Tracking city COsub2/sub emissions from space using a high-resolution inverse modelling approach: a case study for Berlin, Germany

摘要

pstrongAbstract./strong Currently, 52span class="thinspace"/span% of the world's population resides in urban areas and as a consequence, approximately 70span class="thinspace"/span% of fossil fuel emissions of COsub2/sub arise from cities. This fact, in combination with large uncertainties associated with quantifying urban emissions due to lack of appropriate measurements, makes it crucial to obtain new measurements useful to identify and quantify urban emissions. This is required, for example, for the assessment of emission mitigation strategies and their effectiveness. Here, we investigate the potential of a satellite mission like Carbon Monitoring Satellite (CarbonSat) which was proposed to the European Space Agency (ESA) to retrieve the city emissions globally, taking into account a realistic description of the expected retrieval errors, the spatiotemporal distribution of COsub2/sub fluxes, and atmospheric transport. To achieve this, we use (i)??a high-resolution modelling framework consisting of the Weather Research Forecasting model with a greenhouse gas module (WRF-GHG), which is used to simulate the atmospheric observations of column-averaged COsub2/sub dry air mole fractions (XCOsub2/sub), and (ii)??a Bayesian inversion method to derive anthropogenic COsub2/sub emissions and their errors from the CarbonSat XCOsub2/sub observations. We focus our analysis on Berlin, Germany using CarbonSat's cloud-free overpasses for 1 reference year. The dense (wide swath) CarbonSat simulated observations with high spatial resolution (approximately 2span class="thinspace"/spankmspan class="thinspace"/spana????a??span class="thinspace"/span2span class="thinspace"/spankm) permits one to map the city COsub2/sub emission plume with a peak enhancement of typically 0.8a??1.35span class="thinspace"/spanppm relative to the background. By performing a Bayesian inversion, it is shown that the random error (RE) of the retrieved Berlin COsub2/sub emission for a single overpass is typically less than 8a??10span class="thinspace"/spanMtspan class="thinspace"/spanCOsub2/subspan class="thinspace"/spanyrsupa??1/sup (about 15a??20span class="thinspace"/span% of the total city emission). The range of systematic errors (SEs) of the retrieved fluxes due to various sources of error (measurement, modelling, and inventories) is also quantified. Depending on the assumptions made, the SE is less than about 6a??10span class="thinspace"/spanMtspan class="thinspace"/spanCOsub2/subspan class="thinspace"/spanyrsupa??1/sup for most cases. We find that in particular systematic modelling-related errors can be quite high during the summer months due to substantial XCOsub2/sub variations caused by biogenic COsub2/sub fluxes at and around the target region. When making the extreme worst-case assumption that biospheric XCOsub2/sub variations cannot be modelled at all (which is overly pessimistic), the SE of the retrieved emission is found to be larger than 10span class="thinspace"/spanMtspan class="thinspace"/spanCOsub2/subspan class="thinspace"/spanyrsupa??1/sup for about half of the sufficiently cloud-free overpasses, and for some of the overpasses we found that SE may even be on the order of magnitude of the anthropogenic emission. This indicates