Life cycle considerations of nano-enabled agrochemicals: are today's tools up to the task?

• Published in: Environmental science. Nano 2018, Vol.5 (5), p.1057-1069
• Main Authors: Pourzahedi, Leila, Pandorf, Madelyn, Ravikumar, Dwarakanath, Zimmerman, Julie B., Seager, Thomas P., Theis, Thomas L., Westerhoff, Paul, Gilbertson, Leanne M., Lowry, Gregory V.
• Format: Article
• Language: English
• Subjects: Agrochemicals; Data; Data processing; Environmental assessment; Environmental effects; Environmental impact; Environmental impact assessment; Fertilizers; Growth regulators; Life cycle; Life cycle analysis; Life cycle assessment; Life cycles; Nanomaterials; Nanotechnology; Pesticides; Sustainable design; Sustainable development
• ISSN: 2051-8153; 2051-8161
• DOI: 10.1039/C7EN01166K

Engineered nanomaterials (ENMs) used as fertilizers, pesticides and growth regulators will involve direct application of large quantities of ENMs to the environment and products intended for human consumption. Assessing their life cycle environmental impacts to mitigate unintended consequences poses several challenges. In this perspective, we identify obstacles to the application of life cycle assessment (LCA) for evaluating environmental tradeoffs of nano-enabled agrochemical applications. These include: (1) defining functional units that represent the function provided by nano-enabled agrochemicals and that are proportional to the scale of the study (nano-scale vs. field scale), (2) limitations in availability of comprehensive data necessary to inform life cycle material flow (resource use and emissions) for inventory development specific to nano-enabled agrochemical applications,(3) human and environmental exposure and effects data relevant to the agricultural context for impact assessment models, (4) spatial and temporal dependent components that can affect the results of an LCA of nano-enabled agrochemicals, and (5) high data uncertainties and the possibility of their reduction through collaborative efforts between life cycle practitioners and experimental researchers using anticipatory decision-based models. While several of these challenges are experienced in LCA of emerging technologies generally, they are highlighted herein due to their unique or heightened relevance to the use of ENMs in agriculture applications. Addressing challenges in these areas are intended to inform research prioritization to ensure safe and sustainable design, development, and implementation of nano-enabled agrochemicals.