Estimation of fugitive Landfill Methane Emissions using Drone-Based Surface emission Monitoring and GA Optimization

The algorithm identifies positions of leakage sources and to quantify the gas emission rate from the surface of a landfill. An optimization-based approach using Genetic Algorithms (GA) is employed to solve the inverse problem that consists of identifying source data (locations of hot-spots and corresponding emission rates) having only receptor location and surface measurements as input data. Single and multi-objective optimization schemes through GAs are used with surface methane concentration data along with wind speed and wind direction during the monitoring campaign.  This is the measurement data. The optimization methodology uses atmospheric dispersion calculations to predict major methane emissions sources in a landfill. The total emissions of the landfill are then estimated by summing all of the methane sources predicted by the algorithm.

Advantages

• More accurate calculations
• Quicker calculations