Quantification of natural CO2 emissions from mofettes using a low-cost sensor network at the Starzach site in south-west Germany

Yann Georg Büchau , Jens Bange

We present a top-down method to derive carbon dioxide (CO2) emissions from mofettes, using only point measurement time series at irregular locations. Notably, no wind vector information is needed, as gas transport is derived from cross-correlations between sensor stations and subsequently integrated using Gauss’ divergence theorem. The method is applied to an existing low-cost sensor network at the Starzach site near the Black Forest in Germany, for which no comprehensive estimate of the total emissions exists yet. For validation, we use previous bottom-up measurements of individual mofette degassing and a Gaussian puff approach. Over a period of one and a half months around August 2022, we determine an average CO2 emission rate of 3266kgd−1±42% over a 400m2 area. This result is larger than expected and suggests that diffuse degassing plays a more important role at site than previously assumed. The method could also be applied for real-time monitoring of leaky Carbon Capture and Sequestration (CCS) sites, for which the Starzach site is a natural analog.