A Global Meta‐Analysis to Predict Atrazine Sorption from Soil Properties. Issue 6 (1st November 2018)

• Record Type: Journal Article
• Authors: Ou, Ling; Gannon, Travis W.; Arellano, Consuelo; Polizzotto, Matthew L.
• Is Part Of: Journal of Environmental Quality. Volume 47:Issue 6(2018)
• Page Start: 1389
• Page End: 1399
• Publication Date: 2018-11-01
• Subjects: Agricultural ecology -- Periodicals; Environmental engineering -- Periodicals; Pollution -- Periodicals; 630
• DOI: 10.2134/jeq2017.11.0429
• Languages: English
• ISSNs: 0047-2425

Abstract

Abstract : Atrazine (2‐chloro‐4‐ethylamino‐6‐isopropylamino‐1, 3, 5‐triazine) is one of the most widely used herbicides worldwide, and groundwater contamination is of concern, especially in heavily used regions and in edaphic conditions prone to leaching. Soil sorption plays an essential role in atrazine environmental fate, yet consistent atrazine risk prediction remains limited. A quantitative meta‐analysis was conducted to characterize the effect of soil properties on atrazine sorption, using 378 previous observations in 48 publications from 1985 to 2015 globally, which included data on soil properties and sorption parameters. A supplemental regional study was conducted to test the derived meta‐analysis models. The meta‐analysis indicated that percentage organic C (OC) was the most important parameter for estimating atrazine sorption, followed by percentage silt, soil pH, and percentage clay. Meta‐analysis and supplemental study models were developed for Freundlich sorption coefficients ( K f ) and sorption distribution coefficients ( K d ) as a function of OC. The global meta‐analysis models generated positive linear trends for OC with K f and K d ( R 2 = 0.197 and 0.205, respectively). Organic C was highly correlated with K f and K d in supplemental experimental study models ( R 2 = 0.93 and 0.92, respectively), indicating accurate prediction of sorption within the evaluated region. Continental models were investigated, which improved the goodness of fit. Models developed via meta‐analysis may be used to predict atrazine sorption over wide ranges of data, whereas more accurate and refined prediction can be achieved by specific regional models through experimental studies. However, such models could be improved if standardized agroclimatic conditions, soil classification, and other key variables were more widely reported. Core Ideas: Meta‐analysis quantified soil properties governing atrazine sorption. Organic C content had the highest correlation with atrazine soil sorption. Meta‐analysis models showed similar trends to independent experimental results. Continental and supplemental models improved fit compared with global models. Standard climate and soil taxonomic data should be reported to optimize models.