Methane (CH<sub>4</sub>), alongside carbon dioxide (CO<sub>2</sub>), is a key driver of anthropogenic climate change. Reducing CH<sub>4</sub> is crucial for short-term climate mitigation. Waste-related activities, such as landfills, are a major CH<sub>4</sub> source, even in developed countries. Atmospheric concentration measurements using remote sensing offer a powerful way to quantify these emissions. We study waste facilities near Madrid, Spain, where satellite data indicated high CH<sub>4</sub> emissions. For the first time, we combine passive imaging (MAMAP2DL) and active lidar (CHARM-F) remote sensing aboard the German research aircraft HALO, supported by in situ instruments, to quantify CH<sub>4</sub> emissions. Using the CH<sub>4</sub> column data and ECMWF-ERA5 model wind information validated by airborne measurements, we estimate landfill emissions through a cross-sectional mass balance approach. Strong emission plumes are traced up to 20 km downwind on the 4<sup>th</sup> August 2022, with the highest CH<sub>4</sub> column anomalies observed over active landfill areas in the vicinity of Madrid, Spain. Total emissions are estimated at ~13 th<sup>-1</sup>. Single co-located plume crossings from both instruments agree well within 1.2 th<sup>-1</sup> (or 13 %). Flux errors range from ~25 to 40 %, mainly due to boundary layer and wind speed variability. This case study not only showcases the capabilities of applying a simple but fast cross-sectional mass balance approach, as well as its limitations due to challenging atmospheric boundary layer conditions, but also demonstrates the, to our knowledge, first successful use of both active and passive airborne remote sensing to quantify methane emissions from hot spots and independently verify their emissions.