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首页> 外文期刊>Environmental Science & Technology >Re-estimating NH_3 Emissions from Chinese Cropland by a New Nonlinear Model
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Re-estimating NH_3 Emissions from Chinese Cropland by a New Nonlinear Model

机译：通过新的非线性模型重新估算中国农田的NH_3排放

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摘要

Ammonia (NH_3) released to the atmosphere leads to a cascade of impacts on the environment, yet estimation of NH_3 volatilization from cropland soils (V_(NH_3)) in a broad spatial scale is still quite uncertain in China. This mainly stems from nonlinear relationships between V_(NH_3) and relevant factors. On the basis of 495 site-years of measurements at 78 sites across Chinese croplands, we developed a nonlinear Bayesian tree regression model to determine how environmental factors modulate the local derivative of V_(NH_3) to nitrogen application rates (N_(rate)) (VR, %). The V_(NH_3)-N_(rate) relationship was nonlinear. The VR of upland soils and paddy soils depended primarily on local water input and N_(rate), respectively. Our model demonstrated good reproductions of V_(NH_3) compared to previous models, i.e., more than 91% of the observed VR variance at sites in China and 79% of those at validation sites outside China. The observed spatial pattern of V_(NH_3) in China agreed well with satellite-based estimates of NH_3 column concentrations. The average VRs in China derived from our model were 14.8 ± 2.9% and 11.8 ± 2.0% for upland soils and paddy soils, respectively. The estimated annual NH_3 emission in China (3.96 ± 0.76 TgNH_3·yr~(-1)) was 40% greater than that based on the IPCC Tier 1 guideline.
机译：释放到大气中的氨（NH_3）导致对环境的级联影响，但是在中国，从广阔空间尺度上估算农田土壤（V_（NH_3））中的NH_3挥发仍是相当不确定的。这主要源于V_（NH_3）与相关因素之间的非线性关系。基于对中国农田中78个站点的495个站点-年的测量，我们开发了非线性贝叶斯树回归模型，以确定环境因素如何将V_（NH_3）的局部导数调节为氮肥施用率（N_（rate））（ VR，％）。 V_（NH_3）-N_（rate）关系是非线性的。旱地和水稻土的VR分别主要取决于当地的水输入量和N_（速率）。与以前的模型相比，我们的模型展示了V_（NH_3）的良好复制，即在中国站点观察到的VR变异超过91％，在中国以外的验证站点观察到的VR变异超过79％。在中国观测到的V_（NH_3）的空间格局与基于卫星的NH_3色谱柱浓度估算值非常吻合。根据我们的模型得出，中国旱地和稻田的平均VR分别为14.8±2.9％和11.8±2.0％。据估算，中国每年的NH_3排放量（3.96±0.76 TgNH_3·yr〜（-1））比基于IPCC方法1指南的排放量高40％。

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  • 来源
    《Environmental Science & Technology》 |2016年第2期|564-572|共9页
  • 作者

    Feng Zhou; Philippe Ciais; Kentaro Hayashi; James Galloway; Dong-Gill Kim; Changliang Yang; Shiyu Li; Bin Liu; Ziyin Shang; Shuoshuo Gao;

  • 作者单位

    Institute of Integrated Watershed Management, Sino-France Institute of Earth Systems Science, Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing, 100871, P.R. China;

    Laboratoire des Sciences du Climat et de l'Environnement, CEA CNRS UVSQ, 91191 Gif-sur-Yvette, France;

    Carbon and Nutrient Cycles Division, National Institute for Agro-Environmental Sciences, 3-1-3, Kannondai, Tsukuba, Ibaraki 305-8604, Japan;

    Environmental Sciences Department, University of Virginia, Charlottesville, Virginia 22904, United States;

    Wondo Genet College of Forestry and Natural Resources, Hawassa University, Shashemene, Ethiopia;

    Research Institute of Engineering Technology, Yunnan University, Kunming, 650091, P.R. China;

    Research Institute of Engineering Technology, Yunnan University, Kunming, 650091, P.R. China;

    Research Institute of Engineering Technology, Yunnan University, Kunming, 650091, P.R. China;

    Institute of Integrated Watershed Management, Sino-France Institute of Earth Systems Science, Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing, 100871, P.R. China;

    Institute of Integrated Watershed Management, Sino-France Institute of Earth Systems Science, Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing, 100871, P.R. China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
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