Twelve organic compounds commonly found at hazardous waste sites were studied for uptake by hybrid poplar trees. The vegetative uptake of many of these compounds has not previously been demonstrated for plant species being utilized for phytoremediation, such as hybrid poplar trees. Experiments were conducted hydroponically utilizing 14 C-labeled compounds to ascertain translocation and fate. Predictive relationships for the translocation and partitioning to plant tissues were developed from the experimental data. Translocation and partitioning relationships based on compounds' octanol-water partitioning coefficients (log K ow ) produced the best results, but the relationships did not allow for fully accurate prediction of each contaminant's fate. Translocation and subsequent transpiration of volatile organic compounds (VOCs) from the leaves to the atmosphere was shown to be a significant pathway. As full-scale phytoremediation systems are deliberated, the pathways investigated here should be considered in terms of a contaminant removal mechanism and potential contamination of the vegetation.

The rapid increase in both the quantity and complexity of data that are being generated daily in the field of environmental science and engineering (ESE) demands accompanied advancement in data analytics. Advanced data analysis approaches, such as machine learning (ML), have become indispensable tools for revealing hidden patterns or deducing correlations for which conventional analytical methods face limitations or challenges. However, ML concepts and practices have not been widely utilized by researchers in ESE. This feature explores the potential of ML to revolutionize data analysis and modeling in the ESE field, and covers the essential knowledge needed for such applications. First, we use five examples to illustrate how ML addresses complex ESE problems. We then summarize four major types of applications of ML in ESE: making predictions; extracting feature importance; detecting anomalies; and discovering new materials or chemicals. Next, we introduce the essential knowledge required and current shortcomings in ML applications in ESE, with a focus on three important but often overlooked components when applying ML: correct model development, proper model interpretation, and sound applicability analysis. Finally, we discuss challenges and future opportunities in the application of ML tools in ESE to highlight the potential of ML in this field.

Federal legislation in the U.S. mandates increased production of biofuels. To meet the required demand, corn and “traditional” ethanol rendering crops will soak up irrigation water that could exacerbate water shortages in some regions. Further, the agricultural runoff will return much of this water steeped with eutrophication/hypoxia-causing nitrogen and phosphorus to sensitive inland and coastal waterways. Unless more sustainable crop methods are implemented and biotechnology provides more efficient bioenergy plants, the greening of fuel could come with the browning of water. Dominguez-Faus and coauthors present the data and wonder whether society will have to choose between drinking and driving.

Hybrid poplar trees can uptake, hydrolyze, and dealkylate atrazine to less toxic metabolites. In whole plant studies, the parent compound atrazine and 14 C ring-labeled metabolites were extracted from poplar tissues and analyzed via high-pressure liquid chromatography (HPLC) with UV and radiochromatographic detectors in series. The concurrent separation and identification of these metabolites has not been previously reported in higher plants for phytoremediation applications. Unidentified metabolites were also detected. Metabolism of atrazine occurred in poplar roots, stems, and leaves and became more complete with increased residence time in tissues. In poplar cuttings exposed to atrazine for 50 days, the parent compound comprised only 21% of the 14 C label in the leaves, while it constituted 59% of 14 C activity remaining in the soil. After 80 days, the parent compound remaining in the leaves had decreased to only 10% of the 14 C label recovered in the leaves. Preferred metabolic pathways were suggested by relative rates of reaction, and a mathematical model was developed to estimate rate constants for the proposed degradation mechanism. This research provides evidence for vegetative detoxification of contaminants and suggests that phytoremediation of atrazine-contaminated soils may be feasible.

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The phytoremediation of trichloroethylene (TCE) and other chlorinated compounds has been studied over the past decade, and full-scale systems are in place. The results regarding TCE fates and removal pathways are inconclusive and conflicting, particularly the results regarding volatilization to the atmosphere. Research presented here demonstrates that TCE is taken up by trees and volatilized to the atmosphere. TCE diffusion along the transpiration pathway is shown to be the primary process for TCE volatilization, although volatilization can occur from both stems and leaves. Two concurrent processes influence the eventual fate: transport with transpiration stream through xylem tissues and diffusion from transpiration stream to atmosphere. TCE diffusion flux invariably decreased with height for trees planted in soil or grown hydroponically. In both laboratory experiments and field sampling, TCE concentrations in the transpiration stream (e.g., xylem tissues) decreased with elevation. In field samples, TCE concentrations also decreased in the radial direction, providing fundamental evidence for diffusion. The TCE concentrations in tissues responded linearly to the exposure concentrations at the roots, while TCE diffusion from tree stems was influenced by concentration and transpiration rates.

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