2025/11/25 by Yann Büchau, Jens Bange · 1 voice
Environmental Science · Earth and Planetary Sciences · #Atmospheric and Environmental Gas Dynamics #Air Quality Monitoring and Forecasting #Atmospheric chemistry and aerosols
paper · pdf · doi:10.1371/journal.pclm.0000741
openalex created_date 2025/10/10 · openalex publication_date 2025/11/25 · openalex updated_date 2026/07/31
We present a top-down method to derive <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" id="M2"> <mml:mrow> <mml:msub> <mml:mrow> <mml:mi mathvariant="normal">C</mml:mi> <mml:mi mathvariant="normal">O</mml:mi> </mml:mrow> <mml:mrow> <mml:mn>2</mml:mn> </mml:mrow> </mml:msub> </mml:mrow> </mml:math> 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 <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" id="M3"> <mml:mrow> <mml:msub> <mml:mrow> <mml:mi mathvariant="normal">C</mml:mi> <mml:mi mathvariant="normal">O</mml:mi> </mml:mrow> <mml:mrow> <mml:mn>2</mml:mn> </mml:mrow> </mml:msub> </mml:mrow> </mml:math> emission rate of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" id="M4"> <mml:mrow> <mml:mrow> <mml:mn>3266</mml:mn> </mml:mrow> <mml:mtext> </mml:mtext> <mml:msup> <mml:mrow> <mml:mi mathvariant="normal">k</mml:mi> <mml:mi mathvariant="normal">g</mml:mi> <mml:mtext> </mml:mtext> <mml:mi mathvariant="normal">d</mml:mi> </mml:mrow> <mml:mrow> <mml:mo>−</mml:mo> <mml:mn>1</mml:mn> </mml:mrow> </mml:msup> <mml:mi>±</mml:mi> <mml:mn>42</mml:mn> <mml:mi>%</mml:mi> </mml:mrow> </mml:math> over a <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" id="M5"> <mml:mrow> <mml:mrow> <mml:mn>400</mml:mn> </mml:mrow> <mml:mtext> </mml:mtext> <mml:msup> <mml:mi>m</mml:mi> <mml:mn>2</mml:mn> </mml:msup> </mml:mrow> </mml:math> 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 CCS sites, for which the Starzach site is a natural analog.