...
首页> 外文期刊>Journal of near infrared spectroscopy >Field-scale predictions of soil contaminant sorption using visible-near infrared spectroscopy
【24h】

Field-scale predictions of soil contaminant sorption using visible-near infrared spectroscopy

机译:可见-近红外光谱法对土壤污染物吸附的现场规模预测

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

Models used to evaluate leaching of contaminants to groundwater are very sensitive to sorption coefficients (K-d). These models need reliable K-d data at the field scale, but the number of samples required makes the classic batch sorption experiments inappropriate for this purpose. Since visible-near infrared (vis-NIR) spectroscopy is an inexpensive and fast method, it has been used for predicting soil properties related to soil sorption capacity. In this study, we aimed to predict the spatial variation of K-d from vis-NIR spectra for two contaminants: phenanthrene (sorbed on organic fractions) and glyphosate (sorbed on mineral fractions). Forty-five bulk soil samples were collected from an agricultural field in Estrup, Denmark, in a 15 m x 15 m grid. Samples were air-dried, sieved to 2 mm and analysed for selected soil properties. Sorption coefficients were obtained from a batch equilibration experiment. Soil samples were measured with a bench-top spectrometer covering the vis-NIR range between 400 nm and 2500 nm. Partial least squares regression with full cross-validation was used to correlate the soil spectra with K-d values and soil properties. The sorption coefficients ranged from 345 L kg(-1) to 886 L kg(-1) and from 162 L kg(-1) to 536 L kg(-1) for phenanthrene and glyphosate, respectively. The regression coefficients showed that phenanthrene-sorption was correlated with total organic carbon, aluminium oxides and cation exchange capacity, and glyphosate sorption with clay minerals and iron oxides. By means of the vis-NIR spectra we were able to predict phenanthrene (R-2 = 0.95, RMSECV = 31 L kg(-1)) and glyphosate (R-2 = 0.79, RMSECV = 45 L kg(-1)) sorption capacities. A model using vis-NIR spectra plus pH values improved the prediction of glyphosate sorption capacity (R-2 = 0.88, RMSECV = 34 L kg(-1)). The models obtained from vis-NIR spectra successfully-predicted K-d within the investigated field, indicating the potential of vis-NIR spectroscopy as a fast method for determining K-d for input to leaching risk assessment models. However, further studies of different soil types and geographical scales are needed to confirm our findings.
机译:用于评估污染物向地下水中淋溶的模型对吸附系数(K-d)非常敏感。这些模型需要在现场范围内获得可靠的K-d数据,但是所需的样品数量使得经典的批量吸附实验不适用于此目的。由于可见近红外(vis-NIR)光谱是一种廉价且快速的方法,因此已被用于预测与土壤吸附能力有关的土壤特性。在这项研究中,我们旨在通过vis-NIR光谱预测两种污染物的K-d的空间变化:菲(吸附在有机部分上)和草甘膦(吸附在矿物部分上)。在15 m x 15 m的网格中,从丹麦Estrup的一块农田中收集了45个散装土壤样品。将样品风干,过筛至2毫米,并分析选定的土壤特性。吸附系数是从批量平衡实验中获得的。用台式光谱仪测量土壤样品,该光谱仪的可见-近红外范围在400 nm至2500 nm之间。使用具有完全交叉验证的偏最小二乘回归将土壤光谱与K-d值和土壤特性相关联。菲和草甘膦的吸附系数分别为345 L kg(-1)至886 L kg(-1)和162 L kg(-1)至536 L kg(-1)。回归系数表明,菲吸附与总有机碳,氧化铝和阳离子交换容量以及草甘膦对粘土矿物和氧化铁的吸附有关。通过vis-NIR光谱我们可以预测菲(R-2 = 0.95,RMSECV = 31 L kg(-1))和草甘膦(R-2 = 0.79,RMSECV = 45 L kg(-1))吸附能力。使用vis-NIR光谱加上pH值的模型可以改善草甘膦吸附能力的预测(R-2 = 0.88,RMSECV = 34 L kg(-1))。从vis-NIR光谱获得的模型成功地预测了研究范围内的K-d,表明vis-NIR光谱作为确定K-d作为浸出风险评估模型输入的快速方法的潜力。但是,需要进一步研究不同的土壤类型和地理规模,以证实我们的发现。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号