In this study, we introduce a data-driven algorithm designed to optimize the placement of CMS sensors. The algorithm is modular and a visual summary of the algorithm is provided in Section S1 in the Supporting Information (SI) document. The algorithm requires three critical inputs: site-specific wind patterns, emission characteristics, and a predefined sensor budget which dictates the number of sensors that can be deployed. Utilizing these inputs, our algorithm calculates the optimal sensor arrangement within the budget, aiming to maximize emission detection efficiency, defined as the frequency or likelihood with which at least one sensor in the system detects an emission. Detection efficiency, the objective to be optimized in the sensor placement problem, can also be defined using other metrics such as time to first detection or detection fraction based on total time or amount of emissions. Due to the flexibility of GAs, the objective function can be adjusted accordingly without altering the entire framework. The workflow of the algorithm is structured into five distinct steps: