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Simulation of Nitrous Oxide Emissions and Estimation of Global Warming Potential in Turfgrass Systems Using the DAYCENT Model.

Abstract

Nitrous oxide (NO) emissions are an important component of the greenhouse gas budget for turfgrasses. To estimate NO emissions and global warming potential, the DAYCENT ecosystem model was parameterized and applied to turfgrass ecosystems. The annual cumulative NO emissions predicted by the DAYCENT model were close to the measured emission rates of Kentucky bluegrass ( L.) sites in Colorado (within 16% of the observed values). For the perennial ryegrass ( L.) site in Kansas, the DAYCENT model initially overestimated the NO emissions for all treatments (urea and ammonium sulfate at 250 kg N ha yr and urea at 50 kg N ha yr) by about 200%. After including the effect of biological nitrification inhibition in the root exudate of perennial ryegrass, the DAYCENT model correctly simulated the NO emissions for all treatments (within 8% of the observed values). After calibration and validation, the DAYCENT model was used to simulate NO emissions and carbon sequestration of a Kentucky bluegrass lawn under a series of management regimes. The model simulation suggested that gradually reducing fertilization as the lawn ages from 0 to 50 yr would significantly reduce long-term NO emissions by approximately 40% when compared with applying N at a constant rate of 150 kg N ha yr. Our simulation indicates that a Kentucky bluegrass lawn in Colorado could change from a sink to a weak source of greenhouse gas emissions 20 to 30 yr after establishment.

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  • Publisher Full Text
  • Authors

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    Source

    Journal of environmental quality 42:4 2013 Jul pg 1100-8

    MeSH

    Ecosystem
    Global Warming
    Greenhouse Effect
    Lolium
    Models, Theoretical
    Nitrous Oxide

    Pub Type(s)

    Journal Article

    Language

    eng

    PubMed ID

    24216361

    Citation

    * When formatting your citation, note that all book, journal, and database titles should be italicized* Article titles in AMA citation format should be in sentence-case
    TY - JOUR T1 - Simulation of Nitrous Oxide Emissions and Estimation of Global Warming Potential in Turfgrass Systems Using the DAYCENT Model. AU - Zhang,Yao, AU - Qian,Yaling, AU - Bremer,Dale J, AU - Kaye,Jason P, PY - 2013/11/13/entrez PY - 2013/11/13/pubmed PY - 2016/4/24/medline SP - 1100 EP - 8 JF - Journal of environmental quality JO - J. Environ. Qual. VL - 42 IS - 4 N2 - Nitrous oxide (NO) emissions are an important component of the greenhouse gas budget for turfgrasses. To estimate NO emissions and global warming potential, the DAYCENT ecosystem model was parameterized and applied to turfgrass ecosystems. The annual cumulative NO emissions predicted by the DAYCENT model were close to the measured emission rates of Kentucky bluegrass ( L.) sites in Colorado (within 16% of the observed values). For the perennial ryegrass ( L.) site in Kansas, the DAYCENT model initially overestimated the NO emissions for all treatments (urea and ammonium sulfate at 250 kg N ha yr and urea at 50 kg N ha yr) by about 200%. After including the effect of biological nitrification inhibition in the root exudate of perennial ryegrass, the DAYCENT model correctly simulated the NO emissions for all treatments (within 8% of the observed values). After calibration and validation, the DAYCENT model was used to simulate NO emissions and carbon sequestration of a Kentucky bluegrass lawn under a series of management regimes. The model simulation suggested that gradually reducing fertilization as the lawn ages from 0 to 50 yr would significantly reduce long-term NO emissions by approximately 40% when compared with applying N at a constant rate of 150 kg N ha yr. Our simulation indicates that a Kentucky bluegrass lawn in Colorado could change from a sink to a weak source of greenhouse gas emissions 20 to 30 yr after establishment. SN - 0047-2425 UR - https://www.unboundmedicine.com/medline/citation/24216361/Simulation_of_Nitrous_Oxide_Emissions_and_Estimation_of_Global_Warming_Potential_in_Turfgrass_Systems_Using_the_DAYCENT_Model_ L2 - http://dl.sciencesocieties.org/publications/jeq/articles/42/4/1100 DB - PRIME DP - Unbound Medicine ER -