I fully support the justification given by the handling editor

This is an important manuscript documenting performances of MethaneAIR imaging spectrometer for accurately measure emissions of CH4 from oil and gas production and processing facilities The MethaneAIR is a precursor of MethaneSAT, a small satellite intended to revolutionize measurements and modeling of emissions of CH4 at regional (100s of km) and fine scales (< 1 km), across the globe. Its deployment onboard the NSF Gulfsteam-V aircraft is an important step for validation and demonstration of MethaneSAT. The paper demonstrates the instrument's ability to quantify methane emission at various scale and concludes successfully the pre-launch validation phase of MethaneSat.

Air pollution is one of the greatest threats to human health, and many of the adverse health effects can be attributed to aerosols. In addition, aerosols play an important role in regulating climate, both through direct effects and through cloud formation. Aerosols can be detected using satellite-based instruments, but due to the broad range of characteristics and their variability in space and time, aerosol retrieval by remote sensing is not trivial. This highlight paper presents the combination of data from six satellite instruments that complement each other. Three of the satellites are in sun-synchronous orbits (observing the whole Earth once per day) and three in geo-stationary orbit (observing a portion of the Earth several times per hour). The paper shows that by combining data from the six instruments a high-quality, consistent data set can be created with a higher combined spatio-temporal resolution and less gaps than existing data sets. The freely available new aerosol data product is provided at 30 minute resolution and on a 0.25 degree grid in a format convenient for use in satellite studies or ingestion by models, providing data that will further advance the field of aerosol studies.

This manuscript provides a detailed overview of aerosol and cloud products to be expected from the upcoming EarthCARE mission. In documenting the basic steps of processing of the data from the ATLID instrument it will be a very valuable source of information for users of the resulting products.

Chemical ionization mass-spectrometry (CIMS) has been widely used in atmospheric chemistry research to detect oxygenated organic compounds. However, accurate quantification of species which do not have generic standards remains a major challenge for CIMS application, and semi-quantitative methods which have been developed to solve this dilemma usually have very large uncertainties. This work introduced a novel classification approach which greatly enhances the accuracy of semi-quantitative methods and effectively reduces their uncertainties. Although the approach was developed in this work specifically for toluene oxidation products, the concept can also be applied to other oxygenated organic compounds and may significantly enhance the quantification ability of CIMS.