Ground Level Area Sources Research Articles

Comparison of AERMOD and WindTrax dispersion models in determining PM10 emission rates from a beef cattle feedlot

Reverse dispersion modeling has been used to determine air emission fluxes from ground-level area sources, including open-lot beef cattle feedlots. This research compared Gaussian-based AERMOD, the preferred regulatory dispersion model of the U.S. Environmental Protection Agency (EPA), and WindTrax, a backward Lagrangian stochastic-based dispersion model, in determining PM10 emission rates for a large beef cattle feedlot in Kansas. The effect of the type of meteorological data was also evaluated. Meteorological conditions and PM10 concentrations at the feedlot were measured with micrometeorological/eddy covariance instrumentation and tapered element oscillating microbalance (TEOM) PM10 monitors, respectively, from May 2010 through September 2011. Using the measured meteorological conditions and assuming a unit emission flux (i.e., 1 µg/m2-sec), each model was used to calculate PM10 concentrations (referred to as unit-flux concentrations). PM10 emission fluxes were then back-calculated using the measured and calculated unit-flux PM10 concentrations. For AERMOD, results showed that the PM10 emission fluxes determined using the two different meteorological data sets evaluated (eddy covariance-derived and AERMET-generated) were basically the same. For WindTrax, the two meteorological data sets (sonic anemometer data set, a three-variable data set composed of wind parameters, surface roughness, and atmospheric stability) also produced basically the same PM10 emission fluxes. Back-calculated emission fluxes from AERMOD were 32 to 69% higher than those from WindTrax. Implications This work compared the PM10 emission rates determined from a large commercial cattle feedlot in Kansas by reverse dispersion modeling using AERMOD and WindTrax. Emission fluxes derived from AERMOD were greater than those from WindTrax by mean factors of 1.3 to 1.6. Based on the high linearity observed between the two models, emission fluxes derived from one dispersion model for the purpose of simulating dispersion could be applied to the other model using appropriate conversion factors.

Comparison of seasonal phenol and p-cresol emissions from ground-level area sources in a dairy operation in central Texas

Although there are more than 200 odor-causing volatile organic compounds (VOCs), phenol and p-cresol are two prominent odor-causing VOCs found downwind from concentrated animal feeding operations (CAFOs). The VOC emissions from cattle and dairy production are difficult to quantify accurately because of their low concentrations, spatial variability, and limitations of available instruments. To quantify VOCs, a protocol following U.S. Environmental Protection Agency (EPA) Method TO-14A has been established based on the isolation flux chamber method and a portable gas chromatograph (GC) coupled with a purge-and-trap system. The general objective of this research was to quantify phenol and p-cresol emission rates (ERs) from different ground-level area sources (GLASs) in a free-stall dairy during summer and winter seasons using this protocol. Two-week-long sampling campaigns were conducted in a dairy operation in central Texas. Twenty-nine air samples were collected during winter and 37 samples were collected during summer from six specifically delineated GLASs (barn, loafing pen, lagoon, settling basin, silage pile, and walkway) at the free-stall dairy. Thirteen VOCs were identified during the sampling period and the GC was calibrated for phenol and p-cresol, the primary odorous VOCs identified. The overall calculated ERs for phenol and p-cresol were 2656 ± 728 and 763 ± 212 mg hd−1 day−1, respectively, during winter. Overall phenol and p-cresol ERs were calculated to be 1183 ± 361 and 551 ± 214 mg hd−1 day−1, respectively, during summer. In general, overall phenol and p-cresol ERs during winter were about 2.3 and 1.4 times, respectively, higher than those during summer. Implications: Concentrated animal feeding operations contribute a considerable amount of VOCs to the atmosphere. The phenol and p-cresol are two VOCs recognized as potential odor-causing compounds emitted from livestock operation. To develop effective strategies for mitigating livestock odorous VOC emissions, relative emissions from different GLAS in a livestock operation under different climate conditions should be quantified. It is also important to obtain direct estimates of VOC emissions from different GLAS in CAFOs to compile emission inventories. This research determined phenol and p-cresol emissions from different GLAS in a free-stall dairy and also identified areas in a dairy operations that have the highest phenol and p-cresol emissions.

Review of Airborne Emissions from Agricultural Fumigants: Design and Uncertainty Considerations for the Use of the Integrated Horizontal Flux Method

Ground-level area sources, such as those associated with the use of agricultural fumigants, waste disposal sites, wastewater lagoons, and other applications, present a challenge in terms of characterizing atmospheric flux as a function of time. Studies are costly in terms of field activities and laboratory analysis. The optimization of field study design, therefore, is essential to conduct cost-effective research. The collection of on-field profile data for airborne concentration, wind speed, and wind direction can be used in conjunction with the integrated horizontal flux (IHF) method to empirically compute complex source terms as a function of time. This paper focuses on complicating factors and field study design issues for the use of the IHF method. Insights and examples are drawn from five field research studies. The methods and results of characterizing the uncertainty and method precision in the emission fitting for the IHF method also are presented.

Greenhouse Gas Emissions from Ground Level Area Sources in Dairy and Cattle Feedyard Operations

A protocol that consisted of an isolation flux chamber and a portable gas chromatograph was used to directly quantify greenhouse gas (GHG) emissions at a dairy and a feedyard operation in the Texas Panhandle. Field sampling campaigns were performed 5 consecutive days only during daylight hours from 9:00 am to 7:00 pm each day. The objective of this research was to quantify and compare GHG emission rates (ERs) from ground level area sources (GLAS) at dairy and cattle feedyard operations during the summer. A total of 74 air samples using flux chamber were collected from the barn (manure lane and bedding area), loafing pen, open lot, settling basin, lagoons, and compost pile within the dairy operation. For the cattle feedyard, a total of 87 air samples were collected from four corner pens of a large feedlot, runoff holding pond, and compost pile. Three primary GHGs (methane, carbon dioxide, and nitrous oxide) were measured and quantified from both operations. The aggregate estimated ERs for CH4, CO2, and N2O were 836, 5573, 3.4 g hd−1 d−1 (collectively 27.5 kg carbon dioxide equivalent (CO2e) hd−1 d−1), respectively, at the dairy operation. The aggregate ERs for CH4, CO2, and N2O were 3.8, 1399, 0.68 g hd−1 d−1 (1.7 kg CO2e hd−1 d−1), respectively, from the feedyard. The estimated USEPA GHG ERs were about 13.2 and 1.16 kg CO2e hd−1 d−1, respectively, for dairy and feedyard operations. Aggregate CH4, CO2 and N2O ERs at the dairy facility were about 219, 4 and 5 times higher, respectively, than those at the feedyard. At the dairy, average CH4 ERs estimated from the settling basin, primary and secondary lagoons were significantly higher than those from the other GLAS, contributing about 98% of the aggregate CH4 emission. The runoff holding pond and pen surface of the feedyard contributed about 99% of the aggregate CH4 emission. Average CO2 and N2O ERs estimated from the pen surface area were significantly higher than those estimated from the compost pile and runoff pond. The pen surface alone contributed about 93% and 84% of the aggregate CO2 and N2O emission, respectively. Abatement and management practices that address GHG emissions from these sources will likely be most effective for reducing facility emissions.

Determining Seasonal Greenhouse Gas Emissions from Ground-Level Area Sources in a Dairy Operation in Central Texas

ABSTRACT Greenhouse gas (GHG) emissions from agricultural production operations are recognized as an important air quality issue. A new technique following the U.S. Environmental Protection Agency Method TO-14A was used to measure GHG emissions from ground-level area sources (GLAS) in a free-stall dairy operation in central Texas. The objective of this study was to quantify and report GHG emission rates (ERs) from the dairy during the summer and winter using this protocol. A weeklong sampling was performed during each season. A total of 75 and 66 chromatograms of air samples were acquired from six delineated GLAS (loafing pen, walkway, barn, silage pile, settling basin, and lagoon) of the same dairy during summer and winter, respectively. Three primary GHGs—methane (CH4), carbon dioxide (CO2), and nitrous oxide (N2O)—were identified from the dairy operation during the sampling periods. The estimated overall ERs for CH4, CO2, and N2O during the summer for this dairy were 274, 6005, and 7.96 g head−1day−1, respectively. During the winter, the estimated overall CH4, CO2, and N2O ERs were 52, 7471, and 3.59 g head−1day−1, respectively. The overall CH4 and N2O ERs during the summer were approximately 5.3 and 2.2 times higher than those in the winter for the free-stall dairy. These seasonal variations were likely due to fluctuations in ambient temperature, dairy manure loading rates, and manure microbial activity of GLAS. The annualized ERs for CH4, CO2, and N2O for this dairy were estimated to be 181, 6612, and 6.13 g head−1day−1, respectively. Total GHG emissions calculated for this dairy with 500 cows were 2250 t of carbon dioxide equivalent (CO2e) per year. IMPLICATIONS The agricultural sector, especially concentrated animal feeding operations (CAFOs) contribute a considerable amount of GHGs to the atmosphere. To develop abatement strategies to reduce GHG emissions, it is important to learn to collect, analyze, verify, and report real data on actual emissions. Therefore, there is a need for a robust and accurate technique/protocol to measure GHGs from CAFOs. It is important to obtain direct estimates of GHG emissions from different GLAS in CAFOs to compile emission inventories and to develop GLAS-specific abatement strategies.

Seasonal Ammonia Emissions from a Free-Stall Dairy in Central Texas

Studies show that agricultural and animal feeding operations (AFOs) contribute a considerable amount of ammonia (NH3) to the atmosphere. Agricultural NH3 emissions are recognized as an important air quality issue. Biological decomposition of manure from dairy operations results in emissions of NH3 and other gases. There is a need to determine NH3 emission factors (EFs) to compile annual NH3 inventories. NH3 emissions should be estimated from different ground-level area sources (GLAS) including open-lots (cows on earthen corrals), free-stalls (cows in barns), manure composting sites, primary and secondary lagoons, separated solids, and milking parlors. A protocol using flux chambers was used to determine NH3 EFs from different GLAS of a free-stall dairy in central Texas. Data including NH3 emissions from GLAS were collected during winter and summer seasons. NH3 concentration measurements were made using chemiluminescence-based analyzers. The EFs for the free-stall dairy were estimated as 11 ± 4.9 (confidence interval [CI]) kg-NH3 · yr-1 · head-1 for summer and 4.7 ± 4.9 kg-NH3 · yr-1 · head-1 for winter. The estimated annual NH3 EF was 8.4 ± 4.9 kg- NH3 · yr-1 · head-1 for this free-stall dairy. This seasonal difference was attributed to temperature, loading rate of dairy waste, and manure bacterial activity of GLAS. In winter, composted manure and free-stalls contributed nearly 77% of the total NH3 emissions for the dairy; however, in summer, two lagoons at the dairy contributed 65% of the overall NH3 emissions.

Algorithms and analytical solutions for rapidly approximating long-term dispersion from line and area sources

Predicting long-term mean pollutant concentrations in the vicinity of airports, roads and other industrial sources are frequently of concern in regulatory and public health contexts. Many emissions are represented geometrically as ground-level line or area sources. Well developed modelling tools such as AERMOD and ADMS are able to model dispersion from finite (i.e. non-point) sources with considerable accuracy, drawing upon an up-to-date understanding of boundary layer behaviour. Due to mathematical difficulties associated with line and area sources, computationally expensive numerical integration schemes have been developed. For example, some models decompose area sources into a large number of line sources orthogonal to the mean wind direction, for which an analytical (Gaussian) solution exists. Models also employ a time-series approach, which involves computing mean pollutant concentrations for every hour over one or more years of meteorological data. This can give rise to computer runtimes of several days for assessment of a site. While this may be acceptable for assessment of a single industrial complex, airport, etc., this level of computational cost precludes national or international policy assessments at the level of detail available with dispersion modelling. In this paper, we extend previous work [S.R.H. Barrett, R.E. Britter, 2008. Development of algorithms and approximations for rapid operational air quality modelling. Atmospheric Environment 42 (2008) 8105–8111] to line and area sources. We introduce approximations which allow for the development of new analytical solutions for long-term mean dispersion from line and area sources, based on hypergeometric functions. We describe how these solutions can be parameterized from a single point source run from an existing advanced dispersion model, thereby accounting for all processes modelled in the more costly algorithms. The parameterization method combined with the analytical solutions for long-term mean dispersion are shown to produce results several orders of magnitude more efficiently with a loss of accuracy small compared to the absolute accuracy of advanced dispersion models near sources. The method can be readily incorporated into existing dispersion models, and may allow for additional computation time to be expended on modelling dispersion processes more accurately in future, rather than on accounting for source geometry.

Seasonal and Spatial Variations of Ammonia Emissions from an Open-Lot Dairy Operation

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.

Sampler placement to determine emission factors from ground level area sources

Emission factors are used by state air pollution regulatory agencies to regulate emissions from sources of atmospheric pollution. Emission factors for ground level area sources (GLASs) can be determined by sampling ambient pollutant levels and using dispersion modeling to back-calculate the emission rate from a source. This manuscript describes a method used to locate samplers downwind of a GLAS to most accurately determine the emission flux from the source. Contributions from other sources, changes in particle size distributions, and measurement uncertainty are considered.

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.

The Recovery of Ammonia and Hydrogen Sulflde from Ground-Level Area Sources Using Dynamic Isolation Flux Chambers: Bench-Scale Studies

Controlled bench-scale laboratory experiments were conducted to evaluate the recovery of ammonia (NH3) and hydrogen sulflde (H2S) from dynamic isolation flux chambers. H2S (80–4000 ppb) and NH3 (5000–40,000 ppb) samples were diffused through the flux chamber to simulate ground level area source emissions while measuring the inlet and outlet flux chamber concentrations simultaneously. Results showed that the recovery of H2S during a 30-min sampling time was almost complete for concentrations >2000 ppb. At the lowest concentration of 80 ppb, 92.55% of the H2S could be recovered during the given sampling period. NH3 emissions exhibited similar behavior between concentrations of 5000–40,000 ppb. Within the 30-min sampling period, 92.62% of the 5000-ppb NH3 sample could be recovered. Complete recovery was achieved for concentrations >40,000 ppb. Predictive equations were developed for gas adsorption. From these equations, the maximum difference between chamber inlet and outlet concentrations of NH3 or H2S was predicted to be 7.5% at the lowest concentration used for either gas. In the calculation of emission factors for NH3 and H2S, no adsorption correction factor is recommended for concentrations >37,500 ppb and 2100 ppb for NH3 and H2S, respectively. The reported differences in outlet and inlet concentration above these ranges are outside the full-scale sensitivity of the gas sensing equipment. The use of 46–90 m of Teflon tubing with the flux chambers has apparently no effect on gas adsorption, because recovery was completed almost instantaneously at the beginning of the tests.

A Gaussian model for estimating odour emissions from area sources

A Gaussian plume model for the dispersion of odours is modified to calculate the spatial average odour emissions from ground level area sources such as beef cattle feedlots, given simultaneous point measurements of odour concentration and wind speed at a location immediately downwind of the source. The validity of the method is demonstrated as is its application to sources of irregular shape, of finite lateral extent, and with wind directions other than perpendicular to the source. Source size, aerodynamic roughness of the surface and atmospheric stability are shown to be imporant in the selection of the preferred location for the measurements to enable a true spatial average emission rate to be calculated.

CCl 3F (Freon -11) as an indicator of transport processes in an urban atmosphere—a case study in Melbourne

In view of the lack of surface uniformity, and the importance of relatively uniform ground level area sources of pollution in an urban environment, point source diffusion experiments are of limited usefulness in studying transport processes in an urban atmosphere. While it is not feasible to carry out controlled area source diffusion experiments, we argue here that CCl 3F is an existing pollutant which for many cities represents a good ground level area source. For cities such as Melbourne where industrial use of CCl 3F occurs, the effect of a few strong point sources superimposed on the area sources may need to be accounted for. As an example of the use of CCl 3F as an urban atmospheric tracer, vertical concentration profiles and simultaneous profiles of relevant meteorological parameters were obtained at Aspendale during a very stable June night. The profiles show a marked variation of concentration with height which is explained qualitatively by the change in wind direction with height and the variation with direction of the source strength (as determined by a source inventory) around Aspendale. The futility of estimating pollutant concentrations at height from ground level measurements is clear from our results, as is the importance of a knowledge of the non-uniformity of wind (both vertically and horizontally) due to local effects, such as cold air drainage.

Application of the method of variational imbedding to atmospheric diffusion transport

The method of variational imbedding has been adopted for solving the descriptive set of equations governing the transport of pollutants in the atmosphere for two types of dispersion models: 1. (i) Unsteady diffusion transport 2. (ii) steady-state two-dimensional convection-diffusion transport. The diffusivity coefficient K and down-wind speed U have both been taken to have general functional dependence on local pollutant concentration c. The solutions obtained in this paper can be used for theoretical prediction of pollutant concentration across the contaminated atmospheric layer adjacent to the ground level area sources.