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  • 1
    Language: English
    In: Journal of Near Infrared Spectroscopy, June 2016, Vol.24(3), pp.281-291
    Description: Models used to evaluate leaching of contaminants to groundwater are very sensitive to sorption coefficients (Kd). These models need reliable Kd 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 Kd 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 × 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 Kd 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 (R2 = 0.95, RMSECV = 31 L kg−1) and glyphosate (R2 = 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 (R2 = 0.88, RMSECV = 34 L kg−1). The models obtained from vis–NIR spectra successfully predicted Kd within the investigated field, indicating the potential of vis–NIR spectroscopy as a fast method for determining Kd for input to leaching risk assessment models. However, further studies of different soil types and geographical scales are needed to confirm our findings.
    Keywords: Soil Sorption Coefficients ; Glyphosate ; Phenanthrene ; Field Scale ; Visible–Near Infrared Reflectance Spectroscopy ; Multivariate Analysis
    ISSN: 0967-0335
    E-ISSN: 1751-6552
    Source: Sage Journals (Sage Publications)
    Source: SAGE Materials Science and Engineering (Sage Publications)
    Source: SAGE Health Sciences (Sage Publications)
    Source: SAGE Communication and Media Studies (Sage Publications)
    Source: SAGE Journals (Sage Publications)
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  • 2
    Language: English
    In: Journal of Near Infrared Spectroscopy, June 2016, Vol.24(3), pp.215-224
    Description: Soil water repellency (WR) is a widespread phenomenon caused by aggregated organic matter (OM) and layers of hydrophobic organic substances coating the surface of soil particles. These substances have a very low surface free energy, reducing a soil's water attraction. There is focus on WR due to its effects on germination, root growth, liquid–vapour dynamics, surface erosion and leaching of chemicals through fingered flow paths. However, common techniques for measuring WR are time-consuming and expensive. Meanwhile, it is well established that visible near infrared (vis-NIR) spectroscopy is a reliable method for determining soil OM. Potentially it could therefore provide fast measurements of WR through autocorrelation with OM. The aim of this study was to test the feasibility of vis-NIR spectroscopy for estimating the WR of soils with a small gradient in soil organic carbon (SOC) and texture, and to evaluate the effect of soil pretreatment on the predictive ability of WR models. A total of 87 soil samples from an agricultural coarse sandy field in Denmark were analysed for SOC, particle size fractions, water content and WR. Soil samples were scanned with a vis-NIR sensor (350–2500 nm) after air- and oven-drying at 60°C and 105°C. WR, expressed as liquid surface tension (mN m−1), was determined using the molarity of ethanol droplet test. Partial least squares regression models of SOC, texture and water content showed no predictive ability (r2 values between 0.10 and 0.51). However, successful models (r2 = 0.85) were generated for WR. The majority of bands important in the vis-NIR region of WR models were related to different components of OM indicating that, across the investigated field, WR was related to specific hydrophobic components of soil OM rather than to the total amount of carbon. A lower prediction error of the WR model for soils dried at 105°C (1.93 mN m−1) than at 60°C (2.52 mN m−1) can be explained by a lower range of WR values for the soils dried at 105°C. Moreover, a higher temperature reduced the number of absorption bands related to OM, indicating a degradation of hydrocarbon groups and a more hydrophobic character of the soil.
    Keywords: Vis-Nir Spectroscopy ; Plsr ; Soil Wr ; Liquid Surface Tensions
    ISSN: 0967-0335
    E-ISSN: 1751-6552
    Source: Sage Journals (Sage Publications)
    Source: SAGE Materials Science and Engineering (Sage Publications)
    Source: SAGE Health Sciences (Sage Publications)
    Source: SAGE Communication and Media Studies (Sage Publications)
    Source: SAGE Journals (Sage Publications)
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  • 3
    Language: English
    In: Journal of Near Infrared Spectroscopy, June 2013, Vol.21(3), pp.213-222
    Description: Visible and near infrared diffuse reflectance (vis-NIR) spectroscopy is a low-cost, efficient and accurate soil analysis technique and is thus becoming increasingly popular. Soil spectral libraries are commonly constructed as the basis for estimating soil texture and properties. In this study, partial least squares regression was used to develop models to predict the soil organic carbon (SOC) content of 35 soil samples from one field using (i) the Danish soil spectral library (2688 samples), (ii) a spiked spectral library (a combination of 30 samples selected from the local area and the spectral library, 2718 samples) and (iii) three sub-sets selected from the spectral library. In an attempt to improve prediction accuracy, sub-sets of the soil spectral library were made using three different sample selection methods: those geographically closest (84 samples), those with the same landscape and parent material (96 samples) and those with the most alike spectra to spectra from the field investigation (100 samples). These sub-sets were used to develop three calibration models and in predictions of SOC content. The results showed that the geographically closest model, which used the fewest number of samples, gave the lowest root mean square error of prediction (RMSEP) of 0.19% and the highest ratio of performance to deviation (RPD) of 3.7, followed by the spiked library, same parent material, the spectral library and the most alike spectra. The spiked library model also gave a low RMSEP value of 0.19% and high RPD value of 3.7% and performed markedly better than the model without spiking, despite using 30 samples for library spiking. The accuracy of the model developed using a sub-set from a spectral library was highly dependent on geographical location, soil parent material and landscape.
    Keywords: Soil Organic Carbon ; Near Infrared Spectroscopy ; Spectral Library ; Partial Least Square Regression
    ISSN: 0967-0335
    E-ISSN: 1751-6552
    Source: Sage Journals (Sage Publications)
    Source: SAGE Materials Science and Engineering (Sage Publications)
    Source: SAGE Health Sciences (Sage Publications)
    Source: SAGE Communication and Media Studies (Sage Publications)
    Source: SAGE Journals (Sage Publications)
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  • 4
    Language: English
    In: Waste Management & Research, August 2007, Vol.25(4), pp.343-351
    Description: Compost air permeability controls air flow through compost during composting or when using compost as biofilter material. Air permeability is therefore an important characteristic of compost. The relationships between air permeability (ka) in compost and compost dry bulk density (ρb), gravimetric water content (ω), and volumetric air content (ε) was investigated for two types of composts. The composts used were produced from a digested sewage sludge—straw mixture and from garden waste and measurements were conducted on sieved and repacked 100 cm3 compost samples. Results showed a linear relation between log(ka) and ρb at constant values of ω for both composts, indicating an exponential relationship between ka and ρb. The slopes of these relationships generally became more negative with increasing ρb. The results further showed a linear relationship between log(ka) and log(ε) for both composts as also often observed for soils. It was observed that the log(ka) and log(ε) relationships for the garden waste compost all intercepted at the same location despite having very different slopes. This means that it is possible to predict the entire ka—ε relationship using only one measurement of corresponding (ka, ε) for garden waste. It was not possible to determine whether this was also the case for the sewage sludge compost due to difficulties in sample preparation at low and high water content.
    Keywords: Compost ; Air Permeability ; Air-Filled Porosity ; Dry Bulk Density ; Sewage Sludge ; Garden Waste ; Wmr 1101—6 ; Engineering
    ISSN: 0734-242X
    E-ISSN: 1096-3669
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  • 5
    Language: English
    In: Waste Management and Research, Oct, 2006, Vol.24(5), p.473(9)
    Description: The impact of wind turbulence-induced pressure fluctuations at the soil surface on landfill gas transport and emissions to the atmosphere at an old Danish landfill site was investigated using stochastic modelling combined with soil property and gas transport data measured at the site. The impacts of soil physical properties (including air permeability and volumetric water content) and wind-induced pressure fluctuation properties (amplitude and temporal correlation) on landfill gas emissions to the atmosphere were evaluated. Soil-air permeability and pressure fluctuation amplitude were found to be the most important parameters. Wind-induced gas emissions were further compared with gas emissions caused by diffusion and by long-term pressure variations (due to passing weather systems). Here diffusion and wind-induced gas transport were found to be equally important with wind-induced gas transport becoming the most important at lower soil-air contents.
    Keywords: Fluctuations (Physics) -- Research ; Landfill Gases -- Environmental Aspects ; Landfill Gases -- Research ; Stochastic Models -- Usage ; Sanitary Landfills -- Environmental Aspects ; Sanitary Landfills -- Research ; Wind Pressure -- Environmental Aspects ; Wind Pressure -- Research
    ISSN: 0734-242X
    E-ISSN: 10963669
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  • 6
    Language: English
    In: Waste Management and Research, Feb, 2005, Vol.23(1), p.72(7)
    Description: Percolate production and precipitation data for a full-scale landfill in operation measured over a 13-year period were used to evaluate the impact and importance of the hydrological conditions of landfill sections on the percolate production rates. Both active (open) and closed landfill sections were included in the evaluation. A simple top cover model requiring a minimum of input data was used to simulate the percolate production as a function of precipitation and landfill section hydrology. The results showed that changes over time in the hydrology of individual landfill sections (such as section closure or plantation of trees on top of closed sections) can change total landfill percolate production by more than 100%; thus, percolate production at an active landfill can be very different from percolate production at the same landfill after closure. Furthermore, plantation of willow on top of closed sections can increase the evapotranspiration rate thereby reducing percolate production rates by up to 47% compared to a grass cover. This process, however, depends upon the availability of water in the top layer, and so the evaporation rate will be less than optimal during the summer where soil-water contents in the top cover are low.
    Keywords: Evapotranspiration -- Analysis ; Sanitary Landfills -- Management ; Waste Management -- Methods
    ISSN: 0734-242X
    E-ISSN: 10963669
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  • 7
    Language: English
    In: Waste Management & Research, August 2003, Vol.21(4), pp.356-366
    Description: Landfill gas (CO2 and CH4) concentrations and fluxes in soil adjacent to an old, unlined Danish municipal landfill measured over a 48-hour period during the passage of a low-pressure weather system were used to identify processes governing gas fluxes and concentrations. Two different approaches were applied: (I) State-space analysis was used to identify relations between gas flux and short-term (hourly) variations in atmospheric pressure. (II) A numerical gas transport model was fitted to the data and used to quantify short-term impacts of variations in atmospheric pressure, volumetric soil-water content, soil gas permeability, soil gas diffusion coefficients, and biological CH4 degradation rate upon landfill gas concentration and fluxes in the soil. Fluxes and concentrations were found to be most sensitive to variations in volumetric soil water content, atmospheric pressure variations and gas permeability whereas variations in CH4 oxidation rate and molecular coefficients had less influence. Fluxes appeared to be most sensitive to atmospheric pressure at intermediate distances from the landfill edge. Also overall CH4 fluxes out of the soil over longer periods (years) were largest during periods with rapidly decreasing atmospheric pressures resulting in emission of large amounts of CH4 during short periods of time. This effect, however, was less significant for the CO2 fluxes.
    Keywords: Landfill Gas Emission ; Ch4 Oxidation ; Atmospheric Pressure Variations ; State-Space Analysis ; Numerical Modelling ; Sensitivity Analysis ; Wmr 640-3 ; Engineering
    ISSN: 0734-242X
    E-ISSN: 1096-3669
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  • 8
    Language: English
    In: Waste Management & Research, October 2002, Vol.20(5), pp.445-456
    Description: Leachate production and composition data for a municipal landfill measured over a 25-year period was used to investigate important processes and parameters. Long-term leachate production could be satisfactorily predicted from a simple top-layer landfill hydrology model while short-term predictions were less accurate, likely due to water storage in the waste. State-space and multiple regression modelling were used to identify relations between different parameters. State-space models proved most accurate in fitting measured data, likely because temporal correlation between measurements is accounted for unlike multiple regression. State-space modelling showed that temporal correlation in leachate production must be taken into account and confirmed that water storage inside the landfill is important. Temporal correlation is also important when predicting pH and chloride concentrations but less so for BOD5 and NH3/NH4 + concentrations. Leachate flow did in general not have a strong impact upon leachate composition, small effects were observed for Cl-, and NH3/NH4 +concentrations. It was also observed that the mass load of nitrogen from the landfill was strongly dependent upon leachate nitrogen (ammonia/ammonium) concentrations and to a lesser degree upon leachate flow rates. This study introduces state-space modelling in solid waste management as a powerful tool to identify governing parameters for hydrological and bio-chemical processes.
    Keywords: Controlled Municipal Landfill ; Landfill Hydrology ; Top-Layer Model ; Leachate Composition ; State-Space Analysis ; Nitrogen Loading. Wmr 564-7 ; Engineering
    ISSN: 0734-242X
    E-ISSN: 1096-3669
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