3D Aerosol LIDAR
三維氣溶膠激光雷達
（型號：ESS-D200）

1、設備簡介
       希臘Raymetrics氣溶膠激光雷達系統采用世界***進的激光雷達制造工藝，利用不同波段激光信號探測大氣氣溶膠、水汽等垂直闊線，可以實時探測能見度和云底高度等，結合3D掃描技術，可以探測污染物的濃度分布及來源。探測包括氣溶膠、能見度、水汽、火山灰、煙霧、污染來源、云底高度、邊界層高度、光學厚度、消光系數、后向散射系數、色比等。
       其客戶遍布美國、中國、印度、歐洲、南亞、非洲和南美等地區，應用單位包括中國科學院、美國氣象局、英國氣象局、韓國氣象局、空管局、歐空局、德國宇航中心、北京大學、南京大學等，應用領域包括氣象、環境、航空、軍事等科研和應用等。
        希臘Raymetrics可以根據用戶實際需要進行量身定制，例如，ESS-D200型激光雷達用于探測霧、能見度及污染物來源等；ESS-D300型激光雷達則用于探測火山灰、氣溶膠及邊界層高度等；ESS-D400型激光雷達則用于探測水汽濃度垂直闊線等。在這些應用中，可以根據探測的范圍和內容，定制激光器的功率、激光波長、交叉極化波長、拉曼、鏡頭尺寸等，掃描模式也可以選擇垂直觀測或三維掃描等方式。

       產品通過ISO 9001:2008體系，性能及指標滿足歐洲氣溶膠研究激光雷達觀測網（EARLINET）需求，自2012年以來參與了上百個大型科學研究計劃，在大氣科學、天氣預報、環境治理、航空氣象、空間科學等領域發揮了***貢獻。
       ESS-D200型三維掃描氣溶膠激光雷達，擁有大功率激光器、大口徑望遠鏡及全3D掃描方式，可以為航空環境預報及預警提供重要的氣象參數，探測要素包括：能見度、霧、污染物來源及云底高度等，是市場上***秀的氣溶膠雷達系統。


2、ESS-D200雷達主要功能
（1）能見度監測：
       該雷達系統可以提供斜視能見度（SVR），與跑道能見度（RVR）相比，斜視能見度更能真實的反映飛行員的視覺感受。





















（2）云底高度監測：
該雷達系統可以提供三維空間云底高度，可以更真實的反映整個機場上空云的三維分布，而普通的云高儀采樣空間僅為其頭頂上方狹小的區域。
 （3）霧霾監測：該雷達系統可以監測平流霧的分布、動向及來源，可以為航空預警提供預報服務。
 （4）氣溶膠類型甄別：      該雷達系統可以區分火山灰氣溶膠、天然灰塵、煙霧、海洋氣溶膠、冰云、水云等成分，為航空環境預警提供有力技術保障。

 3、ESS-D200雷達輸出產品
氣溶膠、氣溶膠類型、能見度、云底高度、邊界層高度、光學厚度、消光系數、后向散射系數、色比等。3D掃描方式，探測距離10-15km，可以為航空環境預報及預警提供重要的氣象參數。

4、ESS-D200雷達主要特點
（1）激光能量：在355nm單脈沖能量可達~30mJ；
（2）200mm大口徑望遠鏡，有效提升信號效率；
（3）的信噪比，探測距離可達10~15km；
（4）系統可以全自動遠程控制；
（5）系統包含標準軟件包：雷達控制、數據分析和實時顯示及存儲。
（6）符合歐盟標準人眼安全等級60825-1:2007；
（7）兼容歐洲氣溶膠研究激光雷達觀測網（EARLINET）要求；
（8）品質保證：ISO9001:2008管理體系；
（9）應用領域：氣象、環境、航空、軍事、科學研究等。  4技術指標：
掃描范圍：10-15km
標準檢測波長：355 nm co-polar
可拓展監測波段：355 nm cross-polar
                              387 nm nitrogen Raman
分辨率：7.5m
采樣時間分辨率：1秒或者10秒等多種采樣方式
FWHM 帶寬近似：～0.5 nm per wavelength
激光能量：30MJ/每脈沖@355nm
重復率：20Hz
光束擴展：X10
檢測模式：近場和遠場測量的模擬和光子計數
3D掃描范圍：方位角0～357°；天頂角0～90°
內部PC：工業級PC運行窗口
氣候控制：激光雷達頭和控制單元的加熱和空調單元
軟件功能：儀表控制、測量調度、系統對齊和設置程序、數據采集、數據存儲（數據庫）、數據分析、數據可視化
尺寸（主鏡）：200毫米
視場（FOV）：0.25至3 MRAD（用戶可調）
重疊：＜200 m（帶工廠設置FOV）
電源：110 - 240 V, 50 - 60 Hz    
功耗：25 Amps.
尺寸：約1.8 m×1 m×1 m（HXWXD）
重量：約220公斤
自動化：自動化提供遠程可操作的測量調度
保修：1年為標準
技術配件和維護：3天現場安裝培訓課程標準 

5、ESS-D200應用例子
[1] de Miranda, R.M., et al. (2017): The relationship between aerosol particles chemical composition and optical properties to identify the biomass burning contribution to fine particles concentration: a case study for S?o Paulo city, Brazil, Environ Monit Assess, 189: 6. https://doi.org/10.1007/s10661-016-5659-7
 
[2] Gouveia, D. A., et al. (2017): Optical and geometrical properties of cirrus clouds in Amazonia derived from 1 year of ground-based lidar measurements, Atmos. Chem. Phys., 17, 3619-3636, https://doi.org/10.5194/acp-17-3619-2017
 
[3] Dorman C.E. (2017): Early and Recent Observational Techniques for Fog. In: Kora?in D., Dorman C. (eds) Marine Fog: Challenges and Advancements in Observations, Modeling, and Forecasting. Springer Atmospheric Sciences. Springer, Cham
 
[4] Chilinski, M.T., et al. (2016): Modelling and Observation of Mineral Dust Optical Properties over Central Europe, Acta Geophys. 64: 2550. https://doi.org/10.1515/acgeo-2016-0069
 
[5] Guerrero-Rascado, J. L., and Coauthors (2016): Latin American Lidar Network (LALINET) for aerosol research diagnosis on network instrumentation. J. Atmos. Sol.-Terr. Phys., 138–139, 112–120, doi:https://doi.org/10.1016/j.jastp.2016.01.001.
 
[6] George Georgoussis et al. (2016): Signal to Noise Ratio Estimations for a Volcanic Ash Detection Lidar. Case Study: the Met Office, EPJ Web of Conferences 119, 07002, DOI: 10.1051/epjconf/
 
[7] F. Tan et al. (2015): Monsoonal variations in aerosol optical properties and estimation of aerosol optical depth using ground-based meteorological and air quality data in Peninsular Malaysia, Atmos. Chem. Phys., 15, 3755–3771, 2015, doi:10.5194/acp-15-3755-2015
 
[8] Mbengue, S., Alleman, L.Y. & Flament, P. (2015): Bioaccessibility of trace elements in fine and ultrafine atmospheric particles in an industrial environment, Environ Geochem Health, 37: 875. https://doi.org/10.1007/s10653-015-9756-2
 
[9] Rose, C., et al. (2015): Major contribution of neutral clusters to new particle formation at the interface between the boundary layer and the free troposphere, Atmos. Chem. Phys., 15, 3413-3428, https://doi.org/10.5194/acp-15-3413-2015
 
[10] Barbosa, H. M. J., et al (2014): A permanent Raman lidar station in the Amazon: Description, characterization and first results. Atmos. Meas. Tech., 7, 1745–1762, doi:https://doi.org/10.5194/amt-7-1745-2014.
 
[11] Granados-Mu?oz, M. J., et al. (2014): Retrieving aerosol microphysical properties by Lidar-Radiometer Inversion Code (LIRIC) for different aerosol types, J. Geophys. Res. Atmos., 119, 4836–4858, doi:10.1002/2013JD021116.
 
[12] Papayannis A. et al. (2014): Optical, size and mass properties of mixed type aerosols in Greece and Romania as observed by synergy of lidar and sunphotometers in combination with model simulations: A case study, Science of the Total Environment, 500-501 (2014) 277-294, https://dx.doi.org/10.1016/j.scitotenv.2014.08.101
 
[13] Zawadzka, O., Makuch, P., Markowicz, K.M. et al. (2014): Studies of aerosol optical depth with the use of Microtops II sun photometers and MODIS detectors in coastal areas of the Baltic Sea, Acta Geophys. 62: 400. https://doi.org/10.2478/s11600-013-0182-5
 
[14] Navas-Guzmán, F.,  D. et al. (2013): Eruption of the Eyjafjallaj?kull Volcano in spring 2010: Multiwavelength Raman lidar measurements of sulphate particles in the lower troposphere, J. Geophys. Res. Atmos., 118, 1804–1813, doi:10.1002/jgrd.50116.
 
[15] Estellés, V., et al. (2012): Study of the correlation between columnar aerosol burden, suspended matter at ground and chemical components in a background European environment, J. Geophys. Res., 117, D04201, doi:10.1029/2011JD016356.
 
[16] Granados-Mu?oz, M. J., et al. (2012): Automatic determination of the planetary boundary layer height using lidar: One-year analysis over southeastern Spain, J. Geophys. Res., 117, D18208, doi:10.1029/2012JD017524.
 
[17] Hervo, M., et al.(2012), and Sellegri, K.: Physical and optical properties of 2010 Eyjafjallaj?kull volcanic eruption aerosol: ground-based, Lidar and airborne measurements in France, Atmos. Chem. Phys., 12, 1721-1736, https://doi.org/10.5194/acp-12-1721-2012
 
[18] Pérez-Ramírez, D., et al. (2012): Retrievals of precipitable water vapor using star photometry: Assessment with Raman lidar and link to sun photometry, J. Geophys. Res., 117, D05202, doi:10.1029/2011JD016450.
 
[19] Zieliński, T., Petelski, T., Makuch, P. et al. (2012): Studies of aerosols advected to coastal areas with the use of remote technique, Acta Geophys. 60: 1359. https://doi.org/10.2478/s11600-011-0075-4
 
[20] Boulon, J., et al. (2011): Investigation of nucleation events vertical extent: a long term study at two different altitude sites, Atmos. Chem. Phys., 1, https://doi.org/10.5194/acp-11-5625-2011, 2011.
 
[21] Córdoba-Jabonero, C., et al. (2011): Synergetic monitoring of Saharan dust plumes and potential impact on surface: a case study of dust transport from Canary Islands to Iberian Peninsula, Atmos. Chem. Phys., 1, https://doi.org/10.5194/acp-11-3067-2011
 
[22] Guerrero-Rascado, J. L., et al. (2011): Aerosol closure study by lidar, Sun photometry, and airborne optical counters during DAMOCLES field campaign at El Arenosillo sounding station, Spain, J. Geophys. Res., 116, D02209, doi:10.1029/2010JD014510.
 
[23] Themistocleous K. et al. (2010): Monitoring Air Pollution in the Vicinity of Cultural Heritage Sites in Cyprus Using Remote Sensing Techniques. In: Ioannides M., Fellner D., Georgopoulos A., Hadjimitsis D.G. (eds) Digital Heritage. EuroMed 2010. Lecture Notes in Computer Science, vol 6436. Springer, Berlin, Heidelberg
 
[24] George Georgoussis et al. (2009): Continuous measurements of PM at ground level over an industrial area of Evia (Greece) using synergy of a scanning Lidar system and in situ sensors during TAMEX campaign, EMS Annual Meeting Abstracts, Vol. 6, EMS2009-309-5, 2009, 9th EMS / 9th ECAM
 
[25] Guerrero-Rascado, J. L., et al. (2009): Extreme Saharan dust event over the southern Iberian Peninsula in september 2007: active and passive remote sensing from surface and satellite, Atmos. Chem. Phys., 9, 8453-8469, https://doi.org/10.5194/acp-9-8453-2009
 
[26] Kazadzis, S., et al. (2009): Spatial and temporal UV irradiance and aerosol variability within the area of an OMI satellite pixel, Atmos. Chem. Phys., 9, 4593-4601, https://doi.org/10.5194/acp-9-4593-2009
 
[27] Amiridis, V., et al. (2007): Aerosol Lidar observations and model calculations of the Planetary Boundary Layer evolution over Greece, during the March 2006 Total Solar Eclipse, Atmos. Chem. Phys., 7, 6181-6189, https://doi.org/10.5194/acp-7-6181-2007
 
[28] Papayannis, A., et al. (2007): Extraordinary dust event over Beijing, China, during April 2006: Lidar, Sun photometric, satellite observations and model validation, Geophys. Res. Lett., 34, L07806, doi:10.1029/2006GL029125.