ENHANCING QUALITY, UTILITY, SUSTAINABILITY, ENVIRONMENTAL IMPACT OF COTTON AND ITS BYPRODUCTS THROUGH IMPROVEMENT IN HARVEST/GIN PROCESSING
Location: Cotton Ginning Research
Title: Techniques for measuring particle size distribution of particulate matter emitted from animal feeding operations
| Wang-Li, Lingjuan - |
| Cao, Zihan - |
| Buser, Michael - |
| Parnell, Calvin - |
| Zhang, Yuanhui - |
Submitted to: Atmospheric Environment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: August 25, 2012
Publication Date: January 17, 2013
Citation: Cao, Z., Buser, M., Whitelock, D.P., Wang-Li, L., Parnell, C., Zhang, Y. 2013. Techniques for measuring particle size distribution of particulate matter emitted from animal feeding operations. Atmospheric Environment. 66:25-32.
Interpretive Summary: When dealing with dust or particulate emitted from different industries, the size distribution of the dust is one of the most important physical parameters governing how the particles behave in the air. There is some debate about the best method to determine the size distribution of particulate emitted from difference sources. This study found that the size of same dust determined by different particle size analyzers was different. In general, the laser diffraction methods of particle size analysis provided the largest size measurements and broader measurement variability, while the electrical sensing zone method (Coulter Counter) provided the smallest. Also, it was observed that fitting statistical distributions to the measured data produced reasonably accurate mass fraction estimates for particulate less than 10 microns in diameter, but failed to produce accurate mass fraction estimates for particulate with diameter less than 2.5 microns. It is strongly recommended that when reporting a particle size distribution for certain particulate samples the mass fractions of particles with diameter less than 10 and 2.5 microns should also be reported. Federal and state agencies regulate emissions of particulate with diameter less than 10 and 2.5 microns from sources, including ag facilities and processors. For these industries to be regulated equitably, accurate measurements of those emissions are imperative.
Particle size distribution (PSD) is perhaps the most important physical parameter governing the airborne particle behavior. Various methods and techniques are available for conducting PSD analyses. Unfortunately, there is no single agreed upon method to determine the PSDs of particulate matter (PM) emitted from difference sources. This study investigated differences in the PSD measurements by four PSD analyzers: LS13320 multi-wave length laser diffraction particle, LS230 laser diffraction particle size analyzer, LA-300 laser scattering particle size analyzer, and Coulter Counter Muiltisizer3 (CCM3). Total suspended particulate (TSP) samples were collected in a commercial egg production (layer) house using co-located low-volume TSP samplers. The simultaneously collected TSP samples were analyzed by the four analyzers for PSDs. In addition, four types of testing aerosol samples (limestone, starch, No.3 micro aluminum, and No.5 micro aluminum) were also analyzed by these four PSD analyzers. The results of this study suggest when comparing mass median diameters (MMDs) and geometric standard deviations (GSD) of PSDs measured by the different particle size analyzers, there were significant differences in MMDs and GSDs of the PM samples collected in the layer house. In general, the LA-300 provided the largest MMDs, whereas CCM3 gave the smallest ones. LS13 320 analyzer provided the largest GSDs, whereas CCM3 analyzer gave the smallest. The PSD results of testing aerosols measured by the different analyzers were generally consistent with that of the PM samples collected in the layer house. For the field PM samples and the testing aerosols, the laser diffraction method (LS13 320, LS230 and LA-300) provided much larger MMDs and broader distributions (GSDs) than the electrical sensing zone method (CCM3). When comparing mass fractions of PM10 or PM2.5 between the measured values and the lognormal fitting values using measured MMDs and GSDs, it was observed that lognormal fitting method produced reasonably accurate PM10 mass fraction estimations (within 5%) but it failed to produce accurate PM2.5 mass fraction estimations. The mean differences between measured PM2.5 and lognormal-fitting PM2.5 were in range of 54.96% (±13.04%)-94.46% (±3.05%). It is strongly recommended that when reporting a PSD of certain PM samples, in addition to MMD and GSD, the mass fractions of PM10 and PM2.5 should also be reported.