浏览全部资源
扫码关注微信
Received：18 April 2018，
Accepted：23 May 2018，
Published：2019-05
移动端阅览
大气气溶胶成分的复杂变化导致其在气候变化评估中具有很高的不确定性。气溶胶成分遥感利用遥感观测的气溶胶光学—微物理参数，定量估计整层大气气溶胶主要成分含量，具有实时快速、空间覆盖、保持气溶胶自然状态等特点。本文介绍了近年来气溶胶成分遥感在理论基础和观测研究方面的进展情况。首先，在简要回顾反演算法发展的基础上，以目前较先进的成分遥感分类模型(包括黑碳、棕色碳、沙尘、非吸光有机物、细粒子无机盐、海盐和水)为例，详细分析了气溶胶成分遥感反演的思路。据此提出了基于气溶胶综合光学—微物理特性(包括光学吸收/散射、粒径尺度、形状等敏感性特征参数)的气溶胶成分遥感识别方法。之后，结合气溶胶混合方式，讨论了复折射指数计算方法及其对成分反演的影响，并给出了利用同步化学采样观测验证气溶胶成分遥感的一些结果示例。最后，结合观测手段拓展、成分模型优化、反演精度提升、应用能力推广等4个方向，展望了大气气溶胶成分遥感的发展趋势，及其在全球气候变化评估等领域的应用。
Complex and drastic variations of atmospheric aerosol components lead to high uncertainties in climate change assessment. The remote sensing of aerosol composition is the technology often used in aerosol optical and microphysical parametric analysis. These parameters
which are derived from remote sensing measurements
can quantitatively estimate the aerosol components of the entire atmosphere. Remote sensing offers the advantages of real-time and fast detection
spatial coverage
and maintenance of natural aerosol status. This paper presents a comprehensive review of theories
observations
models
and algorithms for aerosol composition remote sensing. First
in the area of algorithm development
we analyze the main ideas and methods for establishing aerosol composition models. In particular
an advanced remote sensing categorization model
which includes black carbon
brown carbon
mineral dust
light-scattering organic matter
inorganic salts
sea salt
and water
is presented in detail. The methods are identified or distinguished according to components (i.e.
sensitivity parameters
including light absorption
size distribution
particulate shape
etc.). Second
for the calculation of the refractive index
some of the typical methods suitable for different aerosol mixing states are compared
and then their impacts on composition retrieval are determined. Third
some examples of remotely sensed aerosol components are given
and a preliminary validation of the retrievals is conducted by using synchronized chemical measurements. Finally
the development tendencies of the remote sensing of atmospheric aerosol composition are summarized from the perspectives of observation capability enhancement
optimization of the categorization model
improvements in retrieval accuracy
extension of application abilities
and identification of utilization prospects in global climate change assessment.
Andreae M O and Gelencsér A. 2006. Black carbon or brown carbon? The nature of light-absorbing carbonaceous aerosols. Atmospheric Chemistry and Physics, 6(10): 3131–3148
Arola A, Schuster G, Myhre G, Kazadzis S, Dey S and Tripathi S N. 2011. Inferring absorbing organic carbon content from AERONET data. Atmospheric Chemistry and Physics, 11(1): 215–225
Bohren C F and Huffman D R. 1998. Absorption and Scattering of Light by Small Particles. New York: John Wiley: 213–219
Bond T C and Bergstrom R W. 2006. Light absorption by carbonaceous particles: An investigative review. Aerosol Science and Technology, 40(1): 27–67
Boucher O, Randall D, Artaxo P, Bretherton C, Feingold G, Forster P, Kerminen V M, Kondo Y, Liao H, Lohmann U, Rasch P, Satheesh S, Sherwood S, Stevens B and Zhang X. 2013. Clouds and aerosols//Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge, UK, New York, NY, USA: Cambridge University Press: 571–658 [DOI: 10.1017/CBO9781107415324.016 http://dx.doi.org/10.1017/CBO9781107415324.016 ]
曹军骥, 李建军. 2016. 二次有机气溶胶的形成及其毒理效应. 地球环境学报, 7(5): 431–441
Cao J J and Li J J. 2016. Formation and toxicological effect of secondary organic aerosols. Journal of Earth Environment, 7(5): 431–441 (
Choi Y and Ghim Y S. 2016. Estimation of columnar concentrations of absorbing and scattering fine mode aerosol components using AERONET data. Journal of Geophysical Research: Atmospheres, 121(22): 13628–13640
Derimian Y, Karnieli A, Kaufman Y J, Andreae M O, Andreae T W, Dubovik O, Maenhaut W and Koren I. 2008. The role of iron and black carbon in aerosol light absorption. Atmospheric Chemistry and Physics, 8(13): 3623–3637
Dey S, Tripathi S N, Singh R P and Holben B N. 2006. Retrieval of black carbon and specific absorption over Kanpur city, northern India during 2001-2003 using AERONET data. Atmospheric Environment, 40(3): 445–456
Dubovik O, Herman M, Holdak A, Lapyonok T, Tanré D, DeuzéJ L, Ducos F, Sinyuk A and Lopatin A. 2011. Statistically optimized inversion algorithm for enhanced retrieval of aerosol properties from spectral multi-angle polarimetric satellite observations. Atmospheric Measurement Techniques, 4(5): 975–1018
Dubovik O, Holben B, Eck T F, Smirnov A, Kaufman Y J, King M D, Tanre D and Slutsker I. 2002. Variability of absorption and optical properties of key aerosol types observed in worldwide locations. Journal of the Atmospheric Sciences, 59(3): 590–608
Dubovik O, Lapyonok T, Litvinov P, Herman M, Fuertes D, Ducos F, Torres B, Derimian Y, Huang Xin, Lopatin A, Chaikovsky A, Asp etsberger M and Federspiel C. 2014. GRASP: a versatile algorithm for characterizing the atmosphere. SPIE Newsroom, 25
Dubovik O, Sinyuk A, Lapyonok T, Holben B N, Mishchenko M, Yang Ping, Eck T F, Volten H, Muñoz O, Veihelmann B, van der Zande W J, Leon J F, Sorokin M and Slutsker I. 2006. Application of spheroid models to account for aerosol particle nonsphericity in remote sensing of desert dust. Journal of Geophysical Research: Atmospheres, 111(D11): D11208
Dubovik O, Smirnov A, Holben B N, King M D, Kaufman Y J, Eck T F and Slutsker I. 2000. Accuracy assessments of aerosol optical properties retrieved from Aerosol Robotic Network (AERONET) Sun and sky radiance measurements. Journal of Geophysical Research: Atmospheres, 105(D8): 9791–9806
Erlick C, Abbatt J P D and Rudich Y. 2011. How different calculations of the refractive index affect estimates of the radiative forcing efficiency of ammonium sulfate aerosols. Journal of the Atmospheric Sciences, 68(9): 1845–1852
Feng Y, Ramanathan V and Kotamarthi V R. 2013. Brown carbon: a significant atmospheric absorber of solar radiation?. Atmospheric Chemistry and Physics, 13(17): 8607–8621
Ganguly D, Ginoux P, Ramaswamy V, Dubovik O, Welton J, Reid E A and Holben B N. 2009. Inferring the composition and concentration of aerosols by combining AERONET and MPLNET data: comparison with other measurements and utilization to evaluate GCM output. Journal of Geophysical Research: Atmospheres, 114(D16): D16203
郝吉明, 许嘉钰, 吴剑, 马乔. 2017. 我国京津冀和西北五省(自治区)大气环境容量研究. 中国工程科学, 19(4): 13–19
Hao J M, Xu J Y, Wu J and Ma Q. 2017. A study of the atmospheric environmental capacity of Jingjinji and of the five northwestern provinces and autonomous regions in China. Engineering Sciences, 19(4): 13–19 (
贺泓, 王新明, 王跃思, 王自发, 刘建国, 陈运法. 2013. 大气灰霾追因与控制. 中国科学院院刊, 28(3): 344–352
He H, Wang X M, Wang Y S, Wang Z F, Liu J G and Chen Y F. 2013. Formation mechanism and control strategies of haze in China. Bulletin of Chinese Academy of Sciences, 28(3): 344–352 (
贺克斌, 贾英韬, 马永亮, 雷宇, 赵晴, Tanaka S, Okuda T. 2009. 北京大气颗粒物污染的区域性本质. 环境科学学报, 29(3): 482–487
He K B, Jia Y T, Ma Y L, Lei Y, Zhao Q, Tanaka S and Okuda T. 2009. Regionality of episodic aerosol pollution in Beijing. Acta Scientiae Circumstantiae, 29(3): 482–487 (
Hecobian A, Zhang X, Zheng M, Frank N, Edgerton E S and Weber R J. 2010. Water-Soluble Organic Aerosol material and the light-absorption characteristics of aqueous extracts measured over the Southeastern United States. Atmospheric Chemistry and Physics, 10(13): 5965–5977
Holben B N, Eck T F, Slutsker I, Tanré D, Buis J P, Setzer A, Vermote E, Reagan J A, Kaufman Y J, Nakajima T, Lavenu F, Jankowiak I and Smirnov A. 1998. AERONET—a federated instrument network and data archive for aerosol characterization. Remote Sensing of Environment, 66(1): 1–16
Hu R M, Blanchet J P and Girard E. 2005. Evaluation of the direct and indirect radiative and climate effects of aerosols over the western Arctic. Journal of Geophysical Research: Atmospheres, 110(D11): D11213
Kandler K and Schütz L. 2007. Climatology of the average water-soluble volume fraction of atmospheric aerosol. Atmospheric Research, 83(1): 77–92
Kirchstetter T W, Novakov T and Hobbs P V. 2004. Evidence that the spectral dependence of light absorption by aerosols is affected by organic carbon. Journal of Geophysical Research: Atmospheres, 109(D21): D21208
Koch D, Bond T C, Streets D, Unger N and van der Werf G R. 2007. Global impacts of aerosols from particular source regions and sectors. Journal of Geophysical Research: Atmospheres, 112(D2): D02205
Koven C D and Fung I. 2006. Inferring dust composition from wavelength-dependent absorption in Aerosol Robotic Network (AERONET) data. Journal of Geophysical Research: Atmospheres, 111(D14): D14205
Lesins G, Chylek P and Lohmann U. 2002. A study of internal and external mixing scenarios and its effect on aerosol optical properties and direct radiative forcing. Journal of Geophysical Research: Atmospheres, 107(D10): AAC 5-1–AAC 5-12
Li L, Zheng X, Li Z Q, Li Z H, Dubovik O, Chen X F and Wendisch M. 2017. Studying aerosol light scattering based on aspect ratio distribution observed by fluorescence microscope. Optics Express, 25(16): A813–A823
Li Z, Gu X, Wang L, Li D, Xie Y, Li K, Dubovik O, Schuster G, Goloub P, Zhang Y, Li L, Ma Y and Xu H. 2013. Aerosol physical and chemical properties retrieved from ground-based remote sensing measurements during heavy haze days in Beijing winter. Atmospheric Chemistry and Physics, 13(20): 10171–10183
Li Z Q, Goloub P, Devaux C, Gu X F, Deuzé J L, Qiao Y L and Zhao F S. 2006. Retrieval of aerosol optical and physical properties from ground-based spectral, multi-angular, and polarized sun-photometer measurements. Remote Sensing of Environment, 101(4): 519–533
Li Z Q, Li L, Zhang F X, Li D H, Xie Y S and Xu H. 2015. Comparison of aerosol properties over Beijing and Kanpur: Optical, physical properties and aerosol component composition retrieved from 12 years ground-based Sun-sky radiometer remote sensing data. Journal of Geophysical Research: Atmospheres, 120(4): 1520–1535
李正强, 李东辉, 李凯涛, 许华, 陈兴峰, 陈澄, 谢一凇, 李莉, 李雷, 李伟, 吕阳, 伽丽丽, 张莹, 顾行发. 2015. 扩展多波长偏振测量的太阳—天空辐射计观测网. 遥感学报, 19(3): 495–519
Li Z Q, Li D H, Li K T, Xu H, Chen X F, Chen C, Xie Y S, Li L, Li L , Li W, Lyu Y, Jia L L, Zhang Y and G X F. 2015. Sun-sky radiometer observation network with the extension of multi-wavelength polarization measurements. Journal of Remote Sensing, 19(3): 495–519 (
Li Z Q, Xu H, Li K T, Li D H, Xie Y S, Li L, Zhang Y, Gu X F, Zhao W, Tian Q J, Deng R R, Su X L, Huang B, Qiao Y L, Cui W Y, Hu Y, Gong C L, Wang Y Q, Wang X F, Wang J P, Du W B, Pan Z Q, Li Z Z and Bu D. 2018. Comprehensive study of optical, physical, chemical, and radiative properties of total columnar atmospheric aerosols over China: An overview of Sun-sky radiometer Observation NETwork (SONET) measurements. Bulletin of the American Meteorological Society, 99(4): 739–755
Loeb N G and Su W Y. 2010. Direct aerosol radiative forcing uncertainty based on a radiative perturbation analysis. Journal of Climate, 23(19): 5288–5293
Morcrette J J, Boucher O, Jones L, Salmond D, Bechtold P, Beljaars A, Benedetti A, Bonet A, Kaiser J W, Razinger M, Schulz M, Serrar S, Simmons A J, Sofiev M, Suttie M, Tompkins A M and Untch A. 2009. Aerosol analysis and forecast in the European Centre for medium-range weather forecasts integrated forecast system: Forward modeling. Journal of Geophysical Research: Atmospheres, 114(D6): D06206
O’Neill N T, Dubovik O and Eck T F. 2001. Modified Ångström exponent for the characterization of submicrometer aerosols. Applied Optics, 40(15): 2368–2375
Qie L L, Li Z Q, Goloub P, Li L, Li D H, Li K T, Zhang Y and Xu H. 2017. Retrieval of the aerosol asymmetry factor from Sun-sky radiometer measurements: application to almucantar geometry and accuracy assessment. Applied Optics, 56(36): 9932–9940
Ramanathan V and Carmichael G. 2008. Global and regional climate changes due to black carbon. Nature Geoscience, 1(4): 221–227
Sato M, Hansen J, Koch D, Lacis A, Ruedy R, Dubovik O, Holben B, Chin M and Novakov T. 2003. Global atmospheric black carbon inferred from AERONET. Proceedings of the National Academy of Sciences of the United States of America, 100(11): 6319–6324
Schuster G L, Dubovik O and Arola A. 2016. Remote sensing of soot carbon - Part 1: distinguishing different absorbing aerosol species. Atmospheric Chemistry and Physics, 16(3): 1565–1585
Schuster G L, Dubovik O, Holben B N and Clothiaux E E. 2005. Inferring black carbon content and specific absorption from Aerosol Robotic Network (AERONET) aerosol retrievals. Journal of Geophysical Research: Atmospheres, 110(D10): D10S17
Schuster G L, Lin B and Dubovik O. 2009. Remote sensing of aerosol water uptake. Geophysical Research Letters, 36(3): L03814
Sun H L, Biedermann L and Bond T C. 2007. Color of brown carbon: a model for ultraviolet and visible light absorption by organic carbon aerosol. Geophysical Research Letters, 34(17): L17813
van Beelen A J, Roelofs G J H, Hasekamp O P, Henzing J S and Röckmann T. 2014. Estimation of aerosol water and chemical composition from AERONET Sun-sky radiometer measurements at Cabauw, the Netherlands. Atmospheric Chemistry and Physics, 14(12): 5969–5987
王玲, 李正强, 李东辉, 李凯涛, 田庆久, 李莉, 张莹, 吕阳, 顾行发. 2012. 基于遥感观测的折射指数光谱特性反演大气气溶胶中沙尘组分含量. 光谱学与光谱分析, 32(6): 1644–1649
Wang L, Li Z Q, Li D H, Li K T, Tian Q J, Li L, Zhang Y, Lü Y and Gu X F. 2012. Retrieval of dust fraction of atmospheric aerosols based on spectra characteristics of refractive indices obtained from remote sensing measurements. Spectroscopy and Spectral Analysis, 32(6): 1644–1649 (
王玲, 李正强, 马䶮, 李莉, 魏鹏. 2013. 利用太阳—天空辐射计遥感观测反演北京冬季灰霾气溶胶成分含量. 遥感学报, 17(4): 944–958
Wang L, Li Z Q, Ma Y, Li L and Wei P. 2013. Retrieval of aerosol chemical composition from ground-based remote sensing data of sun-sky radiometers during haze days in Beijing winter. Journal of Remote Sensing, 17(4): 944–958 (
Wang L, Li Z Q, Tian Q J, Ma Y, Zhang F X, Zhang Y, Li D H, Li K T and Li L. 2013. Estimate of aerosol absorbing components of black carbon, brown carbon, and dust from ground-based remote sensing data of sun-sky radiometers. Journal of Geophysical Research: Atmospheres, 118(12): 6534–6543
王跃思, 姚利, 王莉莉, 刘子锐, 吉东生, 唐贵谦, 张军科, 孙扬, 胡波, 辛金元. 2014. 2013年元月我国中东部地区强霾污染成因分析. 中国科学: 地球科学, 44(1): 15–26
Wang Y S, Yao L, Wang L L, Liu Z R, Ji D S, Tang G Q, Zhang J K, Sun Y, Hu B and Xin J Y. 2014. Mechanism for the formation of the January 2013 heavy haze pollution episode over central and eastern China. Science China Earth Sciences, 44(1): 15–26 (
谢一凇, 李东辉, 李凯涛, 张龙, 陈澄, 许华, 李正强. 2013. 基于地基遥感的灰霾气溶胶光学及微物理特性观测. 遥感学报, 17(4): 970–980
Xie Y S, Li D H, Li K T, Zhang L, Chen C, Xu H and Li Z Q. 2013. Aerosol optical and microphysical properties in haze days based on ground-based remote sensing measurements. Journal of Remote Sensing, 17(4): 970–980 (
Xie Y S, Li Z Q, Li L, Wang L, Li D H, Chen C, Li K T and Xu H. 2014. Study on influence of different mixing rules on the aerosol components retrieval from ground-based remote sensing measurements. Atmospheric Research, 145–146: 267–278
Xie Y S, Li Z Q, Zhang Y X, Zhang Y, Li D H, Li K T, Xu H, Zhang Y, Wang Y Q, Chen X F, Schauer J J and Bergin M. 2017. Estimation of atmospheric aerosol composition from ground-based remote sensing measurements of Sun-sky radiometer. Journal of Geophysical Research: Atmospheres, 122(1): 498–518
魏鹏, 李正强, 王堰, 谢一凇, 张莹, 许华. 2013. 灰霾污染状况下气溶胶组分及辐射效应的遥感估算. 遥感学报, 17(4): 1021–1031
Wei P, Li Z Q, Wang Y, Xie Y S, Zhang Y and Xu H. 2013. Remote sensing estimation of aerosol composition and radiative effects in haze days. Journal of Remote Sensing, 17(4): 1021–1031 (
Zhang Y, Li Z Q, Cuesta J, Li D H, Wei P, Xie Y S and Li L. 2015. Aerosol column size distribution and water uptake observed during a major haze outbreak over Beijing on January 2013. Aerosol and Air Quality Research, 15(3): 945–957
Zhang Y, Li Z Q, Sun Y L, Lv Y and Xie Y S. 2018. Estimation of atmospheric columnar organic matter (OM) mass concentration from remote sensing measurements of aerosol spectral refractive indices. Atmospheric Environment, 179: 107–117
相关文章
相关作者
相关机构
京公网安备11010802024621