A "bottom-up" probabilistic model was developed using engineering first-principles to quantify annualized throughput normalized methane emissions (TNME) from natural gas liquid unloading activities for 18 basins in the United States in 2016. For each basin, six discrete liquid-unloading scenarios are considered, consisting of combinations of well types (conventional and unconventional) and liquid-unloading systems (nonplunger, manual plunger lift, and automatic plunger lift). Analysis reveals that methane emissions from liquids unloading are highly variable, with mean TNMEs ranging from 0.0093% to 0.38% across basins. Automatic plunger-lift systems are found to have significantly higher per-well methane emissions rates relative to manual plunger-lift or non-plunger systems and on average constitute 28% of annual methane emissions from liquids unloading over all basins despite representing only ∼0.43% of total natural gas well count. While previous work has advocated that operational malfunctions and abnormal process conditions explain the existence of super-emitters in the natural gas supply chain, this work finds that super-emitters can arise naturally due to variability in underlying component processes. Additionally, average cumulative methane emissions from liquids unloading, attributed to the natural gas supply chain, across all basins are ∼4.8 times higher than those inferred from the 2016 Greenhouse Gas Reporting Program (GHGRP). Our new model highlights the importance of technological disaggregation, uncertainty quantification, and regionalization in estimating episodic methane emissions from liquids unloading. These insights can help reconcile discrepancies between "top-down" (regional or atmospheric studies) and "bottom-up" (component or facility-level) studies.