التفاصيل البيبلوغرافية
| العنوان: |
Optimizing a dynamic fossil fuel CO2 emission model with CTDAS (v1.0) for an urban area using atmospheric observations of CO2, CO, NOx, and SO2. |
| المؤلفون: |
Super, Ingrid, van der Gon, Hugo A. C. Denier, van der Molen, Michiel K., Dellaert, Stijn N. C., Peters, Wouter |
| المصدر: |
Geoscientific Model Development Discussions; 2020, p1-38, 38p |
| مصطلحات موضوعية: |
FOSSIL fuels, CITIES & towns, TRAFFIC density, POWER resources, EMISSION inventories, MOLE fraction, CARBON cycle |
| مستخلص: |
We present a modelling framework for fossil fuel CO2 emissions in an urban environment, which allows constraints from emission inventories to be combined with atmospheric observations of CO2 and its co-emitted species CO, NOx, and SO2. Rather than a static assignment of average emission rates to each unit-area of the urban domain, the fossil fuel emissions we use are dynamic: they vary in time and space in relation to data that describe or approximate the activity within a sector, such as traffic density, power demand, 2m temperature (as proxy for heating demand), and sunlight and wind speed (as proxies for renewable energy supply). Through inverse modelling, we optimize the relationships between these activity data and the resulting emissions of all species within the dynamic fossil fuel emission model, based on atmospheric mole fraction observations. The advantage of this novel approach is that the optimized parameters (emission factors and emission ratios, N=44) in this dynamic model (a) vary much less over space and time, (b) allow a physical interpretation of mean and uncertainty, and (c) have better defined uncertainties and covariance structure. This makes them more suited to extrapolate, optimize, and interpret than the gridded emissions themselves. The merits of this approach are investigated using a pseudo-observation-based ensemble Kalman filter inversion setup for the Dutch Rijnmond area at 1×1km resolution. [ABSTRACT FROM AUTHOR] |
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| قاعدة البيانات: |
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