Title

Particulate emissions from fall tillage operations as determined via inverse modeling and lidar mass balance techniques

Document Type

Presentation

Journal/Book Title/Conference

ASABE Annual International Meeting

Location

Pittsburgh, PA

Publication Date

1-1-2010

Abstract

Preparation of soil for agricultural crops produces aerosols that may significantly contribute to seasonal atmospheric loadings, especially in areas with a high density of perennial crops. Emissions may originate from the tractor’s diesel engine, the tractor moving over the ground, and the equipment used for tillage. The United States (US) Environmental Protection Agency (EPA) and some state governments are now including more agricultural air pollutant emissions in particulate matter (PM) emissions inventories. However, reductions in tillage PM emissions from traditional practices through the use of conservation management practices (CMPs) have often not been quantified, especially for PM2.5. Potential CMP options include, but are not limited to, no till methods, strip till methods, and methods that reduce the number of operations used. A study was conducted in the Central Valley of California in October 2007 to measure PM emissions from the conventional method of preparing the ground after cotton harvest and going back into cotton the following spring. We also examined a “Combined Operations” method, which combines tillage implements in order to reduce the number of passes in the field, in an adjacent field with an identical cropping system for comparison. Two adjacent fields near Los Banos, CA were selected for this study based on geometry, predominant wind direction, operator cooperation, and similar soil types. Measurements made include: soil properties, meteorological (T, RH, WS, and WD) profiles, filter-based TSP, PM10, and PM2.5 concentrations and aerosol size distribution via optical particle counters at multiple up- and downwind locations and heights, and a calibrated, scanning, three wavelength lidar. Emission rates were determined via 1) inverse modeling (ISCST3 and AERMOD) coupled with the mass concentration measurements and 2) application of a mass balance to the virtual box created around the operation by the scanning lidar system. Emission rates from both conventional and combined operations methods will be presented and compared.

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