Calvin B. Parnell

PARTICULATE MATTER AND AMMONIA EMISSION FACTORS FOR TUNNEL--VENTILATED BROILER PRODUCTION HOUSES IN THE SOUTHERN U.S

Emissions rates for particulate matter less than 10 .m (PM10) and ammonia (NH3) from commercial tunnel–ventilated broiler houses in central Texas were analyzed using linear regressions to develop emission rates as a function of bird weight for broilers on litter. Interior ambient temperature and relative humidity were not found to be significant factors affecting emissions. From the regression equations, emission rates for PM10 and NH3 for average weight birds in these facilities were estimated. Over a 7–week grow–out period, the average bird weight was estimated to be 1.03 kg, the average emission rate for PM10 was 26.5 mg PM10 bird–1 day–1, and the average emision rate for NH3 was 632 mg bird–1 day–1. The emission factor was defined as the total emission in mass per bird for the grow–out period. For typical production conditions and management, the emission factor for PM10 was 1.3 g PM10 bird–1, and for NH3 the emission factor was 31 g NH3 bird–1. These results were compared to values found in the literature. For a facility comprised of four tunnel–ventilated broiler houses with 27,5000 birds per house and a 2–week idle time between 7–week grow–out periods, the emission inventory was calculated to be 828.2 kg PM10 year–1 and 19,780 kg NH3 year–1. The annual emissions for PM10 were below those required to be reported under the Federal Clean Air Act, and there is currently no requirement for NH3 under this legislation.

PARTICLE SIZE DISTRIBUTION OF CATTLE FEEDLOT DUST EMISSION

The cattle feedlot industry is under increased scrutiny and regulatory involvement at state and national levels with regard to particulate matter (PM) emissions from fugitive sources. Concentrations of total suspended particulate matter (TSP) and PM less than 10 micrometers (PM10) aerodynamic equivalent diameter (AED) were measured, using high volume samplers and Sierra Andersen samplers, respectively. Particle size distributions of dust captured on sampler filters were measured with a Coulter Counter model TAII. Mass median diameters for high volume and PM10 samplers averaged 9.5 ± 1.5 and 6.9 ± 0.8 µm (AED), respectively. Three cattle feedlots (17,000 to 40,000 head capacity) in the Southern Great Plains were used in the study.

DESIGN AND EVALUATION OF A LOW-VOLUME TOTAL SUSPENDED PARTICULATE SAMPLER

The regulation of particulate matter (PM) emitted by agricultural sources, e.g., cotton gins, feed mills, and concentrated animal feeding operations (CAFOs), is based on downwind concentrations of particulate matter less than 10 and 2.5 .m (PM10 and PM2.5) aerodynamic equivalent diameter (AED). Both PM10 and PM2.5 samplers operate by pre-separating PM larger than the size of interest (10 and 2.5 .m) prior to capturing the PM on the filter. It has been shown that Federal Reference Method (FRM) PM10 and PM2.5 samplers have concentration measurement errors when sampling PM with mass median diameters (MMD) larger than the size of interest in ambient air. It has also been demonstrated that most PM from agricultural sources typically have particle size distributions with MMDs larger than 10 .m AED. The PM10 concentration measurement error can be as much as 343% for ambient PM with MMD = 20 .m. These errors are a consequence of the PM10 pre-separator allowing a larger mass of PM greater than 10 .m to penetrate to the filter than the mass of PM less than 10 .m captured by the pre-separator. The mass of the particles greater than 10 .m that are allowed to penetrate to the filter introduces a substantial error in the calculated concentration of PM10. Researchers have reported that sampling PM larger than 2.5 .m AED resulted in a shift in the cutpoint of the pre-separator. If this is true for all PM10 and PM2.5 samplers, then the resulting errors in measurement of ambient concentrations could be even larger. One solution to this problem is to measure the concentration of total suspended particulate (TSP) matter and calculate the concentration of PM10 by determining the mass fraction of PM less than size of interest from the particle size distribution (PSD). The “standard” high-volume TSP sampler operates at a volume rate-of-flow in excess of 1.13 m3 min-1 (40 ft3 min-1). Most of the current PM10 and PM2.5 samplers operate at 1 m3 h-1 (0.589 ft3 min-1). Other researchers reported that TSP samplers have a cutpoint of a nominal 45 .m AED. The U.S. EPA specifies the engineering design parameters for TSP samplers. This article reports the engineering design and evaluation of a low-volume (1 m3 h-1) TSP sampler (TSPLV). The results suggest that the new TSPLV may be more robust and more accurate than the “standard” high-volume TSP sampler.

Dust emissions in cattle feedlots.

Dust emissions were measured at three Texas cattle feedlots on 15 occasions in 1987 to determine concentrations of total suspended particulate matter (TSP) and dust with 10 microns or less aerodynamic particle size (PM-10). Net feedlot dust concentrations (downwind minus upwind) ranged from 15.7 to 1,700.1 micrograms per m3 and averaged 412.4 +/- 271.2 micrograms per m3, which is about 37 per cent less than was determined in feedlot dust research in California approximately 17 years earlier. Upwind concentrations averaged 22 per cent of the downwind concentrations. Feedlot dust concentrations were generally highest in early evening and lowest in early morning. Using the Wedding and Andersen-321A PM-10 samplers, the PM-10 dust concentrations were 19 and 40 per cent, respectively, of mean TSP concentrations in direct comparisons. There was good correlation between PM-10 and TSP concentrations. Although dust concentrations decreased with increasing moisture, the correlation coefficients were relatively low. Odor intensity appeared to increase with decreasing net dust concentrations, perhaps due to moisture influences. Mean particle sizes of feedlot dust were 8.5 to 12.2 microns on a particle volume basis and 2.5 to 3.4 microns on a population basis. Respirable dust (below 2 microns) represented only 2.0 to 4.4 per cent of total dust on a particle volume basis. Under conditions of these experiments, the feedlots often exceeded both state and federal (U.S. Environmental Protection Agency) standards for TSP concentrations and for PM-10 concentrations measured using the Andersen-321A sampler. However, feedlots were below the new U.S. Environmental Protection Agency standards when the Wedding PM-10 sampler was used for measuring dust emissions.

Seasonal and spatial variations of ammonia emissions from an open-lot dairy operation.

Abstract There is a need for a robust and accurate technique to measure ammonia (NH3) emissions from animal feeding operations (AFOs) to obtain emission inventories and to develop abatement strategies. Two consecutive seasonal studies were conducted to measure NH3 emissions from an open-lot dairy in central Texas in July and December of 2005. Data including NH3 concentrations were collected and NH3 emission fluxes (EFls), emission rates (ERs), and emission factors (EFs) were calculated for the open-lot dairy. A protocol using flux chambers (FCs) was used to determine these NH3 emissions from the open-lot dairy. NH3 concentration measurements were made using chemiluminescence-based analyzers. The ground-level area sources (GLAS) including open lots (cows on earthen corrals), separated solids, primary and secondary lagoons, and milking parlors were sampled to estimate NH3 emissions. The seasonal NH3 EFs were 11.6 ± 7.1 kg-NH3 yr-1head-1 for the summer and 6.2 ± 3.7 kg-NH3 yr-1head-1 for the winter season. The estimated annual NH3 EF was 9.4 ± 5.7 kg-NH3 yr-1head-1 for this open-lot dairy. The estimated NH3 EF for winter was nearly 47% lower than summer EF. Primary and secondary lagoons (∼37) and open-lot corrals (∼63%) in summer, and open-lot corrals (∼95%) in winter were the highest contributors to NH3 emissions for the open-lot dairy. These EF estimates using the FC protocol and real-time analyzer were lower than many previously reported EFs estimated based on nitrogen mass balance and nitrogen content in manure. The difference between the overall emissions from each season was due to ambient temperature variations and loading rates of manure on GLAS. There was spatial variation of NH3 emission from the open-lot earthen corrals due to variable animal density within feeding and shaded and dry divisions of the open lot. This spatial variability was attributed to dispirit manure loading within these areas.

Particulate matter sampler errors due to the interaction of particle size and sampler performance characteristics : Background and theory

The National Ambient Air Quality Standards (NAAQS) for particulate matter (PM), in terms of PM10 and PM2.5, are ambient air concentration limits set by the EPA that should not be exceeded. Further, state air pollution regulatory agencies (SAPRAs) utilize the NAAQS to regulate criteria pollutants emitted by industries by applying the NAAQS as a property-line concentration limit. The primary NAAQS are health-based standards; therefore, an exceedance implies that it is likely that there will be adverse health effects for the public. Prior to and since the inclusion of PM10 and PM2.5 into the EPAs regulation guidelines, numerous journal articles and technical references have been written to discuss the epidemiological effects, trends, regulations, methods of determining PM10 and PM2.5, etc. A common trend among many of these publications is the use of samplers to collect information on PM10 and PM2.5. Often, the sampler data are assumed to be an accurate measure of PM10 and PM2.5. The fact is that issues such as sampler uncertainties, environmental conditions, and characteristics of the material that the sampler is measuring must be incorporated for accurate sampler measurements. The purpose of this article is to provide the background and theory associated with particle size distribution (PSD) characteristics of the material in the air that is being sampled, sampler performance characteristics, the interaction between these two characteristics, and the effect of this interaction on the regulatory process. The results show that if the mass median diameter (MMD) of the PM to which the sampler is exposed is smaller than the cutpoint of the sampler, then under-sampling occurs. If the MMD of the PM is greater than the cutpoint of the sampler, then over-sampling occurs. The information presented in this article will be utilized in a series of articles dealing with the errors associated with particulate matter measurements.

Combustion of cattle feedlot manure for energy production

Abstract Beef cattle feedlot manure containing 14–18% moisture, 16–42% ash, and 12 400–14 950 kJ/kg heat content was successfully combusted in a fluidized bed combustion (FBC) unit, operated in recirculating bed mode when temperatures were 620 ± 28°C. Higher temperatures in conventional FBC mode caused slagging and ash fouling. Beef cattle feedlot manure may be a useful fuel for on-site energy production.

Particulate Matter Sampler Errors Due to the Interaction of Particle Size and Sampler Performance Characteristics: Ambient PM2.5 Samplers

The National Ambient Air Quality Standards (NAAQS) for particulate matter (PM) in terms of PM2.5 are ambient air concentration limits set by the EPA to protect public health and well-being. Further, some state air pollution regulatory agencies (SAPRAs) utilize the NAAQS to regulate criteria pollutants emitted by industries by applying the NAAQS as property-line concentration limits. Prior to and since the inclusion of the PM2.5 standard, numerous journal articles and technical references have been written to discuss the epidemiological effects, trends, regulation, and methods of determining PM2.5. A common trend among many of these publications is the use of samplers to collect PM2.5 concentration data. Often, the sampler data are assumed to be accurate concentration measures of PM2.5. The fact is that issues such as sampler uncertainties, environmental conditions, and characteristics of the material that the sampler is measuring must be incorporated for accurate sampler measurements. The focus of this article is on the errors associated with particle size distribution (PSD) characteristics of the material in the air that is being sampled, the PM2.5 sampler performance characteristics, the interaction between these two characteristics, and the effect of this interaction on the regulatory process. Theoretical simulations were conducted to determine the range of errors associated with this interaction for the PM2.5 ambient air samplers. Results from the PM2.5 simulations indicated that a source emitting PM characterized by a mass median diameter (MMD) of 20 µm and a geometric standard deviation (GSD) of 1.5 could be forced to comply with a PM2.5 standard that is 14 times more stringent than that required for a source emitting PM characterized by an MMD of 10 µm and a GSD of 1.5, and 59 times more stringent than that required for a source emitting PM characterized by an MMD of 5.7 µm and a GSD of 1.5. Therefore, in order to achieve equal regulation among differing industries, PM2.5 measurements must be based on true concentration measurements.

Comparison of Dispersion Models for Ammonia Emissions from a Ground-Level Area Source

Dispersion models are important tools for determining and regulating pollutant emissions from many sources, including ground-level area sources such as feedyards, dairies, and agricultural field operations. This study compares the calculated emission fluxes of ammonia from a feedyard in the Texas panhandle using four dispersion models: Industrial Source Complex Short Term Version 3 (ISCST3), AERMOD-PRIME, WindTrax, and AUSTAL. ISCST3 and AERMOD are Gaussian plume models, while WindTrax and AUSTAL are backward and forward Lagrangian stochastic models, respectively. Identical measured downwind ammonia concentration data were entered into each model. The results of this study indicate that calculated emission rates and/or emission factors are model specific, and no simple conversion factor can be used to adjust emission rates and/or factors between models. Therefore, emission factors developed using one model should not be used in other models to determine downwind pollutant concentrations.

A THEORETICAL APPROACH FOR PREDICTING NUMBER OF TURNS AND CYCLONE PRESSURE DROP

A new theoretical method for computing travel distance, number of turns, and cyclone pressure drop has been developed and is presented in this article. The flow pattern and cyclone dimensions determine the travel distance in a cyclone. The effective number of turns was calculated based on the travel distance. Cyclone pressure drop is composed of five pressure loss components. The frictional pressure loss is the primary pressure loss in a cyclone. This new theoretical analysis of cyclone pressure drop for 1D2D, 2D2D, and 1D3D cyclones was tested against measured data at different inlet velocities and gave excellent agreement. The results show that cyclone pressure drop varies with the inlet velocity, but not with cyclone diameter.