Environmental transport of endogenous dairy manure estrogens

Predicting Escherichia coli levels in manure using machine learning in weeping wall and mechanical liquid solid separation systems

An increased understanding of the interaction between manure management and public and environmental health has led to the development of Alternative Dairy Effluent Management Strategies (ADEMS). The efficiency of such ADEMS can be increased using mechanical solid-liquid-separator (SLS) or gravitational Weeping-Wall (WW) solid separation systems. In this research, using pilot study data from 96 samples, the chemical, physical, biological, seasonal, and structural parameters between SLS and WW of ADEM systems were compared. Parameters including sodium, potassium, total salts, volatile solids, pH, and E. coli levels were significantly different between the SLS and WW of ADEMS. The separated solid fraction of the dairy effluents had the lowest E. coli levels, which could have beneficial downstream implications in terms of microbial pollution control. To predict effluent quality and microbial pollution risk, we used Escherichia coli as the indicator organism, and a versatile machine learning, ensemble, stacked, super-learner model called E-C-MAN (Escherichia coli-Manure) was developed. Using pilot data, the E-C-MAN model was trained, and the trained model was validated with the test dataset. These results demonstrate that the heuristic E-C-MAN ensemble model can provide a pilot framework toward predicting Escherichia coli levels in manure treated by SLS or WW systems.

Transport of Potential Manure Hormone and Pharmaceutical Contaminants through Intact Soil Columns

Although adding manure to agricultural soils is a commonly practiced disposal method and a means to enhance soil productivity, potential environmental contamination by any associated chemicals of emerging concern (CECs) such as hormones and pharmaceuticals is not well understood. Our objective was to provide field-relevant predictions of soil transport and attenuation of 19 potential manure CECs using undisturbed soil columns irrigated under unsaturated conditions. The CEC concentrations in leached water were monitored for 13 wk using high performance liquid chromatography-time of flight-mass spectrometry (HPLC-TOF-MS), after which time soil in the cores was removed and sampled for extractable CECs. Compounds quantified in column leachate included all four of the added sulfonamide antibiotics and the nonsteroidal, anti-inflammatory drug flunixin. Only trace amounts of several of the seven hormones, five remaining antibiotics, and two antimicrobials leached from the columns from exogenous soil additions. Soil residues of all 19 compounds were detected, with highest extractable amounts for 17α-hydroxyprogesterone > triclosan (antimicrobial) > flunixin > oxytetracycline. Those CECs with the highest recoveries as calculated by summing leached and extractable amounts were flunixin (14.5%), 17α-hydroxyprogesterone (5.3%), triclosan (4.6%), and sulfadimethoxine (4.8%). Manure management to prevent CEC contamination should consider the potential environmental problems caused by negatively charged compounds with the greatest mobility (flunixin and sulfadimethoxine) and those that have long residence times in soil (triclosan, 17α-hydroxyprogesterone, flunixin, and oxytetracycline). Flunixin is particularly important given its mobility and long residence time in soil.