Carbon dioxide plume dispersion simulated at the hectometer scale using DALES: model formulation and observational evaluation

Developing effective global strategies for climate mitigation requires an independent assessment of the green house gas emission inventory at the urban scale. In the framework of the Dutch Ruisdael Observatory infrastructure project, we have enhanced the Dutch Atmospheric Large Eddy-Simulation (DALES) model to simulate carbon diox ide (CO2) plume emission and three-dimensional dispersion within the turbulent boundary layer. The unique ability to ex plicitly resolve turbulent structures a the hectometer resolu tion (100 m) makes DALES particularly suitable for detailed realistic simulations of both singular high-emitting point sources and urban emissions, aligning with the goals of Ruis dael Observatory. The model setup involves a high-resolution simulation (100 m × 100 m) covering the main urban area of the Netherlands (51.5–52.5° N, 3.75–6.45° E). The model integrates meteorological forcing from the HARMONIE AROME weather forecasting model, background CO2 levels from the CAMS reanalysis, and point source emissions and downscaled area emissions derived from the 1 km × 1 km emission inventory from the national registry. The latter are prepared using a sector-specific downscaling workflow, cov ering major emission categories. Biogenic CO2 exchanges from grasslands and forests are interactively included in the hectometer calculations within the heterogeneous land– surface model of DALES. Our evaluation strategy is twofold, comparing DALES simulations with (i) the state-of-the art LOTOS-EUROS model simulations and (ii) Ruisdael surface observations of the urban background in the Rotterdam area at Westmaas and Slufter and in situ rural Cabauw tower mea surements. Our comprehensive statistical analysis confirmed the effectiveness of DALES at modeling the urban-scale CO2 emission distribution and plume dispersion under turbulent conditions but also revealed potential limitations and areas for further improvement. Thus, our new model framework provides valuable insights into the role of anthropogenic and biogenic contributions to local CO2 levels, as well as the transport and dispersion of CO2 emissions. This supports emission uncertainty reduction using atmospheric measure ments and contributes to the development of effective re gional climate mitigation strategies