We introduce an innovative method to distinguish soil nitrogen oxides (NOx=NO+NO2) emissions from satellite-based total NOx emissions using its seasonal characteristics. To evaluate the approach, we compare the deviation between the tropospheric NO2 concentration observed by satellite and two atmospheric composition model simulations driven by the newly estimated soil NOx emissions and the Copernicus Atmosphere Monitoring Service (CAMS) inventory. The estimated average soil NOx emissions in Europe are 2.5 kg N ha-1 yr-1 in 2019, and the annual soil NOx emissions is approximately 2.5 times larger than that of the CAMS inventory. Our method can easily be extended to other regions at middle or high latitudes with similar seasonal characteristics of soil emissions. The soil emissions are subtracted from the total NOx emissions yielding realistic anthropogenic NOx emissions. We further show this also yields realistic anthropogenic CO2 emissions using known CO2/NOx factors from bottom-up inventories.

Recent research has put in evidence the self-lofting capacity of smoke aerosols in the stratosphere and their self-confinement by persistent anticyclones, which prolongs their atmospheric residence time and radiative effects. By contrast, the volcanic aerosols-composed mostly of non-absorptive sulphuric acid droplets-were never reported to be subject of self-lofting nor of dynamical confinement. Here we use high-resolution satellite observations to show that the eruption of Raikoke volcano in June 2019 produced a long-lived stratospheric anticyclone containing 24% of the total erupted mass of sulphur dioxide. The anticyclone persisted for more than 3 months, circumnavigated the globe three times, and ascended diabatically to 27 km altitude through radiative heating of volcanic ash contained by the plume. The mechanism of dynamical confinement has important implications for the planetary-scale transport of volcanic emissions, their stratospheric residence time, and atmospheric radiation balance. It also provides a challenge or “out of sample test” for weather and climate models that should be capable of reproducing similar structures.

Key points: • A new divergence method is developed to estimate methane emissions based on satellite observations, requiring no a priori emissions. • The applicability of this method in identifying and quantifying sources is proven by a GEOS-Chem simulation with known a priori emissions. • The estimated emissions over Texas (United States) based on TROPOMI observations are evaluated and are found to be robust. Abstract We present a new divergence method to estimated methane (CH 4) emissions from satellite observed mean mixing ratio of methane (XCH 4) by deriving the regional enhancement of XCH 4 in the Planetary Boundary Layer (PBL). The applicability is proven by comparing the estimated emissions with its a priori emission inventory from a 3-month GEOS-Chem simulation. When applied to TROPOspheric Monitoring Instrument (TROPOMI) observations, sources from well-known oil/gas production areas, livestock farms and wetlands in Texas become clearly visible in the emission maps. The calculated yearly averaged total CH 4 emission over the Permian Basin is 3.06 [2.82, 3.78] Tg a-1 for 2019, which is consistent with previous studies and double that of EDGAR v4.3.2 for 2012. Sensitivity tests on PBL heights, on the derived regional background and on wind speeds suggest our divergence method is quite robust. It is also a fast and simple method to estimate the CH 4 emissions globally. Plain Language Summary Methane (CH 4) is an important greenhouse gas in the atmosphere and plays a crucial role in the global climate change. It kept increasing over the last decades. About 70% of CH 4 comes from human activities like oil/gas productions or livestock farms. The recently launched TROPOspheric Monitoring Instrument (TROPOMI) provides an opportunity to estimate the emissions of CH 4 on a regional scale. This work presents a new method to fastly derive CH 4 emissions at a fairly high spatial resolution without a priori knowledge of sources.