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Review
. 2017 Jul 22;14(7):826.
doi: 10.3390/ijerph14070826.

Worldwide Regulations of Standard Values of Pesticides for Human Health Risk Control: A Review

Affiliations
Review

Worldwide Regulations of Standard Values of Pesticides for Human Health Risk Control: A Review

Zijian Li et al. Int J Environ Res Public Health. .

Abstract

Abstract: The impact of pesticide residues on human health is a worldwide problem, as human exposure to pesticides can occur through ingestion, inhalation, and dermal contact. Regulatory jurisdictions have promulgated the standard values for pesticides in residential soil, air, drinking water, and agricultural commodity for years. Until now, more than 19,400 pesticide soil regulatory guidance values (RGVs) and 5400 pesticide drinking water maximum concentration levels (MCLs) have been regulated by 54 and 102 nations, respectively. Over 90 nations have provided pesticide agricultural commodity maximum residue limits (MRLs) for at least one of the 12 most commonly consumed agricultural foods. A total of 22 pesticides have been regulated with more than 100 soil RGVs, and 25 pesticides have more than 100 drinking water MCLs. This research indicates that those RGVs and MCLs for an individual pesticide could vary over seven (DDT drinking water MCLs), eight (Lindane soil RGVs), or even nine (Dieldrin soil RGVs) orders of magnitude. Human health risk uncertainty bounds and the implied total exposure mass burden model were applied to analyze the most commonly regulated and used pesticides for human health risk control. For the top 27 commonly regulated pesticides in soil, there are at least 300 RGVs (8% of the total) that are above all of the computed upper bounds for human health risk uncertainty. For the top 29 most-commonly regulated pesticides in drinking water, at least 172 drinking water MCLs (5% of the total) exceed the computed upper bounds for human health risk uncertainty; while for the 14 most widely used pesticides, there are at least 310 computed implied dose limits (28.0% of the total) that are above the acceptable daily intake values. The results show that some worldwide standard values were not derived conservatively enough to avoid human health risk by the pesticides, and that some values were not computed comprehensively by considering all major human exposure pathways.

Keywords: environmental regulatory jurisdiction; health risk uncertainty bounds; human health risk assessment; pesticide exposure; pesticide regulation.

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Conflict of interest statement

The authors have declared that is no conflict of interest in this paper.

Figures

Figure 1
Figure 1
Empirical distributions of the number of worldwide regulatory guidance values (RGVs) and maximum concentration levels (MCLs) compared to the theoretical distribution of a lognormal random variables.
Figure 2
Figure 2
Geographic distribution of the nations regulating the 25 selected pesticides in residential surface soil.
Figure 3
Figure 3
Geographic distribution of the nations regulating the 25 selected pesticides in drinking water.
Figure 4
Figure 4
Log orders of variation (LOV) values and the running average for the commonly regulated pesticides in soil and drinking water.
Figure 5
Figure 5
2,4-D and Glyphosate soil RGVs plotted in the empirical cumulative distribution forms and compared to the log-normal random variable cumulative distributions with identical statistics.
Figure 6
Figure 6
2,4-D and Glyphosate drinking water MCLs plotted in the empirical cumulative distribution forms and compared to the log-normal random variable cumulative distributions with identical statistics.
Figure 7
Figure 7
2,4-D and Glyphosate agricultural commodities implied exposure doses (IEDs) plotted in the empirical cumulative distribution forms and compared to the log-normal random variable cumulative distributions with identical statistics.
Figure 8
Figure 8
2,4-D implied maximum dose limits (IMDLs) computed from soil, drinking water, and the commonly consumed agricultural commodities plotted in the empirical cumulative distribution form and compared to the log-normal random variable cumulative distribution with identical statistics.
Figure 9
Figure 9
Glyphosate IMDLs computed from soil, drinking water, and the commonly consumed agricultural commodities plotted in the empirical cumulative distribution form and compared to the log-normal random variable cumulative distribution with identical statistics.

References

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