收稿日期: 2025-08-27
修回日期: 2025-10-21
网络出版日期: 2025-11-01
基金资助
国家自然科学基金项目(42175154);湖南省杰出青年基金项目(2024JJ2058)
Current Status and Progress of the Infrared Hyperspectral Passive Remote Sensing of Atmospheric Aerosol
Received date: 2025-08-27
Revised date: 2025-10-21
Online published: 2025-11-01
Supported by
the National Natural Science Foundation of China(42175154);The Science Foundation of Hunan Province(2024JJ2058)
气溶胶是影响地气系统能量收支及大气环境变化的关键因子之一，其光学参数的高精度反演一直是大气环境遥感领域的研究热点之一。气溶胶光学被动遥感主要利用其在可见光/近红外波段的散射效应，但该方式大多需要借助太阳散射辐射作为辐射源，在夜间和高纬度冬季（极夜）无法适用。红外高光谱遥感技术可解析气溶胶独特的光谱吸收与散射指纹特征，也是实现气溶胶遥感的手段之一，为传统可见光/近红外反演遥感提供了有力补充。系统阐述了红外高光谱反演气溶胶微物理参数的基本原理，重点对物理机理与探测仪器、辐射传输模型和反演算法等方面的关键技术进行综述。尤其是对已有红外高光谱辐射计的关键参数、红外高光谱正向辐射传输模型的特点以及不同类型反演方法的优缺点进行了探讨分析。基于此，进一步展望了未来研究的发展方向，提出应重点发展高精度、高效率的辐射传输正演模型，深度挖掘红外高光谱数据中的丰富信息以改进反演算法，并积极发展多平台协同探测技术。
胡帅 , 赵嘉琦 , 刘磊 , 党蕊君 , 肖瑶 , 何钰龙 . 红外高光谱被动遥感气溶胶研究现状及进展[J]. 地球科学进展, 2025 , 40(11) : 1097 -1111 . DOI: 10.11867/j.issn.1001-8166.2025.098
Aerosols are key factors influencing the energy balance of the Earth-atmosphere system and atmospheric environmental changes. High-precision inversion of their optical parameters has long been a topic of interest in atmospheric environmental remote sensing. Passive remote sensing of aerosol optics primarily utilizes their scattering effects in the visible/near-infrared wavelength bands. However, this approach typically relies on solar scattered radiation as the radiation source, rendering it inapplicable at night and during high-latitude winters (polar nights). Infrared hyperspectral remote sensing technology can resolve the unique spectral absorption and scattering fingerprint characteristics of aerosols, serving as another means to achieve aerosol remote sensing and providing a powerful supplement to traditional visible/near-infrared inversion techniques. This paper systematically elaborates on the fundamental principles of infrared hyperspectral inversion for aerosol microphysical parameters, focusing on key technologies such as physical mechanisms and detection instruments, radiative transfer models, and inversion algorithms. Particular emphasis is placed on discussing the key parameters of existing hyperspectral radiometers, the characteristics of hyperspectral forward radiative transfer models, and the advantages and disadvantages of different inversion methods. Based on this, the paper further outlines future research directions, proposing a focus on developing high-precision, high-efficiency forward radiative transfer models, utilizing the rich information within hyperspectral data to improve inversion algorithms, and actively advancing multi-platform collaborative detection technologies.
| [1] | DIVAKARLA M G， BARNET C D， GOLDBERG M D， et al. Validation of atmospheric infrared sounder temperature and water vapor retrievals with matched radiosonde measurements and forecasts［J］. Journal of Geophysical Research： Atmospheres， 2006， 111（D9）. DOI： 10.1029/2005JD006116 . |
| [2] | JI D H， PALM M， RITTER C， et al. Ground-based remote sensing of aerosol properties using high-resolution infrared emission and lidar observations in the High Arctic［J］. Atmospheric Measurement Techniques， 2023， 16（7）： 1 865-1 879. |
| [3] | MAURITSEN T， SEDLAR J， TJERNSTR?M M， et al. An Arctic CCN-limited cloud-aerosol regime［J］. Atmospheric Chemistry and Physics， 2011， 11（1）： 165-173. |
| [4] | COUMOU D， di CAPUA G， VAVRUS S， et al. The influence of Arctic amplification on mid-latitude summer circulation［J］. Nature Communications， 2018， 9. DOI： 2018EGUGA.2011737C . |
| [5] | SCHMALE J， ZIEGER P， EKMAN A M L. Aerosols in current and future Arctic climate［J］. Nature Climate Change， 2021， 11（2）： 95-105. |
| [6] | HOLBEN B N， ECK T F， SLUTSKER I， et al. AERONET： a federated instrument network and data archive for aerosol characterization［J］. Remote Sensing of Environment， 1998， 66（1）： 1-16. |
| [7] | LI Donghui， LI Zhengqiang， BIAN Liang， et al. Analysis of aerosol properties using ground-based sun-sky radiometer in polar region［J］. Journal of Remote Sensing， 2013， 17（3）： 553-565. |
| 李东辉， 李正强， 卞良， 等. 极地区域气溶胶地基遥感观测及分析［J］. 遥感学报， 2013， 17（3）： 553-565. | |
| [8] | HERBER A， THOMASON L W， GERNANDT H， et al. Continuous day and night aerosol optical depth observations in the Arctic between 1991 and 1999［J］. Journal of Geophysical Research： Atmospheres， 2002， 107（D10）： AAC6-1-AAC6-13. |
| [9] | PéREZ-RAMíREZ D， ACEITUNO J， RUIZ B， et al. Development and calibration of a star photometer to measure the aerosol optical depth： smoke observations at a high mountain site［J］. Atmospheric Environment， 2008， 42（11）： 2 733-2 738. |
| [10] | O’NEILL N T， ECK T F， SMIRNOV A， et al. Spectral discrimination of coarse and fine mode optical depth［J］. Journal of Geophysical Research： Atmospheres， 2003， 108（D17）. DOI： 10.1029/2002JD002975 . |
| [11] | PATADIA F， LEVY R C， MATTOO S. Correcting for trace gas absorption when retrieving aerosol optical depth from satellite observations of reflected shortwave radiation［J］. Atmospheric Measurement Techniques， 2018， 11（6）： 3 205-3 219. |
| [12] | NOTT G J， DUCK T J. Lidar studies of the polar troposphere［J］. Meteorological Applications， 2011， 18（3）： 383-405. |
| [13] | LIU Y， HUANG J H， HUANG F. A comprehensive review on study methods of aerosol optical properties in different dimensions［J］. IEEE Access， 2023， 11： 36 763-36 786. |
| [14] | HUANG Zhongwei， WANG Yongkai， BI Jianrong， et al. An overview of aerosol lidar： progress and prospect［J］. National Remote Sensing Bulletin， 2022， 26（5）： 834-851. |
| 黄忠伟， 王雍恺， 闭建荣， 等. 气溶胶激光雷达的国内外研究进展与展望［J］. 遥感学报， 2022， 26（5）： 834-851. | |
| [15] | JING Y M， DAI G Y， CHEN X C， et al. Assessment of the three-frequency pulse alternation method for simultaneously troposphere wind and aerosol profiling retrieval in a direct detection lidar［J］. Optics Express， 2025， 33（11）： 22 165-22 184. |
| [16] | LV Z K， LIU D， MAO J T， et al. Research on effective radius retrievals of aerosol particles based on dual-wavelength lidar［J］. Remote Sensing， 2025， 17（8）. DOI： 10.3390/rs17081383 . |
| [17] | LIU G Y， LI J， LI J， et al. Estimation of nighttime aerosol optical depths using atmospheric infrared sounder longwave radiances［J］. Geophysical Research Letters， 2024， 51（8）. DOI： 10.1029/2023GL108120 . |
| [18] | MARQUIS J W， DOLINAR E K， GARNIER A， et al. Estimating the impact of assimilating Cirrus cloud-contaminated hyperspectral infrared radiances for numerical weather prediction［J］. Journal of Atmospheric and Oceanic Technology， 2023， 40（3）： 327-340. |
| [19] | KARTHICK M， SHANMUGAM P， HE X Q. Enhanced POLYMER atmospheric correction algorithm for water-leaving radiance retrievals from hyperspectral/multispectral remote sensing data in inland and coastal waters［J］. Optics Express， 2024， 32（5）： 7 659-7 681. |
| [20] | DEGUINE A， CLARISSE L， HERBIN H， et al. Measuring volcanic ash with high-spectral resolution infrared sounders： role of refractive indices［J］. IEEE Geoscience and Remote Sensing Letters， 2023， 20. DOI： 10.1109/LGRS.2023.3261202 . |
| [21] | CHANG H C， CHARALAMPOPOULOS T. Determination of the wavelength dependence of refractive indices offlame soot［J］. Proceedings of the Royal Society of London （Series A）， 1990， 430： 577-591. |
| [22] | PALIK E. Gallium Arsenide （GaAs）［M］// Handbook of optical constants of solids. Amsterdam： Elsevier， 1997： 429-443. |
| [23] | ELDRIDGE J， PALIK E. Sodium Chloride （NaCl） ［M］//Handbook of optical constants of solids. Amsterdam： Elsevier， 1997： 775-793. |
| [24] | SPITZER W G， KLEINMAN D A. Infrared lattice bands of quartz［J］. Physical Review， 1961， 121（5）： 1 324-1 335. |
| [25] | VOLZ F E. Infrared refractive index of atmospheric aerosol substances［J］. Applied Optics， 1972， 11（4）： 755-759. |
| [26] | JACQUINET-HUSSON N， SCOTT N A， CHéDIN A， et al. The 2003 edition of the GEISA/IASI spectroscopic database［J］. Journal of Quantitative Spectroscopy and Radiative Transfer， 2005， 95（4）： 429-467. |
| [27] | ARONSON J R， EMSLIE A G， MISEO E V， et al. Optical constants of monoclinic anisotropic crystals： gypsum［J］. Applied Optics， 1983， 22（24）： 4 093-4 098. |
| [28] | ROUSH T， POLLACK J， ORENBERG J. Derivation of midinfrared （5-25 μm） optical constants of some silicates and palagonite［J］. Icarus， 1991， 94（1）： 191-208. |
| [29] | HESS M， KOEPKE P， SCHULT I. Optical properties of aerosols and clouds： the software package OPAC［J］. Bulletin of the American Meteorological Society， 1998， 79（5）： 831-844. |
| [30] | LUND M C E， GROTHE H， GOLA A A， et al. Optical constants of HNO3/H2O and H2SO4/HNO3/H2O at low temperatures in the infrared region［J］. The Journal of Physical Chemistry A， 2005， 109（32）： 7 166-7 171. |
| [31] | LASKINA O， YOUNG M A， KLEIBER P D， et al. Infrared optical constants of organic aerosols： organic acids and model Humic-Like Substances （HULIS）［J］. Aerosol Science and Technology， 2014， 48（6）： 630-637. |
| [32] | DEGUINE A， PETITPREZ D， CLARISSE L， et al. Complex refractive index of volcanic ash aerosol in the infrared， visible， and ultraviolet［J］. Applied Optics， 2020， 59（4）： 884-895. |
| [33] | LAND J E. Aerosol absorption measurement by a Shack-Hartmann wavefront sensor［J］. Applied Optics， 2023， 62（18）： 4 836-4 847. |
| [34] | HERBIN H， DESCHUTTER L， DEGUINE A， et al. Complex refractive index of crystalline quartz particles from UV to thermal infrared［J］. Aerosol Science and Technology， 2023， 57（3）： 255-265. |
| [35] | CHEHAB M， HERBIN H， DEGUINE A， et al. First complex refractive indices retrieval from FIR to UV： application to kaolinite particles［J］. Aerosol Science and Technology， 2024， 58（5）： 498-511. |
| [36] | YOU S W， UPADHYAY P， KAPOOR T S， et al. Laboratory synthesis and characterization of wildfire-like dark brown carbon aerosols［J］. Aerosol Science and Technology， 2025， 59（12）： 1 553-1 565. |
| [37] | SOKOLIK I N. The spectral radiative signature of wind-blown mineral dust： implications for remote sensing in the thermal IR region［J］. Geophysical Research Letters， 2002， 29（24）. DOI：10.1029/2002GL015910 . |
| [38] | HONG G， YANG P， HUANG H L， et al. Simulation of high-spectral-resolution infrared signature of overlapping Cirrus clouds and mineral dust［J］. Geophysical Research Letters， 2006， 33（4）. DOI： 10.1029/2005GL024381 . |
| [39] | CHUDNOVSKY A， BEN-DOR E， KOSTINSKI A B， et al. Mineral content analysis of atmospheric dust using hyperspectral information from space［J］. Geophysical Research Letters， 2009， 36（15）. DOI： 10.1029/2009GL037922 . |
| [40] | di BIAGIO C， DOUSSIN J F， CAZAUNAU M， et al. Infrared optical signature reveals the source-dependency and along-transport evolution of dust mineralogy as shown by laboratory study［J］. Scientific Reports， 2023， 13. DOI： 10.1038/s41598-023-39336-7 . |
| [41] | CLOUGH S A， SHEPHARD M W， MLAWER E J， et al. Atmospheric radiative transfer modeling： a summary of the AER codes［J］. Journal of Quantitative Spectroscopy and Radiative Transfer， 2005， 91（2）： 233-244. |
| [42] | GORDON I E， ROTHMAN L S， HILL C， et al. The HITRAN2016 molecular spectroscopic database［J］. Journal of Quantitative Spectroscopy & Radiative Transfer， 2017， 203： 3-69. |
| [43] | STAMNES K， TSAY S C， WISCOMBE W， et al. Numerically stable algorithm for discrete-ordinate-method radiative transfer in multiple scattering and emitting layered media［J］. Applied Optics， 1988， 27（12）： 2 502-2 509. |
| [44] | TURNER D D. Arctic mixed-phase cloud properties from AERI lidar observations［J］. Journal of Applied Meteorology （1988-2005）， 2005， 44（4）： 427-444. |
| [45] | HANSELL R A， LIOU K N， OU S C， et al. Remote sensing of mineral dust aerosol using AERI during the UAE2： a modeling and sensitivity study［J］. Journal of Geophysical Research： Atmospheres， 2008， 113（D18）. DOI： 10.1029/2008JD010246 . |
| [46] | HANSELL R A. Ground and satellite-based remote sensing of mineral dust using AERI Spectra and MODIS thermal infrared window brightness temperature ［D］. Los Angles： University of California， 2008. |
| [47] | BERK A， ANDERSON G P， ACHARYA P K， et al. MODTRAN5： a reformulated atmospheric band model with auxiliary species and practical multiple scattering options［C］// Multispectral and hyperspectral remote sensing instruments and applications II. Honolulu， USA： SPIE， 2005： 13. |
| [48] | WANG Qi， LIU Lei， GAO Taichang， et al. A study on the computational model for high spectral infrared sounder by Fourier transform technique and its influence factors［J］. Spectroscopy and Spectral Analysis， 2019， 39（6）： 1 711-1 716. |
| 王琦， 刘磊， 高太长， 等. 基于ARTS的傅里叶红外高光谱计算模型研究及其影响因素分析［J］. 光谱学与光谱分析， 2019， 39（6）： 1 711-1 716. | |
| [49] | LEVONI C， CERVINO M， GUZZI R， et al. Atmospheric aerosol optical properties： a database of radiative characteristics for different components and classes［J］. Applied Optics， 1997， 36（30）： 8 031-8 041. |
| [50] | LIU C， XU X F， YIN Y， et al. Black carbon aggregates： a database for optical properties［J］. Journal of Quantitative Spectroscopy and Radiative Transfer， 2019， 222/223： 170-179. |
| [51] | SAITO M， YANG P， DING J C， et al. A comprehensive database of the optical properties of irregular aerosol particles for radiative transfer simulations［J］. Journal of the Atmospheric Sciences， 2021， 78（7）： 2 089-2 111. |
| [52] | MENG Z K， YANG P， KATTAWAR G W， et al. Single-scattering properties of tri-axial ellipsoidal mineral dust aerosols： a database for application to radiative transfer calculations［J］. Journal of Aerosol Science， 2010， 41（5）： 501-512. |
| [53] | WANG X， BI L， HAN W， et al. Single-scattering properties of encapsulated fractal black carbon particles computed using the invariant imbedding T-matrix method and deep learning approaches［J］. Journal of Geophysical Research： Atmospheres， 2023， 128（21）. DOI： 10.1029/2023JD039568 . |
| [54] | ZHANG Y H， SAITO M， YANG P， et al. Sensitivities of spectral optical properties of dust aerosols to their mineralogical and microphysical properties［J］. Journal of Geophysical Research： Atmospheres， 2024， 129（10）. DOI： 10.1029/2023JD040181 . |
| [55] | MARTIKAINEN J， MU?OZ O， GóMEZ M J C， et al. Database of Martian dust optical properties in the UV-vis-NIR［J］. Monthly Notices of the Royal Astronomical Society， 2025， 537（2）： 1 489-1 503. |
| [56] | PADILLA R， ADAME J A， HIDALGO P J， et al. Ground-based and AIRS carbon monoxide behavior at El Arenosillo observatory （southwestern Europe）［J］. Atmospheric Environment， 2023， 310. DOI： 10.1016/j.atmosenv.2023.119962 . |
| [57] | WANG W， LIU C， CLARISSE L， et al. Ground-based measurements of atmospheric NH3 by Fourier transform infrared spectrometry at Hefei and comparisons with IASI data［J］. Atmospheric Environment， 2022， 287. DOI： 10.1016/j.atmosenv.2022.119256 . |
| [58] | ZHANG Q， SHAO M. Assimilation of FY-3D and FY-3E hyperspectral infrared atmospheric sounding observation and its impact on numerical weather prediction during spring season over the continental United States［J］. Atmosphere， 2023， 14（6）. DOI： 10.3390/atmos14060967 . |
| [59] | LIAO Yi， GUAN Li. Spectrum accuracy evaluation of FY-3E hyperspectral infrared atmospheric sounder［J］. Progress in Geophysics， 2023， 38（3）： 977-986. |
| 廖翼， 官莉. FY-3E红外高光谱大气探测仪光谱资料精度评估［J］. 地球物理学进展， 2023， 38（3）： 977-986. | |
| [60] | ZENG Z C， LEE L， QI C L. Diurnal carbon monoxide observed from a geostationary infrared hyperspectral sounder： first result from GIIRS on board FengYun-4B［J］. Atmospheric Measurement Techniques， 2023， 16（12）： 3 059-3 083. |
| [61] | CONIGLIO M C， ROMINE G S， TURNER D D， et al. Impacts of targeted AERI and Doppler lidar wind retrievals on short-term forecasts of the initiation and early evolution of thunderstorms［J］. Monthly Weather Review， 2019， 147（4）： 1 149-1 170. |
| [62] | PIERANGELO C， CHéDIN A， HEILLIETTE S， et al. Dust altitude and infrared optical depth from AIRS［J］. Atmospheric Chemistry and Physics， 2004， 4（7）： 1 813-1 822. |
| [63] | PIERANGELO C， MISHCHENKO M， BALKANSKI Y， et al. Retrieving the effective radius of Saharan dust coarse mode from AIRS［J］. Geophysical Research Letters， 2005， 32（20）. DOI： 10.1029/2005GL023425 . |
| [64] | PEYRIDIEU S， CHéDIN A， TANRé D， et al. Saharan dust infrared optical depth and altitude retrieved from AIRS： a focus over North Atlantic-comparison to MODIS and CALIPSO［J］. Atmospheric Chemistry and Physics Discussions， 2009， 9（5）： 21 199-21 235. |
| [65] | PEYRIDIEU S， CHéDIN A， CAPELLE V， et al. Characterisation of dust aerosols in the infrared from IASI and comparison with PARASOL， MODIS， MISR， CALIOP， and AERONET observations［J］. Atmospheric Chemistry and Physics， 2013， 13（12）： 6 065-6 082. |
| [66] | TURNER D D. Ground-based infrared retrievals of optical depth， effective radius， and composition of airborne mineral dust above the Sahel［J］. Journal of Geophysical Research： Atmospheres， 2008， 113（D13）. DOI： 10.1029/2008JD010054 . |
| [67] | DESOUZA-MACHADO S G， STROW L L， IMBIRIBA B， et al. Infrared retrievals of dust using AIRS： comparisons of optical depths and heights derived for a North African dust storm to other collocated EOS A-Train and surface observations［J］. Journal of Geophysical Research： Atmospheres， 2010， 115（D15）. DOI： 10.1029/2009JD012842 . |
| [68] | XU H， CHENG T H， GU X F， et al. New Asia dust storm detection method based on the thermal infrared spectral signature［J］. Remote Sensing， 2015， 7（1）： 51-71. |
| [69] | YAO Z G， LI J， HAN H J， et al. Asian dust height and infrared optical depth retrievals over land from hyperspectral longwave infrared radiances［J］. Journal of Geophysical Research： Atmospheres， 2012， 117（D19）. DOI： 10.1029/2012JD017799 . |
| [70] | KLüSER L， MARTYNENKO D， HOLZER-POPP T. Thermal infrared remote sensing of mineral dust over land and ocean： a spectral SVD based retrieval approach for IASI［J］. Atmospheric Measurement Techniques， 2011， 4（5）： 757-773. |
| [71] | CALLEWAERT S， VANDENBUSSCHE S， KUMPS N， et al. The Mineral Aerosol Profiling from Infrared Radiances （MAPIR） algorithm： version 4.1 description and evaluation［J］. Atmospheric Measurement Techniques， 2019， 12（7）： 3 673-3 698. |
| [72] | CLARISSE L， COHEUR P F， PRATA F， et al. A unified approach to infrared aerosol remote sensing and type specification［J］. Atmospheric Chemistry and Physics， 2013， 13（4）： 2 195-2 221. |
| [73] | VENTRESS L J， MCGARRAGH G， CARBONI E， et al. Retrieval of ash properties from IASI measurements［J］. Atmospheric Measurement Techniques， 2016， 9（11）： 5 407-5 422. |
| [74] | ZHOU M， WANG J， CHEN X， et al. First lunar-light mapping of nighttime dust season oceanic aerosol optical depth over North Atlantic from space［J］. Remote Sensing of Environment， 2024， 312. DOI： 10.1016/j.rse.2024.114315 . |
| [75] | YAN X， SHI W Z， ZHAO W J， et al. Mapping dustfall distribution in urban areas using remote sensing and ground spectral data［J］. Science of the Total Environment， 2015， 506/507： 604-612. |
| [76] | CLARISSE L， CLERBAUX C， FRANCO B， et al. A decadal data set of global atmospheric dust retrieved from IASI satellite measurements［J］. Journal of Geophysical Research： Atmospheres， 2019， 124（3）： 1 618-1 647. |
| [77] | WANG D W， SHEN Z X， ZHANG Q， et al. Winter brown carbon over six of China’s megacities： light absorption， molecular characterization， and improved source apportionment revealed by multilayer perceptron neural network［J］. Atmospheric Chemistry and Physics， 2022， 22（22）： 14 893-14 904. |
/
| 〈 |
|
〉 |
甘公网安备62010202000687
