Modeling Filter Bypass: Impact on Filter Efficiency

Current models and test methods for determining filter efficiency ignore filter bypass, the air that circumvents filter media because of gaps around the filter or filter housing. In this paper, we develop a general model to estimate the size-resolved particle removal efficiency, including bypass, of HVAC filters. The model applies the measured pressure drop of the filter to determine the airflow through the bypass cracks and accounts for particle loss in the bypass cracks. We consider a particle size range of 0.01 to 10 μm, nine typical commercial and residential filters in clean and dust-loaded configurations, and a wide range of bypass gaps typical of those found in real filter installations. The model suggests that gaps on the order of 1 mm around well-seated filters have little effect on the performance of most filters. For high pressure drop filters, small gaps decrease filter performance and large gaps substantially decrease filter performance. Because higher efficiency filters also typically have a larger pressure drop, bypass tends to have a larger effect on high performance filters. The results provided here suggest that bypass can dramatically affect filter performance. INTRODUCTION Filtration in HVAC systems is the most widely used method for protecting people and equipment from airborne particulate matter. To aid in filter selection, there are several standards that address HVAC filtration efficacy including ASHRAE Standard 52.2: Method of Testing General Ventilation Air-Cleaning Devices for Removal Efficiency by Particle Size (ASHRAE 1999) and ASHRAE Standard 52.1: Gravimetric and Dust-Spot Procedures for Testing Air-Cleaning Devices Used in General Ventilation for Removing Particulate Matter (ASHRAE 1992). The result of an ASHRAE Standard 52.2 test includes the Minimum Efficiency Reporting Value (MERV), which classifies filters according to their efficiency. Standard 52.2, as well as most other filter test methodologies, are tests of the filter media, rather than the installed filter system. When applied to real systems, filter test results implicitly assume that no bypass exists around filters. Examination of most residential and commercial HVAC systems suggests that this is not a good assumption: both small and large gaps are common. The purpose of this paper is to simulate the effect of filter bypass on common filters. HVAC filtration has been widely studied, and several studies have measured particle-size resolved efficiencies for a variety of filters (e.g. Hanley et al. 1994; Raynor and Chae 2003). Filter efficiency curves are typically Ushaped with very small particles (<0.05 μm) removed by Brownian diffusion and very large particles (>5 μm) removed by inertial mechanisms. Although most measurements have been made with filter bypass intentionally sealed, there are numerous anecdotal reports of particle bypass. Braun (1986) reported that catastrophic filter bypass led to fouling of an evaporator coil. Ottney (1993) and several others suggest that eliminating filter bypass is an important component of achieving acceptable indoor air quality. Siegel (2002) simulated filter bypass and suggested that even moderate amounts of filter bypass could dramatically increase HVAC heat exchanger fouling. Despite its obvious importance, we know of no existing mathematical models for filter bypass and decisionmakers have limited information available on the effect of bypass. In this paper we present a model of filter bypass that predicts the amount of air that will bypass a filter, and the effect on overall filter efficiency. The most important independent parameters are the size (i.e. gap width) and geometry of the gaps around the filter and the efficiency and pressure drop of the filter. We report several parameters including the volumetric airflow that bypasses the filter (QB) and the effective filter efficiency as a function of particle diameter (ηeff) for the filter system (filter + bypass). We apply our model to a variety of commonly used HVAC filters in order to understand the interplay between filter efficiency, pressure drop, and bypass. From these simulations, we calculate the effective MERV (MERVeff) that accounts for bypass. The results are intended to provide additional assistance when selecting filters and to quantify the benefits associated with eliminating bypass. METHODOLOGY An effective filtration efficiency that includes bypass can be derived by differentiating bypass flow from filtered flow. Knowledge of both the bypass flow rate and the removal of particles in the gap, as well as the flow through the filter and the particle removal by the filter, are needed to implement the model. In order to quantify bypass flow, a quadratic relationship is employed to relate flow to pressure drop in a rectangular sharp-edged crack such as are present in HVAC filter holders or slots. Flow through the filter and filter efficiency are determined from measured data in the literature. The flow through an HVAC filter system (Q) can be considered as the sum of the flow passing through the filter media (QF) and the flow bypassing the filter (QB). The effective particle removal efficiency of the filter can then be written in terms of the penetration fraction of particles passing through the filter (PF) and the penetration fraction of particles bypassing the filter (PB) as shown in Equation 1.       + − = Q Q P Q P B B F F eff 1 η (1) PF is equal to one minus the measured particle removal efficiency, ηF, of a filter with the gap sealed (QB = 0). Hanley et al. (1994) measured PF and Q for various filters with different dust loadings and pressure drops. They eliminated bypass in their experiments, so Q equals QF for their work. The results of Hanley et al. (1994) and the measurements of filters from a major manufacturer by an independent laboratory provide values of PF and QF for our model. We estimated QB by using an expression, derived by Baker et al. (1987), that relates airflow to pressure drop through a rectangular-shaped crack in terms of the crack dimensions. Equation 2 is the Baker et al. (1987) expression applied to a bypass crack around a filter. This expression accounts for both laminar and turbulent flow and is directly applicable to the sharp-edged, rectangular gap between a filter and the filter frame or slot that holds the filter in place. 2 2 2 3 2 ) 5 . 1 ( 12 B B Q H W n Q WH L P ρ μ + + = ∆ (2) where ∆P is the pressure drop across the filter, QB is the flow rate of air bypassing the filter, L is the length of the crack longitudinal to the flow, W is the width of the crack perpendicular to flow, H is the height of the crack, n is the number of right angle bends (n < 3 for Equation 2 to be valid) in the path of bypass flow, μ is the dynamic viscosity of air, and ρ is the density of the air. Baker et al. (1987) experimentally validated their model for ∆P between 0.1 and 100 Pa, and they demonstrated that, for ∆P up to 200 Pa, their model is superior to the power law relationship between pressure drop and flow. The results of Baker et al. (1987) show strongest agreement with measured data for higher Reynolds numbers and large gaps, conditions typical of those around HVAC filters. Equation 2 can be solved for QB, as shown in Equation 3:         +   