Inversion Evaluation of Rare Earth Elements in Soil by Visible-Shortwave Infrared Spectroscopy

According to historical information, more than 300 metal smelting enterprises have been in the southwest of Xiongan for 300 years; however, these polluting enterprises have been gradually closed with the increased intensity of environmental protection. In the paper, 264 soil samples were collected and analyzed in the range of 400 nm–2500 nm by the spectra vista corporation (SVC), and the spectral noise was smoothed by the Savitzky–Golay filter. In order to enhance the spectral differences and curve shapes, mathematical transformations, such as the standard normal variate (SNV), first-order differential (FD), second-order differential (SD), multiple scattering correction (MSC), and continuum removal (CR), were performed on the data, and the correlation between spectral transformation and contents of REEs was analyzed. Moreover, three machine learning models—partial least-squares (PLS), random forest (RF), back propagation neural network (BPNN)—were used to predict the contents of REEs. Experimental results prove that REEs are combined with spectral active substances, such as organic compounds, clay minerals, and iron oxide, and it is possible to determine the contents of REEs using the reflection spectrum. The R2 between the predicted values and measured contents reached 0.986 by using BPNN after FD transformation. More importantly, the predicted values basically agree with the actual situation for CASI/SASI airborne hyperspectral images, and this is an effective technique to obtain the contents of REEs in soil at the study area.

Determination of the multiple-scattering correction factor and its cross-sensitivity to scattering and wavelength dependence for different AE33 Aethalometer filter tapes: a multi-instrumental approach

Providing reliable observations of aerosol particles' absorption properties at spatial and temporal resolutions suited to climate models is of utter importance to better understand the effects that atmospheric particles have on climate. Nowadays, one of the instruments most widely used in international monitoring networks for in situ surface measurements of light absorption properties of atmospheric aerosol particles is the multi-wavelength dual-spot Aethalometer, AE33. The AE33 derives the absorption coefficients of aerosol particles at seven different wavelengths from the measurements of the optical attenuation of light through a filter where particles are continuously collected. An accurate determination of the absorption coefficients from the AE33 instrument relies on the quantification of the non-linear processes related to the sample collection on the filter. The multiple-scattering correction factor (C), which depends on the filter tape used and on the optical properties of the collected particles, is the parameter with both the greatest uncertainty and the greatest impact on the absorption coefficients derived from the AE33 measurements. Here we present an in-depth analysis of the AE33 multiple-scattering correction factor C and its wavelength dependence for two different and widely used filter tapes, namely the old, and most referenced, TFE-coated glass, or M8020, filter tape and the currently, and most widely used, M8060 filter tape. For performing this analysis, we compared the attenuation measurements from AE33 with the absorption coefficients measured with different filter-based techniques. On-line co-located multi-angle absorption photometer (MAAP) measurements and off-line PP_UniMI polar photometer measurements were employed as reference absorption measurements for this work. To this aim, we used data from three different measurement stations located in the north-east of Spain, namely an urban background station (Barcelona, BCN), a regional background station (Montseny, MSY) and a mountaintop station (Montsec d'Ares, MSA). The median C values (at 637 nm) measured at the three stations ranged between 2.29 (at BCN and MSY, lowest 5th percentile of 1.97 and highest 95th percentile of 2.68) and 2.51 (at MSA, lowest 5th percentile of 2.06 and highest 95th percentile of 3.06). The analysis of the cross-sensitivity to scattering, for the two filter tapes considered here, revealed a large increase in the C factor when the single-scattering albedo (SSA) of the collected particles was above a given threshold, up to a 3-fold increase above the average C values. The SSA threshold appeared to be site dependent and ranged between 0.90 to 0.95 for the stations considered in the study. The results of the cross-sensitivity to scattering displayed a fitted constant multiple-scattering parameter, Cf, of 2.21 and 1.96, and a cross-sensitivity factor, ms, of 1.8 % and 3.4 % for the MSY and MSA stations, respectively, for the TFE-coated glass filter tape. For the M8060 filter tape, Cf values of 2.50, 1.96 and 1.82 and ms values of 1.6 %, 3.0 % and 4.9 % for the BCN, MSY and MSA stations, respectively, were obtained. SSA variations also influenced the spectral dependence of C, which showed an increase with wavelength when SSA was above the site-dependent threshold. Below the SSA threshold, no statistically significant dependence of C on the wavelength was observed. For the measurement stations considered here, the wavelength dependence of C was to some extent driven by the presence of dust particles during Saharan dust outbreaks that had the potential to increase the SSA above the average values. At the mountaintop station, an omission of the wavelength dependence of the C factor led to an underestimation of the absorption Ångström exponent (AAE) by up to 12 %. Differences in the absorption coefficient determined from AE33 measurements at BCN, MSY and MSA of around 35 %–40 % can be expected when using the site-dependent experimentally obtained C value instead of the nominal C value. Due to the fundamental role that the SSA of the particles collected on the filter tape has in the multiple-scattering parameter C, we present a methodology that allows the recognition of the conditions upon which the use of a constant and wavelength-independent C is feasible.

A single calibration of near-infrared spectroscopy to determine the quality of forage for multiple species

Near-infrared spectroscopy (NIRS) is an efficient and chemical-free technique for quickly assessing forage quality. However, calibration curves are usually validated for the forage of a single species, while few studies have reported on the forage of multiple species. Therefore, this work aimed to develop a broad system of calibrating curves by NIRS to predict neutral detergent fiber (NDF), acid detergent fiber (ADF) and crude protein (CP) values from single and mixed forage. To accomplish this, single and mixed forage (32 forage species) were sampled over six years (2013 to 2019) from different regions of Santa Catarina state in southern Brazil. Forage samples were chemically analyzed for NDF, ADF and CP levels, followed by performing spectroscopy. Next, calibration curves were calculated as Second Derivative for NDF, First Derivative + Multiplicative Scattering Correction for ADF, and, Multiplicative Scattering Correction for CP. Approximately 200 sample forage, resulted in determination coefficient (R2) values of 0.94, 0.95, and 0.98 and validation values of 0.94, 0.95, and 0.97 for NDF, ADF, and CP, respectively. Thus, calibration curves were properly developed for quality assessment of single or mixed forage for multiple species, resulting in a chemical-free and time-saving tool for routine laboratory use.

Absorption instruments inter-comparison campaign at the Arctic Pallas station

Aerosol light absorption was measured during a 1-month field campaign in June–July 2019 at the Pallas Global Atmospheric Watch (GAW) station in northern Finland. Very low aerosol concentrations prevailed during the campaign, which posed a challenge for the instruments' detection capabilities. The campaign provided a real-world test for different absorption measurement techniques supporting the goals of the European Metrology Programme for Innovation and Research (EMPIR) Black Carbon (BC) project in developing aerosol absorption standard and reference methods. In this study we compare the results from five filter-based absorption techniques – aethalometer models AE31 and AE33, a particle soot absorption photometer (PSAP), a multi-angle absorption photometer (MAAP), and a continuous soot monitoring system (COSMOS) – and from one indirect technique called extinction minus scattering (EMS). The ability of the filter-based techniques was shown to be adequate to measure aerosol light absorption coefficients down to around 0.01 Mm−1 levels when data were averaged to 1–2 h. The hourly averaged atmospheric absorption measured by the reference MAAP was 0.09 Mm−1 (at a wavelength of 637 nm). When data were averaged for >1 h, the filter-based methods agreed to around 40 %. COSMOS systematically measured the lowest absorption coefficient values, which was expected due to the sample pre-treatment in the COSMOS inlet. PSAP showed the best linear correlation with MAAP (slope=0.95, R2=0.78), followed by AE31 (slope=0.93). A scattering correction applied to PSAP data improved the data accuracy despite the added noise. However, at very high scattering values the correction led to an underestimation of the absorption. The AE31 data had the highest noise and the correlation with MAAP was the lowest (R2=0.65). Statistically the best linear correlations with MAAP were obtained for AE33 and COSMOS (R2 close to 1), but the biases at around the zero values led to slopes clearly below 1. The sample pre-treatment in the COSMOS instrument resulted in the lowest fitted slope. In contrast to the filter-based techniques, the indirect EMS method was not adequate to measure the low absorption values found at the Pallas site. The lowest absorption at which the EMS signal could be distinguished from the noise was >0.1 Mm−1 at 1–2 h averaging times. The mass absorption cross section (MAC) value measured at a range 0–0.3 Mm−1 was calculated using the MAAP and a single particle soot photometer (SP2), resulting in a MAC value of 16.0±5.7 m2 g−1. Overall, our results demonstrate the challenges encountered in the aerosol absorption measurements in pristine environments and provide some useful guidelines for instrument selection and measurement practices. We highlight the need for a calibrated transfer standard for better inter-comparability of the absorption results.

Research on Enhanced Detection of Benzoic Acid Additives in Liquid Food Based on Terahertz Metamaterial Devices

It is very important for human health to supervise the use of food additives, because excessive use of food additives will cause harm to the human body, especially lead to organ failures and even cancers. Therefore, it is important to realize high-sensibility detection of benzoic acid, a widely used food additive. Based on the theory of electromagnetism, this research attempts to design a terahertz-enhanced metamaterial resonator, using a metamaterial resonator to achieve enhanced detection of benzoic acid additives by using terahertz technology. The absorption peak of the metamaterial resonator is designed to be 1.95 THz, and the effectiveness of the metamaterial resonator is verified. Firstly, the original THz spectra of benzoic acid aqueous solution samples based on metamaterial are collected. Secondly, smoothing, multivariate scattering correction (MSC), and smoothing combined with first derivative (SG + 1 D) methods are used to preprocess the spectra to study the better spectral pretreatment methods. Then, Uninformative Variable Elimination (UVE) and Competitive Adaptive Reweighted Sampling (CARS) are used to explore the optimal terahertz band selection method. Finally, Partial Least Squares (PLS) and Least square support vector machine (LS-SVM) models are established, respectively, to realize the enhanced detection of benzoic acid additives. The LS-SVM model combined with CARS has the best effect, with the correlation coefficient of prediction set (Rp) is 0.9953, the root mean square error of prediction set (RMSEP) is 7.3 × 10−6, and the limit of detection (LOD) is 2.3610 × 10−5 g/mL. The research results lay a foundation for THz spectral analysis of benzoic acid additives, so that THz technology-based detection of benzoic acid additives in food can reach requirements stipulated in the national standard. This research is of great significance for promoting the detection and analysis of trace additives in food, whose results can also serve as a reference to the detection of antibiotic residues, banned additives, and other trace substances.