Field measurements and stochastic modeling of particle removal in a spray scrubber with heat recovery at a 3 MW biomass boiler

To mitigate climate change, there is an urgent need for carbon-neutral energy sources. The combustion of biomass for district heating is a well-established and energy-efficient method for this. However, biomass combustion generates particulate matter (PM) which has severe consequences for human health. To reduce PM emissions from medium-scale combustion facilities, economically feasible removal solutions are of great importance. This study investigates the performance of a centrifugal spray scrubber integrated with heat recovery installed at a 3 MW biomass-fired boiler, combining on-site aerosol measurements with stochastic modeling. Particle size distributions were measured using a combination of a low-pressure cascade impactor (LPI), an Aerodynamic Particle Sizer (APS), and a Scanning Mobility Particle Sizer (SMPS). Besides particle morphologies, the chemical composition and particle density were derived through stoichiometric reconstruction of scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS) measurements. Experimental results showed the scrubber achieved particle removal close to 100% for particles larger than 1 μm while submicron removal reached between 26% – 36% under varying process conditions. A module-based simulation model, developed and validated against these field measurements, could reproduce the observed performance within the limits of the uncertainties of the measurement data. The model analysis indicates that rear capture, thermophoresis, and diffusiophoresis work as critical mechanisms governing submicron particle removal in combustion-connected scrubbers. These results demonstrate the practical effectiveness of spray scrubbing for coarse PM control and clarify the mechanistic pathways that currently limit yet offer optimization potential for submicron particle removal when coupled with heat recovery.