摘要
大气气溶胶化学成分是决定大气溶胶辐射特性的重要因素,由于大气气溶胶辐射特性的不确定性,导致目前精确评估气溶胶的气候效应仍存在着很大的困难。在卫星遥感定量化应用方面,因标准的气溶胶模式不符合中国地区气溶胶化学组成情况,严重影响我国卫星遥感影像大气校正的效果,并导致后续的定量化应用研究出现较大误差。为此近年来国内外许多研究机构和学者都致力于大气气溶胶理化特性研究,从而解决气溶胶辐射特性不确定的难题,构建精确的大气气溶胶模式,提高遥感地表参数信息定量化的反演精度。目前国际上研究大气气溶胶理化特性更多地基于地基太阳-天空辐射计观测网(AERONET, Aerosol Robotics Network)。其在世界范围内已经建有超过500个站点,统一采用法国CIMEL公司的CE318型太阳-天空辐射计,同时提供高精度的定标以及成熟的气溶胶参数反演产品,为获取全球不同地区的大气气溶胶成分信息提供了坚实基础。与传统的地基采样方法相比,基于太阳-天空辐射计的方法还具有不破坏观测样本、直接获取整层大气气溶胶成分信息的优势。
论文从现有的反演算法出发,充分利用地基太阳-天空辐射计提供的丰富的大气气溶胶特性参数资料,对现有气溶胶化学成分反演方法进行了发展和扩充,建立了一种联合利用气溶胶复折射指数和单次散射反照率参数,同时反演整层大气气溶胶5种化学成分含量的五成分(5-component)反演算法。5种化学成分分别为黑碳(Black Carbon, BC)、沙尘(Dust, DU)、吸收性有机碳(Brown Carbon, BrC)、硫酸铵类(Ammonium Sulfate, AS)和水分(Aerosol Water, AW)。并以京津唐地区为示范区进行了反演应用研究,首次基于遥感方式获取了京津唐地区整层大气气溶胶化学成分含量的时空分布；最后通过与化学成分的原位(in-situ)测量结果对比进行了初步的反演验证。
论文的主要研究成果与结论如下：
(1)根据大量的文献资料,分析了三种主要吸收性成分BC、BrC、DU的复折射指数光谱特征,找出了已有反演算法不能同时选取BrC和DU作为端元成分的原因。基于AERONET全球沙尘、城市/工业和生物质燃烧区三种典型站点的观测资料,统计了DU、BC和BrC的单次散射反照率(SSA)光谱,发现具有类似虚部光谱形态的BrC和DU在SSA光谱曲线上具有可分性：在675-1020nm范围内,BrC的SSA呈现下降趋势,而DU呈现出上升趋势。确定了SSA可以作为除复折射指数以外的另一维信息量,添加到反演算法中,为反演模型中能同时选取三种吸收性端元成分提供了依据。
(2)从SSA的定义出发,结合Mie理论,建立了由气溶胶化学成分含量及其固有物理特性到气溶胶特性参数SSA转换的物理模型,为后续从气溶胶特性参数中反演气溶胶化学成分奠定了基础。
(3)基于太阳-天空辐射计的实际观测资料,利用不同反演算法进行了反演实验,评价分析了不同反演算法对气溶胶特性参数的拟合效果。结果表明,本文的五成分反演模型模拟的气溶胶特性参数与实际观测的拟合效果最好,尤其在受沙尘或燃煤排放影响的情况下,能很好的重现出气溶胶在440nm处强烈吸收的特征；而三成分(BC、AS和AW)反演模型拟合效果最差,无法解释气溶胶在440nm强烈吸收的特征；四成分(BC、DU、AS和AW)反演模型的拟合效果介于两者之间。
(4)选取了以细粒子居多的夏季清洁和冬季灰霾天气、粗细粒子相当的冬季清洁天气,以及以粗粒子为主的沙尘天气的典型观测,利用五成分反演算法进行了反演实验,发现反演结果与实际情况基本吻合,说明本文提出的算法适用于气溶胶中粗细粒子比例为任意取值的情况。
(5)基于2011年4月-2012年3月的太阳-天空辐射计观测资料,利用五成分反演算法,研究了京津唐地区气溶胶化学成分含量的时空分布规律。结果表明,受气溶胶排放源以及相对湿度等气象条件的季节性变化影响,京津唐地区气溶胶中的BC、BrC、DU和AW呈现出明显的季节变化特征。BC一般在冬季略高,春季略低。BrC的高值一般出现11月-次年3月,低值主要出现夏季以及秋季的9月。DU呈现出春季、冬季高,秋季次之,夏季最低的特点。AW呈现出夏季最高,秋季次之,春季最低的特点。兴隆作为大气本底观测站,其气溶胶化学成分含量与受人为影响较大的北京和香河站点存在着明显的差异,主要体现在人为来源的吸收性碳以及沙尘含量低于北京和香河地区,而水分含量高于北京和香河地区。对于香河与北京,由于具有相似的气候特征和气溶胶排放源,气溶胶化学成分组成情况具有较高的相似性。
(6)基于北京地区2001-2012年长时间序列的太阳-天空辐射计观测资料,利用五成分反演算法,研究了北京近12年来气溶胶化学成分含量的变化情况。结果表明,受筹办2008年奥运会采取的大气污染防治措施影响,在此期间,BC的含量呈下降趋势：2008年之前,BC体积比例的最大值在2%以上,而在2008年之后最大值基本都在1-1.5%之间。BrC的含量呈现先下降后回升的趋势,2006-2007年处于最低值,月均体积比例在10%以内。其他三种成分的年均含量在这12年间基本处于一个平稳的状态。DU年均体积比例基本在30%左右,AS主要集中在40%附近,AW基本在25-30%左右。
(7)结合北京地区长时间序列的气溶胶化学成分含量反演结果,初步建立了北京地区气溶胶模式库：煤烟性,沙尘性和水溶性粒子的体积分数为0.02,0.39和0.59。通过与其他有关北京地区气溶胶模式的研究结果比较,表明基于地基遥感观测,结合五成分反演方法,可以建立合理、可信的气溶胶模式。
(8)通过与黑碳仪观测的黑碳质量浓度对比验证,发现黑碳质量浓度的反演结果具有较高的精度。反演结果的相对误差与实际的黑碳质量浓度呈e指数递减关系(R2=0.74)。黑碳质量浓度>2μg/m3时,相对误差基本在45%以下,最小能达到1%；较大的反演误差(>50%)一般出现在黑碳质量浓度较低(<2μg/m3)的时候。
Aerosol chemical components are key factors influencing the aerosol radiative properties. In the field of climate change research, it is still difficult to evaluate aerosol radiative forcing accurately. The main reason is the difficulty in accurately determining the radiative properties of aerosols. Additionally, in the field of atmospheric correction for the satellite remotely sensed imageries, the unsuitable selection of atmospheric aerosol mode will result in low accuracy of quantitative remote sensing retrievals. Hence, in order to better understand the aerosol radiative characteristics, more and more research institutions and scholars are committed to explore the physical and chemical properties of atmospheric aerosols. Recently, some researches have started to give their attention to study aerosol physical and chemical properties based on Aerosol Robotics Network (AERONET), a network of more than500surface sun-sky radiometers (or sun photometers) located throughout the world, providing a long term view and an extensive spatial coverage. In addition, AERONET provides high-precision calibration for each instrument and mature inversion products related to aerosol properties, which makes it possible to access to the information of atmospheric aerosol chemical composition in different regions over the world. Compared to the in-situ chemical sampling method, estimate of the content of aerosol chemical components through the sun-sky radiometer measurements has the superiorities of automatically acquiring the aerosol information within the entire atmosphere in real-time and without direct contact to the aerosol.
In this study, according to the aerosol optical properties, we firstly simplify the aerosol as a mixture of five components. They are three absorbing components like Black Carbon (BC), Brown Carbon (BrC), and dust (DU); one scattering (non-absorbing) component of ammonium sulfate (AS) as well as water, which is responsible for aerosol hygroscopic characteristics. Then, we present a method to retrieve columnar contents of these five chemical components simultaneously from spectral refractive indices and spectral single scattering albedo (SSA) obtained from the sun-sky radiometer measurements. This method is a succession of several previous studies, but has advantages in providing simultaneous determination of BC, BrC, and DU. We then implement this method to investigate the column-integrated aerosol composition over Jing-Jin-Tang region, China using the sun-sky radiometer measurements. In the last part, we validate the retrieved BC concentrations with the in-situ measurements.
The main results and conclusions of the research are presented as follows:
(1) According to the published literatures, the spectral variation characteristics of imaginary refractive indices (k) of BC, BrC, and DU are examined to find out the reason why the current researches did not choose BrC and DU simultaneously as the end-members in the retrieval. The SSA spectra of BC, BrC, and DU are investigated based on the measurements from typical AERONET sites of desert dust, biomass and urban/industrial. We find that the difficulty in distinguishing BrC and DU based on k spectra can be solved by examining the shape of the SSA spectra. The shape of DU SSA from675-1020nm follows an increasing (or neutral) pattern, while for BrC it follows a deceasing pattern. This provides the basis that in addition to the spectral refractive index, SSA spectra can also be added into the inversion algorithm, and accordingly three major absorbing aerosols of BC, BrC and DU can be considered simultaneously as the end-members in the retrieval.
(2) According to the definition of the SSA, a physical model associating SSA with the content and the inherent physical properties of aerosol components is established combined with the Mie theory, which provides the foundation to retrieve aerosol chemical composition from the parameters of aerosol properties.
(3) Based on the sun-sky radiometer measurements, inversion experiments using different inversion algorithms are carried out. Results show that the calculated aerosol property parameters with the five-component inversion model proposed in this research match the observed ones from the sun-sky radiometer best. Especially, when the aerosols are influenced by dust or coal burning emissions, the five-component inversion model can fully reproduce the aerosol's enhanced absorption at440nm. However, the three-component (BC, AS, and AW) inversion model works worst and can not explain the enhanced absorption characteristics of aerosols at440nm. The performance of the four-component inversion model (BC, DU, AS, and AW) is in between the five-component and three-component inversion model.
(4) The five-component inversion model is applied to investigate the aerosol chemical composition under different weather conditions, i.e., the clear day in Summer with the fine particles dominated in the aerosol, the hazy and clear days in winter with the coarse particles comparable to the fine particles, and the dusty day with the coarse particles dominated in the aerosol. It turns out that the retrieved results for each case is reasonable, which indicates that the five-component inversion algorithm proposed here is applicable for various mixing ratios of the coarse particles to the fine particles in the aerosol.
(5) Based on the sun-sky radiometer measurements obtained from Apr.,2011to Mar.,2012, the spatiotemporal variations of the columnar content of the five aerosol chemical components over Jing-Jin-Tang region are explored using the five-component inversion algorithm. The results show that there exist apparent seasonal variation trends for BC, BrC, DU, and AW, as a result of the seasonal changes of the aerosol emission sources as well as weather conditions such as relative humidity. BC is generally higher in winter and lower in spring. BrC peaks form November to the following March, and reaches to the minimum in summer and in September of autumn. DU dominates in spring and winter, followed by autumn, and is minimum summer. AW peaks in summer, followed by autumn and is minimum in spring. Xinglong, as the atmospheric background site, is different in aerosol chemical composition compared to the other two sites of Beijing and Xianghe in this region. Moreover, due to similar climatic characteristics and aerosol emission sources, the aerosol chemical compositions show relatively high similarity between Xianghe and Beijing.
(6) Based on the sun-sky radiometer measurements obtained from2001-2012over Beijing, the change trends in the contents of aerosol chemical components in the past12years are investigated using the five-component inversion algorithm. The results showed that the content of BC is decreased gradually, caused by energy-saving emission reduction measures being taken by the government to the prepare for the2008Olympic Games. The volume fraction of BC is over2%before2008, but less than2%after2008. The content of BrC is decreasing before2006and2007, but increasing afterwards. For the other three components, i.e. DU, AS and AW, the contents are basically in a steady state in the past12years. The yearly averaged content of DU is about30%in volume fraction, AS is mainly in the vicinity of40%, and AW is about25-30%.
(7) According to the inversion results of aerosol chemical composition over Beijing during2001-2012, the preliminary atmospheric aerosol mode is establishment. For Beijing, the soot, dust and water-soluble type particles account for2%,39%and59% respectively in the dry aerosol. This result is comparable with other published results related to Beijing's atmospheric aerosol mode, indicating that a reasonable and credible atmospheric aerosol mode can be obtained from ground-based remote sensing data using the aerosol chemical composition inversion algorithm.
(8) Consistent temporal variation trends and good correlations are found between retrieved BC mass concentration and in-situ measurements. The large relative errors of the retrieved BC mass concentration exist when the actual BC mass concentration is lower(<2μg/m3). As the actual BC mass concentration increases, the relative error is decreased following an e exponential function (R2=0.74). The relative error of the retrieved BC mass concentration is basically less than45%and can even reach to1%when the actual BC mass concentration is above2μg/m3.
引文
[1]石广玉,王标,张华,et al.大气气溶胶的辐射与气候效应.大气科学.2008,32(4)：826-840.
[2]颜鹏,李维亮,秦瑜.近年来大气气溶胶模式研究综述.应用气象学报.2004,5：629-640.
[3]张小曳.中国大气气溶胶及其气候效应的研究.地球科学进展.2007,22(1)：12-16.
[4]Jung J., Lee H., Kim Y. J., et al. Aerosol chemistry and the effect of aerosol water content on visibility impairment and radiative forcing in Guangzhou during the 2006 Pearl River Delta campaign. Journal of Environmental Management.2009,90(11): 3231-3244.
[5]IPCC,2007. Radiative forcing of climate change, in Climate Change 2007. New York:Cambridge University Press.2007.
[6]Chin M., Kahn R. A., Schwartz S. E. U.S. Climate Change Science Program Synthesis and Assessment Product 2.3. Atmospheric Aerosol Properties and Climate Impacts. Washington, D.C., U.S.:U.S. Climate Change Science Program.2009. p.55-56.
[7]Seinfeld J. H., Pandis S. N. Atmospheric Chemistry and Physics. New York:John Wiley & Sons Inc.1998.
[8]姚青,韩素芹,毕晓辉.天津2009年3月气溶胶化学组成及其消光特性研究.中国环境科学.2012,32(2)：214-220.
[9]Delene D. J., Ogren J. A. Variability of aerosol optical properties at four North American surface monitoring sites. Journal of the Atmospheric Sciences.2002,59(6): 1135-1150.
[10]Schwartz S. E. The Whitehouse effect-Shortwave radiative forcing of climate by anthropogenic aerosols:An overview. Journal of Aerosol Science.1996,27(3):359-382.
[11]Haywood J. M., Shine K. P. Multi-spectral calculations of the direct radiative forcing of tropospheric sulphate and soot aerosols using a column model. Quarterly Journal of the Royal Meteorological Society.1997,123(543):1907-1930.
[12]Jacobson M. Z. Strong radiative heating due to the mixing state of black carbon in atmospheric aerosols. Nature.2001,409(6821):695-697.
[13]Liousse C., Penner J. E., Chuang C., et al. A global three-dimensional model study of carbonaceous aerosols. Journal of Geophysical Research-Atmospheres.1996, 101(D14):19411-19432.
[14]Myhre G., Stordal F., Restad K., et al. Estimation of the direct radiative forcing due to sulfate and soot aerosols. Tellus Series B-Chemical and Physical Meteorology.1998, 50(5):463-477.
[15]Penner J. E., Chuang C. C., Grant K. Climate forcing by carbonaceous and sulfate aerosols. Climate Dynamics.1998,14(12):839-851.
[16]Charlock T. P., Sellers W. D. Aerosol Effects on Climate-Calculations with Time-Dependent and Steady-State Radiative-Convective Models. Journal of the Atmospheric Sciences.1980,37(6):1327-1341.
[17]Haywood J. M., Shine K. P. The Effect of Anthropogenic Sulfate and Soot Aerosol on the Clear-Sky Planetary Radiation Budget. Geophysical Research Letters.1995,22(5): 603-606.
[18]郝丽,杨文,吴统文,et al.沙尘气溶胶的光学特性及辐射强迫效应.中国沙漠.2010,30(6)：1477-1482.
[19]Charlson R. J., Heintzenberg J. Aerosol Forcing of Climate led. New York:Wiley. 1995.
[20]IPCC,2001. Radiative forcing of climate change, in Climate Change 2001. New York:Cambridge University Press.2001.
[21]Hegg D., Larson T., Yuen P. F. A Theoretical-Study of the Effect of Relative-Humidity on Light-Scattering by Tropospheric Aerosols. Journal of Geophysical Research-Atmospheres.1993,98(D10):18435-18439.
[22]Chin M., Kahn R. A., Schwartz S. E. Atmospheric Aerosol Properties and Climate Impacts (CCSP 2009). U.S. Climate Change Science Program and the Subcommittee on Global Change Research.2009.
[23]饶玫瑰,苗放,叶成名,et al.6S模型在成都平原气溶胶光学厚度反演中的应用研究.长江大学学报(自然科学版).2011,8(8)：35-38.
[24]田庆久,郑兰芬.基于遥感影像的大气辐射校正和反射率反演方法.应用气象学报.1998,9(4)：456-461.
[25]唐洪钊,晏磊,李成才,et al.基于MODIS高分辨率气溶胶反演的ETM+影像大气校正.地理与地理信息科学.2010：26(4)：12-15.
[26]巩慧,田国良,余涛,et al. MODIS辐照度法定标试验研究.遥感学报.2010,(2)：207-218.
[27]Holben B. N., Eck T. F., Slutsker I., et al. AERONET-A federated instrument network and data archive for aerosol characterization. Remote Sensing of Environment. 1998,66(1):1-16.
[28]杨校军,陈雨时,张晔FLAASH模型输入参数对校正结果的影响.遥感信息.2008,(6)：32-37.
[29]赵祥,梁顺林,刘素红,et al高光谱遥感数据的改正暗目标大气校正方法研究.中国科学(D辑：地球科学).2007,37(12)：1653-1659.
[30]Vermote E. F., Tanre D., Deuze J. L., et al. Second Simulation of the Satellite Signal in the Solar Spectrum,6S:An overview. Ieee Transactions on Geoscience and Remote Sensing.1997,35(3):675-686.
[31]李成才.MODIS遥感气溶胶光学厚度及应用于区域环境大气污染研究[博士].北京：北京大学,2002.
[32]辛金元.中国地区气溶胶光学特性地基联网观测与研究[博士].兰州：兰州大学,2007.
[33]Li Z. Q., Ackerman T. P., Wiscombe W., et al. Have clouds darkened since 1995? Science.2003,302(5648):1150-1151.
[34]Fan J. W., Leung L. R., Li Z. Q., et al. Aerosol impacts on clouds and precipitation in eastern China:Results from bin and bulk microphysics. Journal of Geophysical Research-Atmospheres.2012,117(D16), doi:10.1029/2011JD016537.
[35]Zhao C., Liu X., Leung L. R. Impact of the Desert dust on the summer monsoon system over Southwestern North America. Atmospheric Chemistry and Physics.2012, 12(8):3717-3731.
[36]Zhao C. S., Tie X. X., Lin Y. P. A possible positive feedback of reduction of precipitation and increase in aerosols over eastern central China. Geophysical Research Letters.2006,33(11):doi:10.1029/2006GL025959.
[37]吴兑,毕雪岩,邓雪娇,et al.珠江三角洲大气灰霾导致能见度下降问题研究.气象学报.2006,64(4)：510-517.
[38]仲兆庆,王福涛.大气颗粒物与人群疾病的关系.山东环境.1999,(6)：62.
[39]岑世宏.京津唐城市群大气PM_(10)和PM_(2.5)理化特征及健康效应研究[博士].北京：中国矿业大学(北京),2011.
[40]Maynard R. L. The Urban Atmosphere and its effects. London:Imperial College Press.2001.
[41]Huang J. P., Lin B., Minnis P., et al. Satellite-based assessment of possible dust aerosols semi-direct effect on cloud water path over East Asia. Geophysical Research Letters.2006,33(19), DOI:10.1029/2006GL026561.
[42]王娉.华北地区碳气溶胶排放源状况研究[硕士].北京：中国气象科学研究院,2009.
[43]赵斌.华北地区大气污染源排放状况研究[硕士].北京：中国气象科学研究院,2007.
[44]彭应登,钟良,刘翠玲.北京PM2.5污染特点及防治途径.节能与环保.2012,(03)：52-54.
[45]Li Z. Q., Gu X., Wang L., et al. Aerosol physical and chemical properties retrieved from ground-based remote sensing measurements during heavy haze days in Beijing winter. Atmospheric Chemistry and Physics Discussion.2013,13:5091-5122.
[46]高健,张岳翀,王淑兰,et al.北京2011年10月连续灰霾过程的特征与成因初探.环境科学.2012,25(11)：1201-1207.
[47]Jeong C. H., McGuire M. L., Godri K. J., et al. Quantification of aerosol chemical composition using continuous single particle measurements. Atmospheric Chemistry and Physics.2011,11(14):7027-7044.
[48]张仁健,王明星,张文,et al.北京冬春季气溶胶化学成分及其谱分布研究.气候与环境研究.2000,5(1)：6-12.
[49]洪也,马雁军,刘宁微.沈阳冬季大气颗粒物化学成分及其来源的分析.环境科学与技术.2010,33(6E)：292-296.
[50]Giere R., Blackford M., Smith K. TEM study of PM2.5 emitted from coal and tire combustion in a thermal power station. Environmental Science & Technology.2006, 40(20):6235-6240.
[51]郭士伦,R.Brandt, P.Vater环境气溶胶的核孔膜、扫描电子显微镜和微电子探针研究.原子能科学技术.2002,36(6)：558-560.
[52]Ginoux P., Chin M., Tegen I., et al. Sources and distributions of dust aerosols simulated with the GOCART model. Journal of Geophysical Research-Atmospheres. 2001,106(D17):20255-20273.
[53]Huneeus N., Chevallier F., Boucher O. Estimating aerosol emissions by assimilating observed aerosol optical depth in a global aerosol model. Atmospheric Chemistry and Physics.2012,12(10):4585-4606.
[54]Koch D., Schulz M., Kinne S., et al. Evaluation of black carbon estimations in global aerosol models. Atmospheric Chemistry and Physics.2009,9(181):9001-9026.
[55]Bond T. C., Streets D. G., Yarber K. F., et al. A technology-based global inventory of black and organic carbon emissions from combustion. Journal of Geophysical Research-Atmospheres.2004,109(D14203), doi:10.1029/2003JD003697.
[56]Park R. J., Jacob D. J., Chin M., et al. Sources of carbonaceous aerosols over the United States and implications for natural visibility. Journal of Geophysical Research-Atmospheres.2003,108(D12):4355, doi:10.1029/2002JD003190.
[57]Dubovik O., King M. D. A flexible inversion algorithm for retrieval of aerosol optical properties from Sun and sky radiance measurements. Journal of Geophysical Research-Atmospheres.2000,105(D16):20673-20696.
[58]Dubovik O., Holben B. N., Lapyonok T., et al. Non-spherical aerosol retrieval method employing light scattering by spheroids. Geophysical Research Letters.2002, 29(10):54-1-54-4.
[59]Dubovik O., Sinyuk A., Lapyonok T., et al. Application of spheroid models to account for aerosol particle nonsphericity in remote sensing of desert dust. Journal of Geophysical Research-Atmospheres.2006,111(D11208), doi:10.1029/2005JD006619.
[60]Li Z. Q., Goloub P., Devaux C., et al. Retrieval of aerosol optical and physical properties from ground-based spectral, multi-angular, and polarized sun-photometer measurements. Remote Sensing of Environment.2006,101(4):519-533.
[61]Li Z. Q., Goloub P., Dubovik O., et al. Improvements for ground-based remote sensing of atmospheric aerosol properties by additional polarimetric measurements. Journal of Quantitative Spectroscopy & Radiative Transfer.2009,110(17):1954-1961.
[62]Kaufman Y. J., Gitelson A., Karnieli A., et al. Size Distribution and Scattering Phase Function of Aerosol-Particles Retrieved from Sky Brightness Measurements. Journal of Geophysical Research-Atmospheres.1994,99(D5):10341-10356.
[63]Schuster G. L., Dubovik O., Holben B. N. Angstrom exponent and bimodal aerosol size distributions. Journal of Geophysical Research-Atmospheres.2006,111(D7), DOI:10.1029/2005JD006328.
[64]Reid J. S., Eck T. F., Christopher S. A., et al. Use of the Angstrom exponent to estimate the variability of optical and physical properties of aging smoke particles in Brazil. Journal of Geophysical Research-Atmospheres.1999,104(D22):27473-27489.
[65]Eck T. F., Holben B. N., Dubovik O., et al. Columnar aerosol optical properties at AERONET sites in central eastern Asia and aerosol transport to the tropical mid-Pacific. Journal of Geophysical Research-Atmospheres.2005,110(D6), DOI: 10.1029/2004JD005274.
[66]Eck T. F., Holben B. N., Reid J. S., et al. Wavelength dependence of the optical depth of biomass burning, urban, and desert dust aerosols. Journal of Geophysical Research-Atmospheres.1999,104(D24):31333-31349.
[67]Eck T. F., Holben B. N., Dubovik O., et al. Column-integrated aerosol optical properties over the Maldives during the northeast monsoon for 1998-2000. Journal of Geophysical Research-Atmospheres.2001,106(D22):28555-28566.
[68]Eck T. F., Holben B. N., Ward D. E., et al. Characterization of the optical properties of biomass burning aerosols in Zambia during the 1997 ZIBBEE field campaign. Journal of Geophysical Research-Atmospheres.2001,106(D4):3425-3448.
[69]Eck T. F., Holben B. N., Ward D. E., et al. Variability of biomass burning aerosol optical characteristics in southern Africa during the SAFARI 2000 dry season campaign and a comparison of single scattering albedo estimates from radiometric measurements. Journal of Geophysical Research-Atmospheres.2003,108(D13), DOI: 10.1029/2002JD002321.
[70]Dubovik O., Holben B., Eck T. F., et al. Variability of absorption and optical properties of key aerosol types observed in worldwide locations. Journal of the Atmospheric Sciences.2002,59(3):590-608.
[71]Smirnov A., Holben B. N., Kaufman Y. J., et al. Optical properties of atmospheric aerosol in maritime environments. Journal of the Atmospheric Sciences.2002,59(3): 501-523.
[72]Smirnov A., Holben B. N., Dubovik O., et al. Atmospheric aerosol optical properties in the Persian Gulf. Journal of the Atmospheric Sciences.2002,59(3):620-634.
[73]Keil A., Haywood J. M. Solar radiative forcing by biomass burning aerosol particles during SAFARI 2000:A case study based on measured aerosol and cloud properties. Journal of Geophysical Research-Atmospheres.2003,108(D13), doi: 10.1029/2002JD002315.
[74]Kaskaoutis D. G., Kambezidis H. D. Investigation into the wavelength dependence of the aerosol optical depth in the Athens area. Quarterly Journal of the Royal Meteorological Society.2006,132(620):2217-2234.
[75]Derimian Y., Karnieli A., Kaufman Y. J., et al. The role of iron and black carbon in aerosol light absorption. Atmospheric Chemistry and Physics.2008,8(13):3623-3637.
[76]Bergstrom R. W., Russell P. B., Hignett P. Wavelength dependence of the absorption of black carbon particles:Predictions and results from the TARFOX experiment and implications for the aerosol single scattering albedo. Journal of the Atmospheric Sciences.2002,59(3):567-577.
[77]Russell P. B., Bergstrom R. W., Shinozuka Y., et al. Absorption Angstrom Exponent in AERONET and related data as an indicator of aerosol composition. Atmospheric Chemistry and Physics.2010,10(3):1155-1169.
[78]Ackermann J. The extinction-to-backscatter ratio of tropospheric aerosol:A numerical study. Journal of Atmospheric and Oceanic Technology.1998,15(4):1043-1050.
[79]Gobbi G. P., Barnaba F., Giorgi R., et al. Altitude-resolved properties of a Saharan dust event over the Mediterranean. Atmospheric Environment.2000,34(29):5119-5127.
[80]Barnaba F., Gobbi G. P. Aerosol seasonal variability over the Mediterranean region and relative impact of maritime, continental and Saharan dust particles over the basin from MODIS data in the year 2001. Atmospheric Chemistry and Physics.2004,4:2367-2391.
[81]Clarke A., McNaughton C., Kapustin V., et al. Biomass burning and pollution aerosol over North America:Organic components and their influence on spectral optical properties and humidification response. Journal of Geophysical Research-Atmospheres. 2007,112(D12), doi:10.1029/2006JD007777.
[82]胡欢陵,许军,黄正.中国东部若干地区大气气溶胶虚折射指数特征.大气科学.1991,15(3)：18-23.
[83]Muller T., Schladitz A., Kandler K., et al. Spectral particle absorption coefficients, single scattering albedos and imaginary parts of refractive indices from ground based in situ measurements at Cape Verde Island during SAMUM-2. Tellus Series B-Chemical and Physical Meteorology.2011,63(4):573-588.
[84]Muller T., Schladitz A., Massling A., et al. Spectral absorption coefficients and imaginary parts of refractive indices of Saharan dust during SAMUM-1. Tellus Series B-Chemical and Physical Meteorology.2009,61(1):79-95.
[85]Schuster G. L., Dubovik O., Holben B. N., et al. Inferring black carbon content and specific absorption from Aerosol Robotic Network (AERONET) aerosol retrievals. Journal of Geophysical Research-Atmospheres.2005,110(D10), doi: 10.1029/2004JD004548.
[86]Larson S. M., Cass G. R., Hussey K. J., et al. Verification of Image-Processing Based Visibility Models. Environmental Science & Technology.1988,22:629-637.
[87]何金海,王振会,银燕,et al.大气科学.北京：科学出版社.2008.
[88]Maria S. F., Russell L. M., Gilles M. K., et al. Organic aerosol growth mechanisms and their climate-forcing implications. Science.2004,306:1921-1924.
[89]石广玉.大气辐射学.第一版ed.北京：科学出版社.2007.
[90]Koven C. D., Fung I. Inferring dust composition from wavelength-dependent absorption in Aerosol Robotic Network (AERONET) data. Journal of Geophysical Research-Atmospheres.2006,111(D14), doi:10.1029/2005JD006678.
[91]Wagner R., Ajtai T., Kandler K., et al. Complex refractive indices of Saharan dust samples at visible and near UV wavelengths:a laboratory study. Atmospheric Chemistry and Physics Discussion.2012,12:2491-2512.
[92]Kirchstetter T. W., Novakov T., Hobbs P. V. Evidence that the spectral dependence of light absorption by aerosols is affected by organic carbon. Journal of Geophysical Research-Atmospheres.2004,109 (D21), doi:10.1029/2004JD004999.
[93]Bahadur R., Praveen P. S., Xu Y. Y., et al. Solar absorption by elemental and brown carbon determined from spectral observations. Proceedings of the National Academy of Sciences of the United States of America.2012,109(43):17366-17371.
[94]Feng Y., Ramanathan V., Kotamarthi V. R. Brown carbon:a significant atmospheric absorber of solar radiation? Atmospheric Chemistry and Physics Discussion. 2013,13:2795-2833.
[95]Schuster G. L., Lin B., Dubovik O. Remote sensing of aerosol water uptake. Geophysical Research Letters.2009,36(3), doi:10.1029/2008GL036576.
[96]Arola A., Schuster G., Myhre G., et al. Inferring absorbing organic carbon content from AERONET data. Atmospheric Chemistry and Physics.2011,11(1):215-225.
[97]许黎,樊小标,石广玉,et al.对流层平流层气溶胶粒子的形态和化学组成.气象学报.1998：40-48.
[98]孙天乐,何凌燕,黄晓锋,et al.深圳市冬季黑碳气溶胶的粒径分布和混合状态特征.科学通报.2011,56(21)：1703-1710.
[99]许黎,王亚强,陈振林,et al.黑碳气溶胶研究进展Ⅰ：排放、清除和浓度.地球科学进展.2006,21(4)：352-360.
[100]王吉明,曹艳华,叶小峰,et al.东亚地区气溶胶化学成分特性分析及数值模拟研究.江西农业大学学报.2010,32(1)：190-198.
[101]李嘉伟,韩志伟,张仁健.2010年春季东亚地区沙尘气溶胶和PM_(10)的模拟研究.中国环境科学.2011,31(10)：1600-1608.
[102]王跃思,辛金元,李占清,et al.中国地区大气气溶胶光学厚度与Angstrom参数联网观测(2004-08～2004-12).环境科学.2006,27(9)：1703-1711.
[103]杨辉,刘文清,刘建国,et al.激光雷达监测北京城区夏季边界层气溶胶.中国激光.2006,33(9)：1255-1259.
[104]赵一鸣,江月松,张绪国,et al.利用CALIPSO卫星数据对大气气溶胶的去偏振度特性分析研究.光学学报.2009,29(11)：2943-2951.
[105]邬明权,牛铮,乔玉良,et al.基于MODIS数据的北京气溶胶类型特性与影响因素分析.地球信息科学学报.2009,11(4)：541-548.
[106]陈斌.利用卫星和AERONET观测资料对东亚地区吸收性气溶胶识别及其光学特征分析[博士].兰州：兰州大学,2012.
[107]胡方超,王振会,张兵,et al.遥感试验数据确定大气气溶胶类型的方法研究.中国激光.2009,36(2)：312-317.
[108]王玲,田庆久,李姗姗.利用MODIS资料反演杭州市500米分辨率气溶胶光学厚度.遥感信息.2010,(003)：50-54.
[109]王玲,李正强,李东辉,et al.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.2012,32(6)：1644-1649.
[110]Cantrell B. K., Whitby K. T. Aerosol Size Distributions and Aerosol Volume Formation for a Coal-Fired Power-Plant Plume. Atmospheric Environment.1978,12(1): 323-333.
[111]Rosen J. M., Hofmann D. J., Singh S. P. Steady-State Stratospheric Aerosol Model. Journal of the Atmospheric Sciences.1978,35:1304-1313.
[112]Yang M., Howell S. G., Zhuang J., et al. Attribution of aerosol light absorption to black carbon, brown carbon, and dust in China-interpretations of atmospheric measurements during EAST-AIRE. Atmospheric Chemistry and Physics.2009,9(6): 2035-2050.
[113]Moosmuller H., Chakrabarty R. K., Arnott W. P. Aerosol light absorption and its measurement:A review. Journal of Quantitative Spectroscopy & Radiative Transfer. 2009,110(11):844-878.
[114]Sharma S., Brook J. R., Cachier H., et al. Light absorption and thermal measurements of black carbon in different regions of Canada. Journal of Geophysical Research-Atmospheres.2002,107(D24), doi:10.1029/2002JD002496.
[115]Rogge W. F., Mazurek M. A., Hildemann L. M., et al. Quantification of Urban Organic Aerosols at a Molecular-Level-Identification, Abundance and Seasonal-Variation. Atmospheric Environment Part a-General Topics.1993,27(8):1309-1330.
[116]Turpin B. J., Huntzicker J. J. Secondary Formation of Organic Aerosol in the Los-Angeles Basin-a Descriptive Analysis of Organic and Elemental Carbon Concentrations. Atmospheric Environment Part a-General Topics.1991,25(2):207-215.
[117]Turpin B. J., Huntzicker J. J. Identification of Secondary Organic Aerosol Episodes and Quantitation of Primary and Secondary Organic Aerosol Concentrations during Scaqs. Atmospheric Environment.1995,29(23):3527-3544.
[118]康富贵,李耀辉.近10a西北地区沙尘气溶胶研究综述.干早气象.2011,29(2)：144-150.
[119]Kinne S., Schulz M., Textor C., et al. An AeroCom initial assessment-optical properties in aerosol component modules of global models. Atmospheric Chemistry and Physics.2006,6(7):1815-1834.
[120]Textor C., Schulz M., Guibert S., et al. Analysis and quantification of the diversities of aerosol life cycles within AeroCom. Atmospheric Chemistry and Physics. 2006,6(7):1777-1813.
[121]宿兴涛,王汉杰,宋帅,et al.近10年东亚沙尘气溶胶辐射强迫与温度响应.高原气象.2011,30(5)：1300-1307.
[122]Shao Y., Dong C. H. A review on East Asian dust storm climate, modelling and monitoring. Global and Planetary Change.2006,52(1):1-22.
[123]Eck T. F., Holben B. N., Sinyuk A., et al. Climatological aspects of the optical properties of fine/coarse mode aerosol mixtures. Journal of Geophysical Research-Atmospheres.2010,115(D19205),doi:10.1029/2010JD014002.
[124]Goloub P., Li Z., Dubovik O., et al. PHOTONS/AERONET sunphotometer network overview. Description-Activities-Results-art. no.69360V. Fourteenth International Symposium on Atmospheric and Ocean Optics/Atmospheric Physics.2007: 69360V-69360V-15.
[125]Li Z. Q., Blarel L., Podvin T., et al. Transferring the calibration of direct solar irradiance to diffuse-sky radiance measurements for CIMEL Sun-sky radiometers. Applied Optics.2008,47(10):1368-1377.
[126]Company M. S. OPERATING MANUAL:AETHALOMETER(?) microAeth(?) Model AE51. Berkeley, California:Magee Scientific Company.2009.
[127]娄淑娟,毛节泰,王美华.北京地区不同尺度气溶胶中黑碳含量的观测研究.环境科学学报.2005,25(1)：17-22.
[128]杨溯,张武,史晋森,et al.半干旱地区黑碳气溶胶特征初步分析.气候与环境研究.2010,15(6)：756-764.
[129]潘小乐,王自发,王喜全,et al.2008北京奥运会前后城区黑碳气溶胶浓度的变化特征.气候与环境研究.2010,(005)：616-623.
[130]Yu X. N., Zhu B., Zhang M. G. Seasonal variability of aerosol optical properties over Beijing. Atmospheric Environment.2009,43(26):4095-4101.
[131]曾令建,缪启龙,高庆先,et al.沙尘天气对北京大气环境质量及太阳辐射的影响.环境科学研究.2011,24(4)：433-439.
[132]Cao J. J., Lee S. C., Chow J. C., et al. Spatial and seasonal distributions of carbonaceous aerosols over China. Journal of Geophysical Research-Atmospheres.2007, 112(D22), doi:10.1029/2006JD008205.
[133]Lin P., Hu M., Deng Z., et al. Seasonal and diurnal variations of organic carbon in PM2.5 in Beijing and the estimation of secondary organic carbon. Journal of Geophysical Research-Atmospheres.2009,114(D2), doi:10.1029/2008JD010902.
[134]Bergstrom R. W., Pilewskie P., Russell P. B., et al. Spectral absorption properties of atmospheric aerosols. Atmospheric Chemistry and Physics.2007,7(23):5937-5943.
[135]Russell L. M., Bahadur R., Ziemann P. J. Identifying organic aerosol sources by comparing functional group composition in chamber and atmospheric particles. Proceedings of the National Academy of Sciences of the United States of America.2011, 108(9):3516-3521.
[136]Mukai H., Ambe Y. Characterization of a Humic Acid-Like Brown Substance in Airborne Particulate Matter and Tentative Identification of Its Origin. Atmospheric Environment.1986,20(5):813-819.
[137]Formenti P., Elbert W., Maenhaut W., et al. Inorganic and carbonaceous aerosols during the Southern African Regional Science Initiative (SAFARI 2000) experiment: Chemical characteristics, physical properties, and emission data for smoke from African biomass burning. Journal of Geophysical Research-Atmospheres.2003,108(D13), doi: 10.1029/2002JD002408.
[138]Chung C. E., Ramanathan V., Decremer D. Observationally constrained estimates of carbonaceous aerosol radiative forcing. Proceedings of the National Academy of Sciences of the United States of America.2012,109(29):11624-11629.
[139]Bahadur R., Feng Y., Russell L. M., et al. Impact of California's air pollution laws on black carbon and their implications for direct radiative forcing. Atmospheric Environment.2011,45(5):1162-1167.
[140]Hess M., Herd C. R. Carbon Black. New York:Mercel Dekker.1993.
[141]D'Almeida G. A., Koepke P., Shettle E. P. Atmospheric aerosols:Global climatology and radiative characteristics. Hampton, Virginia, USA:Deepak Publilshing. 1991.
[142]Sokolik I. N., Toon O. B. Incorporation of mineralogical composition into models of the radiative properties of mineral aerosol from UV to IR wavelengths. Journal of Geophysical Research-Atmospheres.1999,104(D8):9423-9444.
[143]Schnaiter M., Horvath H., Mohler O., et al. UV-VIS-NIR spectral optical properties of soot and soot-containing aerosols. Journal of Aerosol Science.2003,34(10): 1421-1444.
[144]Heller W. Remarks on Refractive Index Mixture Rules. Journal of Physical Chemistry.1965,69(4):1123-1129.
[145]Hanel G. Real Part of Mean Complex Refractive Index and Mean Density of Samples of Atmospheric Aerosol Particles. Tellus.1968,20(3):371-379.
[146]Hasan H., Dzubay T. G. Apportioning Light Extinction Coefficients to Chemical-Species in Atmospheric Aerosol. Atmospheric Environment.1983,17(8):1573-1581.
[147]Lowenthal D. H., Watson J. G., Saxena P. Contributions to light extinction during project MOHAVE. Atmospheric Environment.2000,34(15):2351-2359.
[148]Ouimette J. R., Flagan R. C. The Extinction Coefficient of Multicomponent Aerosols. Atmospheric Environment.1982,16(10):2405-2419.
[149]Liu Y. G., Daum P. H. Relationship of refractive index to mass density and self-consistency of mixing rules for multicomponent mixtures like ambient aerosols. Journal of Aerosol Science.2008,39(11):974-986.
[150]Dey S., Tripathi S. N., Singh R. P., et al. Retrieval of black carbon and specific absorption over Kanpur city, northern India during 2001-2003 using AERONET data. Atmospheric Environment.2006,40(3):445-456.
[151]Bergstrom.R. W.. Predictions of the spectral absorption and extinction coefficients of an urban air pollution aerosol model[J]. Atmospheric Environment (1967),1972,6(4): 247-258.
[152]Wiscombe W. J. Improved Mie Scattering Algorithms. Applied Optics.1980, 19(9):1505-1509.
[153]Bond T. C., Bergstrom R. W. Light absorption by carbonaceous particles:An investigative review. Aerosol Science and Technology.2006,40(1):27-67.
[154]Horvath H. TMOSPHERIC LIGHT-ABSORPTION-A REVIEW. Atmospheric Environment Part a-General Topics.1993,27(3):293-317.
[155]李东辉,李正强,卞良,et al.极地区域气溶胶地基遥感观测及分析.遥感学报.2013,17(3),13.
[156]中国气象局.霾的观测和预报等级.北京：中国气象出版社.2010.
[157]Li Z. Q., Gu X. F., Wang L., et al. Aerosol physical and chemical properties retrieved from ground-based remote sensing measurements during heavy haze days in Beijing winter. Atmos Chem Phys Discuss.2013:13,5091-5122, doi:10.5194/acpd-13-5091-2013.
[158]Gong S. L., Zhang X. Y., Zhao T. L., et al. Characterization of soil dust aerosol in China and its transport and distribution during 2001 ACE-Asia:2. Model simulation and validation. Journal of Geophysical Research-Atmospheres.2003,108(D9), doi: 10.1029/2002JD002633.
[159]Duan F. K., Liu X. D., He K. B., et al. Characteristics and source identification of particulate matter in wintertime in Beijing. Water Air and Soil Pollution.2007,180(1-4): 171-183.
[160]Yuan H., Zhuang G. S., Li J., et al. Mixing of mineral with pollution aerosols in dust season in Beijing:Revealed by source apportionment study. Atmospheric Environment.2008,42(9):2141-2157.
[161]Li W. J., Shao L. Y., Buseck P. R. Haze types in Beijing and the influence of agricultural biomass burning. Atmospheric Chemistry and Physics.2010,10:8119-8130.
[162]张军华.地面和卫星遥感中国地区气溶胶光学特性[博士].北京：北京大学,2000.
[163]李晓静,刘玉洁,红邱.,et al.利用MODIS资料反演北京及其周边地区气溶胶光学厚度的方法研究.气象学报.2003,5(61)：580-591.
[164]李成才MODIS遥感气溶胶光学厚度及应用于区域环境大气污染研究[博士].北京：北京大学,2002.
[165]唐洪钊,晏磊,李成才,et al.基于MODIS高分辨率气溶胶反演的ETM+影像大气校正.地理与地理信息科学.2010,26(4)：12-15.
[166]王宏,石广玉,T.Aoki, et al.2001年春季东亚-北太平洋地区沙尘气溶胶的辐射强迫.科学通报.2004,49(19)：1993-2000.
[167]Khalizov A. F., Xue H. X., Wang L., et al. Enhanced Light Absorption and Scattering by Carbon Soot Aerosol Internally Mixed with Sulfuric Acid. Journal of Physical Chemistry A.2009,113(6):1066-1074.
[168]Lesins G., Chylek P., Lohmann U. A study of internal and external mixing scenarios and its effect on aerosol optical properties and direct radiative forcing. Journal of Geophysical Research-Atmospheres.2002,107(D10):4094, doi: 10.1029/2001JD000973.
[169]Ma N., Zhao C. S., Muller T., et al. A new method to determine the mixing state of light absorbing carbonaceous using the measured aerosol optical properties and number size distributions. Atmospheric Chemistry and Physics.2012,12(265):2381-2397.
[170]Sportisse B. Fundamentals in Air Pollution. New York:Springer.2008.
[171]Kaaden N., Massling A., Schladitz A., et al. State of mixing, shape factor, number size distribution, and hygroscopic growth of the Saharan anthropogenic and mineral dust aerosol at Tinfou, Morocco. Tellus Series B-Chemical and Physical Meteorology.2009, 61(1):51-63.
[172]Naoe H., Hasegawa S., Heintzenberg J., et al. State of mixture of atmospheric submicrometer black carbon particles and its effect on particulate light absorption. Atmospheric Environment.2009,43(6):1296-1301.
[173]Zhang X. Y., Wang Y. Q., Niu T., et al. Atmospheric aerosol compositions in China:spatial/temporal variability, chemical signature, regional haze distribution and comparisons with global aerosols. Atmospheric Chemistry and Physics.2012,12(2): 779-799.
[174]Bohren C. F., Huffman D. R. Absorption and Scattering of light by small particle. New York:Wiley.1998.
[175]Carlson T., Caverly R. Radiative Characteristics of Saharan Dust at Solar Wavelengths. Transactions-American Geophysical Union.1977,82(21):3141-3152.
[176]Patterson E. M., Gillette D. A., Stockton B. H. Complex Index of Refraction between 300 and 700 Nm for Saharan Aerosols. Journal of Geophysical Research-Oceans and Atmospheres.1977,82(21):3153-3160.
[177]Todd M. C., Washington R., Martins J. V., et al. Mineral dust emission from the Bodele Depression, northern Chad, during BoDEx 2005. Journal of Geophysical Research-Atmospheres.2007,112(D6), doi:10.1029/2006JD007170.
[178]d'Almeida G. A., Koepke P., Shettle E. P. Atmospheric Aerosols:Global Climatology and Radiative Characteristics. VA:A.Deepak Publishing.1991.