Model Development and Validation of Pesticide Volatilization from Soil and Crop Surfaces Post Spraying during Agricultural Practices
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| Language: | English |
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Ohio University / OhioLINK
2020
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| Online Access: | http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1588610082125279 |
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ndltd-OhioLink-oai-etd.ohiolink.edu-ohiou1588610082125279 |
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oai_dc |
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NDLTD |
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English |
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NDLTD |
| topic |
Environmental Engineering Environmental Science Agricultural Chemicals Agricultural Engineering Atmospheric Sciences Soil Sciences Pesticide Volatilization numerical model sensitivity analyses risk assessment |
| spellingShingle |
Environmental Engineering Environmental Science Agricultural Chemicals Agricultural Engineering Atmospheric Sciences Soil Sciences Pesticide Volatilization numerical model sensitivity analyses risk assessment Ghosh, Saikat Model Development and Validation of Pesticide Volatilization from Soil and Crop Surfaces Post Spraying during Agricultural Practices |
| author |
Ghosh, Saikat |
| author_facet |
Ghosh, Saikat |
| author_sort |
Ghosh, Saikat |
| title |
Model Development and Validation of Pesticide Volatilization from Soil and Crop Surfaces Post Spraying during Agricultural Practices |
| title_short |
Model Development and Validation of Pesticide Volatilization from Soil and Crop Surfaces Post Spraying during Agricultural Practices |
| title_full |
Model Development and Validation of Pesticide Volatilization from Soil and Crop Surfaces Post Spraying during Agricultural Practices |
| title_fullStr |
Model Development and Validation of Pesticide Volatilization from Soil and Crop Surfaces Post Spraying during Agricultural Practices |
| title_full_unstemmed |
Model Development and Validation of Pesticide Volatilization from Soil and Crop Surfaces Post Spraying during Agricultural Practices |
| title_sort |
model development and validation of pesticide volatilization from soil and crop surfaces post spraying during agricultural practices |
| publisher |
Ohio University / OhioLINK |
| publishDate |
2020 |
| url |
http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1588610082125279 |
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AT ghoshsaikat modeldevelopmentandvalidationofpesticidevolatilizationfromsoilandcropsurfacespostsprayingduringagriculturalpractices |
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1719457172677459968 |
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ndltd-OhioLink-oai-etd.ohiolink.edu-ohiou15886100821252792021-08-03T07:14:50Z Model Development and Validation of Pesticide Volatilization from Soil and Crop Surfaces Post Spraying during Agricultural Practices Ghosh, Saikat Environmental Engineering Environmental Science Agricultural Chemicals Agricultural Engineering Atmospheric Sciences Soil Sciences Pesticide Volatilization numerical model sensitivity analyses risk assessment <p>Pesticides volatilize from soil and plant surfaces to the atmosphere after spray applications in agricultural fields which can cause inhalational exposure to bystanders. It is important to quantify such volatilization with reasonable confidence for risk assessment of the inhalation exposure. A mechanistic model was developed here to simulate the underlying transport processes and deploy it as a standalone tool that a regulatory body can use to predict volatilization emissions of various pesticides for determination of inhalation exposure. The overall volatilization model includes a soil sub-model and a plant sub-model. The model accounts for the effect of meteorology, soil conditions, pesticide adsorption and volatilization. </p><p>The soil model simultaneously resolves the soil profile of temperature, moisture, and pesticide concentrations to compute the time-dependent volatilization. The numerical model for soil treatment was in good agreement with an analytical solution at stagnant boundary conditions. The model performance of 14 pesticides against the analytical solution showed coefficient of determination (R<sup>2</sup>) values of 0.76 to 0.99 and index of agreement (IOA) values of 0.43 to 0.98. The soil model was also validated with observations at field conditions with variable meteorology.</p><p>The time-dependent predicted volatilization compared well against measurements of two surface treated pesticides - metolachlor and triallate with R<sup>2</sup> value of 0.4 and 0.7, respectively. The model prediction of the fumigant volatilization of 1,3-dichloropropene was in good agreement with the field observations (R<sup>2</sup>=0.8 and IOA=0.9).</p><p>The plant model utilizes a simple resistance scheme with mass transfer of the pesticide on the leaf surface through a diffusive canopy boundary and an atmospheric boundary layer above the canopy. The model also accounts the loss of pesticide mass on the leaf surface due to penetration into leaf cuticle and photo-degradation as first-order kinetic rates. Volatilization of chlorpyrifos from plant surface was predicted reasonably well with the field observations (R<sup>2</sup> = 0.96 and IOA = 0.9). </p><p>Uncertainty analyses with Monte Carlo simulations of metolachlor volatilization showed that the soil model was most sensitive to pesticide adsorption to soil. A negative Pearson correlation coefficient (r = -0.98) illustrates that the volatilization prediction will largely decrease with high values of the adsorption coefficient. The soil model was not significantly sensitive to the Henry’s law constant of the pesticide. Monte Carlo simulations of chlorpyrifos volatilization showed that the plant model was significantly sensitive to the Henry’s law constant, solubility, and air diffusivity of the pesticide. </p><p>Sensitivity analyses of the model to different locations and seasons with varying meteorological conditions were also performed. Large variations in the soil model predictions was noted with volatilization significantly increasing at hot climatic conditions. High temperature accelerates the evaporation and upward pesticide flux in the soil consequently increasing the volatilization. The plant model was relatively less sensitive to the temperature with lowest volatilization occurring during winter season. </p><p>Health risks due to inhalation exposure was also estimated with peak volatilization rates from the current model and compared against estimates by a regulatory screening tool. Inhalation concentrations at various downwind distances from the field were computed using a dispersion model. Inhalation risks were shown to be remarkably high for triallate and 1,3-dichloropropene. </p><p>The current work demonstrates the development and performance of an operational mechanistic model that can be used for health risk assessment of inhalation exposure to pesticides. Further evaluation of the model with comprehensive field measurements is warranted prior to implementation of regulations. </p> 2020-09-22 English text Ohio University / OhioLINK http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1588610082125279 http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1588610082125279 unrestricted This thesis or dissertation is protected by copyright: all rights reserved. It may not be copied or redistributed beyond the terms of applicable copyright laws. |