Abstract

Distribution of pesticide residues in the environment and their transport to surface water bodies is one of the most important environmental challenges. Fate of pesticides in the complex environments, especially in aquatic phases such as lakes and rivers, is governed by the main properties of the contaminants and the environmental properties. In this study, a multimedia mass modeling approach using the Quantitative Water Air Sediment Interaction (QWASI) model was applied to explore the fate of organochlorine pesticide residues of methoxychlor, α-HCH and endosulfan–sulfate in the lake Naivasha (Kenya). The required physicochemical data of the pesticides such as molar mass, vapor pressure, air–water partitioning coefficient (KAW), solubility, and the Henry’s law constant were provided as the inputs of the model. The environment data also were collected using field measurements and taken from the literature. The sensitivity analysis of the model was applied using One At a Time (OAT) approach and calibrated using measured pesticide residues by passive sampling method. Finally, the calibrated model was used to estimate the fate and distribution of the pesticide residues in different media of the lake. The result of sensitivity analysis showed that the five most sensitive parameters were KOC, logKow, half-life of the pollutants in water, half-life of the pollutants in sediment, and KAW. The variations of outputs for the three studied pesticide residues against inputs were noticeably different. For example, the range of changes in the concentration of α-HCH residue was between 96% to 102%, while for methoxychlor and endosulfan-sulfate it was between 65% to 125%. The results of calibration demonstrated that the model was calibrated reasonably with the R2 of 0.65 and RMSE of 16.4. It was found that methoxychlor had a mass fraction of almost 70% in water column and almost 30% of mass fraction in the sediment. In contrast, endosulfan–sulfate had highest most fraction in the water column (>99%) and just a negligible percentage in the sediment compartment. α-HCH also had the same situation like endosulfan–sulfate (e.g., 99% and 1% in water and sediment, respectively). Finally, it was concluded that the application of QWASI in combination with passive sampling technique allowed an insight to the fate process of the studied OCPs and helped actual concentration predictions. Therefore, the results of this study can also be used to perform risk assessment and investigate the environmental exposure of pesticide residues.

Highlights

  • The contamination of water bodies by pesticide residues that can originate from agricultural application is considered as one of the most important environmental issues [1,2]

  • The Quantitative Water Air Sediment Interaction (QWASI) model was used to find out the fate of some organochlorine pesticides (OCPs) residues in lake Naivasha

  • The lake was considered as a well-mixed environment in the modeling approach, and the data of the passive sampling campaign [22] as well as the environmental and physicochemical properties of the pesticides was used as the input data of the model

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Summary

Introduction

The contamination of water bodies by pesticide residues that can originate from agricultural application is considered as one of the most important environmental issues [1,2]. The Level III model, which is the most complex level, consists of all the procedures that affect the transport and fate of the pollutants in an actual environment These fugacity models are easy to understand and apply for the assessment of the long-term variations of chemicals [11]. The multimedia mass modeling approach was applied to explore the fate of organochlorine pesticides residues in the lake Naivasha (Kenya). In addition to the studies mentioned earlier, several recent researches have applied QWASI or other kinds of modelling approaches [24,25,26,27,28,29] In most of these studies, fugacity models have been applied to explore the fate of chemical residues in different media. Due to the high concentration of Lindane residue (e.g., α-HCH), endosulfan–sulfate and methoxychlor [22], it was decided to explore the fate of these residues in the aquatic environment of Naivasha

Data Acquisition
Environment
Pesticides Properties
Sensitivity Analysis and Calibration
Results and Discussion
Results ofof the formethoxychlor methoxychlor
Conclusions
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