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United States Department of Agriculture

Agricultural Research Service

Research Project: ENHANCING QUALITY, UTILITY, SUSTAINABILITY, ENVIRONMENTAL IMPACT OF COTTON AND ITS BYPRODUCTS THROUGH IMPROVEMENT IN HARVEST/GIN PROCESSING

Location: Cotton Ginning Research

Title: Characterization of cotton gin particulate matter emissions-database development

Authors
item Carom, Daniela -
item Buser, Michael -
item Whitelock, Derek
item Boykin Jr, James
item McConnell, Laura

Submitted to: ASABE Annual International Meeting
Publication Type: Abstract Only
Publication Acceptance Date: July 31, 2012
Publication Date: July 31, 2012
Citation: Carom, D.A., Buser, M.D., Whitelock, D.P., Boykin Jr, J.C., Mcconnell, L.L. 2012. Characterization of cotton gin particulate matter emissions-database development. ASABE Annual International Meeting. PRESENTATION ONLY- Paper No. 121336902.

Technical Abstract: In 2006, EPA implemented a more rigorous standard for PM2.5 in 2006 and all the cotton gins are or will be impacted by this standard. The primary issues associated with implementing this standard are: 1) very limited cotton gin PM2.5 data are available; 2) sampler errors, recent research indicates that current PM2.5 sampling methods could be over-estimating cotton gin PM2.5 emission concentrations by as much as 14 times; and 3) over-prediction of dispersion models, some studies in the literature suggest that these models could be over-predicting cotton gin boundary line concentrations by more than four times the actual concentrations. The cotton ginners’ associations across the cotton belt, including the National, Texas, Southern, Southeastern, and California associations, agreed to collaborate to collect additional gin emissions data that could be used fill the various PM2.5 data gaps that currently exist. A previous paper described how the data was collected and provided an overview of the database management for the project. This paper is an update of the database development and discusses issues like public accessibility, user interface, data compilation and further uses in model development and evaluation.

Last Modified: 10/24/2014
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