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ARS Home » Plains Area » Las Cruces, New Mexico » Cotton Ginning Research » Research » Publications at this Location » Publication #287663

Title: Design and development of a large scale low-volume air sampling system

item BUSER, MICHAEL - Oklahoma State University
item KOLLER, ADRIAN - Oklahoma State University
item Whitelock, Derek
item Pelletier, Mathew

Submitted to: ASABE Annual International Meeting
Publication Type: Abstract Only
Publication Acceptance Date: 7/31/2012
Publication Date: 7/31/2012
Citation: Buser, M.D., Koller, A.A., Whitelock, D.P., Pelletier, M.G. 2012. Design and development of a large scale low-volume air sampling system. ASABE Annual International Meeting. PRESENTATION ONLY.; Number 121336719.

Interpretive Summary:

Technical Abstract: Increasing regulatory pressure on particulate matter emissions originating at agricultural operations and processing plants has created a needed for additional industry specific data. The required data generally includes point source or stack sampling and non-point source data. For this manuscript the focus is on non-point source data generally collected with ambient air samplers. For small sources or small scale sampling campaigns researchers generally use EPA approved ambient samplers, such as the TEOM. However for large scale sampling campaigns were twenty or more sampling points are required, samplers like the TEOM become impractical due to their large size, high cost, low data storage capacity, and high power consumption. In the past, these drawbacks forced the researchers to work with very few sampling points even when examining large processing plants that may cover several tens of acres. Consequentially, the resolutions of the resulting data sets were extremely limited and verifying dispersion modeling results with this data is difficult if not impossible. In 2003 the USDA Agricultural Research Service initiated a project to develop a new air sampler that would mitigate the shortcomings of then currently available ambient air samplers. The completion of the design and development was eventually conducted at Oklahoma State University and the full system was deployed in 2008 with a total of 120 sampling points. Recent studies have incorporated the large scale comprehensive sampling setup that covered areas as large as 28 ha. The measurement points are arranged in concentric circles with radii of about 100, 200, and 300 m around the pollution source. The inner most circle consists of stand-alone samplers. The inlets of these units are located at 2 m above ground. The middle circle of the sampling arrangement consists of tower samplers. The towers sample the air at 1, 2, 3, 4.5, 7.25, and 10 m above ground, respectively. An anemometer provides wind speed and direction measurements at each altitude of the tower. This allows later for the reconstruction of a detailed wind profile and flow pattern over much of the sampled area. The outermost circle of samplers is again made up of stand-alone units. The low-volume airflow rate of 16.67 lpm is electronically monitored and controlled by a system developed by the USDA-ARS. The system measures the pressure drop across an orifice that is in line with the airflow. Closed-loop control of the airflow rate is achieved with a solenoid valve in the line between the pump and sampler. Flow rate is regulated on a five or thirty second interval depending on the deviation from the target value. Each system is equipped to record wind speed and direction from a MetOne (Grants Pass, OR) 034b anemometer. Data are collected eight times per second and generate sixteen second averages. On sixteen second intervals, pressure drop, wind speed and direction, and solenoid position logged along with ambient temperature, relative humidity, and barometric pressure. The system contains a MaxStream XStream OEM RF modem that is used to transmit the data back to a base station to track filter loading and system status. Each sampler provides ample onboard data storage capacity that allows continuous operation for several days without interruption of the data logging.