Evaluation of the environmental impacts of agricultural systems using life cycle thinking, focusing on marginal changes, technological advances, and regional characteristics.

摘要

Driven by rapid adoption and sustained improvements of genetic technologies and agronomic management practices, agricultural productivity has experienced a substantial growth worldwide since the start of the green revolution in 1960s. This growth has enabled the humanity to escape from the well-known Malthusian Trap. With the success in agricultural productivity, however, comes what is also known as "the other inconvenient truth" (Foley 2009). That is, modern agriculture has become one of the major drivers of global environmental change and is pushing the earth system beyond its safe operating boundaries (Rockstrom et al. 2009). Further, even more challenges lie ahead, given the growing number of population and increasing diversion of foods to fuels.;In this dissertation, three topics related to US agricultural systems are explored. In the first chapter, the environmental properties of US corn and cotton production and implications of land cover change from cotton to corn are evaluated using state-specific data and life cycle impact assessment. The results show that U.S. cotton and corn productions per hectare on average generate roughly similar impacts for most impact categories such as eutrophication and smog formation. Life cycle water use and freshwater ecotoxicity impacts of corn per hectare on average are smaller than those of cotton. When marginal impact is analyzed, however, the results show that the shifts from cotton to corn in cotton-growing states aggravates most of the regional environmental impacts while relieving freshwater ecotoxicity impact. The differences in the two estimates are due mainly to underlying regional disparities in crop suitability that affects input structure and environmental emissions.;In the second chapter, the carbon payback time (CPT) of corn ethanol expansion is re-examined considering three aspects: (1) yields of newly converted lands (i.e., marginal yield), (2) technology improvements over time within the corn ethanol system, and (3) temporal sensitivity of climate change impacts. The results show that without technological advances, the CPT estimates for corn ethanol from newly converted Conservation Reserve Program (CRP) land exceed 100 years for all Marginal to Average (MtA) yield ratios tested except for the case where MtA yield ratio is 100 %. When the productivity improvements within corn ethanol systems since previous CPT estimates and their future projections are considered, the CPT estimates fall into the range of 15 years (100 % MtA yield ratio) to 56 years (50 % MtA yield ratio), assuming land conversion takes place in early 2000s. Incorporating diminishing sensitivity of GHG emissions to future emissions year by year, however, increases the CPT estimates to17 to 88 years. For 60 MtA yield ratio, the CPT is estimated to be 43 years, which is relatively close to previous CPT estimates (i.e., 40 to 48 years) but with very different underlying reasons.;In the third chapter, the trends and underlying drivers of changes in non-global environmental impacts of major crops in the U.S. are investigated. The results show that the impact per hectare corn and cotton generated on the ecological health of freshwater systems decreased by about 50% in the last decade. This change is associated with the use of genetically modified (GM) crops, which has reduced the application of insecticides and relatively toxic herbicides such as atrazine. However, the freshwater water ecotoxicity impact per hectare soybean produced increased by 3-fold, mainly because the spread of invasive species, soybean aphid, has resulted in an increasing use of insecticides. In comparison, other impact categories remained relatively stable. By evaluating the relative ecotoxicity potential of a large number of pesticides, our analysis offers new insight into the benefits associated with genetically modified (GM) crops. The finding that different impact categories show different degrees of changes suggests that agricultural inventory data can be updated selectively in LCA to maximize cost-effectiveness.