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United States Department of Agriculture

Agricultural Research Service

Research Project: MANAGEMENT OF AGRICULTURAL AND NATURAL RESOURCE SYSTEMS TO REDUCE ATMOSPHERIC EMISSIONS AND INCREASE RESILIENCE TO CLIMATE CHANGE Title: Comparisons of measurements and predictions of PM concentrations and emission rates from a wind erosion event

Authors
item Moore, Kori -
item Wojick, Michael -
item Marchant, Christopher -
item Martin, Randal -
item Pfeiffer, Richard
item Prueger, John
item Hatfield, Jerry

Submitted to: Meeting Proceedings
Publication Type: Proceedings
Publication Acceptance Date: August 4, 2011
Publication Date: September 24, 2011
Citation: Moore, K.D., Wojick, M.D., Marchant, C.C., Martin, R.L., Pfeiffer, R.L., Prueger, J.H., Hatfield, J.L. 2011. Comparisons of measurements and predictions of PM concentrations and emission rates from a wind erosion event. International Symposium on Erosion and Landscape Evolution. Paper No. 11020.

Technical Abstract: Wind erosion can affect agricultural productivity, soil stability, and air quality. Air quality concerns deal mainly with human health and welfare issues, but are also related to long range transport and deposition of crustal materials. Regulatory standards for ambient concentrations of particulate matter (PM) with equivalent aerodynamic diameters = 10 µm (PM10) and = 2.5 µm (PM2.5) have been established in many countries in an effort to protect the health and welfare of their citizens. Wind erosion events may lead to high PM levels that exceed air quality standards and are health hazards. Quantifying suspended wind-blown dust emissions and resulting PM concentrations from wind erosion events are of significant interest to researchers and air quality governing organizations. A high wind event causing visible soil suspension occurred on May 20, 2008 in California’s San Joaquin Valley. On this day, PM concentrations around a 25 acre field with fine sandy loam soil were being measured as part of an agricultural tillage PM emissions study. Meteorological parameters were monitored by a weather station at 5 m and two 15.3 m towers vertically profiling wind speed, wind direction, temperature, and humidity. Point sensor PM instruments deployed were a vertical and horizontal array of optical particle counters (OPCs) and portable filter-based PM samplers. A remote sensing scanning Lidar (light detection and ranging) system with three wavelengths (1064 nm, 532 nm, and 352 nm) called Aglite was also deployed. The OPCs were used to calibrate the Lidar return signal to particle count and volume concentration. Mass concentration calibrations for both the OPCs and Lidar were accomplished using a mass conversion factor (MCF) calculated from OPC and filter-based PM data collected that day. The filter-based sampling was stopped upon completion of the tillage activity while the OPCs and Lidar continued to collect data during part of the wind erosion event. Since this was not designed as a wind erosion study, measurements of neither creep nor saltation were made. Emission rates (ERs) were calculated using a vertical flux equation with OPC PM data, inverse modeling using AERMOD with OPC PM data, and through the application of a mass balance to upwind and downwind vertical Lidar scans. PM values measured downwind of the field were consistently much higher than those measured upwind, showing significant suspension and vertical dispersion of soil particles from the field up to 9 m. Particle size distributions and PM levels were also consistently higher at 2 m than 9 m in both upwind and downwind locations, suggesting most particles in the wind-blown dust plumes stayed near the surface. All OPCs, especially those downwind had high counts for particles > 1 µm relative to counts of particles < 1 µm in comparison with typical ambient atmosphere particle size distributions. The Lidar detected wind-blown dust plumes of varying size, location, and duration on the downwind field edge from 10 m to 50 m in elevation. ERs based on the vertical flux equation were 3.9 µg/s-m2 for PM2.5, 174.2 µg/s-m2 for PM10, and 872.0 µg/s-m2 for TSP while ERs from inverse modeling were 6.1 µg/s-m2 for PM2.5, 268.7 µg/s-m2 for PM10, and 1,488.9 µg/s-m2 for TSP. These PM10 ERs are similar to other values in literature. The Lidar-based ERs were three orders of magnitude lower than those from the other two methods. A minimum measurement height of ~10 m due to safety concerns, means the Lidar is unable to adequately detect plumes that are close to the ground, such as the wind erosion plumes seen on this day.

Last Modified: 10/25/2014
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