Location: Soil, Water & Air Resources ResearchTitle: Particulate emissions calculations from fall tillage operations using point and remote sensors Author
Submitted to: Transactions of the ASABE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/14/2013
Publication Date: N/A
Citation: N/A Interpretive Summary: Dust from agricultural operations is often considered to be an air quality problem, and in different regions of the country the dust levels can be large enough to be seen as dust plumes. Although, there is a large amount of qualitative information on the release of dust from agricultural sources there is little quantitative information which would permit a direct comparison of different management practices for their effectiveness in reducing dust emissions. To address this question a study was conducted in the Central Valley of California to compare emissions from two different tillage systems used in a field after cotton harvest. The first system was the traditional method of multiple tillage operations while the second system combined these operations into a single implement pass through the field. Observations of the emissions were made with a variety of techniques capable of measuring the different sizes of dust. Use of the combined tillage system reduced the dust emission by over 30% compared to conventional systems. This information is of value to air quality staff, producers, and equipment manufacturers.
Technical Abstract: Preparation of soil for agricultural crops produces aerosols that may significantly contribute to seasonal atmospheric loadings of particulate matter (PM). Efforts to reduce PM emissions from tillage operations through a variety of conservation management practices (CMP) have been made but the reductions have not been quantified. A study was conducted in California’s San Joaquin Valley in October 2007 to quantify emissions reductions from CMP practices. Measurements of PM emissions were made from conventional tillage methods and a “Combined Operations” CMP method, which combines several tillage implements in order to reduce the number of tractor passes in the field. Measurements were made of soil moisture, bulk density, meteorological profiles, filter-based TSP (total suspended PM), PM10 (PM with an equivalent aerodynamic diameter = 10 µm), and PM2.5 (PM with an equivalent aerodynamic diameter = 2.5 µm) concentrations, and aerosol size distribution. A mass-calibrated, scanning, three wavelength lidar estimated PM through a series of algorithms. Emission rates (ERs) and factors (EFs) were determined via inverse modeling with AERMOD (American Meteorological Society and EPA regulatory model) coupled with the mass concentration measurements and application of a mass balance to lidar data. Derived PM10 EFs for conventional operations are generally in agreement with values found in the literature. Sampling irregularities with a few filter-based samples prevented estimation of a complete set of inverse modeling emissions estimates; however, lidar measurements provided a complete ER/EF dataset. The control effectiveness of the CMP was calculated based on lidar-derived EFs to be 0.29 ± 0.02, 0.60 ± 0.01, and 0.25 ± 0.01 for PM2.5, PM10, and TSP size fractions, respectively. Implementation of this CMP provides effective methods for the reduction of PM emissions into the atmosphere.