Abstract
A network for continuously monitoring episodic air particulate matter (PM) concentration from smaller-scale abatement and emissions mechanism experiments was implemented at a research cattle feedyard, operated by Texas A&M AgriLife Research, in Amarillo, TX. The data was generated through Tapered Element Oscillating Microbalance (TEOM) monitors- a recognized technology for the direct measurement of particulate matter concentrations. The data files span 10-years of size-resolved particulate matter concentration data (PM10), both upwind and downwind, collected in the period 2011-2019, and complemented by relevant ancillary information, such as on-station meteorological data (including 10- and 2-meter wind speed, wind direction, air temperature, relative humidity, and precipitation), feedyard operational parameters, and regional air quality indicators. The processed and outlier-free datasets are available at hourly and daily scales at a central repository in Zenodo. Researchers, educators, and policymakers can reuse these datasets to implement mechanistic and machine learning models of airborne dust dispersion and discuss air pollution mitigation strategies in the livestock industry.