Methane Airborne Mapper MAMAP

  • Methane airborne MAPper (MAMAP): A new airborne 2 channel NIR-SWIR grating spectrometer system for column-averaged methane and carbon dioxide observations from aircraft. A joint research project of the:
  • Institute of Environmental Physics / Remote Sensing (IUP/IFE), University of Bremen (Germany) and the
  • Helmholtz Centre Potsdam, German Research Centre for Geosciences (GFZ).

Scientific Objectives

  • Carbon dioxide (CO2) and methane (CH4) are the two most important anthropogenic greenhouse gases (GHG) contributing to climate change. In addition CH4 plays an important role in the chemistry cycle of the atmosphere.
  • Despite the importance of understanding the global atmospheric CH4 and CO2 budgets, our current knowledge about the sources (and sinks) of CH4 and CO2 has significant gaps. This arises in part because of the difficulty in estimating the highly spatially and temporally variable anthropogenic and natural atmospheric source emissions.
  • Up to now, flux estimates of CH4 and CO2 of current global, synoptic, and mesoscale 3-D chemical transport and climate models (CTM and CM) are based on either bottom-up or top-down approaches.
  • Bottom-up flux estimates of anthropogenic sources are typically compiled by national authorities by the assessments of economic statistical data or by emission factor estimates using a variety of procedures. For bottom-up flux estimates of natural sources, ground-based microscale measurements are collected from a variety of different techniques, such as closed chamber and eddy covariance methods. Emission and flux estimates obtained by these techniques are typically assigned to specific soil/vegetation types and then are spatially extrapolated to meso and synoptic scales using, for example, a global vegetation index, derived from satellite imaging data.
  • Top-down global, synoptic, and mesoscale emission estimates are based on precise and accurate atmospheric in-situ concentration measurements of the relevant gases from surface networks, tall towers, helicopters, aircrafts, and trains. These measurements are then inverted by inverse models to estimate flux rates between the surface and the atmosphere. Natural and anthropogenic bottom-up flux estimates are typically input into the inversion calculations. Based on the measured data the anthropogenic and natural fluxes are modified during the inversion calculation in a way that the simulated atmospheric concentrations better match the observations. As a result of the coarse density of the surface observation network, information about surface fluxes distant from the network is still not well defined and ambiguous. Especially discrimination of the different source types remains still inaccurate.
  • With the launch of the environmental satellites ENVISAT and GOSAT, with the SCIAMACHY and TANSO-FTS instruments on board new remote sensing data were incorporated for the first time to estimate the annual CH4 (and CO2) surface fluxes at a resolution of several degrees using top-down inverse modeling. Because SCIAMACHY’s and GOSAT's large typical footprints of 60 km × 30 km (for SCIAMACHY) and 10 km diameter (for GOSAT), and the large gaps between the typical measurements of GOSAT single local emissions cannot be accurately resolved in the currently available satellite data. Therefore the contribution of small “hot-spot” areas and single facilities is not sufficiently resolved with the existing ground-based and satellite observational systems.
  • To fill this gap, a team from the IUP Bremen and the GFZ designed and built an airborne remote sensing system, which is capable to detect surface sources of CH4 and CO2 at both local and regional resolution and coverage. The instrument is designed to measure the column averaged mixing ratio of methane (XCH4) and carbon dioxide (XCO2) with a total column relative accuracy and precision of equal or better than ~ 1% with respect to the atmospheric background.
  • MAMAP can not only deliver significant information on greenhouse gas emissions from localized sources like hard coal mines, large landfills, natural gas and oil production facilities, power plants, (mud) volcanoes, on- and offshore natural gas blowouts etc. but may also serve to validate and complement satellite measurements of current and future satellite missions, e.g. like the proposed greenhouse gas satellite mission CarbonSat (Bovensmann et al., 2010, ).
  • The instrument is able to deliver quantitative column information, well suited for quantitative emission estimates based on inverse atmospheric modeling. Such data can be used for instance for quantification of accidental emissions with source strengths like reported by TOTAL for the ELGIN accident (see also here or for top-down estimates of the total emissions from large oil and gas production facilities and fields) or for top-down estimates of the total emissions from large oil and gas production facilities and and fields.
  • (see also here for AGU 2014 handout).