Quantifying city-scale methane emissions based on ground-site, mobile, and satellite observations: an observing system simulation experiment (OSSE)

As a hotspot for greenhouse gas emissions, cities also represent a major opportunity for mitigating greenhouse gases including methane. However, city-scale methane emissions are often inadequately resolved in most of existing global/national “bottom-up” inventories, because of coarse-resolution and biased activity data or proxies used for constructing these inventories. The observation-based “top-down” inversion method provides an alternative approach to detect and quantify city-scale methane emissions, but it is often limited by the availability of useful city observations. Here, we construct a city-scale inversion system using a high-resolution (4 km) WRF-GHG transport model for a megacity, Hangzhou, in the densely populated Yangtze River Delta of China. We perform an observing system simulation (OSSE) to assess the ability of different observation systems (including ground-site, mobile, satellite observations, and their combinations) to constrain and resolve methane emissions from Hangzhou. The construction of “true” observations in OSSE accounts for main characteristics of different observations systems, e.g., temporally continuous but spatially sparse ground-site observations, spatially continuous but temporally sparse mobile observations, and coarse-resolution and low-precision satellite column observations. The results show that ground-level observations (including ground sites and mobile observations), though taken within the city, largely reflect signals from up-wind adjacent regions with large methane emission. The small local signals in the sparse ground-level observations have little constraining in the inference city posterior emissions and lead to large uncertainties. Joint inversion of ground and satellite observations with a wider modeling domain leads to a more accurate posterior emission of the targeted city, as it better captures and distinguish the contribution from surrounding regions. This result also underscores the accuracy of model transport for the city-scale emission estimation.