WattTime, a nonprofit that is now a subsidiary of the Rocky Mountain Institute, made a splash earlier this year with Automated Emissions Reduction. AER is a program that uses real-time grid data and machine learning to determine exactly when the grid is producing the cleanest electricity. It can then automatically adjust power consumption to match up with those times, ensuring that users take advantage of the lowest-carbon power available. (Many kinds of power consumption can be safely shifted in time, like water heaters, battery charging, and some industrial processes; they are “dispatchable.”) AER is, as the name indicates, entirely automated; it works behind the scenes, without any user intervention.
WattTime will use data from satellites that make theirs publicly available (like the European Union’s Copernicus network and the US Landsat network), as well as data from a few private companies that charge for their data (like Digital Globe). The data will come from a variety of sensors operating at different wavelengths, including thermal infrared that can detect heat.
The images will be processed by various algorithms to detect signs of emissions. It has already been demonstrated that a great deal of pollution can be tracked simply through identifying visible smoke. WattTime says it can also use infrared imaging to identify heat from smokestack plumes or cooling-water discharge. Sensors that can directly track NO2 emissions are in development, according to WattTime executive director Gavin McCormick.
Between visible smoke, heat, and NO2, WattTime will be able to derive exact, real-time emissions information, including information on carbon emissions, for every power plant in the world. (McCormick says the data may also be used to derive information about water pollutants like nitrates or mercury.)