommons.org/licenses/by/4.0)

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