This item was digitized as part of the Million Books Project led by Carnegie Mellon University and supported by grants from the National Science Foundation (NSF). Cornell University coordinated the participation of land-grant and agricultural libraries in providing historical agricultural information for the digitization project; the University of Arizona Libraries, the College of Agriculture and Life Sciences, and the Office of Arid Lands Studies collaborated in the selection and provision of material for the digitization project.

This item was digitized as part of the Million Books Project led by Carnegie Mellon University and supported by grants from the National Science Foundation (NSF). Cornell University coordinated the participation of land-grant and agricultural libraries in providing historical agricultural information for the digitization project; the University of Arizona Libraries, the College of Agriculture and Life Sciences, and the Office of Arid Lands Studies collaborated in the selection and provision of material for the digitization project.

This item was digitized as part of the Million Books Project led by Carnegie Mellon University and supported by grants from the National Science Foundation (NSF). Cornell University coordinated the participation of land-grant and agricultural libraries in providing historical agricultural information for the digitization project; the University of Arizona Libraries, the College of Agriculture and Life Sciences, and the Office of Arid Lands Studies collaborated in the selection and provision of material for the digitization project.

Poor regional air quality in some states across the US cotton belt has resulted in increased pressure on agricultural sources of particulate matter (PM) from air pollution regulators. Moreover, inaccurate emission factors used in the calculation of annual emissions inventories led to the identification of cotton harvesting as a significant source of PM10 in California and Arizona. As a result, cotton growers in these states are now required to obtain air quality permits and submit management practice plans detailing the actions taken by the producer to reduce fugitive PM emissions from field operations. The objective of this work was to develop accurate PM emission factors for cotton harvesting in terms of total suspended particulate (TSP), PM10, and PM2.5. Two protocols were developed and used to develop PM emission factors from cotton harvesting operations on three farms in Texas during 2006 and 2007. Protocol one utilized TSP concentrations measured downwind of harvesting operations with meteorological data measured onsite in a dispersion model to back-calculate TSP emission flux values. Flux values, determined with the regulatory dispersion models ISCST3 and AERMOD, were converted to emission factors and corrected with results from particle size distribution (PSD) analyses to report emission factors in terms of PM10 and PM2.5. Emission factors were developed for two-row (John Deere 9910) and sixrow (John Deere 9996) cotton pickers with protocol one. The uncertainty associated with the emission factors developed through protocol one resulted in no significant difference between the emission factors for the two machines. Under the second protocol, emission concentrations were measured onboard the six-row cotton picker as the machine harvested cotton. PM10 and PM2.5 emission factors were developed from TSP emission concentration measurements converted to emission rates using the results of PSD analysis. The total TSP, PM10, and PM2.5 emission factors resulting from the source measurement protocol are 1.64 ± 0.37, 0.55 ± 0.12, and 1.58E- 03 ± 4.5E-04 kg/ha, respectively. These emission factors contain the lowest uncertainty and highest level of precision of any cotton harvesting PM emission factors ever developed. Thus, the emission factors developed through the source sampling protocol are recommended for regulatory use.