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Performance comparison between a miniaturized and a conventional near infrared reflectance (NIR) spectrometer for characterizing soil carbon and nitrogen
摘要： Miniaturized near infrared spectrometers are now available, at more affordable prices than conventional spectrometers, but their performances have been poorly studied to date. This paper aimed at comparing the performances of the JDSU MicroNIR 2200 spectrophotometer (weight < 0.1 kg) with those of a conventional bench-top instrument for predicting carbon and nitrogen contents in laboratory conditions, on a range of representative Malagasy soils. Though its noticeably narrower and less resolved spectra (1151–2186 nm at 8.15 nm step vs. 1100–2498 nm at 2 nm step), the microspectrometer yielded predictions in independent validation that were almost as accurate as those of the conventional instrument (standard errors of prediction were 4.6 vs. 3.4 gC kg?1 after bias correction, and 0.36 vs. 0.35 gN kg?1, respectively). Due to noisy features, the MicroNIR spectra needed mathematical pretreatment (e.g. standard normal variate SNV), and bias correction for C, for providing accurate predictions, while the raw absorbance spectra from the conventional instrument did not. Furthermore, building multivariate models with MicroNIR spectra required less latent variables than with their conventional counterparts, and these models were less prone to performance degradation when applied to independent validation samples. Fitting the spectra of the conventional instrument to those of the MicroNIR (1150–2182 nm at 2 or 8 nm step) showed that (moderately) less accurate MicroNIR predictions could be firstly attributed to narrower spectral range rather than to poorer resolution. Considering their performances, such microspectrometers could thus represent a cost-effective alternative to conventional spectrometers. They have now to be tested in field conditions.
关键词： Near infrared reflectance spectroscopy (NIRS),Soil organic carbon,Madagascar,Soil total nitrogen,Microspectrometer
更新于2025-09-23 15:22:29
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Efficiency of sequential UV/H2O2 and biofilm process for the treatment of secondary effluent
摘要： In response to the shortage of water resources, multiple processes have been applied to turn wastewater secondary effluent (SE) into potable water. However, trace organic contaminants (TOrCs) and high concentrations of organic matter contained in SE pose a significant challenge to the reclamation. In this manuscript, combined UV-based and biofilm processes were used to treat the SE spiked with ibuprofen (IBU) and clofibric acid (CA). The efficiency of these sequential treatments was characterized in terms of changes in dissolved organic carbon (DOC), absorbance at 254 nm (A254), fluorescence excitation-emission matrix (FEEM), the concentration of IBU and CA, and molecular weight of SE. Parallel factor (PARAFAC) was applied as the analysis method for FEEM of the samples and two fluorescent components were successfully identified: humic-like substances (C1) and protein-like matter (C2). Large reductions in A254, C1, C2, IBU, and CA were observed during the UV-based processes, especially with the addition of H2O2. Nearly 50% of A254, 80% of the component C1 were decreased and almost complete removal of the component C2 and TOrCs was achieved by UV/2.0 mM H2O2 after 90-min treatment. During the oxidation processes, the formation of lower molecular weight (LMW) compounds was detected, and the biodegradability of the organic matters was greatly increased. Although no significant DOC reduction was obtained in UV-based processes, an obvious further DOC reduction (30~60%) was achieved by biofilm treatment following UV-based processes, especially after UV/H2O2 treatments. In the meantime, large amounts of LMW were removed in the biofilm treatment process. This manuscript provides an effective advanced treatment of SE for the removal of DOC and TOrCs, facilitating the wastewater reclamation.
关键词： Trace organic contaminants,Removal,Biofilm,Secondary effluent,Dissolved organic carbon,UV/H2O2
更新于2025-09-23 15:21:21
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From micro to macro-contaminants: The impact of low-energy titanium dioxide photocatalysis followed by filtration on the mitigation of drinking water organics
摘要： This study evaluated strategies targeting macro- and micro-organic contaminant mitigation using low-energy titanium dioxide photocatalysis. Energy inputs of 1, 2, and 5 kWh m-3 resulted in incomplete oxidation of macro-organic natural organic matter, signified by greater reductions of UV254 and specific ultraviolet UV absorbance (SUVA) in comparison to dissolved organic carbon (DOC). The rate of UV254 removal was 3 orders of magnitude greater than the rate of DOC degradation. Incomplete oxidation improved operation of downstream filtration processes. Photocatalysis at 2 kWh m-3 increased the bed life of downstream granular activated carbon (GAC) filter by 340% relative to direct filtration pretreatment. Likewise, photocatalysis operated ahead of microfiltration decreased fouling, resulting in longer filter run times. Using 2 kWh m-3 photocatalysis increased filter run time by 36 times in comparison to direct filtration. Furthermore, levels of DOC and UV254 in the membrane permeate improved (with no change in removal across the membrane) using low-energy photocatalysis pretreatments. While high-energy UV inputs provided high levels of removal of the estrogenic micro-organics estrone (E1), 17β-estradiol (E2), estriol (E3), and 17α-ethynlestradiol (EE2), low-energy photocatalysis did not enhance removal of estrogens beyond levels achieved by photolysis alone. In the cases of E1 and E3, the addition of TiO2 as a photocatalyst reduced degradation rates of estrogens compared to UV photolysis. Overall, process electrical energy per order magnitude reductions (EEOs) greatly improved using photocatalysis, versus photolysis, for the macro-organics DOC, UV254, and SUVA; however, energy required for removal of estrogens was similar between photolysis and photocatalysis.
关键词： granular activated carbon (GAC),estrogens,UV photolysis,dissolved organic carbon (DOC),advanced oxidation process (AOP),natural organic matter (NOM)
更新于2025-09-23 15:21:01
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A novel single-cavity three-wavelength photoacoustic spectrometer for atmospheric aerosol research
摘要： The spectral light-absorbing behavior of carbonaceous aerosols varies depending on the chemical composition and structure of the particles. A new single-cavity three-wavelength photoacoustic spectrometer was developed and characterized for measuring absorption coefficients at three wavelengths across the visible spectral range. In laboratory studies, several types of soot with different organic content were generated by a diffusion flame burner and were investigated for changes in mass-specific absorption cross section (MAC) values, absorption and scattering ?ngstr?m exponents (αabs and αsca), and single scattering albedo (ω). By increasing the organic carbonaceous (OC) content of the aerosol from 50 to 90 % of the total carbonaceous mass, for 660 nm nearly no change of MAC was found with increasing OC content. In contrast, for 532 nm a significant increase, and for 445 nm a strong increase of MAC was found with increasing OC content of the aerosol. Depending on the OC content, the ?ngstr?m exponents of absorption and scattering as well as the single scattering albedo increased. These laboratory results were compared to a field study at a traffic-dominated urban site, which was also influenced by residential wood combustion. For this site a daily average value of αabs(445–660) of 1.9 was found.
关键词： light absorption,carbonaceous aerosols,organic carbon,photoacoustic spectrometer,black carbon,single scattering albedo,?ngstr?m exponents
更新于2025-09-23 15:19:57
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Atmospheric particulate matter characterization by Fourier transform infrared spectroscopy: a review of statistical calibration strategies for carbonaceous aerosol quantification in US measurement networks
摘要： Atmospheric particulate matter (PM) is a complex mixture of many different substances and requires a suite of instruments for chemical characterization. Fourier transform infrared (FT-IR) spectroscopy is a technique that can provide quantification of multiple species provided that accurate calibration models can be constructed to interpret the acquired spectra. In this capacity, FT-IR spectroscopy has enjoyed a long history in monitoring gas-phase constituents in the atmosphere and in stack emissions. However, application to PM poses a different set of challenges as the condensed-phase spectrum has broad, overlapping absorption peaks and contributions of scattering to the mid-infrared spectrum. Past approaches have used laboratory standards to build calibration models for prediction of inorganic substances or organic functional groups and predict their concentration in atmospheric PM mixtures by extrapolation. In this work, we review recent studies pursuing an alternate strategy, which is to build statistical calibration models for mid-IR spectra of PM using collocated ambient measurements. Focusing on calibrations with organic carbon (OC) and elemental carbon (EC) reported from thermal–optical reflectance (TOR), this synthesis serves to consolidate our knowledge for extending FT-IR spectroscopy to provide TOR-equivalent OC and EC measurements to new PM samples when TOR measurements are not available. We summarize methods for model specification, calibration sample selection, and model evaluation for these substances at several sites in two US national monitoring networks: seven sites in the Interagency Monitoring of Protected Visual Environments (IMPROVE) network for the year 2011 and 10 sites in the Chemical Speciation Network (CSN) for the year 2013. We then describe application of the model in an operational context for the IMPROVE network for samples collected in 2013 at six of the same sites as in 2011 and 11 additional sites. In addition to extending the evaluation to samples from a different year and different sites, we describe strategies for error anticipation due to precision and biases from the calibration model to assess model applicability for new spectra a priori. We conclude with a discussion regarding past work and future strategies for recalibration. In addition to targeting numerical accuracy, we encourage model interpretation to facilitate understanding of the underlying structural composition related to operationally defined quantities of TOR OC and EC from the vibrational modes in mid-IR deemed most informative for calibration. The paper is structured such that the life cycle of a statistical calibration model for FT-IR spectroscopy can be envisioned for any substance with IR-active vibrational modes, and more generally for instruments requiring ambient calibrations.
关键词： thermal-optical reflectance,statistical calibration,elemental carbon,IMPROVE network,Chemical Speciation Network,FT-IR spectroscopy,organic carbon,atmospheric particulate matter
更新于2025-09-19 17:15:36
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Light absorption by organic aerosol emissions rivals that of black carbon from residential biomass fuels in South Asia
摘要： Solid biomass fuel-based residential cookstoves are the largest source of aerosol emissions in the Indian subcontinent. For assessing radiative forcing due to this pollutant source, laboratory-generated cookstove performance datasets are currently used, which have established black carbon (BC) as the dominant atmospheric warming aerosol species. We report findings on the strong near-ultraviolet wavelength absorption characteristics of emitted organic carbon (OC) aerosol from household stove combustion of nationally-representative biomass fuels. OC emission from cookstoves have been conventionally parameterized in emission inventory and regional climate models to be non-light-absorbing in the visible solar spectra. We conclude that light-absorbing OC contributes roughly as much as BC to total absorption cross-sections, thereby enhancing the associated positive forcing estimates. Our findings underscore the importance of including light-absorbing OC within the subcontinent’s air quality and climate impact assessment frameworks.
关键词： South Asia,black carbon,radiative forcing,biomass fuels,organic carbon,light absorption,cookstoves,aerosol emissions
更新于2025-09-19 17:13:59
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Soil Content Accurately Modeled Using Spectroscopy
摘要： Soil is the foundation of food production on the planet. Clay and organic carbon content of the soil are among the most influential factors in soil functions, productivity, and management. Current laboratory methods for studying clay and organic carbon are slow, highly uncertain, and expensive. Visible near-infrared spectroscopy has shown to be a powerful tool to detect and quantify molecules of interest in a sample. In an article recently published in the Soil Science Society of America Journal, researchers report on a novel method of combinatory on-the-go spectroscopy and soil electrical conductivity measurements in agricultural fields as a substitute to soil sample collection and laboratory analysis. The team used multivariate regression methods to predict soil clay and organic carbon in soil using the rapidly obtained data. They found that although the uncontrolled spectral measurement environment in the field introduced a large amount of noise in the dataset, comprehensive spectral preprocessing and redundant variable removal could still lead to accurate models. Furthermore, it was shown that spectroscopy alone could provide the best results without the need for adding electrical conductivity data. In addition to the practical applications in soil and agricultural studies, the results also have important implications for future sensor design, data processing, and soil modeling.
关键词： soil content,organic carbon,multivariate regression,spectroscopy,clay
更新于2025-09-16 10:30:52
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Soil organic carbon predictions in Subarctic Greenland by visible–near infrared spectroscopy
摘要： Release of carbon from high-latitude soils to the atmosphere may have significant effects on Earth’s climate. In this contribution, we evaluate visible–near-infrared spectroscopy (vis-NIRS) as a time- and cost-efficient tool for assessing soil organic carbon (SOC) concentrations in South Greenland. Soil samples were collected at two sites and analyzed with vis-NIRS. We used partial least square regression (PLS-R) modeling to predict SOC from vis-NIRS spectra referenced against in situ dry combustion measurements. The ability of our approach was validated in three setups: (1) calibration and validation data sets from the same location, (2) calibration and validation data sets from different locations, and (3) the same setup as in (2) with the calibration model enlarged with few samples from the opposite target area. Vis-NIRS predictions were successful in setup 1 (R2 = 0.95, root mean square error of prediction [RMSEP] = 1.80 percent and R2 = 0.82, RMSEP = 0.64 percent). Predictions in setup 2 had higher errors (R2 = 0.90, RMSEP = 7.13 percent and R2 = 0.78, RMSEP = 2.82 percent). In setup 3, the results were again improved (R2 = 0.95, RMSEP = 2.03 percent and R2 = 0.77, RMSEP = 2.14 percent). We conclude that vis-NIRS can obtain good results predicting SOC concentrations across two subarctic ecosystems, when the calibration models are augmented with few samples from the target site. Future efforts should be made toward determination of SOC stocks to constrain soil–atmosphere carbon exchange.
关键词： visible–near-infrared spectroscopy,subarctic,Soil organic carbon,Greenland
更新于2025-09-12 10:27:22