Mineralization of 17β-estradiol in 36 surface soils from Alberta, Canada

Abstract

Recent column studies suggest that pesticide fate models could be used to estimate the fate of estrogens in soil. Estrogens are detected in livestock manure which is used as a nutrient source on agricultural land. This is the first study to examine estrogen mineralization in a wide range of agricultural soils at the regional-scale. Soil samples were collected from upper and lower landscape positions of 18 agricultural fields in an area spanning 49–60°N longitude and 110–120°W latitude and these samples were used to determine 17β-estradiol mineralization parameters in microcosm experiments. Maximum 17β-estradiol mineralization (Max) ranged from 5.8% to 19.2% and was, on average, significantly (P<0.05) less than the 47.9–61.9% range measured in the same soils for the widely-used herbicide 2,4-D (2,4-dichlorophenoxyacetic acid). Maximum 17β-estradiol mineralization was positively correlated to Kd-17β-estradiol (r=0.62, P<0.001) while 2,4-D maximum mineralization was negatively correlated to Kd-2,4-D (r=−0.52, P<0.01), even though 17β-estradiol and 2,4-D sorption parameters (Kd) were positively correlated (r=0.62, P<0.001), and both Kd-17β-estradiol and Kd-2,4-D values were significantly positively correlated to SOC (r=0.71, P<0.001; and r=0.67, P<0.001, respectively). Hence, the mineralization of 2,4-D decreases as its sorption to soils increases while the mineralization of 17β-estradiol increases as its sorption to soil increases. This suggests that some steps in the 17β-estradiol mineralization process are occurring in the sorbed phase. Equations to predict 17β-estradiol and 2,4-D sorption and mineralization parameters were established using Partial Least Squares regression. Significant models for mineralization (r2 from 0.42 to 0.56) had lower r2 than significant sorption models (r2 from 0.78 to 0.85). Given the poor results of the mineralization regression models, we conclude that probability density functions, rather than regression models, are likely to be more useful for describing pesticide or estrogen mineralization parameters at the regional scale. Based on our findings, agri-environmental policy-analysis in Alberta should use the log–logistic probability density function to describe the mineralization rate (k) of either 17β-estradiol or 2,4-D at the large-scale. Max-17β-estradiol at the large-scale is best described by the extreme values probability density function and Max-2,4-D by the triangular probability density function.