Effect of spectral resolution on the measurement of monoaromatic hydrocarbons by DOAS

The excellent response characteristics and detection sensitivity with much lower operational cost and the capability to discriminate between the isomer of some monoaromatic hydrocarbons （MAHCs） make differential optical absorption spectroscopy （DOAS） a powerful tool to trace concentration variation of MAHCs. But due to the similarity in chemical structure, those MAHCs have the similar overlapped characteristic absorption structures, which make the selection of instrumental parameter critical to the accurate detection of MAHCs. Firstly, the spectral resolution used in DOAS system determines the nonlinear absorption of O2 and the mass dependence of characteristic absorption structure; thereby it determines the effect of elimination error of O2 absorption in the atmospheric spectra for the detection of MAHCs. Secondly, spectral resolution determines the differential absorption characteristics of twelve MAHCs representing major constituents in technical solvents used in the automobile industry and the interference of spectral overlapping. Thirdly, the spectral resolution determines the sensitivity, time resolution and linear range. So the spectral resolution range with the best ratio of signal to noise is used to determine the most suitable spectral resolution range, as well as the spectral resolution range that ensure the characteristic absorption structure of MAHCs and the minimization of O2 absorption interference. Finally, 0.15-0.16 nm （FWHM： full width at half maximum） is assumed to be closest to the optimum spectral resolution and it is confirmed by the results of practical measurement of MAHCs by DOAS.

Investigation of hearing aid users'speech understanding in noise and their spectral-temporal resolution skills

Purpose:Our study aims to compare speech understanding in noise and spectral-temporal resolution skills with regard to the degree of hearing loss,age,hearing aid use experience and gender of hearing aid users.Methods:Our study included sixty-eight hearing aid users aged between 40-70 years,with bilateral mild and moderate symmetrical sensorineural hearing loss.Random gap detection test,Turkish matrix test and spectral-temporally modulated ripple test were implemented on the participants with bilateral hearing aids.The test results acquired were compared statistically according to different variables and the correlations were examined.Results:No statistically significant differences were observed for speech-in-noise recognition,spectraltemporal resolution among older and younger adults in hearing aid users(p>0.05).There wasn’t found a statistically significant difference among test outcomes as regards different hearing loss degrees(p>0.05).Higher performances were obtained in terms of temporal resolution in male participants and participants with more hearing aid use experience(p<0.05).Significant correlations were obtained between the results of speech-in-noise recognition,temporal resolution and spectral resolution tests performed with hearing aids(p<0.05).Conclusion:Our study findings emphasized the importance of regular hearing aid use and it showed that some auditory skills can be improved with hearing aids.Observation of correlations among the speechin-noise recognition,temporal resolution and spectral resolution tests have revealed that these skills should be evaluated as a whole to maximize the patient’s communication abilities.

Luojia-HSSR:A high spatial-spectral resolution remote sensing dataset for land-cover classification with a new 3D-HRNet

High Spatial and Spectral Resolution(HSSR)remote-sensing images can provide rich spectral bands and detailed ground information,but there is a relative lack of research on this new type of remote-sensing data.Although there are already some HSSR datasets for deep learning model training and testing,the data volume of these datasets is small,resulting in low classification accuracy and weak generalization ability of the trained models.In this paper,an HSSR dataset Luojia-HSSR is constructed based on aerial hyperspectral imagery of southern Shenyang City of Liaoning Province in China.To our knowledge,it is the largest HSSR dataset to date,with 6438 pairs of 256×256 sized samples(including 3480 pairs in the training set,2209 pairs in the test set,and 749 pairs in the validation set),covering area of 161 km2 with spatial resolution 0.75 m,249 Visible and Near-Infrared(VNIR)spectral bands,and corresponding to 23 classes of field-validated ground coverage.It is an ideal experimental data for spatial-spectral feature extraction.Furthermore,a new deep learning model 3D-HRNet for interpreting HSSR images is proposed.The conv-neck in HRNet is modified to better mine the spatial information of the images.Then,a 3D convolution module with attention mechanism is designed to capture the global-local fine spectral information simultaneously.Subsequently,the 3D convolution is inserted into the HRNet to optimize the performance.The experiments show that the 3D-HRNet model has good interpreting ability for the Luojia-HSSR dataset with the Frequency Weighted Intersection over Union(FWIoU)reaching 80.54%,indicating that the Luojia-HSSR dataset constructed in this paper and the proposed 3D-HRnet model have good applicable prospects for processing HSSR remote sensing images.

DETERMINATION OF GASEOUS COMPOSITION IN THE MIDDLE ATMOSPHERE BY USING HIGH SPECTRAL RESOLUTION METHODS

One of the crucial problems in study on the middle atmosphere is to determine the concentration and distribution of some trace gases.In this aspect,sounding methods with high spectral resolution have been developed by many scientists.Some major trace gases and their spectral characteristics,space-borne limb method for determination of trace gases in the middle atmosphere are introduced,requirements for used methods and instruments,development and challenge encountered by sounding of trace gases with high spectral resolution are discussed in this paper.

An Algorithm for Detecting Ice Cloud at Different Altitudes by Combining Dual CrIS Full Spectrum Resolution CO2 Channels

Using infrared sensors to detect ice clouds in different atmospheric layers is still a challenge.The different scattering and absorption properties of longwave and shortwave infrared channels can be utilized to fulfill this purpose.In this study,the release of Suomi-NPP Cross-track Infrared Sounder(Cr IS)full spectrum resolution is used to select and pair channels from longwave(~15μm)and shortwave(~4.3μm)CO2 absorption bands under stricter conditions,so as to better detect ice clouds.Besides,the differences of the weighting function peaks and cloud insensitive level altitudes of the paired channels are both within 50 h Pa so that the variances due to atmospheric conditions can be minimized.The training data of clear sky are determined by Visible Infrared Imaging Radiometer Suite(VIIRS)cloud mask product and used to find the linear relationship between the paired longwave and shortwave CO2 absorption channels.From the linear relationship,the so-called cloud emission and scattering index(CESI)is derived to detect ice clouds.CESI clearly captures the center and the ice cloud features of the Super Typhoon Hato located above 415 h Pa.Moreover,the CESI distributions agree with cloud top pressure from the VIIRS in both daytime and nighttime in different atmospheric layers.

Multi-domain High-Resolution Platform for Integrated Spectroscopy and Microscopy Characterizations

In recent decades,materials science has experienced rapid development and posed increasingly high requirements for the characterizations of structures,properties,and performances.Herein,we report on our recent establishment of a multi-domain(energy,space,time)highresolution platform for integrated spectroscopy and microscopy characterizations,offering an unprecedented way to analyze materials in terms of spectral(energy)and spatial mapping as well as temporal evolution.We present several proof-of-principle results collected on this platform,including in-situ Raman imaging(high-resolution Raman,polarization Raman,low-wavenumber Raman),time-resolved photoluminescence imaging,and photoelectrical performance imaging.It can be envisioned that our newly established platform would be very powerful and effective in the multi-domain high-resolution characterizations of various materials of photoelectrochemical importance in the near future.

Quantitative Analysis of Cr in Milk Powder by Laser Induced Breakdown Spectroscopy( LIBS)

At present, heavy metal pollution in food occurs frequently, which requires a novel method for rapid detection. Laser induced breakdown spectroscopy （LIBS） is a new technique for rapid and environmental friendly detection, but it lacks high sensitivity and stability which restrict its development. In this study, Cr-polluted infant milk powder was used as experimental material to explore the feasibility of the application of LIBS technique in food safety detection. Aiming at improving the precision and accuracy of Cr detection by LIBS technique, LIBS spectra of samples were collected by a spectrometer with an intensified charge-cou- pled device （ICCD） using three gratings with different resolutions to comprehensively compare and analyze the stability, sensitivity and quantitative analysis accura- cy of LIBS detection. The results showed that average relative standard deviation （RSD） of LIBS spectral intensity was below 10%, indicating good stability. LIBS signals were collected by three gratings for quantitative analysis, and the results demonstrated that the linear correlation coefficient R2 of fitting curves was 0. 248 87, 0.903 12 and 0.992 81, respectively; the relative errors between actual and predicted concentrations were 38.23%, 8.84% and 7.43%, respectively, indicating that gratings with higher resolutions could lead to higher linear correlation coefficient and better detection accuracy. According to the results, high-resolu- tion spectrometer could significantly improve the accuracy of LIBS detection of Cr concentration in milk powder, suggesting that it is feasible to detect heavy metals in food by LIBS technique with the improvement of core device performance.

NASA’s Mission ACTIVATE: Objectives, Strategies, and Limitations

The primary goal of this report is to describe the operational concepts of NASA’s ACTIVATE mission. ACTIVATE hopes to improve the understanding of aerosol dispersion and models, provide accurate data for aerosols’ characterization and ozone profiles, and establish knowledge of the relationships between aerosols and water. ACTIVATE’s science objectives are to quantify Na-CCN-Nd relationships and reduce uncertainty in model cloud droplet activation parameterizations, improve process-level understanding and model representation of factors governing cloud micro/macro-physical properties and how they couple with cloud effects on aerosol, plus assess advanced remote sensing capabilities for retrieving aerosol and cloud properties related to aerosol-cloud interactions. ACTIVATE utilizes the fixed-wing B-200 King Air to collect data. Data collected by ACTIVATE is highly relevant for meteorologists and environmental scientists looking to understand more about aerosol-cloud formations. Finally, ACTIVATE is a 5-year mission spanning from January 2019 to December 2023 and has used, and will continue to use, instruments such as the High Spectral Resolution Lidar-2 (HSRL-2), the Research Scanning Polarimeter (RSP), and the Diode Laser Hygrometer (DLH).

Evaluation of the Minimum Size of a Window for Harmonics Signals

Windowing applied to a given signal is a technique commonly used in signal processing in order to reduce spectral leakage in a signal with many data. Several windows are well known: hamming, hanning, beartlett, etc. The selection of a window is based on its spectral characteristics. Several papers that analyze the amplitude and width of the lobes that appear in the spectrum of various types of window have been published. This is very important because the lobes can hide information on the frequency components of the original signal, in particular when frequency components are very close to each other. In this paper it is shown that the size of the window can also have an impact in the spectral information. Until today, the size of a window has been chosen in a subjective way. As far as we know, there are no publications that show how to determine the minimum size of a window. In this work the frequency interval between two consecutive values of a Fourier Transform is considered. This interval determines if the sampling frequency and the number of samples are adequate to differentiate between two frequency components that are very close. From the analysis of this interval, a mathematical inequality is obtained, that determines in an objective way, the minimum size of a window. Two examples of the use of this criterion are presented. The results show that the hiding of information of a signal is due mainly to the wrong choice of the size of the window, but also to the relative amplitude of the frequency components and the type of window. Windowing is the main tool used in spectral analysis with nonparametric periodograms. Until now, optimization was based on the type of window. In this paper we show that the right choice of the size of a window assures on one hand that the number of data is enough to resolve the frequencies involved in the signal, and on the other, reduces the number of required data, and thus the processing time, when very long files are being analyzed.

Vegetation Products Derived from Fengyun-3D Medium Resolution Spectral Imager-Ⅱ

The surface vegetation condition has been operationally monitored from space for many years by the Advanced Very High Resolution Radiometer(AVHRR) and the Moderate Resolution Imaging Spectroradiometer(MODIS) instruments. As these instruments are close to the end of their design life, the surface vegetation products are required by many users from the new satellite missions. The MEdium Resolution Spectral Imager-Ⅱ(MERSI-Ⅱ) onboard the Fengyun(FY) satellite(FY-3 series;FY-3 D) is used to retrieve surface vegetation parameters. First, MERSI-Ⅱ solar channel measurements at the red and near-infrared(NIR) bands at the top of atmosphere(TOA) are corrected to the surface reflectances at the top of canopy(TOC) by removing the contributions of scattering and absorption of molecules and aerosols. The normalized difference vegetation index(NDVI) at both the TOA and TOC is then produced by using the same algorithms as the MODIS and AVHRR. The MERSI-Ⅱ enhanced VI(EVI) at the TOC is also developed. The MODIS technique of compositing the NDVI at various timescales is applied to MERSI-Ⅱ to generate the gridded products at different resolutions. The MERSI-Ⅱ VI products are consistent with the MODIS data without systematic biases. Compared to the current MERSI-Ⅱ EVI generated from the ground operational system, the MERSI-Ⅱ EVI from this study has a much better agreement with MODIS after atmospheric correction.

A Thin Cloud Removal Method from Remote Sensing Image for Water Body Identification

In this paper,a thin cloud removal method was put forward based on the linear relationships between the thin cloud reflectance in the channels from 0.4 μm to 1.0 μm and 1.38 μm.Channels of 0.66 μm,0.86 μm and 1.38 μm were chosen to extract the water body information under the thin cloud.Two study cases were selected to validate the thin cloud removal method.One case was applied with the Earth Observation System Moderate Resolution Imaging Spectroradiometer(EOS/MODIS) data,and the other with the Medium Resolution Spectral Imager(MERSI) and Visible and Infrared Radiometer(VIRR) data from Fengyun-3A(FY-3A).The test results showed that thin cloud removal method did not change the reflectivity of the ground surface under the clear sky.To the area contaminated by the thin cloud,the reflectance decreased to be closer to the reference reflectance under the clear sky after the thin cloud removal.The spatial distribution of the water body area could not be extracted before the thin cloud removal,while water information could be easily identified by using proper near infrared channel threshold after removing the thin cloud.The thin cloud removal method could improve the image quality and water body extraction precision effectively.

Extracting Soil Moisture from Fengyun-3D Medium Resolution Spectral Imager-Ⅱ Imagery by Using a Deep Belief Network

Obtaining continuous and high-quality soil moisture(SM) data is important in scientific research and applications,especially for agriculture, meteorology, and environmental monitoring. With the continuously increasing number of artificial satellites in China, the acquisition of SM data from remote sensing images has received increasing attention.In this study, we constructed an SM inversion model by using a deep belief network(DBN) to extract SM data from Fengyun-3 D(FY-3 D) Medium Resolution Spectral Imager-Ⅱ(MERSI-Ⅱ) imagery;we named this model SM-DBN.The SM-DBN consists of two subnetworks: one for temperature and the other for SM. In the temperature subnetwork, bands 1, 2, 3, 4, 24, and 25 of the FY-3 D MERSI-Ⅱ imagery, which are relevant to temperature, were used as inputs while land surface temperatures(LST) obtained from ground stations were used as the expected output value when training the model. In the SM subnetwork, the input data included LSTs generated from the temperature subnetwork, normalized difference vegetation index(NDVI), and enhanced vegetation index(EVI);and the SM data obtained from ground stations were used as the expected outputs. We selected the Ningxia Hui Autonomous Region of China as the study area and used selected MERSI-Ⅱ images and in-situ observation station data from 2018 to 2019 to develop our dataset. The results of the SM-DBN were validated by using in-situ SM data as a reference, and its performance was also compared with those of the linear regression(LR) and back propagation(BP) neural network models. The overall accuracy of these models was measured by using the root mean square error(RMSE) of the differences between the model results and in-situ SM observation data. The RMSE of the LR, BP neural network, and SM-DBN models were 0.101, 0.083, and 0.032, respectively. These results suggest that the SM-DBN model significantly outperformed the other two models.

High resolution X-ray spherically bent crystal spectrometer for laser-produced plasma diagnostics

A new high spectral resolution crystal spectrometer is designed to measure very low emissive X-ray spectra of laser-produced plasma in 0.5-0.9 nm range. A large open aperture （30 ×20 （mm）） mica （002） spherically bent crystal with curvature radius R = 380 mm is used as dispersive and focusing element. The imaging plate is employed to obtain high spectral resolution with effective area of 30 × 80 （mm）. The long designed path of the X-ray spectrometer beam is 980 mm from the source to the detector via the crystal. Experiment is carried out at a 20-J laser facility. X-ray spectra in an absolute intensity scale is obtained from Al laserproduced plasmas created by laser energy of 6.78 J. Samples of spectra obtained with spectral resolution of up to E/△E - 1500 are presented. The results clearly show that the device is good to diagnose laser high-density plasmas.

High resolution full-spectrum water Raman lidar

Knowledge of the temporal-spatial distribution of water content in atmosphere and water phase change in cloud is important for atmospheric study. For this purpose, we have developed a high resolution full-spectrum water Raman lidar that can collect Raman signals from ice, water droplets and water vapor simultaneously. A double-grating polychromator and a 32-channel photomultiplier-tube detector are used to obtain a spectral resolution of-0.19 nm in the full Raman spectrum range of water, Preliminary observations present the water Raman spectrum characteristics of both the mixed-phase cloud and humid air under cloudless condition.

The quantitative evaluation of application of hyperspectral data based on multi-parameters joint optimization

In order to evaluate the mineral identification of the hyperspectral data and make a trade-off of the imaging system parameters,a quantitative evaluation approach based on the multi-parameters joint optimization is proposed for the hyperspectral remote sensing.In the proposed approach,the mineral identification is defined as the number of the minerals identified and the key imaging parameters employed include ground sample distance(GSD)and spectral resolution(SR).Certain limitations are found among parameters that are used for analyzing the imaging processes.The constraints include the industrial manufacturing level,application requirements and the quantitative relationship among the GSD,the SR and the signal-to-noise ratio(SNR).Regression analysis is used to investigate the quantitative relationship between the mineral identification and the key imaging system parameters.Then,an optimization model for the trade-off study is established by combining the regression equation with the constraints.The airborne hyperspectral image collected by Hymap is applied to evaluate the performance of the proposed approach.The experimental results reveal that the approach can achieve the evaluation of the mineral identification and the trade-off of key imaging system parameters.The error of the prediction is within one kind of mineral.

Simple aspects of femtosecond stimulated Raman spectroscopy

Femtosecond stimulated Raman spectroscopy （FSRS）, using an overlapping pair of narrow band Raman pump and broadband probe pulses with heterodyne detection along the probe pulse direction, is a new nonlinear spectroscopic technique to record vibrational spectra of even highly fluorescent molecules and to study vibrational dynamics on excited electronic states of molecules, as in photoisomerization. FSRS is described by diagrammatic third-order perturbation theory with wave packet analysis. The phase matching condition gives rise to forty-eight terms for FSRS, but the resonant condition reduces it to just eight terms, which can be depicted by Feynman dual time-line diagrams, or closed time path loop diagrams, or the complementary four-wave mixing energy level diagrams. The eight terms fall into four sets-SRS（I）, SRS（Ⅱ）, IRS（I）, IRS（Ⅱ）-where SRS stands for stimulated Raman scattering and IRS stands for inverse Raman scattering. The SRS（I） set can also account for spontaneous Raman scattering, but the remaining SRS（Ⅱ）, IRS（I） and IRS（Ⅱ） terms are only present in stimulated scattering with the presence of a probe field. The SRS（I） set accounts for the Stokes Raman lines while the IRS（I） term accounts for the anti-Stokes lines, relative to the Raman pump frequency, in the FSRS spectrum. The remaining SRS（Ⅱ） and IRS（Ⅱ） terms give rise to broad baselines. Using a harmonic oscillator model, analytic results are obtained for the four-time correlation functions in the third-order polarizations. The issue of high time and high frequency resolution in time-resolved FSRS spectra is discussed. Calculations are made with the theory to compare with experimental results for： （a） resonance FSRS of fluorescent Rhodamine 6G and （b） 2D-FSRS from a coherent vibrational state that has been prepared by an impulsive, off-resonant pump pulse on CDCl3. The calculated results compared well with experimental results, and in the case of 2D-FSRS on CDCl3 there is a dominant cascade effect contributing to the FSRS spectra.

Upgrade of beamline 3W1B at Beijing Synchrotron Radiation Facility

To improve the performance of Beamline 3WIB at the Beijing Synchrotron Radiation Facility for the soft X-ray magnetic linear dichroism research at transition metals L2,3 edges, a new monochromator was designed and built to replace the original one. After the assemblage, alignment and adjustment of the monochromator system, the first commissioning results were obtained. The photon energy range is from 50 to 1000 eV with spectral resolutions of 1600 at 250 eV and 1000 at 870 eV. The photon flux is of the order of 10s-109 photons/s/200 mA/0.1%BW. In the electron＇s orbital plane the linear polarization degree of the light is higher than 99% at 704 eV. The beamline has satisfied the basic experimental requirements.

Stability evaluation of the PROSPECT model for leaf chlorophyll content retrieval

The radiative transfer model,PROSPECT,has been widely applied for retrieving leaf biochemical traits.However,little work has been conducted to evaluate the stability of the PROSPECT model with consideration of multiple factors(i.e.,spectral resolution,signal-to-noise ratio,plant growth stages,and treatments).This study aims to investigate the stability of the PROSPECT model for retrieving leaf chlorophyll(Chl)content(Cab).Leaf hemispherical reflectance and transmittance of oilseed rape were acquired at different spectral resolutions,noise levels,growth stages,and nitrogen treatments.The Chl content was also measured destructively by using a microplate spectrophotometer.The performance of the PROSPECT model was compared with a commonly used random forest(RF)model.The results showed that the prediction accuracy of PROSPECT and RF models for Cab did not produce significant differences under varied spectral resolutions ranging from 1 to 20 nm.The ranges of the relative root mean square errors(rRMSE)of the PROSPECT and RF models were 12%-13%and 11.70%-12.86%,respectively.However,the performance of both models for leaf Chl retrieval was strongly influenced by the noise level with the rRMSE of 13-15.37%and 12.04%-15.80%for PROSPECT and RF,respectively.For different growth stages,the PROSPECT model had similar prediction accuracies(rRMSE=9.26%-12.41%)to the RF model(rRMSE=9.17%-12.70%).Furthermore,the superiority of the PROSPECT model(rRMSE=10.10%-12.82%)over the RF model(rRMSE=11.81%-15.47%)was prominently observed when tested with plants growth at different nitrogen treatment levels.The results demonstrated that the PROSPECT model has a more stable performance than the RF model for all datasets in this study.

Alignment of the photoelectron spectroscopy beamline at NSRL

Tile photoelectron spectroscopy beamline at National Synchrotron Radiation Laboratory （NSRL） is equipped with a spherical grating monochromator with the included angle of 174. Three gratings with line density of 200, 700 and 1200 lines/mm are used to cover the energy region from 60 eV to 1000 eV. After several years＇ operation, the spectral resolution and flux throughput were deteriorated, and realignment was necessary to improve the performance. First, the wavelength scanning mechanism, the optical components position and the exit slit guide direction are aligned according to tile design value. Second, the gratings are checked by Atomic Force Microscopy （AFM） and then the gas absorption spectrum is measured to optimize the focusing condition of the monoehromator. The spectral resolving power E/AE is recovered to the designed value of 1000@244 eV. The flux at the end station for the 200 lines/ram grating is about 1010 photons/sec/200 mA, which is in accordance with the design. The photon flux for the 700 lines/mm grating is about 5 108 photons/sec/200mA, which is lower than expected. This poor flux throughput may be caused by carbon contamination on the optical components. The 1200 lines/ram grating has roughness much higher than expected so the diffraction efficiency is too low to detect any signal. A new grating would be ordered. After the alignment, the beamline has significant performance improvements in both the resolving power aim the flux throughput for 200 and 700 lines/ram gratings and is provided to users.

Rapid discovery and identification of 68 compounds in the active fraction from Xiao-Xu-Ming decoction(XXMD) by HPLC-HRMS and MTSF technique

Xiao-Xu-Ming decoction（XXMD） was a traditional Chinese prescription and first recorded in ＂Bei Ji Qian Jin Yao Fang＂.It has been widely used to treat theoplegia and the sequel of theoplegia in China.In the present work,high-performance liquid chromatography coupled with high resolution mass spectrometry（HPLC-HRMS） combined with the mass spectral tree similarity filter technique（MTSF）was used to rapidly discover and identify the compounds of the active fraction of XXMD.A total of 3362 compounds were automatically detected by HPLC-HRMS,and final 68 compounds were identified in the active fraction of XXMD.including 14 templated compounds（reference compounds）,50 related compounds fished by MTSF technique,and 4 unrelated compounds identified by manual method.This study successfully applied MTSF technology for the first time to discover and identify the components of Chinese prescription.The results demonstrated that MTSF technique should be useful to the discovery and identification of compounds in Chinese prescription.This study also proved that MTSF can be applied to the targeted phytochemical separation.