Dust source identification using MODIS: A comparison of techniques applied to the Lake Eyre Basin, Australia

The impact of mineral aerosol (dust) in the Earth's system depends on particle characteristics which are initially determined by the terrestrial sources from which the sediments are entrained. Remote sensing is an established method for the detection and mapping of dust events, and has recently been used to identify dust source locations with varying degrees of success. This paper compares and evaluates five principal methods, using MODIS Level 1B and MODIS Level 2 aerosol data, to: (a) differentiate dust (mineral aerosol) from non-dust, and (2) determine the extent to which they enable the source of the dust to be discerned. The five MODIS L1B methods used here are: (1) un-processed false colour composite (FCC), (2) brightness temperature difference, (3) Ackerman's (1997: J.Geophys. Res., 102, 17069-17080) procedure, (4) Miller's (2003:Geophys. Res. Lett. 30, 20, art.no.2071) dust enhancement algorithm and (5) Roskovensky and Liou's (2005: Geophys. Res. Lett. 32, L12809) dust differentiation algorithm; the aerosol product is MODIS Deep Blue (Hsu et al., 2004: IEEE Trans. Geosci. Rem. Sensing, 42, 557-569), which is optimised for use over bright surfaces (i.e. deserts). These are applied to four significant dust events from the Lake Eyre Basin, Australia. OMI AI was also examined for each event to provide an independent assessment of dust presence and plume location. All of the techniques were successful in detecting dust when compared to FCCs, but the most effective technique for source determination varied from event to event depending on factors such as cloud cover, dust plume mineralogy and surface reflectance. Significantly, to optimise dust detection using the MODIS L1B approaches, the recommended dust/non-dust thresholds had to be considerably adjusted on an event by event basis. MODIS L2 aerosol data retrievals were also found to vary in quality significantly between events; being affected in particular by cloud masking difficulties. In general, we find that OMI AI and MODIS AQUA L1B and L2 data are complementary; the former are ideal for initial dust detection, the latter can be used to both identify plumes and sources at high spatial resolution. Overall, approaches using brightness temperature difference (BT10-11) are the most consistently reliable technique for dust source identification in the Lake Eyre Basin. One reason for this is that this enclosed basin contains multiple dust sources with contrasting geochemical signatures. In this instance, BTD data are not affected significantly by perturbations in dust mineralogy. However, the other algorithms tested (including MODIS Deep Blue) were all influenced by ground surface reflectance or dust mineralogy; making it impossible to use one single MODIS L1B or L2 data type for all events (or even for a single multiple-plume event). There is, however, considerable potential to exploit this anomaly, and to use dust detection algorithms to obtain information about dust mineralogy.     

用高速光器件分析仪测试高增益CATV光站

介绍了使用安捷伦50Ω高速光器件分析仪测试75Ω高增益CATV接收光站的原理和方法。着重解决了测试过程中遇到的测试设备与被测产品阻抗不匹配问题和被测产品增益过高问题。对于阻抗不匹配问题,采用光器件分析仪的去嵌入功能实现50Ω和75Ω间的匹配;对于增益过高问题,采用降低光器件分析仪的光调制度方法来降低光站增益。从实验结果分析,两种解决方法完全可行,并且不会引入测试误差。     

A multi-sensor comparison of sulphur dioxide emissions from the 2005 eruption of Sierra Negra volcano, Galápagos Islands

Sulphur dioxide retrievals of three satellite-based sensors (the Total Ozone Mapping Spectrometer, the Ozone Monitoring Instrument and the Moderate Resolution Imaging Spectroradiometer) were performed on the volcanic cloud from the Sierra Negra, Galápagos Islands eruption of October 22 to October 30, 2005. Near-coincidental plume acquisitions on 23 October from each of the sensors were compared spatially on a pixel-by-pixel basis in order to assess the level of agreement between the retrievals. The variation in pixel size and shape between sensors was accounted for by resampling MODIS data to the geometry of the UV sensors.It was found that correlations between retrievals were wide ranging with estimates of total tonnage ranging from 60 kt up to 1800 kt. Spatial comparisons show variation according to plume altitude and overpass time and are compounded by interference from other volcanic species as well as individual instrument error.The comparison of these sensors provides an insight into the relative merits of each method and illustrates the usefulness of a holistic approach to satellite remote sensing of sulphur dioxide. This will permit the development of more robust retrieval schemes and therefore increasingly reliable estimations of volcanic SO₂ emissions.     

遥感监测2005~2015年中国NO2时空特征及分析影响因素

基于OMI对流层NO²柱浓度产品研究了2005~2015年中国及各省(市、区)NO²时空变化及影响因素:①中国对流层NO²柱浓度2005~2009年波动较小,2010~2011年升幅较大,2012年较2011年有所下降,2013年与2012年持平,2014、2015年持续大幅下降;②中国NO²高浓度分布面积11年来变化显著,五级高浓度分布面积2005~2011年呈显著上升趋势,2011年面积最大为37.2万km²;2011~2013年波动较小;2014~2015年呈直线下降趋势,2015年降低到6.1万km²;③上海、天津两市对流层NO²柱浓度处于五级高浓度水平,其中上海是中国浓度最高的城市,山东是中国浓度最高的省;④对流层NO²柱浓度的变化与第二产业生产总值相关性很大,需要调整优化产业结构降低第二产业比重才能得到改善;长期依赖燃煤高污染的能源结构也是导致NO²浓度居高不下的一个重要原因,亟需开发新能源以替代煤燃料等各种办法;机动车保有量快速增加,汽车标准及油品跟不上国际发展水平,导致NO²排放量大增。     

一种基于OMI数据的中国区域对流层O3的反演方法

近年来, 臭氧成为我国各大城市大气的首要污染物, 因此对流层臭氧产品对于监测近地面臭氧浓度十分重要, 然而现有的对流层臭氧产品不能满足高空间分辨率、高时间分辨率的监测要求.利用时空拟合法对臭氧监测仪(OMI)臭氧总量数据进行修复, 再根据对流层臭氧残差法反演中国区域的对流层臭氧总量数据, 其结果表明: 从定性的角度考虑, 时空拟合法具有更好的修复效果, 从定量的角度考虑, 时空拟合法相对于克里金插值法和反距离加权法的RMSE、MAE均较小.利用对流层臭氧残差法得到的对流层臭氧廓线数据与OMI/MLS的官方臭氧产品有着较高的相关性, 其相关系数R最高为0.82.     

A swing arm method for profile measurement of large optical concave surfaces in the lapping process

Generally, optical components are fabricated by grinding, lapping, and polishing. Usually, these processes take a long time to obtain high surface quality. Therefore, in the case of large optical components, on-machine inspection (OMI) is essential, because the workpiece is fragile and difficult to set up for fabricating and measuring. This paper describes a swing arm method for measuring the surface profile of large optical concave mirrors. The measuring accuracy and uncertainty for the method are studied. Experimental results show that this method is especially useful in the lapping process, where an accuracy of 3–5 μm is obtained. Inspection data is also provided to correct the residual figuring error in lapping or polishing processes .     

Analysis of the Spatial and Temporal Distribution Variatio of Formaldehyde by the OMI Satellite Sensor

In recent years，the atmospheric environmental issues become increasingly significant.Formaldehyde (HCHO) as a kind of carcinogen，its global testing to understand the spatial and temporal distribution and content in the atmosphere，has important significance for the detection of air quality and public safety.The study on the use of satellite AURE mounted OMI (Ozone Monitoring Instrument) a new generation of atmospheric detection sensors，data for the 2005~2014 January，April，July，October Tianshui vertical columns of tropospheric HCHO concentrations of trace data for each year.By VISON，GIS and other software combined with the product handling，explores the spatial distribution of Tianshui area HCHO，the time variation and their influencing factors.The results show that: the study area，the vertical columns of tropospheric HCHO concentration in 2005 showing sustained growth trend in 2012，2012~2014 chronology exhibit significantly decreased;winter and summer HCHO vertical column concentrations significantly higher than the spring and autumn，which highest in summer and winter followed; the eastern part of the study area and adjacent areas in Shanxi\|parts of Gangu County，Wushan County，exhibits a significantly higher value and lower central region of HCHO Tianshui vertical column density，and in 2014 the performance of HCHO concentration in the study area values are generally higher.Studies have shown that remote sensing is important for large\|scale atmospheric environmental monitoring.     

基于OMI数据的兰州及附近地区大气边界层SO2量值变化初步分析

环境遥感是遥感技术应用的重要领域。随着高光谱遥感技术和定量遥感理论的发展,利用OMI、MODIS等数据开展大气SO²分布的研究得到关注。OMI是新一代大气成分探测传感器,其痕量数据产品OMSO²在反演大气SO²量值中有较好的效果。选取2005年2、5、8、11月及2005~2008年各年2月每日的OMI Level-2痕量数据,采用遥感和GIS方法,对兰州及附近地区大气边界层SO²空间分布、季节变化和冬季年际变化进行了分析。结果表明:研究区内SO²量值呈离散面状分布,兰州-白银、金昌是两个明显的高值区;冬季SO²量值明显高于其他季节,年际变化波动比较明显。研究表明,利用OMI Level\|2痕量数据产品,能够对较大尺度范围人类活动排放SO²状况进行检测和评估。     

基于MAX-DOAS 的淮北地区NO2柱浓度观测研究

基于多轴差分吸收光谱技术 (MAX-DOAS) 反演 NO2 柱浓度的方法, 构建了相应的地基 MAX-DOAS 系统, 开 展了 NO2 柱浓度变化特征的观测。反演中选取天顶方向的光谱作为参考光谱, 通过非线性最小二乘法反演出 NO2 斜柱浓度 (SCD), 结合不同观测方向的斜柱浓度得到 NO2 差分斜柱浓度 (dSCD), 再利用几何近似法得到大气质量 因子 (AMF), 最终获取 NO2 垂直柱浓度 (VCD)。于 2019 年 6 月至 2020 年 5 月在淮北地区开展了为期一年的外场 实验, 研究结果表明淮北地区 NO2 VCD的月均值在观测期间内呈现倒“U”型变化, 在 12 月份达到最高值 2.13×1016 molecules·cm−2, 在 8 月份达到最低值 5.23×1015 molecules·cm−2。将 MAX-DOAS 观测结果的日均值与 OMI 卫星 (云 系数分别为 0 < FeC ≤ 0.1 和 0 < FeC ≤ 0.3) 测量结果进行对比, 发现两者具有较好的相关性 (R2 = 0.88, R2 = 0.90), 表明 MAX-DOAS 不仅可以准确反演出 NO2 垂直柱浓度, 还可以验证卫星数据。     

Assessment of NO2 satellite observations for en-route aircraft emissions detection

In this work we examine the possibility of using satellite remote sensors for the detection of air traffic emissions produced during the en-route segment of flight in the Upper Troposphere/Lower Stratosphere region (8000-12,000 m). NO₂ has been considered as the tracer of aircraft plumes with highest possibility of being successfully detected from space. An analysis of the technical potential of the current orbital sensors capable of measuring NO₂ in the proximity of the tropopause has been conducted. In order to estimate an upper bound for the NO₂ column related to aircraft emissions, the Canary Islands Corridor has been selected for conducting a simple emission calculation exercise based on real air traffic and operational data, assuming an ideal atmospheric scenario. The results obtained in this approximation have been compared to the actual information retrieved from space sensors. An in-depth inspection of the NO₂ column data for two particular areas (Canary Islands Corridor and North Atlantic Flight Corridor) obtained in recent years by SCIAMACHY and OMI has also been carried out.The general conclusions of this viability study are not optimistic. The estimated maximum NO₂ column value attributable to aircraft emissions at cruise altitudes were lower than the detection limits associated with SCIAMACHY and OMI for NO₂ column measurements. As a result, detecting and quantifying the actual NO₂ levels in aircraft corridors by space remote sensing is a very challenging task.