Integrating Lidar and Atmospheric Boundary Layer Measurements to Determine Fluxes and Dynamics of Particulate Emissions from an Agriculture Facility

Lidar technology offers the ability to quantify concentrations of small particulates in the atmosphere in certain ranges of time and space. While this is a valuable tool to visualize the behavior of plumes emitted from the surface, the actual flux of particles cannot be estimated from such data alone. To determine the mass flux of particles, the concentrations must be properly integrated with wind and turbulence properties. The goal of this study is to utilize a model that uses wind and particle density information to calculate the flux of particles from an animal facility near Ames, Iowa. The model is a simplified conservation equation for particle density in the atmosphere. This approach essentially quantifies fluxes in and out of a box centered over the facility and estimates the surface source by assuming conservation of mass. In addition, we hypothesize that distinct turbulence structures will sometimes interact with the intermittency of the surface emission from the buildings, resulting in episodic changes in emission fluxes from the site. A second objective involves documenting how intermittent the emission plumes are and how they are connected to periodic large scale turbulence events. Lidar data of particle size and density in the vicinity of the site were collected during an intensive field campaign lasting nearly 2 weeks. In addition to the lidar data, turbulence data were measured at several levels on each of three towers, located upwind, inside and downwind of the source area. The model requires measurements of the vertical profiles of both concentrations of particulates and the mean horizontal wind. The concentrations were measured using the lidar, while winds were measured using a combination of cup anemometers and sonic anemometers. This allows the emission fluxes to be calculated during 15 to 30 minute periods when winds are consistent. Flux calculations await the final calibration of the lidar returns using measured particle densities. Flux estimates will be made when distinct plumes are observed under steady-state wind conditions. Current results are presented showing evidence of episodic plumes of CO2 in response to intermittent vertical motions of turbulences. Introduction Agricultural facilities and operations result in emission of various particles and gases to the atmosphere. Among these are small particles. The emissions of small particulates from such facilities need to be quantified in order to determine the effects of such operations on air quality. Unfortunately, the size and heterogeneous nature of such facilities makes it impossible to make any simple direct measurements of emission rates. The emergence of lidar allows measurements to be made of the spatial distribution of particles including size and density. The USU lidar was developed exactly for this purpose and allows the spatial distribution of particle density to be quantified for the atmosphere in the vicinity of an agricultural facility. However, lidar measurements of particle density will not yield the actual rate of emission from the site. This requires an integration of particle density data from the lidar with wind and turbulence information. Determining the surface flux of particulates in this way still poses a challenge. The animal facilities especially are quite heterogeneous and variable in size. The sources have a spatially complex pattern and have distinct effects on wind and turbulence. The typical micrometeorological approaches used to estimate surface fluxes are also problematic in these cases, since they are predicated on a uniform surface or source region of adequate spatial extent. In this case we propose using a simplified form of the conservation equation for particle density of the air to estimate the emissions for a confined animal facility near Ames, Iowa. The simplified conservation equation can be written as: