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. Black carbon aerosols are the second largest contributorto global warming while also being linked to respiratory and cardiovasculardisease. These particles are generally found in smoke plumes originatingfrom biomass burning and fossil fuel combustion. They are also heavilyconcentrated in smoke plumes originating from oil fires, exhibiting thelargest ratio of black carbon to organic carbon. In this study, weidentified and analysed oil smoke plumes derived from 30 major industrialevents within a 12-year timeframe. To our knowledge, this is the first studyof its kind that utilized a synergetic approach based on satellite remotesensing techniques. Satellite data offer access to these events, which, asseen in this study, are mainly located in war-prone or hazardous areas. Thisstudy focuses on the use of MODIS (Moderate Resolution ImagingSpectroradiometer) and CALIPSO (Cloud-Aerosol Lidar and Infrared PathfinderSatellite Observations) products regarding these types of aerosol while alsohighlighting their intrinsic limitations. By using data from both MODISinstruments on board Terra and Aqua satellites, we addressed the temporalevolution of the smoke plume while assessing lidar-specific properties andplume elevation using CALIPSO data. The analysis method in this study wasdeveloped to better differentiate between oil smoke aerosols and the localatmospheric scene. We present several aerosol properties in the form ofplume-specific averaged values. We believe that MODIS values are aconservative estimation of plume aerosol optical depth (AOD) since MODIS algorithms rely on generalaerosol models and various atmospheric conditions within the look-up tables,which do not reflect the highly absorbing nature of these smoke plumes.Based on this study we conclude that the MODIS land algorithms are not yetsuited for retrieving aerosol properties for these types of smoke plumes dueto the strong absorbing properties of these aerosols. CALIPSO retrievalsrely heavily on the type of lidar solutions showing discrepancy betweenconstrained and unconstrained retrievals. Smoke plumes identified within alarger aerosol layer were treated as unconstrained retrievals and resultedin conservative AOD estimates. Conversely, smoke plumes surrounded by clearair were identified as opaque aerosol layers and resulted in higher lidarratios and AOD values. Measured lidar ratios and particulate depolarizationratios showed values similar to the upper ranges of biomass burning smoke.Results agree with studies that utilized ground-based retrievals, inparticular for Ångström exponent (AE) and effective radius(Reff) values. MODIS and CALIPSO retrieval algorithms disagree on AODranges, for the most part, due to the extreme light-absorbing nature ofthese types of aerosols. We believe that these types of studies are a strongindicator for the need of improved aerosol models and retrieval algorithms.

A novel method of identifying and analysing oil smoke plumes based on MODIS and CALIPSO satellite data