Demonstrating an approach for including pesticide use in life-cycle assessment: Estimating human and ecosystem toxicity of pesticide use in Midwest corn farming

PURPOSE: This study demonstrates an approach to assess human health and ecotoxicity impacts of pesticide use by including multiple environmental pathways and various exposure routes using the case of corn grown for bio-based fuel or chemical production in US Midwestern states. METHODS: Multiple tools including an environmental emission model (PestLCI), an impact analysis tool (USEtox), and additional databases were utilized to estimate the state-specific pesticide releases and their associated spatially explicit toxicity in Midwest states. RESULTS AND DISCUSSION: On average, chlorpyrifos and acetochlor exhibit the highest human toxicity potential (HTP) and the highest ecotoxicity potential (ETP) impact scores, respectively. The different ranking orders of pesticides for human health and ecosystem toxicity suggest that there are tradeoffs between these two impact categories. While the air pathway can account for 10–97 % of HTP, the water pathway is the dominating contributor for ETP for most of the pesticides. Moreover, while chlorpyrifos, fipronil, 2,4-D-2-ethylhexyl ester, simazine, and glufosinate–ammonium together account for more than 80 % of HTP per kilogram harvested corn, acetochlor is the dominating contributor in ETP due to its high ecotoxicity characterization factor and high application rates for corn. In addition, the spatial variation analysis shows that South Dakota and Missouri are the states that have the highest HTP (per kg corn), while Kansas exhibits the highest ETP (per kg corn) among Midwest states. CONCLUSIONS: HTP and ETP exhibit large variations across various pesticides, US states, and application times. While chemical properties and toxicity characteristics can result in up to five orders of magnitude of variation in HTP and ETP, the rest of the parameters (such as application times, soil properties, and climate conditions) can affect the results by up to two orders of magnitude.