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Nutrient loads to surface water from row crop production

Content Provider	Springer Nature Link
Author	Powers, Susan E.
Copyright Year	2007
Abstract	Eutrophication and hypoxia, which are already serious environmental issues in the Midwestern region of the United States and the Gulf of Mexico, could worsen with an increase emphasis on the use of corn and soybeans for biofuels. Eutrophication impacts from agriculture are difficult to integrate into an LCA due to annual variability in the nutrient loads as a factor of climatic conditions. This variability has not been included in many relevant energy or row crop LCAs. The objective of this research was to develop a relatively simple method to accurately quantify nutrient loadings from row crop production to surface water that reflects annual variations due to weather. A set of watersheds that comprise most of eastern Iowa was studied. Ample data describing corn-soybean agriculture in this region and nutrient loadings to the Mississippi River enabled the development, calibration and validation of the model for this particular region.A framework for estimating lifecycle inventory data for variable nutrient loading from corn-soybean agriculture was developed. The approach uses 21 years of country-average data for agricultural and annual rainfall for 33 counties that approximate three major watersheds in eastern Iowa. A linear equation describes the relationship between the fraction of the applied nutrients that leach into the surface water and the annual rainfall. Model parameters were calibrated by minimizing the error in the difference between actual and modeled cumulative discharge to the Mississippi River over the period 1988–1998. Data from 1978–1987 were used to validate the method. Two separate approaches were then used to allocate the nutrient flows between the corn and soybeans.The total nitrogen (TN) and total phosphorus (TP) leaching models provide good representation of the variability in measured nutrient loads discharged from eastern Iowa watersheds to the Mississippi River. The calibrated model estimates are within 1.1% of the actual 11-year cumulative TN load and 0.3% of the TP load. In contrast, a standard method used in other lifecycle assessments for estimating nutrient leaching based on a constant fraction of the nutrients leached provides a reasonable average, but does not capture the annual variability. Estimates of the TN load that can be allocated to corn range from 60 and 99% between two allocation methods considered. This difference stems from a poorly understood symbiosis of nitrogen flows within the corn-soybean rotation that is difficult to integrate into an LCA.Lifecycle inventories can include improved estimates non-point source nutrient flows to surface waters by incorporating climatic variability. Nutrient discharges to surface water are estimated with emission factors as a linear function of the annual rainfall rate. Water quality data is required to calibrate this model for a given region. In comparison with a standard approach that uses an average emission factor, the model presented here is superior in terms of capturing the variability that is correlated to an increase in the size of the hypoxic zone in the Gulf of Mexico.Lifecycle inventories quantifying nutrient discharges from corn-soybean production should include the variability in these flows that occur due to climatic conditions. Failure to do so will reduce the LCA’s capability of quantifying the very significant eutrophication and hypoxia impacts associated with wet years.
Starting Page	399
Ending Page	407
Page Count	9
File Format	PDF
ISSN	09483349
Journal	The International Journal of Life Cycle Assessment
Volume Number	12
Issue Number	6
e-ISSN	16147502
Language	English
Publisher	Ecomed
Publisher Date	2007-02-17
Publisher Place	Landsberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Biofuels corn eutrophication hypoxia non-point source pollution nutrient leaching soybean water quality Environment Environmental Economics
Content Type	Text
Resource Type	Article
Subject	Environmental Science

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