The quantification of emissions of the greenhouse gas methane is essential for attributing the roles of anthropogenic activity and natural phenomena in global climate change. Our current measurement systems and networks whilst having improved during 5 the last decades, are deficient in many respects. For example, the emissions from localised and point sources such as landfills or fossil fuel exploration sites are not readily assessed. A tool developed to better understand point sources of the greenhouse gases carbon dioxide and methane is the optical remote sensing instrument MAMAP, operated from aircraft. After a recent instrument modification, retrievals of the column 10 averaged dry air mole fractions for methane XCH4 (or for carbon dioxide XCO2) derived from MAMAP data, have a precision of about 0.4% or better and thus can be used to infer emission rate estimates using an optimal estimation inverse Gaussian plume model or a simple integral approach. CH4 emissions from two coal mine ventilation shafts in Western Germany surveyed 15 during the AIRMETH2011 measurement campaign are used as examples to demonstrate and assess the value of MAMAP data for quantifying CH4 from point sources. While the knowledge of the wind is an important input parameter in the retrieval of emissions from point sources and is generally extracted from models, additional information from a turbulence probe operated on-board the same aircraft was utilised to 20 enhance the quality of the emission estimates. Although flight patterns were optimised for remote sensing measurements, data from an in-situ analyser for CH4 were found to be in good agreement with retrieved dry columns of CH4 from MAMAP and could be used to investigate and refine underlying assumptions for the inversion procedures. With respect to the total emissions of the mine at the time of the overflight, the in25 ferred emission rate of 50.4 ktCH4 yr−1 has a difference of less than 1% compared to officially reported values by the mine operators, while the uncertainty, which reflects variability of the sources and conditions as well as random and systematic errors, is about ±13.5 %.