基于PSO-BP神经网络的气溶胶质量浓度测量系统湿度补偿

气溶胶质量浓度是衡量大气质量的一项关键性指标.在基于单粒子光散射的气溶胶质量浓度测量时,环境湿度变化对其影响较大.尤其在湿度较高时,颗粒物的外貌特征和折射率都会发生相应变化,采用低湿度条件下系统的标定参数来反演气溶胶质量浓度会产生较大误差.考虑以上原因,提出建立基于粒子群优化的BP神经网络补偿模型对不同湿度条件下的测量结果进行数据融合修正.实验结果表明,经过PSO-BP神经网络湿度补偿后,相对湿度较高时引起的测量误差约从原来的-10%~-45%减小为-5%~-30%,整体平均相对误差减小了10%,说明该方法削弱了相对湿度对气溶胶质量浓度测量系统的影响,有效提高了系统的测量精度.     

动态光散射测量超细颗粒实验系统仿真

由于进行动态光散射超细颗粒大小测量实验困难.为准确测量,利用多尺度的小波变换技术,提出了一种小波变换的动态光散射信号的模拟方法,建立了一个测量超细颗粒的实验仿真系统.首先,系统采用小波变换的信号模拟方法获取动态光散射信号,然后,利用AR模型谱估计方法对模拟信号进行功率谱计算,最终采用非线性最小二乘法对功率谱进行拟合反演出粒径,从而实现了颗粒测量实验系统的仿真.采用该系统,对100nm及500hm颗粒测量实验进行了仿真,仿真测量的粒径反演误差分别为1.22％及0.82％,满足国标误差要求.因此,改进系统用于动态光散射测量超细颗粒实验仿真是可行的,为动态光散射技术的研究提供了一种简易、便捷的实验方法.     

JFC-1激光粉尘浓度测量仪

利用粉尘颗粒的光散射原理实时测量粉尘相对质量浓度（单位：mg/m^3），即散射光强度与粉尘质量浓度（或体积）成正比；是“滤膜采样-称重法”的更新换代产品，是与国外先进测量手段接轨的重要测量仪器。     

基于MATLAB的激光警戒方法研究

在大面积激光警戒中,主要是探测被大气散射的光。气溶胶对激光的散射作用远大于大气分子。本文介绍了Mie散射理论和城市气溶胶的质量浓度谱分布,在此基础上,运用Mie散射理论,对城市气溶胶进行了散射光强计算,计算结果表明,处于1.0μm峰值的气溶胶粒子散射的光强远大于处于4.5μm峰值的气溶胶粒子所散射的光强。     

基于LabVIEW的光子信号高速采集与分析

纳米颗粒散射光信号的获取是利用动态光散射技术分析纳米颗粒粒径的基础。介绍了由嵌入式控制器和高速数据采集卡组成的高速采集装置,讨论了在基于虚拟仪器软件平台的程序设计中遇到的有关光子信号的高速采集、存储、显示回放、计数和时间间隔判断等问题;通过与动态光散射仪在相同条件下采集到的1 s内的光子数进行对比,得到了更能反映纳米颗粒散射光子信号的结果,为今后利用这些结果进行光子信号的相关分析提供了可靠的依据,也能为高速光子信号的接收提供有用的参考。     

基于分形维数的雷达信号脉内调制方式识别

分形维数是分形理论中的重要参数,其中盒维数可以描述分形信号的几何尺度信息,信息维数描述分形信号在平面空间上的分布信息。因此利用分形理论从信号中提取盒维数和信息维数作为分类特征,这种特征可包含信号幅度、频率和相位的变化规律,并集中了不同调制信号之间的差异信息。通过计算若干种常见脉内调制雷达辐射源信号的盒维数与信息维数,表明了分形维数在分类意义上是有效的特征。并由分类识别的仿真实验验证了基于分形维数进行的分类具有较高的识别率。     

气溶胶光学厚度、类型及廓线对CO2反演的敏感性分析

位于1.6和2.06 μm附近的短波红外波段可用于探测低层大气CO²信息,然而除大气分子(主要是CO²)吸收外,大气分子散射、气溶胶和云散射也是限制这些波段的卫星测量信号的主要因素,因此气溶胶光学参数及其垂直分布也必然制约着GOSAT(Greenhouse Gases Observing Satellite)CO²的反演精度。利用正演模式DISORT分析气溶胶光学厚度(AOD)、类型以及廓线对CO²反演精度的敏感性,旨在提高CO²反演精度。结果表明:①不同类型气溶胶AOD增大对CO²柱总量的影响各不相同,且CO²柱总量变化量的变化趋势也不相同,这取决于气溶胶的散射相函数与单次散射反照率的大小;②气溶胶类型变化会导致CO²柱总量变化,且这种变化随着AOD增大而增大;③对于满足指数分布的沙尘气溶胶,标高的低估会导致反演的CO²柱总量偏大,而气溶胶的集中分布导致反演的CO²柱总量偏小,且气溶胶层越高,反演的CO²柱总量越小。     

基于氧气A吸收带高光谱反射信息的气溶胶廓线反演算法及模拟反演验证

为反演对流层气溶胶消光系数廓线,提出了一种新的、基于氧气A光谱吸收带高光谱反射信息的反演方法。这种方法在经典的线性约束反演算法的基础上引入了两个与气溶胶柱光学厚度相关的订正因子,通过实现目标廓线和反演廓线的光学柱厚度差异最小,进而动态选择拉格朗日系数。为验证新方法的有效性和精度,借助了CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations)气溶胶廓线产品和高光谱辐射传输模拟,模拟反演海洋下垫面晴空和沙尘两种情景下气溶胶消光系数廓线,结果表明新的方法能够比较准确地获得对流层内气溶胶廓线的数值,尤其在多次散射比较强的沙尘条件下,相对误差能够控制在51%以下;在晴空时,相对误差能够控制在20%以下。如果加入订正信息,反演精度能够进一步提高。     

基于内源光信号的纤维光学内镜设计

内镜检查是临床消化道疾病诊疗的最主要手段,其功能是获取组织的结构信息。在消化道疾病的发生和发展过程中通常伴随着功能信息如血氧及与代谢相关参数的改变。论文基于内源光信号成像技术开发了一套纤维光学内镜系统,能够测量生物组织氧合血红蛋白、脱氧血红蛋白、细胞色素C、细胞色素氧化酶、黄素腺嘌呤二核苷酸（Flavin adenine dinucleotide, FAD）和散射特性等6种功能信息的变化量。设计注射过量亚硝酸钠（800 mg/kg）的小鼠实验,利用所设计的纤维光学内镜成功获得了注射药物3、6、9、12、15以及18 min后同视野、在体的血氧及与代谢相关参数图像。实验模型的氧合血红蛋白含量持续减少,脱氧血红蛋白的含量持续增加。研究表明内源光信号的纤维光学内镜系统能够准确反映生物组织功能信息的变化规律。     

尘埃粒子检测仪校正系统的改进

一、引言 目前,国内外检测洁净环境中尘埃颗粒的仪器,即尘埃粒子计数器,是以尘埃粒子在白光束或激光束中产生的光散射现象为原理(见图1)。当空气中的尘埃粒子随采样气流穿过光敏感区时,就会产生与其粒径相关的散射光脉冲,其中的一部分散射光被收集并投射于光电倍增管或半导体光敏器件。这样,便将散射光脉冲信号变为相应的电脉冲信号。信号处理系统将电脉冲信号放大,并经幅度甄别器分档,再由机内微处理器处理,最后得到各档粒径的尘埃粒子数。     

Retrieval and analysis of aerosol optical characteristics in Hubei Province,China, based on CALIPSO

The aerosol optical characteristics in Hubei Province, China, derived from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), are investigated. Through this spaceborne lidar, some limitations of airborne and ground-based systems can be overcome and a global survey of clouds and aerosol can be provided. First, a lidar ratio selection algorithm is introduced. Since the lidar ratio (the aerosol extinction-to-backscatter ratio, S _a) is an important parameter used in aerosol retrieval, it is required for a reliable aerosol model. After retrieving the original signal, aerosol optical parameters are obtained. Based on these steps, the impacts of atmospheric motion on aerosol diffusion in different layers, the distribution of these aerosols, as well as their time-changing characteristic in Hubei Province are discussed. The studies show that in areas of plains aerosols are easily influenced by wind; furthermore, aerosol distribution in the western Hubei Province is usually influenced by biomass burning and in eastern Hubei by industrial emission. Although errors still exist, the aerosol optical characteristics in different regions are strongly related to the ground surface, wind direction and visible distinctions exist in urban and country areas.     

Retrieval of microphysical and optical properties in aerosol plumes with hyperspectral imagery: L-APOM method

This paper presents the retrieval method L-APOM which aims at characterizing the microphysical and optical properties of aerosol plumes from hyperspectral images with high spatial resolution. The inversion process is divided into three steps: estimation of the ground reflectance below the plume, characterization of the standard atmosphere (gases and background aerosols) and estimation of the plume aerosols properties. As using spectral information only is not sufficient to insure uniqueness of solutions, original constraints are added by assuming slow spatial variations of particles properties within the plume. The whole inversion process is validated on a large set of simulated images and reveals to remain accurate even in the worst cases of noise: relative estimation errors of aerosol properties remain between 10% and 20% in most cases. L-APOM is applied on a real AVIRIS hyperspectral image of a biomass burning plume for which in situ measurements are available. Retrieved properties appear globally consistent with measurements.     

Optical–microphysical properties of smoke haze from Siberian forest fires in summer 2012

A comprehensive experiment on the study of dynamics of optical and microphysical characteristics of submicron aerosols in the near-ground air layer was carried out in June–August of 2012 under conditions of extremely strong smoke haze originating from vast forest fires in Siberia. Variations of the spectral angular scattering coefficients and the degree of linear polarization in the visible wavelength range are studied, as well as the mass concentrations of dry fractions of aerosol and black carbon, relative content of black carbon (BC fraction), single scattering albedo, particle size distribution function, complex refractive index of the particulate matter, and parameter of condensation activity of aerosol. Peculiarities of differences between optical and microphysical characteristics of near-ground aerosol in smoke haze and under smokeless conditions are revealed. This study is important for validation of results of remote sensing of the composition of smoke haze and background atmosphere obtained from satellite data and sun photometric measurements at the Aerosol Robotic Network (AERONET).     

A multiple scattering algorithm for atmospheric correction of remotely sensed ocean colour (MERIS instrument): Principle and implementation for atmospheres carrying various aerosols including absorbing ones

A multiple scattering algorithm for atmospheric correction of satellite ocean colour observations is described. This algorithm, precisely designed for the MERIS instrument, globally assesses the combined contributions of aerosols and molecules to the multiple scattering regime. The approach was introduced in a previous work, where it was shown that, for a given aerosol, multiple scattering effects can be assessed through the relationship between the aerosol optical thickness and the relative increase in the path radiance that results from the progressive introduction of this aerosol within an aerosol-free atmosphere. Based on considerations about the accuracy to which the water-leaving radiances should be retrieved, the need to account for multiple scattering is argued. The principle of the algorithm is then presented, and tests and sensitivity studies (especially as regards aerosol type and vertical distribution) are performed to assess its performance in terms of errors on the retrieved water-leaving reflectances and pigment concentrations. The algorithm is able to perform the correction for atmospheres carrying several aerosol types, including absorbing ones, through their identification in the near-infrared, and through the detection of their absorption by means of appropriate assumptions on the marine signals at 510 and 705nm.     

A deep-learning model for the amplitude inversion of internal waves based on optical remote-sensing images

The amplitude of internal waves is an important parameter for the remote-sensing detection. However, there is no analytic method developed for the amplitude inversion of internal waves based on optical remote-sensing images. In this article, the deep-learning model is introduced to inverse the amplitude of internal waves based on a large number of optical remote-sensing images. The peak-to-peak distance and 15 types of texture characteristic parameters of images are computed, and the relationship between the amplitude of internal waves and the characteristic parameters of remote-sensing images are also investigated. In addition, based on the correlation difference between these parameters and the amplitude, three types of deep-learning model are established by selecting different parameters as input variables. Results show that the inverted amplitude of internal waves from our models shows good agreement with the in-situ data of internal waves, and the average errors between them are about 6.7%, 4.9%, and 3.6%, respectively, which indicates that the deep-learning model is effective for amplitude inversion of internal waves based on optical remote-sensing images.     

2008~2016年MODIS多角度大气校正气溶胶产品在中国的时空分布及变化趋势

探究全国大气气溶胶分布及变化特征,准确了解中国地区气溶胶光学特性对研究大气环境污染、应对全球气候变化是非常重要的。对2008~2016年的MODIS MAIAC气溶胶光学厚度数据在中国的适用性进行验证,并采用Mann-Kendall方法,从不同的时空尺度和气溶胶类型上分析中国地区AOD值的时空变化特征。结果表明：①验证表明C6的MAIAC反演结果在中国AERONET匹配点上表现良好,C6的MAIAC反演AOD结果适用于中国区域;②从年际尺度上看,2008~2016年AOD年均值整体呈波动下降;从季节尺度上看,AOD季节变化呈春季整体高、夏季中心高、秋冬季水平低的特点,各省AOD平均值及各省份划区AOD平均值随季节变化趋势相似。③在空间上,AOD呈东南高、西北低、高值中心聚集的特征。④中国AOD变化整体呈现出东部减少且集聚,西部增加且分散的变化特征。可进一步探究不同种类气溶胶分布和气溶胶与典型大气污染物分布关系,以期为中国环境污染治理提供更好的决策指导。     

Aerosol optical depth spatio-temporal characterization over the Canadian BOREAS domain

A complete set of Advanced Very High Resolution Radiometer (AVHRR) data (75 images) is used to retrieve aerosol optical depth (AOD) over dense vegetation and over lake water in the visible AVHRR channel. The present approach for remote sensing of aerosols from the National Oceanic and Atmospheric Administration (NOAA)-11 AVHRR sensor is based on the detection of atmospherically dominated signals over dark surface covers such as dense dark vegetation (DDV). Such targets were identified using the reflective portion of the middle-wave AVHRR channel 3 signal. When a fixed DDV surface reflectance is subtracted from the observed reflectance after correction for all other atmospheric effects, the remaining part, which is due to aerosols, is inverted to derive aerosol optical thickness using a look-up table (LUT) similar to that used in water surface inversion. The algorithm was applied to the daily afternoon NOAA-11 AVHRR (1?km×1?km) data acquired from the end of May to mid-August 1994 over the Canadian 1000?km×1000?km Boreal Ecosystem Atmosphere Study (BOREAS) domain. A validation analysis using five ground-based Sun photometers within the studied area shows the good performance of the retrieval algorithm. The approach allows detailed analysis of the AOD spatio-temporal behaviour at the regional scale useful for climate and transport model validation.     

Algorithms for aerosol retrieval based on scattering calculations

This paper focuses on how to determine an accurate aerosol model based on simulations of light scattering. Our algorithms come from an idea that aerosol characteristics can be estimated in terms of the scattering behavior. The correlation coefficients between measurements of atmospheric aerosols and the simulated values for model particles are used to retrieve aerosol characteristics.The space-borne data by Nimbus7-CZCS at a wavelength 0.67 μm and the photopolarimetric measurements of aerosols with a portable photopolarimeter (FPR2000) at wavelengths of 0.559, 0.662, and 0.811 μm are examined in this work. It is shown here that aerosol models are precisely determined by combining use of polarization measurements and radiance data.     

The effect of aerosol vertical profiles on satellite-estimated surface particle sulfate concentrations

The aerosol vertical distribution is an important factor in determining the relationship between satellite retrieved aerosol optical depth (AOD) and ground-level fine particle pollution concentrations. We evaluate how aerosol profiles measured by ground-based lidar and simulated by models can help improve the association between AOD retrieved by the Multi-angle Imaging Spectroradiometer (MISR) and fine particle sulfate (SO4) concentrations using matched data at two lidar sites. At the Goddard Space Flight Center (GSFC) site, both lidar and model aerosol profiles marginally improve the association between SO4 concentrations and MISR fractional AODs, as the correlation coefficient between cross-validation (CV) and observed SO4 concentrations changes from 0.87 for the no-scaling model to 0.88 for models scaled with aerosol vertical profiles. At the GSFC site, a large amount of urban aerosols resides in the well-mixed boundary layer so the column fractional AODs are already excellent indicators of ground-level particle pollution. In contrast, at the Atmospheric Radiation Measurement Program (ARM) site with relatively low aerosol loadings, scaling substantially improves model performance. The correlation coefficient between CV and observed SO4 concentrations is increased from 0.58 for the no-scaling model to 0.76 in the GEOS-Chem scaling model, and the model bias is reduced from 17% to 9%. In summary, despite the inaccuracy due to the coarse horizontal resolution and the challenges of simulating turbulent mixing in the boundary layer, GEOS-Chem simulated aerosol profiles can still improve methods for estimating surface aerosol (SO4) mass from satellite-based AODs, particularly in rural areas where aerosols in the free troposphere and any long-range transport of aerosols can significantly contribute to the column AOD.