Bilge Dumping off the Coast of Brazil

The cause of the massive oil spill plaguing Brazil’s beaches is still unknown, but monitoring reveals a potential new bilge dumping incident

We still haven’t found the cause of the massive oil spill that’s been plaguing Brazil’s beaches since early September.  

But SkyTruth’s continued surveillance of the coast of northeastern Brazil, in response to one of the country’s worst oil-related environmental disasters ever, has uncovered what appears to be another previously unreported bilge dumping incident off the coast of Joao Pessoa in the state of Paraiba. Located about 20 km offshore, a 25 km-long slick appears to originate from the Grajau, a Brazil-flagged liquefied petroleum gas (LPG) tanker. Slicks such as this are a hallmark of the intentional dumping of untreated, oily bilge wastes from vessels underway at sea, although there may be other explanations for this slick (for example, the ship was experiencing a serious mechanical problem). The slick (a long, dark streak) and vessel (a bright spot at the south end of the slick) are shown on this Sentinel-1 radar satellite image taken on the 19th of July. We identified the vessel using their public AIS tracking broadcasts, extracted from the ShipView vessel-tracking platform. The image was captured at 07:53 UTC; a careful look at the AIS broadcasts from Grajau just before and after the image was taken show that the vessel we can see on the radar image is very likely Grajau.

Recent discoveries of bilge dumping in the Atlantic Ocean along Brazil’s coast reveal that this is a persistent problem that — as in many places — lacks effective enforcement. None of the slicks we’ve seen appear big enough to be the source of the oil plaguing Brazil’s beaches. This potential bilge slick from Grajau is no exception: it’s a modest-sized slick compared with the dozens of bilge slicks we’ve seen from other places around the world that are occasionally more than 100 km long. And this slick, just 20 km offshore, probably would have dissipated or washed ashore several weeks before the thick globs of heavy oil began to appear on the beaches in early September.

Nevertheless, bilge dumping is a chronic source of oil pollution in the ocean that has been hidden for too long. Now that we can see it, and can identify the likely polluters, it’s time for governments to take action to bring this illegal practice to an end.

AIS ship-tracking broadcasts (red dots) from the Brazil-flagged LPG tanker Grajau, overlain on a Sentinel-1 radar satellite image showing an apparent bilge-dumping slick (dark streak) and the vessel that appears to be responsible (bright spot, indicated within the red circle). Based on the AIS data, we think this vessel is likely the Grajau. See inset map at upper right for detail. Image was collected at 07:53 on July 19.

The location of the boat, relative to Brazil’s coastline.

New Data Available on the Footprint of Surface Mining in Central Appalachia

The area of Central Appalachia impacted by surface mining has increased — by an amount equal to the size of Liechtenstein — despite a decline in coal production.

SkyTruth is releasing an update for our Central Appalachian Surface Mining data showing the extent of surface mining in Central Appalachia. While new areas continue to be mined, adding to the cumulative impact of mining on Appalachian ecosystems, the amount of land being actively mined has declined slightly.

This data builds on our work published last year in the journal PLOS One, in which we produced the first map to ever show the footprint of surface mining in this region. We designed the data to be updated annually. Today we are releasing the data for 2016, 2017, and 2018.

Mountaintop mine near Wise, Virginia. Copyright Alan Gignoux; Courtesy Appalachian Voices; 2014-2.

Coal production from surface mines, as reported to the US Energy Information Administration (EIA), has declined significantly for the Central Appalachian region since its peak in 2008. Likewise, the area of land being actively mined each year has steadily decreased since 2007. But because new land continues to be mined each year, the overall disturbance to Appalachian ecosystems has increased. From 2016 to 2018 the newly mined areas combined equaled 160 square kilometers – an area the size of the nation of Liechtenstein. One of the key findings of our research published in PLOS ONE was that the amount of land required to extract a single metric ton of coal had tripled from approximately 10 square meters in 1985 to nearly 30 square meters in 2015. Our update indicates that this trend still holds true for the 2016-2018 period: Despite the overall decrease in production, in 2016 approximately 40 square meters of land were disturbed per metric ton of coal produced – an all time high. This suggests that it is getting harder and harder for companies to access the remaining coal.

Active mine area (blue) and reported surface coal mine production in Central Appalachia (red) as provided by the US Energy Information Administration (EIA). The amount of coal produced has declined much more dramatically than the area of active mining.

This graph shows the disturbance trend for surface coal mining in Central Appalachia. Disturbance is calculated by dividing the area of actively mined land by the reported coal production for Central Appalachia as provided by the EIA.

Tracking the expansion of these mines is only half the battle. We are also developing landscape metrics to assess the true impact of mining on Appalachian communities and ecosystems. We are working to generate a spectral fingerprint for each identified mining area using satellite imagery. This fingerprint will outline the characteristics of each site; including the amount of bare ground present and information about vegetation regrowing on the site. In this way we will track changes and measure recovery by comparing the sites over time to a healthy Appalachian forest.

Mining activity Southwest of Charleston, WV. Land that was mined prior to 2016 is visible in yellow, and land converted to new mining activity between 2016 and 2018 is displayed in red.

Recovery matters. Under federal law, mine operators are required to post bonds for site reclamation in order “to ensure that the regulatory authority has sufficient funds to reclaim the site in the case the permittee fails to complete the approved reclamation plan.” In other words, mining companies set aside money in bonds to make sure that funds are available to recover their sites for other uses once mining ends. If state inspectors determine that mine sites are recovered adequately, then mining companies recover their bonds.

But the regulations are opaque and poorly defined; most states set their own requirements for bond release and requirements vary depending on the state, the inspector, and local landscapes. And as demand for coal steadily declines, coal companies are facing increasing financial stress, even bankruptcy. This underlines the importance of effective bonding that actually protects the public from haphazardly abandoned mining operations that may be unsafe, or unusable for other purposes.

We are now working to track the recovery of every surface coal mine in Central Appalachia. By comparing these sites to healthy Appalachian forests we will be able to grade recovery. This will allow us to examine how fully these sites have recovered, determine to what degree there is consistency in what qualifies for bond-release, and to what extent the conditions match a true Appalachian forest.

Bilge Dumping Caught in Indonesia – Again!

SkyTruth identified the bulk carrier Lumoso Aman as the likely polluter via AIS and satellite imagery.

On October 10, 2019, SkyTruth discovered yet another likely bilge dumping incident in Southeast Asian waters. At 10:25:26 UTC (Coordinated Universal Time), Sentinel-1 Imagery captured this oily pollution during routine monitoring of the Makassar Strait. Lingering off the southwest coast of Sulawesi, Indonesia, this oil slick measures approximately 33 kilometers long. The slick and the suspected responsible vessel (circled in red in Figure 1 below) appear roughly 100 kilometers west of the coast of Makassar, the capital of Sulawesi. Makassar is a port city with active commerce and tourism.

Figure 1: A vessel suspected of bilge dumping.

We identified the potential culprit through AIS (Automatic Identification System) broadcasts from the Lumoso Aman (Figure 2), a bulk cargo carrier operating under the flag of Indonesia. 

Figure 2: A picture of the Lumoso Aman, courtesy of Vessel Finder.

Bilge dumping is the disposal of waste water from a ship’s lower hull. Bilge water is supposed to be treated before it’s discharged, but sometimes vessel operators will bypass the pollution control equipment and flush oily, untreated bilge into the ocean – in direct violation of international marine pollution law. You can learn more about this ongoing source of ocean pollution, and how SkyTruth identifies perpetrators, in our recent post about bilge dumping in Southeast Asia.

Our motto at SkyTruth is “If you can see it, you can change it.” We tirelessly monitor the ocean with this vision in mind, to be watchdogs and defenders of our Earth’s waters. No matter how remote these areas of pollution appear to be, we can see them with satellite images. These seemingly remote bodies of water are connected to waters throughout the world. Just as air pollution migrates between contiguous countries or states, oil pollution can find its way to any coastline and harm coastal environments and communities. With continued monitoring, we hope that nations, communities, and enforcement agencies can hold ship operators accountable, making it clear that bilge pollution is an unacceptable threat to the world’s ocean ecosystems. 

Figure 3: SkyTruth intern Tatianna Evanisko tracks polluting vessels around the world from the SkyTruth offices in Shepherdstown WV. Photo credit: Johnna Armstrong.

New Oil and Gas Flaring Data Available

Updated data means anyone can see where, and how much, natural gas is being flared in their area.

SkyTruth has updated its Annual Flare Volume map to include 2017 and 2018 data. We first launched the map in 2017 to provide site specific estimates of the annual volume of gas flared during oil and gas production worldwide.

What is flaring?

Flaring is the act of burning off excess natural gas from oil wells when it can’t economically be stored and sent elsewhere. Flaring is also used to burn gases that would otherwise present a safety problem. But flaring from oil wells is a significant source of greenhouse gases. The World Bank estimated that 145 billion cubic meters of natural gas were flared in 2018; the equivalent of the entire gas consumption of Central and South America combined. Gas flaring also can negatively affect wildlife, public health, and even agriculture.

What can I do?

SkyTruth’s map allows users to search the data by virtually any geographic area they’re interested in, then easily compare and download flare volume totals from 2012 through 2018 to observe trends. In addition, it separates flaring into upstream (flaring of natural gas that emerges when crude oil is brought to the Earth’s surface), downstream oil (refineries) and downstream gas (natural gas processing facilities). Residents, researchers, journalists and others concerned about gas emissions in their city or study area can easily determine the sources of the problem using the latest data available, and how much gas has been flared.

VIIRS Satellite Instrument and the Earth Observation Group

The data we use in the SkyTruth map is a product of the Visible Infrared Imaging Radiometer Suite (VIIRS) satellite instrument, which produces the most comprehensive listing of gas flares worldwide. VIIRS data has moved to a new home this year at the Earth Observation Group in the Colorado School of Mines’ Payne Institute for Public Policy. SkyTruth also uses the VIIRS nightfire data in its popular flaring visualization map.

Thanks to the Earth Observation Group for continuing to make the nightfire data freely available to the public! They have authored the following papers for those interested in the VIIRS instrument and how the flare volume is calculated.

Elvidge, C. D., Zhizhin, M., Hsu, F -C., & Baugh, K. (2013).VIIRS nightfire: Satellite pyrometry at night. Remote Sensing 5(9), 4423-4449.

Elvidge, C. D., Zhizhin, M., Baugh, K. E, Hsu, F -C., & Ghosh, T. (2015). Methods for global survey of natural gas flaring from Visible Infrared Imaging Radiometer Suite Data. Energies, 9(1), 1-15.

Elvidge, C. D., Bazilian, M. D., Zhizhin, M., Ghosh, T., Baugh, K., & Hsu, F. C. (2018). The potential role of natural gas flaring in meeting greenhouse gas mitigation targets. Energy Strategy Reviews, 20, 156-162.

What About the Oceans? Mapping Offshore Infrastructure

Mapping stationary structures in the ocean helps us track fishing vessels and monitor pollution more effectively.

We’re all accustomed to seeing maps of the terrestrial spaces we occupy. We expect to see cities, roads and more well labeled, whether in an atlas on our coffee table or Google Maps on our smartphone. SkyTruthers even expect to access information about where coal mines are located or where forests are experiencing regrowth. We can now see incredibly detailed satellite imagery of our planet. Try looking for your house in Google Earth. Can you see your car in the driveway?

In comparison, our oceans are much more mysterious places. Over seventy percent of our planet is ocean, yet vast areas are described with only a handful of labels: the Pacific Ocean, Coral Sea, Strait of Hormuz, or Chukchi Sea for example. And while we do have imagery of our oceans, its resolution decreases drastically the farther out from shore you look. It can be easy to forget that humans have a permanent and substantial footprint across the waters of our planet. At SkyTruth, we’re working to change that.

Former SkyTruth senior intern Brian Wong and I are working to create a dataset of offshore infrastructure to help SkyTruth and others more effectively monitor our oceans. If we know where oil platforms, aquaculture facilities, wind farms and more are located, we can keep an eye on them more easily. As technological improvements fuel the growth of the ocean economy, allowing industry to extract resources far out at sea, this dataset will become increasingly valuable. It can help researchers examine the effects of humanity’s expanding presence in marine spaces, and allow activists, the media, and other watchdogs to hold industry accountable for activities taking place beyond the horizon.

What We’re Doing

Brian is now an employee at the Marine Geospatial Ecology Lab (MGEL) at Duke University. But nearly two years ago, at a Global Fishing Watch research workshop in Oakland, he and I discussed the feasibility of creating an algorithm that could identify vessel locations using Synthetic Aperture Radar (SAR) imagery. It was something I’d been working on on-and-off for a few weeks, and the approach seemed fairly simple.

Image 1. SkyTruth and Global Fishing Watch team members meet for a brainstorming session at the Global Fishing Watch Research Workshop, September 2017. Photo credit: David Kroodsma, Global Fishing Watch.

Readers who have been following SkyTruth’s work are probably used to seeing SAR images from the European Space Agency’s Sentinel-1 satellites in our posts. They are our go-to tools for monitoring marine pollution events, thanks to SAR’s ability to pierce clouds and provide high contrast between slicks and sea water. SAR imagery provides data about the relative roughness of surfaces. With radar imagery, the satellite sends pulses to the earth’s surface. Flat surfaces, like calm water (or oil slicks), reflect less of this data back to the satellite sensor than vessels or structures do, and appear dark. Vessels and infrastructure appear bright in SAR imagery because they experience a double-bounce effect. This means that — because such structures are three-dimensional — they typically reflect back to the satellite more than once as the radar pulse bounces off multiple surfaces. If you’re interested in reading more about how to interpret SAR imagery this tutorial is an excellent starting point.

Image 2. The long, dark line bisecting this image is a likely bilge dump from a vessel captured by Sentinel-1 on July 2, 2019. The bright point at its end is the suspected source. Read more here.

Image 3. The bright area located in the center of this Sentinel-1 image is Neft Daşları, a massive collection of offshore oil platforms and related infrastructure in the Caspian Sea.

Given the high contrast between water and the bright areas that correspond to land, vessels, and structures (see the vessel at the end of the slick in Image 2 and Neft Daşları in Image 3), we thought that if we could mask out the land, picking out the bright spots should be relatively straightforward. But in order to determine which points were vessels, we first needed to identify the location of all the world’s stationary offshore infrastructure, since it is virtually impossible to differentiate structures from vessels when looking at a single SAR image. Our simple task was turning out to be not so simple.

While the United States has publicly available data detailing the locations of offshore oil platforms (see Image 4), this is not the case for other countries around the world. Even when data is available, it is often hosted across multiple webpages, hidden behind paywalls, or provided in formats which are not broadly accessible or useable. To our knowledge, no one has ever published a comprehensive, global dataset of offshore infrastructure that is publicly available (or affordable).

Image 4. Two versions of a single Sentinel-1 image collected over the Gulf of Mexico, in which both oil platforms and vessels are visible. On the left, an unlabelled version which illustrates how similar infrastructure and vessels appear. On the right, oil platforms have been identified using the BOEM Platform dataset.

As we began to explore the potential of SAR imagery for automated vessel and infrastructure detection, we quickly realized that methods existed to create the data we desired. The Constant False Alarm Rate algorithm has been used to detect vessels in SAR imagery since at least 1988, but thanks to Google Earth Engine we are able to scale up the analysis and run it across every Sentinel-1 scene collected to date (something which simply would not have been possible even 10 years ago). To apply the algorithm to our dataset, we, among other things, had to mask out the land, and then set the threshold level of brightness that indicated the presence of a structure or vessel. Both structures and vessels will have high levels of reflectance. So we then had to separate the stationary structures from vessels. We did this by compiling a composite of all images for the year 2017. Infrastructure remains stationary throughout the year, while vessels move. This allowed us to clearly identify the infrastructure.

Image 5. An early version of our workflow for processing radar imagery to identify vessel locations. While the project shifted to focus on infrastructure detection first, many of the processing steps remained.

Where We Are Now

Our next step in creating the infrastructure dataset was testing the approach in areas where infrastructure locations were known. We tested the algorithm’s ability to detect oil platforms in the Gulf of Mexico, where the US Bureau of Ocean Energy Management (BOEM) maintains a dataset. We also tested the algorithm’s ability to identify wind turbines. We used a wind farm boundary dataset provided by the United Kingdom Hydrographic Office to validate our dataset, as well as information about offshore wind farms in Chinese waters verified in media reports, with their latitude and longitude available on Wikipedia.

Image 6. Wind farms in the Irish Sea, west of Liverpool.

Our results in these test areas have been very promising, with an overall accuracy of 96.1%. The methodology and data have been published by the journal Remote Sensing of Environment. Moving beyond these areas, we are continuing to work with our colleagues at MGEL to develop a full global dataset. What started as a project to identify vessels for GFW has turned into an entirely different, yet complementary, project identifying offshore infrastructure around the world.

Image 7. This animated map shows the output of our offshore infrastructure detection algorithm results (red) compared to the publicly available BOEM Platform dataset (yellow).

In addition to helping our partners at Global Fishing Watch identify fishing vessels, mapping the world’s offshore infrastructure will help SkyTruth more effectively target our daily oil pollution monitoring work on areas throughout the ocean that are at high risk for pollution events from oil and gas drilling and shipping (such as bilge dumping). This is also the first step towards one of SkyTruth’s major multi-year goals: automating the detection of marine oil pollution, so we can create and publish a global map of offshore pollution events, updated on a routine basis.

Be sure to keep an eye out for more updates, as we will be publishing the full datasets once we complete the publication cycles.