To reflect the trend of farm energy efficiency gains, we adopted the estimates from the widely used GREET model , which shows an efficiency increase of about 30% for corn and soybean growth over the last decade. Few studies exist on cotton and wheat on-farm energy change, thus we assumed a similar 30% efficiency gain for them over the timescale investigated. Note that we did not consider nitrogen from manure considering that it is small relative to other nitrogen sources .Building on our previous studies , we estimated a large number of emissions from all the agricultural inputs applied based on emission factors from various models and references . Most of the emissions are pesticides and speciated Volatile Organic Compounds . Estimation of pesticide emissions was slightly more complicated than that of other emissions, thus a detailed explanation is in order. Several approaches to pesticides emissions have been applied in literature and LCA databases. For example, the Ecoinvent database assumes that all pesticides remain in soil after application . The PestLCI model, on the other hand,plastic grow bag treats agricultural soil as part of the technosphere and excludes the impacts of pesticides on ecosystems in the soil .
And yet there is another approach that estimates pesticide emissions to different compartments . We adopted the third approach here. Following Berthoud et al. , we used a pesticide’s vapor pressure to approximate its air emissions, assumed a generic factor of 0.5% of the total applied for pesticides lost to water systems through runoff and leaching, and assumed the remaining fraction, capped at 85% of the total applied, for pesticides emitted to soil.Last, the data we compiled are at the state level, but given our emphasis on the change of environmental impacts of U.S. agriculture on average we aggregated the state-level results to present totals. We also aggregated the three different types of wheat into one “wheat” by adding up their annual agricultural inputs and outputs. In deriving the impacts per ton of crop produced, we followed previous studies and used 3-year average yield data to reduce annual variation caused by possible extreme weathers such as droughts and floods. For example, 2001 impact per ton for corn was calculated by dividing 2001 impact per ha by the average corn yield of 2000, 2001, and 2002. As Fig. 4.2 reflects, changes in the average irrigation water use from 2002 to 2012 were also moderate for corn, cotton, and wheat, with variations <20% between 2002 and 2007 or between 2002 and 2012. In contrast, a noticeable upward trend can be observed for soybean. Average irrigation water use per ha soybean produced increased by around 50%, from 180 m3 in 2002 to 270 m3 in 2012. On a per ton basis, the percentage increase is 30%, from 4300 to 5600 m3 , due to yield increase over the period. Behind this upward trend are several factors, including the slightly increasing irrigation intensity for irrigated area, but the major contributor is the growth in area irrigated and its share in the total area harvested .
What led to the growth in soybean area irrigated is unclear, however, and further research is needed. Here, we offer a possible explanation. In the past “ethanol decade,” soybean and corn areas substantially expanded, into other cropland and also grassland . Because such marginal land as grassland is on average not as fertile as existing corn or soybean land , irrigation might have been applied to boost or maintain yield. Consequently, as total soybean and corn areas expanded, so also did the area irrigated. In the case of corn, however, although area irrigated grew from 4.0 to 5.4 million ha between 2002 and 2012, its share in the total area harvested only slightly increased . Additionally, irrigation intensity for area irrigated decreased from 1480 to 1234 m3 ha-1 . As a result, average irrigation use per ha or per ton corn produced barely changed from 2002 to 2012. Major contributors include reduced use of herbicides atrazine and acetochlor, and of insecticides terbfos, dimethenamid, and, especially, chlorpyrifos . The downward trend is likely due to the continuous expansion of herbicide resistant and insect-resistant corn, particularly glyphosate tolerant and Btcorn. Since its introduction in 1996, HR corn has now expanded to over 70%of cornfield , resulting in increasing use of glyphosate compounds in place of conventional herbicides like atrazine and acetocholor. In fact, glyphosate and related compounds had gradually surpassed atrazine and other herbicides over the past decade to become the most commonly applied pesticide . As glyphosate compounds are relatively less toxic to ecosystems compared with the replaced herbicides like atrazine and acetochlor , the overall ecotoxicity impact of corn attributable to herbicides decreased moderately between 2001 and 2010. Meanwhile, Bt corn has also dominated U.S. cornfield now , offering both economic and environmental benefits by protecting yield and reducing handling and use of insecticides .
This likely further contributed to the downward trend of corn’s freshwater ecotoxicity impact. Similar to corn, the freshwater ecotoxicity impact of cotton decreased by 60% from 2000 to 2007, due to the reduced use of herbicides chlorpyrifos, lambda–cyhalothrin, and particularly cyfluthrin . Application of cyfluthrin reduced from 11 g ha-1 in 2000 to 4 g ha-1 in 2007. Similar to corn, the downward trend in cotton’s freshwater ecotoxicity impact was attributable to the expansion of HR and Bt varieties, which are now planted 95% and 75% of U.S. cotton field respectively . Our result on decreasing freshwater ecotoxicity impact of corn and cotton due to changes in pesticide use and patterns reinforces previous findings . Unlike corn and cotton, soybean’s freshwater ecotoxicity impact quintupled between 2002 and 2012. HR soybean has also expanded dramatically in the US, now planted on 95% of soybean field . Along with the expansion, application of glyphosatecompounds per ha has increased by over 60% between 2002 and 2012, and now they account for 80% of total pesticides applied in soybean growth. However, the benefits of HR soybean seem to have been entirely offset by the increasing use of insecticides lambdacyhalothrin, cyfluthrin, and chlorpyrifos . This is due to the invasion of soybean aphid, a species native to eastern Asia and first detected in North America in 2000, and application of insecticides has been the primary means of pest management . Since its first detection, soybean aphid had rapidly spread to 30 states in the U.S. by 2009 and become a major source of economic loss in soybean production . As a result, the total quantity of insecticides applied to soybean quadrupled between 2002 and 2012, resulting in a 3-fold increase in soybean’s freshwater ecotoxicity impact. The freshwater ecotoxicity impact of wheat increased by about 40% from 2000 to 2009, attributable partly to increased use of several insecticides including chlorpyrifos, cyfluthrin, beta–cyfluthrin, and lambda–cyhalothrin. Also, pesticide application rate in general increased from 0.45 kg ha-1 in 2000 to 0.88 kg ha-1 in 2009. Unlike the other major crops, however,PE grow bag there is not a clear explanation for the upward trend. One possible reason may be the growing resistance of pests as a result of increasing pesticide use. Further research is needed in this area. We conducted sensitivity analysis to test the robustness of the changes in freshwater ecotoxicity impact, considering that it is our major finding and that large uncertain is involved in the estimation of pesticide emissions and assessment of their ecotoxicity impact . First, the proportion in which pesticides are emitted to water systems was identified as the major contributor to crops’ freshwater ecotoxicity. Literature also shows it may vary greatly, from 5% to 0.1% or even less . We thus built 3 scenarios to test the sensitivity of the ecotoxicity result to different leaching and runoff rates. Additionally, we also tested the sensitivity of the trends to other analytical approaches to pesticide emissions , with one assuming all pesticides to remain in soils and the other excluding the impact of pesticides on agricultural soils. All 5 scenarios are presented in Fig. 4.4, which reinforces the trends identified of freshwater ecotoxicity impact regardless of different runoff and leaching rates and analytical approaches to pesticide emissions. Second, impact assessment of freshwater ecotoxicity is also highly uncertain, with the uncertainty range for TRACI 2.0 being likely 1-2 orders of magnitude . However, detailed information on the distribution of each characterization factor is not available yet, thus a full uncertainty analysis is not feasible at this stage. To further test the robustness of the ecotoxicity results, we applied two other characterization models to evaluate the aquatic ecotoxicity impact of pesticide emissions.
For corn, cotton, and soybean, the other two models confirm the directionality of the changes but generally show a lower magnitude of change . This is due in part to differences in the number of pesticides covered by the three models and in part to differences in the relative ecotoxicity potential they assign to each pesticide. Generally, IMPACT 2002+ and CML 2001 cover a smaller number of pesticides than TRACI 2.0, thus they may not capture all the changes in pesticide use and patterns that are captured by TRACI 2.0. For wheat, however, the three characterization models seem to disagree on the directionality as well as the magnitude of changes. A detailed comparison, together with contribution analysis, is provided in the Appendix C. In this study, we evaluated several non-global environmental impacts of U.S. corn, cotton, soybean, and wheat, and analyzed how they changed in the past decade. Due likely to the increasing adoption of genetically modified varieties, freshwater ecotoxicity impact per ha corn produced declined by around 50% from 2001 to 2010 and per ha cotton produced declined by 60% from 2000 to 2007. Due to the invasion of alien species and increasing use of insecticides, freshwater ecotoxicity impact per ha soybean produced increased by 3-fold from 2002 to 2012. In the meantime, on-farm irrigation water use per ha soybean harvested increased by about 50%. In comparison, other non-global impacts were relatively stable. The major implication of our study is that identifying the underlying drivers of the dynamical mechanisms in agricultural systems would be essential for making informed agricultural decisions and policies, prioritizing LCA data update needs, and interpreting LCA results. By evaluating the relative ecotoxicity potential of a large number of pesticides, we found that the use of GM crops have contributed to substantial declines in corn and cotton’s freshwater ecotoxicity impact. This finding provides an opportunity for better assessing the trade offs between the potential impacts of GM and conventional crops, as opposed to comparisons based mainly on the total quantity of pesticides applied . Additionally, our results suggest that updates on agricultural inventory data can be done selectively, with regular updates needed for impact categories that are highly dynamic, such as pesticide related ecotoxicity. Studies relying on single-year and outdated data may inaccurately portray a crop’s ecotoxicity impact; even just a few years of data age may under or overestimate the ecotoxicity impact. This also implies that we should exercise caution when interpreting an LCA study in which ecotoxicity impact of agricultural processes plays an important role in the overall conclusion. Broadly, our study highlights the importance of understanding the dynamics in the input and output structure of a process or a technology in LCA . The focus of our study was to evaluate how environmental impacts of agriculture might have changed in the past decade. Our results that show decreasing freshwater ecotoxicity impacts for corn and cotton are not intended to prove that GM crops are overall more ecologically friendly than conventional crops. Other impacts of GM crops that could not have been evaluated due to the limitations of the current LCIA methods should also be taken into consideration in such comparisons. Current LCIA methods, for example, are not able to properly evaluate potential adverse effects of Bt toxin on populations of non-target species and elevated risk of species invasiveness through genetic modifications . In addition, it should be noted that the trend of decreasing ecotoxicity impact is unlikely to continue for cotton and corn.