The 2010 Oil Spill in the Gulf of Mexico: Flow-Rate Estimation Based on Satellite-Images Analysis1

2019 ◽  
Vol 141 (5) ◽  
Author(s):  
Diego Garcia Giraldo ◽  
Ronald W. Yeung
Keyword(s):  
Oil Spill ◽  
Flow Rate ◽  
Drill Pipe ◽  
Upper And Lower Bounds ◽  
Constant Thickness ◽  
A Value ◽  
Oil Flow ◽  
Moderate Resolution ◽  
Drilling Unit ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract The Deepwater Horizon Mobile Offshore Drilling Unit (MODU) was one of several classes of floatable drilling systems. The explosion on April 20, 2010 led to fatalities and the worst oil spill in the U.S. We present an independent estimate of the oil-flow rate into The Gulf caused by the drill-pipe rupture. We employed the NASA Moderate-Resolution Imaging-Spectroradiometer (MODIS) satellite photographs, starting from the days immediately following the disaster, to determine the magnitude of spill. From these images, we obtained the surface area of the spill and calculated the oil flow rate by two different methods based on contrasting luminance within that area. The first assumes a constant thickness for the total area with upper and lower bounds for the thickness. The second separates the area into different patches based on the luminance levels of each. The probability density function (PDF) of such luminance plots showed natural groupings, allowing patches be identifiable. Each patch maps to a specific thickness. This second approach provides a more accurate average thickness. With the assumption that evaporation and other loss amounted to ∼40% of the spill, we obtained, from the first method, a flow rate ranging from 9,300 barrels per day (BPD) to 93,000 BPD. A value of 51,200 BPD was obtained using patch-separation method. This latter estimate was a plausible value, obtained from the current analysis, but with no details presented in an Extended Abstract in OMAE2012, is remarkably consistent with the “official U.S.-Govt. estimates.”

The 2010 Oil Spill in the Gulf of Mexico: Flow-Rate Estimation Based on Satellite-Images Analysis

2018 ◽  
Author(s):  
Diego Garcia Giraldo ◽  
Ronald W. Yeung
Keyword(s):  
Gulf Of Mexico ◽  
Oil Spill ◽  
Flow Rate ◽  
Oil Spills ◽  
Upper And Lower Bounds ◽  
Constant Thickness ◽  
Simple Method ◽  
Oil Flow ◽  
The Usa ◽  
Moderate Resolution Imaging Spectroradiometer

The Deepwater Horizon Mobile Offshore Drilling Unit (MODU) was one of several classes of floatable drilling machines. The explosion on April 20, 2010 led to the worst ecological disaster with regard to oil spills in the USA. The objective of this paper is to develop a logical and independent estimate of the oil flow rate into the Gulf of Mexico produced by the rupture in this rig. We employed the NASA Moderate Resolution Imaging Spectroradiometer (MODIS) satellite photographs [1] starting from the days immediately following the disaster to determine the size and intensity of the oil spill. From these images, we obtained the surface area of the oil spill and calculated the oil flow rate by two different methods based on contrasting luminance within the area. The first assumes a constant thickness for the total area with upper and lower bounds for the thickness. The second method separates the spill area into different patches, based on the luminance levels of each. It was found that the probability density function (PDF) of the luminance plots typically showed some natural grouping, allowing patches to be defined. Each patch maps to a specific thickness and the result of the addition of all the patches provides a more accurate average thickness of the spill. With the assumption that evaporation and other loss amounted to 40% of the spill, we obtained, as a result of this analysis procedure, a minimum flow rate of 9,300 barrels per day and a maximum of 93,000 barrels per day using the first method. A value of 51,200 barrels per day was obtained using the method based on patch separation. This latter estimate was a reasonable value obtained based on this relatively simple method but with no details presented in an Extended Abstract in OMAE2012 [4]. It is remarkably consistent with the “official US-Govt. estimates” of [2, 3].

scholarly journals Improving the RST-OIL Algorithm for Oil Spill Detection under Severe Sun Glint Conditions

2019 ◽  
Vol 11 (23) ◽  
pp. 2762 ◽  
Author(s):  
Valeria Satriano ◽  
Emanuele Ciancia ◽  
Teodosio Lacava ◽  
Nicola Pergola ◽  
Valerio Tramutoli
Keyword(s):  
Oil Spill ◽  
Satellite Remote Sensing ◽  
Good Accuracy ◽  
Deepwater Horizon ◽  
Test Case ◽  
Oil Spill Detection ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Global Growth

In recent years, the risk related to oil spill accidents has significantly increased due to a global growth in offshore extraction and oil maritime transport. To ensure sea safety, the implementation of a monitoring system able to provide real-time coverage of large areas and a timely alarm in case of accidents is of major importance. Satellite remote sensing, thanks to its inherent peculiarities, has become an essential component in such a system. Recently, the general Robust Satellite Technique (RST) approach has been successfully applied to oil spill detection (RST-OIL) using optical band satellite data. In this paper, an advanced configuration of RST-OIL is presented, and we aim to extend its applicability to a larger set of observation conditions, referring, in particular, to those in the presence of severe sun glint effects that generate some detection limits to the RST-OIL standard algorithm. To test such a configuration, the DeepWater Horizon platform accident from April 2010 was selected as a test case. We analyzed a time series of Moderate Resolution Imaging Spectroradiometer (MODIS) images that are usually significantly affected by sun glint in the Gulf of Mexico area. The accuracy of the achieved results was evaluated for comparison with a well-established satellite methodology based on microwave data, which confirms the potential of the proposed approach in identifying the oil presence on the scene with good accuracy and reliability, even in these severe conditions.

The Deep-Water-Horizon Spill: Flow-Rate Estimation Based on Satellite Images

2012 ◽  
Author(s):  
Diego Garcia Giraldo ◽  
Ronald W. Yeung
Keyword(s):  
Gulf Of Mexico ◽  
Flow Rate ◽  
Deep Water ◽  
Infrared Imaging ◽  
Oil Spills ◽  
Imaging Spectrometer ◽  
Riser Pipe ◽  
Oil Flow ◽  
Plume Modeling ◽  
Drilling Unit

The “Deep Water Horizon” Mobil Offshore Drilling Unit (MODU) is one of several classes of floatable drilling machines. As a consequence of the accident on April 20, 2010, the worst ecological disaster with regard to oil spills in the US history was generated in the Gulf of Mexico, causing extensive damage to marine and wildlife habitats, as well as the Gulf’s fishing and tourism industries. Since that moment, experts are trying to estimate the total amount of oil being lost into the sea. The objective of this presentation is to report a procedure developed in the first author’s thesis1 an independent and logical estimate of the oil flow rate into the Gulf of Mexico produced by the rupture in this rig. There are a number of possible approaches to estimate the flow rate of oil spilling into the Gulf of Mexico. The Plume Modeling Team has developed an approach by observing video image of the oil/gas mixture escaping from the kinks in the riser and the end of the riser pipe. The Mass Balance Team has developed a range of values using USGS (US Geological Survey) and NOAA (National Oceanic and Atmospheric Administration) data analysis collected from NASA’s (National Aeronautics and Space Administration) Airborne Visible InfraRed Imaging Spectrometer (AVIRIS). Finally, a reality-check estimate was based on the amount of oil collected by the Riser Insertion Tube Tool (RITT) plus the estimate of how much oil is escaping from the RITT, and from the kink in the riser. However, there are several limitations in each of these techniques.

scholarly journals ALGORITMA UNTUK DETEKSI TUMPAHAN MINYAK DI LAUT TIMOR MENGGUNAKAN CITRA MODIS

2017 ◽  
Vol 4 (1) ◽  
pp. 41-62
Author(s):  
Muhammad Sudibjo ◽  
Vincentius P. Siregar ◽  
Jonson Lumban Gaol
Keyword(s):  
Principal Component Analysis ◽  
Oil Spill ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Principal Component ◽  
Component Analysis ◽  
Fluorescence Index ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

Tumpahan minyak di Laut Timor yang terjadi pada tahun 2009 telah menyebarkan minyak seluas 10.842.81 km2.Tumpahan minyak ini berhasil dideteksi oleh satelit Moderate Resolution Imaging Spectroradiometer (MODIS). Tujuan dari penelitian ini adalah membandingkan hasil deteksi tumpahan minyak dari beberapa algoritma dengan citra menggunakan citra MODIS dan melihat perbedaan visual yang dihasilkan. Algoritma yang digunakan adalah Oil Spill Index, Fluorescence Index, Principal Component Analysis (PCA), Normalized Difference Vegetation Index (NDVI). Visualisasi tumpahan minyak yang terlihat pada citra MODIS dengan algoritma oil spill indeks dan fluorescence index lebih cerah dibandingkan dengan badan air disekitarnya dan juga memiliki nilai piksel lebih tinggi, sedangkan visualisasi minyak menggunakan algoritma PCA dan NDVI lebih gelap dibandingkan dengan badan air disekitarnya dan juga memiliki nilai piksel yang lebih rendah. Hasil uji akurasi yang dilakukan terhadap algoritma oil splill index, fluorescence index, PCA, NDVI berturut-turut sebagai berikut 41%, 46%, 41%, dan 60%

scholarly journals Influence of Straw Burning on Urban Air Pollutant Concentrations in Northeast China

2019 ◽  
Vol 16 (8) ◽  
pp. 1379 ◽  
Author(s):  
Zhenzhen Wang ◽  
Jianjun Zhao ◽  
Jiawen Xu ◽  
Mingrui Jia ◽  
Han Li ◽  
...  
Keyword(s):  
Northeast China ◽  
Arable Land ◽  
Pollution Index ◽  
Air Pollutant ◽  
Thermal Anomalies ◽  
Pollutant Concentrations ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Straw Burning ◽  
Moderate Resolution Imaging Spectroradiometer

Northeast China is China’s primary grain production base. A large amount of crop straw is incinerated every spring and autumn, which greatly impacts air quality. To study the degree of influence of straw burning on urban pollutant concentrations, this study used The Moderate-Resolution Imaging Spectroradiometer/Terra Thermal Anomalies & Fire Daily L3 Global 1 km V006 (MOD14A1) and The Moderate-Resolution Imaging Spectroradiometer/Aqua Thermal Anomalies and Fire Daily L3 Global 1 km V006 (MYD14A1) data from 2015 to 2017 to extract fire spot data on arable land burning and to study the spatial distribution characteristics of straw burning on urban pollutant concentrations, temporal variation characteristics and impact thresholds. The results show that straw burning in Northeast China is concentrated in spring and autumn; the seasonal spatial distributions of PM2.5, PM10 andAir Quality Index (AQI) in 41 cities or regions in Northeast China correspond to the seasonal variation of fire spots; and pollutants appear in the peak periods of fire spots. In areas where the concentration coefficient of rice or corn is greater than 1, the number of fire spots has a strong correlation with the urban pollution index. The correlation coefficient R between the number of burned fire spots and the pollutant concentration has a certain relationship with the urban distribution. Cities are aggregated in geospatial space with different R values.

scholarly journals A Climatological Assessment of Intense Desert Dust Episodes over the Broader Mediterranean Basin Based on Satellite Data

2021 ◽  
Vol 13 (15) ◽  
pp. 2895
Author(s):  
Maria Gavrouzou ◽  
Nikolaos Hatzianastassiou ◽  
Antonis Gkikas ◽  
Christos J. Lolis ◽  
Nikolaos Mihalopoulos
Keyword(s):  
Mediterranean Basin ◽  
Eastern Mediterranean ◽  
Mean Value ◽  
Early Spring ◽  
Dust Aerosol ◽  
Ozone Monitoring Instrument ◽  
Central Mediterranean ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

A satellite algorithm able to identify Dust Aerosols (DA) is applied for a climatological investigation of Dust Aerosol Episodes (DAEs) over the greater Mediterranean Basin (MB), one of the most climatologically sensitive regions of the globe. The algorithm first distinguishes DA among other aerosol types (such as Sea Salt and Biomass Burning) by applying threshold values on key aerosol optical properties describing their loading, size and absorptivity, namely Aerosol Optical Depth (AOD), Aerosol Index (AI) and Ångström Exponent (α). The algorithm operates on a daily and 1° × 1° geographical cell basis over the 15-year period 2005–2019. Daily gridded spectral AOD data are taken from Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua Collection 6.1, and are used to calculate the α data, which are then introduced into the algorithm, while AI data are obtained by the Ozone Monitoring Instrument (OMI) -Aura- Near-UV aerosol product OMAERUV dataset. The algorithm determines the occurrence of Dust Aerosol Episode Days (DAEDs), whenever high loads of DA (higher than their climatological mean value plus two/four standard deviations for strong/extreme DAEDs) exist over extended areas (more than 30 pixels or 300,000 km2). The identified DAEDs are finally grouped into Dust Aerosol Episode Cases (DAECs), consisting of at least one DAED. According to the algorithm results, 166 (116 strong and 50 extreme) DAEDs occurred over the MB during the study period. DAEDs are observed mostly in spring (47%) and summer (38%), with strong DAEDs occurring primarily in spring and summer and extreme ones in spring. Decreasing, but not statistically significant, trends of the frequency, spatial extent and intensity of DAECs are revealed. Moreover, a total number of 98 DAECs was found, primarily in spring (46 DAECs) and secondarily in summer (36 DAECs). The seasonal distribution of the frequency of DAECs varies geographically, being highest in early spring over the eastern Mediterranean, in late spring over the central Mediterranean and in summer over the western MB.

scholarly journals Study of Injection Method for Maximizing Oil-Cooling Performance of Electric Vehicle Motor with Hairpin Winding

Energies ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 747
Author(s):  
Taewook Ha ◽  
Dong Kyu Kim
Keyword(s):  
Electric Vehicle ◽  
Flow Rate ◽  
Film Formation ◽  
Formation Rate ◽  
Cooling Performance ◽  
Oil Film ◽  
Injection Method ◽  
Cooling Method ◽  
Oil Flow ◽  
Oil Injection

The oil injection method was studied to maximize the cooling performance of an electric vehicle motor with a hairpin winding. The cooling performance of the motor using the oil cooling method is proportional to the contact area of the oil and the coil. A numerical analysis was conducted to examine the effect of the spray nozzle type on the oil flow. The dripping nozzle forms the thickest oil film on the coil, making it the most effective for cooling of hairpin-type motors. Subsequently, an experimental study was conducted to optimize the nozzle diameter and number of nozzles. When the inlet diameter and number was 6.35 mm and 6, the oil film formation rate was 53%, yielding the most uniform oil film. Next, an experiment was performed to investigate the effects of the oil temperature and flow rate on the oil flow. The oil film formation rate was the highest (83%) when the oil temperature was 40 °C and the flow rate was 6 LPM.

scholarly journals 250-m Aerosol Retrieval from FY-3 Satellite in Guangzhou

2021 ◽  
Vol 13 (5) ◽  
pp. 920
Author(s):  
Zhongting Wang ◽  
Ruru Deng ◽  
Pengfei Ma ◽  
Yuhuan Zhang ◽  
Yeheng Liang ◽  
...  
Keyword(s):  
Mixing Model ◽  
Blue Band ◽  
Aerosol Retrieval ◽  
Aerosol Distribution ◽  
Medium Resolution ◽  
Fine Spatial Resolution ◽  
Yearly Average ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

Aerosol distribution with fine spatial resolution is crucial for atmospheric environmental management. This paper proposes an improved algorithm of aerosol retrieval from 250-m Medium Resolution Spectral Image (MERSI) data of Chinese FY-3 satellites. A mixing model of soil and vegetation was used to calculate the parameters of the algorithm from moderate-resolution imaging spectroradiometer (MODIS) reflectance products in 500-m resolution. The mixing model was used to determine surface reflectance in blue band, and the 250-m aerosol optical depth (AOD) was retrieved through removing surface contributions from MERSI data over Guangzhou. The algorithm was used to monitor two pollution episodes in Guangzhou in 2015, and the results displayed an AOD spatial distribution with 250-m resolution. Compared with the yearly average of MODIS aerosol products in 2015, the 250-m resolution AOD derived from the MERSI data exhibited great potential for identifying air pollution sources. Daily AODs derived from MERSI data were compared with ground results from CE318 measurements. The results revealed a correlation coefficient between the AODs from MERSI and those from the ground measurements of approximately 0.85, and approximately 68% results were within expected error range of ±(0.05 + 15%τ).

scholarly journals New generation geostationary satellite observations support seasonality in greenness of the Amazon evergreen forests

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Hirofumi Hashimoto ◽  
Weile Wang ◽  
Jennifer L. Dungan ◽  
Shuang Li ◽  
Andrew R. Michaelis ◽  
...  
Keyword(s):  
Cloud Cover ◽  
Seasonal Patterns ◽  
Optical Remote Sensing ◽  
Amazon Forest ◽  
Evergreen Forests ◽  
Geostationary Satellites ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
New Generation

AbstractAssessing the seasonal patterns of the Amazon rainforests has been difficult because of the paucity of ground observations and persistent cloud cover over these forests obscuring optical remote sensing observations. Here, we use data from a new generation of geostationary satellites that carry the Advanced Baseline Imager (ABI) to study the Amazon canopy. ABI is similar to the widely used polar orbiting sensor, the Moderate Resolution Imaging Spectroradiometer (MODIS), but provides observations every 10–15 min. Our analysis of NDVI data collected over the Amazon during 2018–19 shows that ABI provides 21–35 times more cloud-free observations in a month than MODIS. The analyses show statistically significant changes in seasonality over 85% of Amazon forest pixels, an area about three times greater than previously reported using MODIS data. Though additional work is needed in converting the observed changes in seasonality into meaningful changes in canopy dynamics, our results highlight the potential of the new generation geostationary satellites to help us better understand tropical ecosystems, which has been a challenge with only polar orbiting satellites.

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