Monitoring Greenhouse Gases from Space 24/7 with CarbonWatch
CarbonWatch has the ability to identify and monitor the largest sources of carbon emissions from humans, day and night.
The five percent of carbon emissions in the atmosphere, biosphere, and oceans attributable to human activity has disrupted the Earth’s natural carbon cycle and is driving long-term climate change. The ability to regularly identify and monitor the largest sources of human carbon generation will have a significant impact on how we manage solutions to reduce these greenhouse emissions.
At Aerospace, engineers are developing efficient space-based sensors capable of continuously observing the Earth to pinpoint greenhouse gas emissions. Leveraging low-cost small satellites with on-board artificial intelligence processing, Aerospace has created a novel carbon dioxide (CO2) and carbon monoxide (CO) remote sensing system.
CarbonWatch has the ability to measure prominent greenhouse gases regardless of visible light levels, providing a 24-hour day/night space based remote sensing system. This day/night capability can help spot variability in near surface carbon plumes — a source for which few direct measurements exist.
Remote Sensing in the Dark
Contemporary remote sensing instruments can observe background concentrations of greenhouse gases but are limited in the ability to tease out human-generated contributions. Existing sensors can only observe and measure in daylight with long periods between revisiting the same geographic areas. CarbonWatch overcomes these technological limitations by relying on mid-infrared spectral remote sensing capabilities.
“Shortwave and near infrared sensors require sunlight, and longwave instruments can measure carbon dioxide at night but cannot measure carbon monoxide,” according to imaging spectroscopy research scientist, Dr. Katherine Saad. “With mid-infrared, you get the best of the infrared spectrum.”
The instrument’s sensors can measure CO2 and CO signals independent from sunlight, using a replicable simplified architecture and an automated onboard processing system. The device will measure exchanges from specific point sources, including power plants, oil refineries, and wildfires. Scientists then integrate this data with the background CO2 measurements to parse out which facilities are producing carbon dioxide and exacerbating the global climate imbalance.
“Observations by CarbonWatch will inform scientists on the current status of carbon use,” said Dr. John Hackwell, Aerospace Technical Fellow and project lead. “The data collected can be applied to global climate-related discussions, such as the Paris Agreement.”
The CarbonWatch Constellation
Unlike existing sensors, CarbonWatch will be able to detect whether different levels of carbon are emitted throughout a 24-hour period. The team envisions an eventual constellation of 25 CarbonWatch sensors to yield twice-daily coverage of the Earth.
“Having multiple satellites means that if one of them fails, you haven’t jeopardized your whole mission,” said Hackwell. “Coverage will go down a little, but you can still observe and collect data.”
The sensor is compact in terms of size, weight, and power. Noting the effect a payload can have on its future host vehicle, the team designed the instrument to be adaptable—part of a larger satellite bus or a standalone 12U CubeSat. Traditionally burdensome elements, such as a sensor’s need to be actively pointed, were removed. The technology observes roughly 100 km swaths at a time by scanning nadir directly below at the Earth’s surface at the orbital rate of the host spacecraft.
Designed with proliferation and manufacturability in mind, CarbonWatch is optimized to meet the global greenhouse gas monitoring mission by using readily available parts for a low-cost production environment.
Using AI to Automate and Process Spectral Data
A challenge for post-data collection is that the amount of raw information generated from a constellation of spectral sensors is too unwieldy to communicate to ground for processing. Leveraging artificial intelligence and machine learning algorithms created for spectral remote sensing, the CarbonWatch processor can assess the spectral data onboard the satellite. Once trained, the algorithms will be automated to enable the spacecraft to send back identified emitter information to the ground system.
In the future, a constellation of these sensors could be observing Earth day and night — collecting data to quantify emissions and provide a fuller image of how our activities affect the carbon cycle.
“CarbonWatch will contribute to a broader understanding of Earth science, while also taking note of point emitters,” said Hackwell. “Being aware of specific sources is particularly useful for future conversations about the effects of human activity on climate change.”
Interested in how we envision space sensor data and artificial intelligence being combined to bring these observations to your phone? Read The Future of Ubiquitous, Realtime Intelligence: A GEOINT Singularity.