Spectral Calibration Research Articles

Evaluating NIRS for predicting faecal fibre, protein fractions and digestibility in dairy sheep and goats fed alfalfa hay and concentrate

This study evaluated the effectiveness of near-infrared spectroscopy (NIRS) in predicting faecal fibre, protein fractions and total tract apparent digestibility in dairy sheep and goats fed varying ratios of alfalfa-hay and concentrate. A total of 180 faecal samples from dairy sheep and goats were collected and chemically analysed. Faecal samples underwent also NIRS spectral acquisition and calibration models were obtained through modified partial least square regression and tested for robustness. The NIRS provided excellent estimations for N and CP as % as is (R 2 ExV 0.91 and 0.91, RPD 3.16 and 3.33, respectively), good estimation for N, CP and ND soluble CP % DM (R 2 ExV 0.90, 0.90 and 0.85, RPD 3.14, 2.90 and 2.48) and ND soluble CP expressed as % as is (R 2 ExV 0.87, RPD 2.55), approximative quantitative prediction for acid detergent insoluble crude protein (ADICP) and ADIN % acid detergent fibre (ADF) (R 2 ExV 0.79 and 0.71, RPD 1.93 and 1.78, respectively) and ADICP as % as is (R 2 ExV 0.67, RPD 1.70) but resulted to be less effective when predicting all the other components. The prediction models for total-tract digestibility (ttD) of ADICP performed best among the developed equations (R 2 ExV 0.57, RPD 1.38), but the model was not sufficient for precise predictions, suggesting a good capacity of NIRS to predict faecal N excretion but also intrinsic limitations of faecal spectra due to the partial residual nutrients content, compared to the diet. Increasing the number of calibration samples and values, the forage species, and the F:C ratios in the diet offered to the animals could improve the NIRS performance.

On-orbit spectral characteristics analysis of the greenhouse gases monitoring instrument: Spectral wavelength stability and instrumental line shape stability

The Greenhouse Gases Monitoring Instrument (GMI) is a carbon satellite payload developed based on the principle of spatial heterodyne spectroscopy technology, which is specifically designed for the global analysis of greenhouse gases (CO2 and CH4) “sources” and “sinks”. Due to the low concentration and minimal gradient variations of CO2 and CH4 in the atmosphere, higher precision is required for their retrieval. Vibrations during satellite launch and harsh space environments during on-orbit operation may cause changes in the performance of various payload components, resulting in decreased quality of spectrum products and retrieval precision. This paper proposes a set of on-orbit spectral characteristic evaluation methods tailored for the GMI to monitor the quality of its spectrum. It also develops an adaptive blind pixel detection and correction algorithm specifically for the GMI and optimizes the interferogram processing flow algorithm. On-orbit spectral calibration is performed, and methods to evaluate spectral characteristic parameters have been established. The analysis focuses on the variations of the spectral characteristics in the CO2-1 bands (1.575 μm) of the GMI during one-year of on-orbit calibration spectrum. The initial spectral wavenumber offset is 0.133 cm−1 after entering orbit, and the average spectral wavenumber offset is 0.0313 cm−1 during stable operation. During the one-year period, the maximum variation in the instrumental line shape function of the GMI is 0.006 cm−1. The observed spectrum obtained in nadir observation mode, underwent to accuracy verification. The results demonstrate consistency between the spectral peak wavenumbers and the relative trend changes of the observed and theoretical spectrum, with an average relative residual of 0.987%.

Spectral Background Calibration of Scanning Habitable Environments with Raman and Luminescence for Organics and Chemicals (SHERLOC) Spectrometer Onboard the Perseverance Rover Enables Identification of a Ubiquitous Martian Spectral Component.

The Perseverance rover landed at Jezero crater, Mars, on 18 February 2021, with a payload of scientific instruments to examine Mars' past habitability, look for signs of past life, and process samples for future return to Earth. The instrument payload includes the Scanning Habitable Environments with Raman and Luminescence for Organics and Chemicals (SHERLOC) deep ultraviolet Raman and fluorescence imaging spectrometer designed to detect, characterize, and map the presence of organics and minerals on the Martian surface. Operation and engineering constraints sometimes result in the acquisition of spectra with features near the detection limit. It is therefore important to separate instrumental (background) spectral components and spectral components inherent to Martian surface materials. For SHERLOC, the instrumental background is assessed by collecting spectra in the stowed-arm configuration where the instrument is pointed at the Martian nighttime sky with no surface sample present in its optical path. These measurements reveal weak Raman and fluorescence background spectral signatures as well as charged-coupled device pixels prone to erroneous intensity spikes separate from cosmic rays. We quantitatively describe these features and provide a subtraction procedure to remove the spectral background from surface spectra. By identifying and accounting for the SHERLOC Raman background features within the median Raman spectra of Martian target scans, we find that the undefined silicate spectral feature interpreted to be either amorphous silicate or plagioclase feldspar is ubiquitously found in every Mars target Raman scan collected through Sol 751.

Current Progress of EUV Spectral Responsivity Calibration for EUV Lithography at CMS/ITRI

Abstract To support the development of advanced EUV lithography for the semiconductor industry in Taiwan, a calibration system for photodiodes’ spectral responsivity was established. The current system utilizes the synchrotron radiation light source and the method is traceable to PTB, Germany. The wavelength range is from 10 nm to 15 nm, including the most often used 13.5 nm. Several techniques were studied to compensate for light source fluctuation and to reduce the measurement uncertainty. The relative expanded uncertainty of the spectral responsivity calibration at 13.5 nm is 4.6 % (k=2). A wafer-type EUV radiant power meter designed to be used in EUV lithography chambers is being developed. Our goal is to develop simple and reliable methods for on-site EUV optical power measurement and dose estimation.

New Mie Scattering Diffuse Targets Development and Characterization

Abstract Earth science remote sensing observations require the detection and measurement of light originating from bright targets, such as clouds, and darker targets, such as an open ocean. This requirement drives the need to design, develop, and characterize improved calibration targets in support of current and future NASA instruments. New diffuse targets to be used as spectral albedo calibration standards were developed and characterized. The new targets based on fused silica or/and pressed and sintered Polytetrafluoroethylene (PTFE) were developed to be Earth scene specific. The various reflectance levels are achieved by modifying the material parameters, thickness, and surface finish. The new targets were characterized in cleanroom environment. We acquired high accuracy reflectance and transmittance data using a precision optical scatterometer and spectrophotometer located in the NASA Goddard Space Flight Center (GSFC) Diffuser Calibration Lab. The Total hemispherical reflectance (THR) and Bidirectional Reflectance Distribution Function (BRDF) were measured over the range of solar incident and scattered elevation and azimuthal angles typically realized on orbit by remote sensing instruments. We intend to space certify the new calibration targets after concluding on-orbit testing on the International Space Stations (ISS) scheduled for the second half of 2023.

Novel multi-function setup comprising ultra-bright uniform source for spectral and radiometric calibrations of digital imaging sensors and multiple spectrometric applications

Abstract A new setup is being developed for calibrating CCD/CMOS sensors and cameras, and measuring spectrophotometric quantities in both point-wise and imaging modes. The setup includes a laser-driven light source (LDLS), double-grating monochromator, and an integrating sphere with specific design for two-dimensional (2D) spectrophotometric measurements of complex samples and spectral responsivity calibration of digital imaging sensors and cameras in the visible to near infrared (VIS-NIR) region. The setup can cover a spectral range from 250 nm to 2000 nm with relatively high radiance. The study presents optimization and validation work in the visible through NIR spectral range, up to 1000 nm. Preliminary experiments suggest improved accuracy and lower uncertainties for better metrological performance and sophisticated applications. The developed instrument promises a variety of novel applications while suppressing systematic errors and inaccuracies. The presented measurements results include the validation of 2D spectral reflectance/transmittance measurements in the 360-1000 nm spectral region using selected homogenous standards. Additionally provided are the findings of demonstration measurements for 2D spectral transmittance and the CCD camera’s spectral responsivity within the same spectral range.

Calibration of MAJIS (Moons and Jupiter Imaging Spectrometer): V. Validation with mineral samples and reference materials.

MAJIS (Moons and Jupiter Imaging Spectrometer) is the imaging spectrometer onboard ESA's JUICE (JUpiter and ICy Moons Explorer) spacecraft that operates in the visible and near/mid-infrared between 0.5 and 5.54μm. Before the launch of JUICE in April 2023, MAJIS underwent a comprehensive on-ground calibration campaign in between August and September 2021 in the IAS (Institut d'Astrophysique Spatiale, Université Paris-Saclay) calibration facilities. Among all the operations, calibration sequences using a set of natural mineral samples and synthetic reference materials were acquired in order to characterize MAJIS performances under conditions assumed to be close to certain future observation configurations. Here, we analyze these calibration measurements using comparison with laboratory reference spectra to quantify MAJIS spectral and spatial performances while observing these solid surfaces. We first assess the MAJIS absolute spectral calibration of the visible and near-infrared channel covering half of the wavelength range. We then quantify spectral performances in terms of global spectral slopes, band detection, band shape, and depth retrievals, over most of the spectral range using six mineral samples. We conclude that for most configurations, the MAJIS instrument demonstrates excellent spectral performances compliant with the requirements. MAJIS can, however, be affected by stray light contributions, notably for wavelengths lower than about 1.2μm, and some performances of the instrument may then be significantly impacted depending on viewing conditions. In particular, we have identified cases of spectral contrast reduction up to 40%, absolute spectral shifts up to 2-3nm, and spectral smile variability by +/1nm. Finally, we used the MAJIS internal scanning mirror to test its ability to construct hyperspectral images of a few samples: we present the first band depth maps derived with MAJIS while observing a serpentine/carbonate sample, as well as an evaluation of MAJIS spatial point spread function. Overall, the analysis of MAJIS behavior while observing samples confirms most MAJIS expected performance requirements, while revealing subtle spectral perturbations that may be related to stray light and viewing conditions. These differences will be further investigated in-flight during the cruise, with a solar reflected target such as the Moon, as well as Jupiter before the JUICE orbital insertion.

Quantitative analysis of spectral properties and composition of primitive achondrites (acapulcoites, lodranites and winonaites)

The establishment of robust meteorite-asteroid links has been a major focus of planetary exploration, and a major driver of asteroid sample return missions. Reflectance spectroscopy has been shown to be a powerful tool for this purpose. For the meteorites dominated by silicate minerals, quantitative analysis of spectral absorption features caused by the Fe2+-bearing minerals (mainly olivine and pyroxene) is a common method to determine mafic silicate mineralogy and end member abundances, and establish the relationship between them and possible parent bodies. In this study, the reflectance spectra of 22 primitive achondrites (acapulcoites, lodranites and winonaites) from NASA RELAB database were analyzed to determine their positions in the plot of the band area ratio (BAR) and 1 μm band center (Band I center). We found that Band I center and BAR of acapulcoites and lodranites are in roughly the same range. Acapulcoite-lodranite partially overlap with the field of H chondrites in the plot of the BAR and Band I center. This overlap means that spectral calibrations (also referred to as mineralogical formulas) based on the two types of meteorites needs to be applied with caution. The 2 μm band center of acapulcoite–lodranite is significantly lower than that of H chondrites, which is consistent with the conclusion of previous studies and provides a means to separate these two groups. In addition, the choice of spectral parameter analysis techniques may be a potential error source in similar studies. We provide generalized spectral fields of primitive achondrites in the plot of the BAR and Band I center derived from two widely used technologies.

Ratiometric surface-enhanced Raman spectroscopy detection of 5-hydroxyindole-3-acetic acid based on Au@MIL-125@MIPs substrates

5-Hydroxyindole-3-acetic acid (5-HIAA) is a molecular marker that can be used in the early diagnosis of carcinoid tumors, and the development of sophisticated 5-HIAA assays is therefore of great importance. Surface-enhanced Raman spectroscopy (SERS) has been widely used for the rapid and sensitive detection of disease biomarkers. Insufficient specificity for tumor markers and poor spectral reproducibility are the bottlenecks in the practical use of SERS technology. In this study, based on MIL-125 surface-loaded gold nanoparticles (Au@MIL-125), a novel strategy was proposed to obtain Au@MIL-125@molecularly imprinted polymers (MIPs) as functional SERS substrates by wrapping a thin MIP shell around the Au@MIL-125 surface for selective separation followed by a 5-HIAA assay. The Raman peak intensity ratio (I865/I1078) was used to quantify 5-HIAA after a SERS spectral calibration with an embedded internal standard (i.e., 4-aminobenzenethiol) to improve the quantitative accuracy. The linear range was from 10−11 to 10−7 M, and the limit of detection (LOD) was 5.45 × 10−13 M. The method of integrating the MIPs with the metal MOF-based nanocomposites was shown to be useful in the analysis of real samples using SERS. The application of SERS for the selective and quantitative detection of analytes in real sample analysis, therefore, has great potential.

Local Modeling by Adapting Source Calibration Models to Analyte Shifted Target Domain Samples Without Reference Values.

Spectral multivariate calibration aims to derive models characterizing mathematical relationships between sample analyte amounts and corresponding spectral responses. These models are effective at predicting target domain sample analyte amounts when target samples are within the analyte and spectral calibration source domain. Models fail when target samples shift (analyte amounts and/or spectra) from the original calibration domain model. A total recalibration solution requires acquisition of new sample reference values and spectra. However, obtaining enough reference values to distinguish the target domain may be challenging or expensive. A simpler approach adapts the original model to the target domain using target sample spectra without analyte reference values (unlabeled). Analytical chemists have developed several machine learning algorithms using unlabeled regression domain adaptation processes. Unfortunately, prediction accuracy declines for these methods depending on how much the target domain analyte distribution has shifted from the calibration distribution, and regression transfer learning methods are instead needed. Regression domain adaptation and transfer learning are often referred to as model updating in analytical chemistry, but regression domain adaptation only applies to spectral shifts. The regression transfer learning method presented in this paper named null augmentation regression constant analyte (NARCA) leverages unlabeled repeat spectra of a single target sample to update an original calibration model to the shifted target domain sample. With sample repeat spectra, the analyte amount can be assumed constant or nearly constant for NARCA and because models are formed for one sample, NARCA operates as a local modeling method. The performance of NARCA as a regression transfer learning method is evaluated using five near-infrared data sets.

A bidirectional domain separation adversarial network based transfer learning method for near-infrared spectra

Traditional calibration transfer (CT) methods usually fail to adapt the source domain model to the target domain because of changes associated with the instrument, detection environment, sample composition, or sample type. Most deep transfer learning (DTL) methods have shown reliable capability in extracting domain-invariant representations. However, factors unique to the spectral domain limit their development and application, including difficulty in obtaining labeled samples, numerous spectral perturbation factors, and the scarcity of spectral databases. To address these challenges, we here introduce the Bidirectional Domain-Separating Adversarial Network (BiDSAN), based on a deep adversarial network transfer architecture, for learning and adapting to distribution/domain differences between sample spectra. BiDSAN incorporates Wasserstein divergence (w-div) and dynamic adversarial factor into the domain critic (discriminator) to accelerate the extraction of spectral shared components. Additionally, the use of the spectral signal distortion ratio as a loss function and the introduction of a bidirectional mechanism further enhanced the training accuracy and speed of spectral models. Calibration analyses were tested on pharmaceutical and two sets of wood datasets, corresponding to three common domain/distribution difference scenarios discussed in the study. Compared to existing CT and DTL methods, the proposed BiDSAN method demonstrated superior spectral signal calibration capability and stability, achieving unsupervised domain adaptation for similar samples and, for the first time, obtaining ideal prediction results in cross-species spectral domain adaptation. Our method represents significant potential for using DTL approaches in spectral domain adaptation.

Comment on Yu et al. Land Surface Temperature Retrieval from Landsat 8 TIRS—Comparison between Radiative Transfer Equation-Based Method, Split Window Algorithm and Single Channel Method. Remote Sens. 2014, 6, 9829–9852

Accurate land surface temperature (LST) retrieval from satellite data is pivotal in environmental monitoring and scientific research. This study addresses the impact of variability in the effective wavelengths used for LST retrieval from the Thermal Infrared Sensor (TIRS) data of Landsat 8. We conduct a detailed analysis comparing the effective wavelengths reported by Yu et al. (2014) and those derived from data provided by the USGS. Our analysis reveals significant variability in the effective wavelengths for bands 10 and 11 of Landsat 8. By applying Planck’s Law and utilizing the K1 and K2 coefficients available in the metadata of Landsat 8 products, we derive the effective wavelengths for bands 10 and 11. We also rederive the effective wavelength by integrating the spectral response function of the TIRS1 sensor. Our findings indicate that the effective wavelength for band 10 is 10.814 μm, aligning with the USGS data, while the effective wavelength for band 11 is 12.013 μm. We discuss the implications of these corrected effective wavelengths on the accuracy of LST retrieval algorithms, particularly the single channel algorithm (SC) and the radiative transfer equation (RT) employed by Yu et al. The importance of using precise effective wavelengths in satellite-based temperature retrieval is emphasized, to ensure the reliability and consistency of results. This analysis underscores the critical role of accurate spectral calibration parameters in remote sensing studies and provides valuable insights in the field of land surface temperature retrieval from Landsat 8 TIRS data.

Handheld In Situ Methods for Soil Organic Carbon Assessment

Soil organic carbon (SOC) assessment is crucial for evaluating soil health and supporting carbon sequestration efforts. Traditional methods like wet digestion and dry combustion are time-consuming and labor-intensive, necessitating the development of non-destructive, cost-efficient, and real-time in situ measurements. This review focuses on handheld in situ methodologies for SOC estimation, underscoring their practicality and reasonable accuracy. Spectroscopic techniques, like visible and near-infrared, mid-infrared, laser-induced breakdown spectroscopy, and inelastic neutron scattering each offer unique advantages. Preprocessing techniques, such as external parameter orthogonalization and standard normal variate, are employed to eliminate soil moisture content and particle size effects on SOC estimation. Calibration methods, like partial least squares regression and support vector machine, establish relationships between spectral reflectance, soil properties, and SOC. Among the 32 studies selected in this review, 14 exhibited a coefficient of determination (R2) of 0.80 or higher, indicating the potential for accurate SOC content estimation using in situ approaches. Each study meticulously adjusted factors such as spectral range, pretreatment method, and calibration model to improve the accuracy of SOC content, highlighting both the methodological diversity and a continuous pursuit of precision in direct field measurements. Continued research and validation are imperative to ensure accurate in situ SOC assessment across diverse environments. Thus, this review underscores the potential of handheld devices for in situ SOC estimation with good accuracy and leveraging factors that influence its precision. Crucial for optimizing carbon farming, these devices offer real-time soil measurements, empowering land managers to enhance carbon sequestration and promote sustainable land management across diverse agricultural landscapes.

Development of a four-color quasimonochromatic X-ray microscope for laser plasma research.

X-ray multicolor imaging diagnosis obtains the spatial distribution of the imploding core during laser inertial confinement fusion. We propose a four-color quasimonochromatic X-ray microscope based on the Kirkpatrick-Baez microscope configuration, covering the medium-to-high-energy X-ray range. Composed of single-layer film mirrors and periodic multilayer film mirrors, the microscope features high spatial resolution and spectral resolution. Furthermore, zoned coating technology achieves common field-of-view (FOV) imaging at four energy points: 4.51, 6.4, 8.4, and 9.67 keV. When assembled and calibrated in the laboratory, the microscope achieved central FOV spatial resolutions of 3.9, 3.7, 4.0, and 4.1 µm at 4.51, 6.4, 8.04, and 9.67 keV, respectively. Finally, a spectral calibration experiment confirmed spectral selectivity at the four energy points.

Spectral and timing calibration of eXTP-SFA engineering model in 100XF

Spectral and timing calibration of eXTP-SFA engineering model in 100XF

A survey of methane point source emissions from coal mines in Shanxi province of China using AHSI on board Gaofen-5B

Abstract. Satellite-based detection of methane (CH4) point sources is crucial in identifying and mitigating anthropogenic emissions of CH4, a potent greenhouse gas. Previous studies have indicated the presence of CH4 point source emissions from coal mines in Shanxi, China, which is an important source region with large CH4 emissions, but a comprehensive survey has remained elusive. This study aims to conduct a survey of CH4 point sources over Shanxi's coal mines based on observations of the Advanced Hyperspectral Imager (AHSI) on board the Gaofen-5B satellite (GF-5B/AHSI) between 2021 and 2023. The spectral shift in centre wavelength and change in full width at half-maximum (FWHM) from the nominal design values are estimated for all spectral channels, which are used as inputs for retrieving the enhancement of the column-averaged dry-air mole fraction of CH4 (ΔXCH4) using a matched-filter-based algorithm. Our results show that the spectral calibration on GF-5B/AHSI reduced estimation biases of the emission flux rate by up to 5.0 %. We applied the flood-fill algorithm to automatically extract emission plumes from ΔXCH4 maps. We adopted the integrated mass enhancement (IME) model to estimate the emission flux rate values from each CH4 point source. Consequently, we detected CH4 point sources in 32 coal mines with 93 plume events in Shanxi province. The estimated emission flux rate ranges from 761.78 ± 185.00 to 12 729.12 ± 4658.13 kg h−1. Our results show that wind speed is the dominant source of uncertainty contributing about 84.84 % to the total uncertainty in emission flux rate estimation. Interestingly, we found a number of false positive detections due to solar panels that are widely spread in Shanxi. This study also evaluates the accuracy of wind fields in ECMWF ERA5 reanalysis by comparing them with a ground-based meteorological station. We found a large discrepancy, especially in wind direction, suggesting that incorporating local meteorological measurements into the study CH4 point source are important to achieve high accuracy. The study demonstrates that GF-5B/AHSI possesses capabilities for monitoring large CH4 point sources over complex surface characteristics in Shanxi.

Panda-UV Unlocks Deeper Protein Characterization with Internal Fragments in Ultraviolet Photodissociation Mass Spectrometry.

Ultraviolet photodissociation (UVPD) mass spectrometry unlocks insights into the protein structure and sequence through fragmentation patterns. While N- and C-terminal fragments are traditionally relied upon, this work highlights the critical role of internal fragments in achieving near-complete sequencing of protein. Previous limitations of internal fragment utilization, owing to their abundance and potential for random matching, are addressed here with the development of Panda-UV, a novel software tool combining spectral calibration, and Pearson correlation coefficient scoring for confident fragment assignment. Panda-UV showcases its power through comprehensive benchmarks on three model proteins. The inclusion of internal fragments boosts identified fragment numbers by 26% and enhances average protein sequence coverage to a remarkable 93% for intact proteins, unlocking the hidden region of the largest protein carbonic anhydrase II in model proteins. Notably, an average of 65% of internal fragments can be identified in multiple replicates, demonstrating the high confidence of the fragments Panda-UV provided. Finally, the sequence coverages of mAb subunits can be increased up to 86% and the complementary determining regions (CDRs) are nearly completely sequenced in a single experiment. The source codes of Panda-UV are available at https://github.com/PHOENIXcenter/Panda-UV.

Research on automatic spectral calibration algorithm for echelle spectrometer

Echelle spectrometers are highly sensitive to errors due to their high spectral resolution. Spectral drift can easily occur due to changes in the environment and minor disturbances in the instrument. Therefore, it is crucial to perform spectral calibration before operating the instrument. Since traditional calibration techniques demanded a substantial investment of both time and human resources, a rapid automatic spectral calibration method has been improved in this paper. An automated process of spectral calibration is proposed which overcomes the challenges of conventional high-dimensional parameter inversion. The calibration process is significantly accelerated by employing a segmented and polynomial fitting method for model calibration. The results of precise tests conducted using characteristic wavelengths from various element lamps demonstrate that this method achieves a mean spectral accuracy deviation of 0.0096 nm, with a maximum error of 0.024 nm in the long-wave region. These accuracy levels meet the requirements of the echelle spectrometer. Therefore, the proposed strategy offers a more reliable and efficient tool for spectral analysis technology, while notably reducing the time and labor involved in spectral calibration.

Preflight Spectral Calibration of the Ozone Monitoring Suite-Nadir on FengYun 3F Satellite

The Ozone Monitoring Suite-Nadir (OMS-N) instrument is the first hyperspectral remote sensor in the ultraviolet band of China’s Fengyun series satellites. It can be used to detect several kinds of atmospheric constituents. This paper describes the prelaunch spectral calibration of the OMS-N onboard FengYun 3F. Several critical spectral parameters including the spectral resolution, spectral dispersion, and the instrument spectral response function were determined through laser-based measurements. A secondary peak of the instrument spectral response function from the short wavelength side of the ultraviolet band was found, and the possible influence on data applications was analyzed using a reference solar model and radiative transfer model. The results indicate that the spectral resolution and spectral accuracy of OMS-N meet the mission requirements. However, the asymmetries in the instrument spectral response function in the ultraviolet band were found near nadir rows, which are expressed as the “asymmetric central peak” and “secondary peak”. The analysis results show that if the influences of the instrument spectral response function “asymmetric central peak” and “secondary peak” in the ultraviolet band are ignored, they will bring an error as large as 5% at the center of the absorption line.

Research on Automatic Wavelength Calibration of Passive DOAS Observations Based on Sequence Matching Method

Passive differential optical absorption spectroscopy (DOAS) is widely used to monitor the three-dimensional distribution of atmospheric pollutants. However, the observational and retrieval accuracy of this technique is significantly influenced by the precise wavelength calibration of solar spectra. Current calibration methods face challenges in automation when dealing with complex remote-sensing conditions. We introduce a novel automatic wavelength calibration algorithm for passive DOAS based on sequence-matching technology to estimate the spectral parameters of the spectrometer channels, integrating advanced processing measures such as feature structure enhancement and sub-pixel interpolation. These measures significantly reduce the dependency on reference spectrum resolution and accurately correct even minor spectral shifts. We perform sensitivity experiments using synthetic spectra to determine optimal retrieval configurations, followed by field tests at four cities on the Yangtze River Delta, China, to calibrate and compare passive DOAS instruments of various resolutions. Comparative verification in these field studies demonstrated that our algorithm was suitable for rapid spectral calibration within a wider resolution range of 0.03 nm to 0.1 nm with a wavelength inversion error < 0.01 nm. This highlights the applicability and calibration precision of our algorithm.