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<p>Correlations of nighttime atmospheric methane (<span class="inline-formula">CH₄</span>) and <span class="inline-formula">²²²</span>radon (<span class="inline-formula">²²²Rn</span>) observations in Heidelberg, Germany, were evaluated with the radon tracer method (RTM) to estimate the trend of annual nocturnal <span class="inline-formula">CH₄</span> emissions from 1996–2020 in the footprint of the station. After an initial 30 <span class="inline-formula">%</span> decrease in emissions from 1996 to 2004, there was no further systematic trend but small inter-annual variations were observed thereafter. This is in accordance with the <i>trend</i> of total emissions until 2010 reported by the EDGARv6.0 inventory for the surroundings of Heidelberg and provides a fully independent top-down verification of the bottom-up inventory <i>changes</i>. We show that the reliability of total nocturnal <span class="inline-formula">CH₄</span> emission estimates with the RTM critically depends on the accuracy and representativeness of the <span class="inline-formula">²²²Rn</span> exhalation rates estimated from soils in the footprint of the site. Simply using <span class="inline-formula">²²²Rn</span> fluxes as estimated by Karstens et al. (2015) could lead to biases in the estimated greenhouse gas (GHG) fluxes as large as a factor of 2. RTM-based GHG flux estimates also depend on the parameters chosen for the nighttime correlations of <span class="inline-formula">CH₄</span> and <span class="inline-formula">²²²Rn</span>, such as the nighttime period for regressions and the <span class="inline-formula"><i>R</i>²</span> cut-off value for the goodness of the fit. Quantitative comparison of total RTM-based top-down flux estimates with bottom-up emission inventories requires representative high-resolution footprint modelling, particularly in polluted areas where <span class="inline-formula">CH₄</span> emissions show large heterogeneity. Even then, RTM-based estimates are likely biased low if point sources play a significant role in the station footprint as their emissions may not be fully captured by the RTM method, for example, if stack emissions are injected above the top of the nocturnal inversion layer or if point-source emissions from the surface are not well mixed into the footprint of the measurement site. Long-term representative <span class="inline-formula">²²²Rn</span> flux observations in the footprint of a station are indispensable in order to apply the RTM method for reliable <i>quantitative</i> flux estimations of GHG emissions from atmospheric observations.</p>