Autor: |
Andrei Radovici, Lucia Timea Deaconu, Doina Nicolae, Alexandru Mereuță, Nikolaos Papagiannopoulos, Horațiu Ștefănie, Alexandru Ozunu, Nicolae Ajtai, Camelia Botezan |
Rok vydání: |
2021 |
Předmět: |
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ISSN: |
1680-7324 |
Popis: |
Black carbon aerosols are the second largest contributor to global warming while also being linked to respiratory and cardiovascular disease. These particles are generally found in smoke plumes originating from biomass burning and fossil fuel combustion. They are also heavily concentrated in smoke plumes originating from oil fires exhibiting the largest ratio of black carbon to organic carbon. In this study, we identified and analyzed oil smoke plumes derived from 30 major industrial events within a 12-year timeframe. To our knowledge, this is the first study of its kind that utilized a synergetic approach based on satellite remote sensing techniques. One objective of this study is to highlight the importance of satellite remote sensing techniques in identifying these types of events. As opposed to ground stations, satellite data offers access to remote areas all over the globe which would otherwise be very difficult to reach. Satellite data offers access to these events which, as seen in this study, are mainly located in war prone or hazardous areas. This study focuses on the use of MODIS (Moderate Resolution Imaging Spectroradiometer) and CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) products regarding these types of aerosol while also highlighting their intrinsic limitations. By using data from both MODIS instruments onboard Terra and Aqua satellites we addressed the temporal evolution of the smoke plume while assessing Lidar specific properties and plume elevation using CALIPSO data. We present several aerosol properties in the form of plume specific averaged values. The MODIS ocean algorithms were successful in retrieving aerosol properties which, on average, ranged from −0.06 to 0.16 for plume specific AOD, −0.18 to 1.25 for Ångström exponent and 0.29 to 1.73 µm for the effective radius. CALIPSO measurements showed values of plume AOD ranging from 0 to 0.14 (532 nm) and 0 to 0.13 (1064 nm) except for one event where AOD values showed 1.52 (532 nm) and 1.42 (1064 nm). AE values ranged from 0.11 to 0.33 which were in agreeance with MODIS values. A large discrepancy can be found in one event where CALIPSO measured AOD values 5 times higher than MODIS. This event also produced the largest lidar ratio at 109 sr (532 nm) and 86 (1064 nm). Other lidar ratio values ranged from 37 to 55 sr however these unconstrained solutions were obtained for the entire layer of which the plumes were a part of and thus did not reflect specific plume conditions. Particulate backscatter values ranged from 0.002 to 0.0017 km−1 sr−1 while extinction coefficient values ranged from 0.10 to 1.65 km−1. On average backscatter and extinction coefficient values were 2 to 9 times higher than local background values. Particulate depolarization ratios ranged from 0.11 to 0.15 in 4 out of 6 cases while the remaining two ranged from 0.27 to 0.32 where dust was highly dominant. The values represented in this study are in good agreement with similar studies that used ground based and flight measurements. We believe that MODIS values are a conservative estimation of plume AOD since MODIS algorithms rely on general aerosol models and various atmospheric conditions within the look-up tables which do not reflect the highly absorbing nature of these smoke plumes. CALIPSO measurements are heavily dependent on lidar ratios which are not directly measured if plumes within the planetary boundary layer. We also believe that AOD values based on CALIPSO measurements are conservative in nature since heavy absorbing smoke would yield larger lidar ratios and AOD values. Based on this study we conclude that the MODIS land algorithms are not yet suited for retrieving aerosol properties for these types of smoke plumes due to the strong absorbing properties of these aerosols. We believe that these types of studies are a strong indicator for the need of improved aerosol models and retrieval algorithms. |
Databáze: |
OpenAIRE |
Externí odkaz: |
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