Determination of aerosol type from multiband aerosol optical depth based on lookup table

Chen JIA; Lin SUN; Yunfang CHEN; Zhepeng LYU; Jing WEI; Huiyong YU; Xinpeng TIAN

doi:10.11834/jrs.20176026

Views : 0 下载量: 77 CSCD: 3 更多指标

PDF
Export
Share
Collection
Album

Determination of aerosol type from multiband aerosol optical depth based on lookup table
Vol. 21, Issue 3, Pages: 386-395(2017)
Published： 2017-5 ，

Accepted： 17 November 2016
DOI： 10.11834/jrs.20176026

扫描看全文

Chen JIA, Lin SUN, Yunfang CHEN, et al. Determination of aerosol type from multiband aerosol optical depth based on lookup table. [J]. Journal of Remote Sensing 21(3):386-395(2017)
DOI：

Chen JIA, Lin SUN, Yunfang CHEN, et al. Determination of aerosol type from multiband aerosol optical depth based on lookup table. [J]. Journal of Remote Sensing 21(3):386-395(2017) DOI： 10.11834/jrs.20176026.

摘要

针对传统气溶胶类型确定方法的局限性以及当前气溶胶类型确定存在的困难，提出一种使用多波段气溶胶光学厚度数据确定气溶胶类型的方法。基于大气颗粒物的散射与吸收特性分析，通过构建查找表的方法实现气溶胶类型的确定。该方法利用Mie散射理论通过正向模拟不同类型气溶胶粒子数量与多波段光学厚度之间的关系来构建查找表，基于该查找表，使用440 nm、670 nm、870 nm及1020 nm 4个波段的气溶胶光学厚度确定气溶胶类型。使用模拟的多波段气溶胶光学厚度数据开展了气溶胶类型的确定实验，分析了不同波段气溶胶光学厚度误差对气溶胶类型确定结果的影响。结果表明，该方法可根据4个波段的气溶胶光学厚度以较高的精度确定出沙尘性、水溶性和煤烟3种气溶胶粒子的数量，从而确定气溶胶类型。

Abstract

The high-precision determination of aerosol models is crucial for analyzing the environmental impact of aerosols and for the remote sensing of Aerosol Optical Depth (AOD). However

the determination of aerosol type remains difficult

hence severely restricting highly accurate AOD retrieval and the application of aerosol optical products in environmental monitoring. A high-precision method for estimating aerosol models is proposed in this paper. The determination of aerosol type plays a vital role in the analysis of aerosol optical properties and is also an essential part of highly accurate AOD retrieval. Conventional methods

which utilize aerosol optical properties to determine aerosol types

are based on the relationship between the AOD of a single band and different aerosol types. However

due to the complex absorption and scattering properties of aerosols

it is difficult to obtain highly accurate aerosol types from AOD data with a single band. Hence

multiband AODs were introduced to enhance the accuracy of determining aerosol types. None the less

the current methods for estimating aerosol types with multiband AODs are iterative with complex and slow calculation processes. A new method to determine aerosol type with multiband AOD data was proposed to overcome the existing difficulties of current methods. Aerosol type is determined based on a lookup table

which is built using the forward simulation of relations between the particle numbers of different aerosol types and multiband AOD data based on Mie scattering theory. AOD at the wavebands of 440

670

870

and 1020 nm are adopted to determine aerosol type. The method was used to estimate aerosol types with multiband AOD. To evaluate the effectiveness of the proposed method

multiband AODs are simulated and applied in the validation experiment. Dust

water-soluble

and soot aerosol types are estimated with high precision. The effects of multiband AOD error on aerosol type determination are also analyzed. Results show that the proposed method can determine aerosol types with high stability. Compared with the current real-time determination method of aerosol types

the approach proposed in this paper is fast and can be used to estimate aerosol type from pixel-scale satellite data with multiband AODs. Furthermore

this method can improve the inversion accuracy of aerosol optical thickness

as well as promote the application of aerosol optical products in environmental pollution monitoring.

关键词

气溶胶类型气溶胶光学厚度Mie散射查找表方法

Keywords

aerosol typeAerosol Optical Depth (AOD)Mie-scatteringlook-up table method

references

Andreae M O and Crutzen P J. 1997.Atmospheric aerosols: biogeochemical sources and role in atmospheric chemistry. Science, 276(5315): 1052–1058

Cappa C D, Che D L, Kessler S H, Kroll J H and Wilson K R. 2011. Variations in organic aerosol optical and hygroscopic properties upon heterogeneous OH oxidation. Journal of Geophysical Research: Atmospheres, 116(D15): D15204

Charlson R J, Schwartz S E, Hales J M, Cess R D, Coakley Jr J A, Hansen J E and Hofmann D J. 1992. Climate forcing by anthropogenic aerosols.Science, 255(5043): 423–430

Che H Z, Zhao H J, Wu Y F, Xia X G, Zhu J, Dubovik O, Estelles V, Ma Y J, Wang Y F, Wang H, Wang Y Q, Zhang X Y and Shi G Y. 2015. Application of aerosol optical properties to estimate aerosol type from ground-based remote sensing observation at urban area of northeastern China. Journal of Atmospheric and Solar-Terrestrial Physics, 132: 37–47

陈好, 顾行发, 程天海, 余涛, 李正强. 2013. 中国地区气溶胶类型特性分析. 遥感学报, 17(6): 1559–1571

Chen H, Gu X F, Cheng T H, Yu T and Li Z Q. 2013. Characteristics of aerosol types over China. Journal of Remote Sensing, 17(6): 1559–1571

D’Almeida G A, Koepke P and Shettle E P. Atmospheric Aerosols: Global Climatology and Radiative Characteristics. Hampton, Va: A Deepak Pub, 1991.

Deepak A and Gerber H.1983. Report of the Experts Meeting on Aerosols and their Climatic EffectsWilliamsburg, VA, 28-30March 1983. Williamsburg: World Meteorological Organization, 1983.

Du H. 2004. Mie-scattering calculation.Applied Optics, 43(9): 1951–1956

范娇, 郭宝峰, 何宏昌. 2015. 基于MODIS数据的杭州地区气溶胶光学厚度反演. 光学学报, 35(1): 101001

Fan J, Guo B F and He H C. 2015. Retrieval of aerosol optical thickness with MODIS data over Hangzhou.ActaOpticaSinica, 35(1): 101001

胡方超, 王振会, 张兵, 李俊生. 2009. 遥感试验数据确定大气气溶胶类型的方法研究. 中国激光, 36(2): 312–317

Hu F C, Wang Z H, Zhang B and Li J S. 2009. Study on method for determining atmospheric aerosol type using remote sensing experimental data. Chinese Journal of Lasers, 36(2): 312–317

Kaskaoutis D G, Kambezidis H D, Hatzianastassiou N, Kosmopoulos P G and Badarinath K V S. 2007. Aerosol climatology: on the discrimination of aerosol types over four AERONET sites. Atmospheric Chemistry and Physics, 7(3): 6357–6411

Kaskaoutis D G, Badarinath K V S, Kharol S K, Sharma A R and Kambezidis H D. 2009. Variations in the aerosol optical properties and types over the tropical urban site of Hyderabad, India. Journal of Geophysical Research: Atmospheres, 114(D22): D22204

Kaufman Y J and Sendra C. 1988.Algorithm for automatic atmospheric corrections to visible and near-IR satellite imagery. International Journal of Remote Sensing, 9(8): 1357–1381

King M D, Kaufman Y J, Menzel W P and Tanré D. 1992.Remote sensing of cloud, aerosol, and water vapor properties from the moderate resolution imaging spectrometer (MODIS).IEEE Transactions on Geoscience and Remote Sensing, 30(1): 2–27

Kumar K R, Yin Y, Sivakumar V, Kang N, Yu X N, Diao Y W, Adesina A J and Reddy R R. 2015. Aerosol climatology and discrimination of aerosol types retrieved from MODIS, MISR and OMI over Durban (29.88°S, 31.02°E), South Africa. Atmospheric Environment, 117: 9–18

Lee J, Kim J, Song C H, Kim S B, Chun Y, Sohn B J and Holben B N. 2010. Characteristics of aerosol types from AERONET sunphotometer measurements.Atmospheric Environment, 44(26): 3110–3117

Lekhtmakher S and Shapiro M. 2005.About randomness of aerosol size distributions. Journal of Aerosol Science, 36(12): 1459–1467

Levy R C. 2007. Retrieval of Tropospheric Aerosol Properties over Land From Visible and Near-Infrared Spectral Reflectance: Application over Maryland. Washington: University of Maryland, College Park.

Mie G. 1908. Beiträgezur OptiktrüberMedien, speziellkolloidaler Metallösungen. Annalen der Physik, 330(3): 377–445

Nicolae D, Belegante L, Talianu C and Vasilescu J. 2015. Using artificial neural networks to retrieve the aerosol type from multi-spectral lidar data//EGU General Assembly Conference Abstracts. Vienna, Austria: EGU: 9793.

Pathak B, Bhuyan P K, Gogoi M and Bhuyan K. 2012.Seasonal heterogeneity in aerosol types over Dibrugarh-North-Eastern India. Atmospheric Environment, 47: 307–315

Rama G K, Arafath S M, Balakrishnaiah G, Raja O R K, Siva K R N, Lingaswamy A P, Pavan K S, Uma D K, Reddy R R and Suresh B S. 2015. Columnar-integrated aerosol optical properties and classification of different aerosol types over the semi-arid region, Anantapur, Andhra Pradesh.Science of the Total Environment, 527-528: 507–519

Ramanathan V, Crutzen P J, Lelieveld J, Mitra A P, Althausen D, Anderson J, Andreae M O, Cantrell W, Cass G R, Chung C E, Clarke A D, Coakley J A, Collins W D, Conant W C, Dulac F, Heintzenberg J, Heymsfield A J, Holben B, Howell S, Hudson J, Jayaraman A, Kiehl J T, Krishnamurti T N, Lubin D, McFarquhar G, Novakov T, Ogren J A, Podgorny I A, Prather K, Priestley K, Prospero J M, Quinn P K, Rajeev K, Rasch P, Rupert S, Sadourny R, Satheesh S K, Shaw G E, Sheridan P and Valero F P J. 2001. Indian Ocean experiment: an integrated analysis of the climate forcing and effects of the great Indo-Asian haze. Journal of Geophysical Research: Atmospheres, 106(D22): 28371–28398

Sreekanth V. 2014.On the classification and sub-classification of aerosol key types over south central peninsular India: MODIS–OMI algorithm. Science of the Total Environment, 468-469: 1086–1092

Srivastava A K, Yadav V, Pathak V, Singh S, Tiwari S, Bisht D S and Goloub P. 2014. Variability in radiative properties of major aerosol types: a year-long study over Delhi—an urban station in Indo-Gangetic Basin. Science of the Total Environment, 473-474: 659–666

Sun L, Wei J, Bilal M, Tian X P, Jia C, Guo Y M and Mi X T. 2016. Aerosol optical depth retrieval over bright areas using landsat 8 OLI images.Remote Sensing, 8(1): 23

Tan F Y, Lim H S, Abdullah K, Yoon T L and Holben B. 2015. AERONET data-based determination of aerosol types.Atmospheric Pollution Research, 6(4): 682–695

美国环境保护局. 2008. 颗粒物环境空气质量USEPA基准(上卷). 北京: 中国环境科学出版社: 11–103

U.S. Environmental Protection Agency. 2008. Air Quality Criteria for Particulate Matter. Beijing: China Environmental Science Press: 11–103

王中挺, 厉青, 王桥, 李莘莘, 陈良富, 周春艳, 张丽娟, 徐拥军. 2012. 利用深蓝算法从HJ-1数据反演陆地气溶胶. 遥感学报, 16(3): 596–610

Wang Z T, Li Q, Wang Q, Li S S, Chen L F, Zhou C Y, Zhang L J and Xu Y J. 2012. HJ-1 terrestrial aerosol data retrieval using deep blue algorithm. Journal of Remote Sensing, 16(3): 596–610

Alert me when the article has been cited

提交

Fine mapping of PM_2.5 based on measurements from geostationary satellites and grid monitoring stations

Overall design and on-orbit verification of synchronization monitoring atmosphere corrector on high-resolution multi-mode satellite （GFDM）