Literature DB >> 20830913

Laboratory system for dust generation from soils.

Rebecca A Domingo1, Randal J Southard, Kiyoung Lee.   

Abstract

Farm workers and residential communities adjacent to agricultural fields can be exposed to soil dust generated during field operations at levels that could result in respiratory problems. However, field sampling of agricultural dust faces logistical problems from spatial and temporal differences in soil properties, field operations, and meteorological conditions. To minimize these problems, we designed a dust generator that simulates dust generation during tilling of agricultural fields to provide samples of particulate matter derived from bulk soil and developed optimal operating conditions to assure reproducible results. The dust generator consisted of a rotating chamber, where soil samples were loaded and tumbled, and a settling chamber, where airborne soil dust samples were collected using particle size-selective samplers. The following operating conditions for dust generation were evaluated: initial soil mass, air intake, rotation speed, and sampling time to optimize dust sampling. We compared the laboratory-generated dust from soil samples with field dust that we collected from the same plots during agricultural operations. We determined from X-ray diffraction and energy-dispersive X-ray analyses that the mineralogy and chemical composition of field- and laboratory-generated dust were similar, indicating that the apparatus reasonably simulated field mechanical processes that produce airborne particulate matter from soils. The results suggest that the laboratory dust generator provides reliable samples of soil-derived dust and could be useful for future studies involving airborne particulate material from soils.

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Year:  2010        PMID: 20830913     DOI: 10.2134/jeq2008.0380

Source DB:  PubMed          Journal:  J Environ Qual        ISSN: 0047-2425            Impact factor:   2.751


  1 in total

1.  Automatically Controlled Dust Generation System Using Arduino.

Authors:  Dan Hofstetter; Eileen Fabian; Dorian Dominguez; A Gino Lorenzoni
Journal:  Sensors (Basel)       Date:  2022-06-17       Impact factor: 3.847

  1 in total

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