  Black carbon (BC) is an important pollutant aerosol emitted by numerous human
activities, including gas flaring. Improper combustion in flaring activities
can release large amounts of BC, which is harmful to human health and has a
strong climate warming effect. To our knowledge, no study has ever directly
monitored BC emissions from satellite imagery. Previous works quantified BC
emissions indirectly, by applying emission coefficients to flaring volumes
estimated from satellite imagery. Here, we develop a deep learning framework
and apply it to Sentinel-2 imagery over North Africa during 2022 to detect and
quantify BC emissions from gas flaring. We find that BC emissions in this
region amount to about 1 million tCO$_{2,\mathrm{eq}}$, or 1 million passenger
cars, more than a quarter of which are due to 10 sites alone. This work
demonstrates the operational monitoring of BC emissions from flaring, a key
step in implementing effective mitigation policies to reduce the climate impact
of oil and gas operations.
