1a.Objectives (from AD-416)
1. Improve methods for the quantification of emissions from individual agricultural sources and whole agricultural facilities or management operations.
2. Develop methods to predict emissions and their dispersion from individual sources and whole facilities or management operations.
3. Validate the prediction tools for a variety of agricultural sources.
1b.Approach (from AD-416)
In a previous project a prototype lidar system for measuring particulate matter emissions was developed and evaluated. This system will be refined to improve the portability, usability and reliability for routine measurements across a wide variety of agricultural systems. Evaluation of the system will include comparisons against in situ samples of particulates to increase the reliability of the method using accepted EPA verification methodologies. Comparisons will be used to provide detailed specifications of the performance capabilities of the unit. Evaluation of the emissions measurement capabilities will be conducted under laboratory and field conditions. Integration of the particulate and gaseous units with ancillary micrometeorology will be coordinated with ARS scientists during field measurements. The development of new systems for the measurement of gaseous emissions from agricultural sources will include identification of the most critical gases of interest to agriculture, characterization of system capabilities, and performance compared to accepted standards. A project review will be conducted during the first year.
The goal of this project is to refine the LiDAR system for the measurement of particulates emitted from agricultural operations and provide a more detailed evaluation of the performance of the instrument. The AgLite LiDAR system has been deployed in two tillage comparison studies to evaluate the impact of reduced tillage on particulate emissions from agricultural operations. The LiDAR system was able to measure the particulate plume and provide an estimate of the flux density of particulates at the 2.5, 10, and total suspended particulate classes. The estimates derived from the LiDAR were similar to those estimated with dispersion models for these situations. Implementation of conservation tillage practices reduce the particulate load in the atmosphere and reduce the energy use from farming operations. There are continuing refinements to the operating system to increase the reliability and operability of the instrumentation suite to increase the usability and reduce the labor requirements for operation and data processing. There is a scheduled monthly teleconference to discuss progress on the project and email exchanges to share information and data analysis.