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An Improved Indirect Procedure for Estimating Pesticide Volatility from Field Trials
Author(s) -
Cryer Steven A.,
Havens Patrick L.,
Hillger David E.,
Wesenbeeck Ian J.
Publication year - 2015
Publication title -
journal of environmental quality
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.888
H-Index - 171
eISSN - 1537-2537
pISSN - 0047-2425
DOI - 10.2134/jeq2015.03.0125
Subject(s) - volatility (finance) , environmental science , pesticide , field trial , field (mathematics) , econometrics , toxicology , economics , chemistry , mathematics , biology , ecology , pure mathematics , organic chemistry
Conventional indirect approaches for estimating pesticide volatility from agricultural fields require an air dispersion model and near‐field, temporal air concentration measurements. The model pesticide flux profile is chosen such that field observations are recovered. Ross et al. (1996) first proposed a back‐calculation method (BCM) using a single iteration of the Industrial Source Complex Short Term (ISCST) parameterized by a unit source flux. The unit flux is updated by scaling with the slope of a linear regression line between model predictions and actual field observations at each measured time point and location, yielding an estimate for the field flux that occurred over the sampling period. The BCM is expanded using a downhill simplex optimization procedure requiring many ISCST iterations to consecutively adjust the volatility flux rate such that the sum of the squared residuals between predicted and measured air concentrations is minimized (denoted as BCMO). The BCMO is ideally suited for comparing the volatility of different pesticide formulations of the same active from field studies performed simultaneously. Comparison of the BCM and BCMO from field trials containing single (Texas) and multiple simultaneously treated fields (Indiana) are provided for pesticides ranging from low to high volatility. The advanced BCMO is a better alternative than the original BCM, as shown by closer model predictions to measured air concentrations. A major advantage of the BCMO is the ability to extract unique flux source strengths for each field when multiple fields are present and treated consecutively and contiguously with each field emitting pesticide mass at different rates. Core Ideas The classical back‐calculation method is refined using optimization (BCMO). The classical BCMO consistently improved flux estimates for all pesticides and scenarios investigated. The classical BCMO can separate measured air concentrations to respective contributing sources. The classical BCMO offers an improved alternative to the original methodology for all pesticides.