Suchergebnisse

Particulate matter (PM) emissions from agricultural operations are an important issue for air quality and human health and a topic of interest to government regulators. PM emission rates from a dairy in the San Joaquin Valley of California were investigated during June 2008. The facility had 1,885 total animals, including 950 milking cows housed in free‐stall pens with an open‐lot exercise area, and 935 dry cows, steers, bulls, and heifers housed in open lots. Point sensors, including filter‐based aerodynamic mass samplers and optical particle counters (OPC), were deployed at select points around the facility to measure optical and aerodynamic particulate concentrations. Simultaneously, vertical PM concentration profiles were measured both upwind and downwind of the facility using lidar. The lidar was calibrated to provide mass concentration information using the OPCs and filter measurements. Emission rates were estimated over this period using both an inverse modeling technique coupled with the filter‐based measurements and a mass‐balance technique applied to lidar data. Mean emission rates calculated using inverse modeling (±95% confidence interval) were 3.8 (±3.2), 24.8 (±14.5), and 75.9 (±33.2) g d‐1 AU‐1 for PM2.5, PM10, and TSP, respectively. Mean emissions rates based on lidar data were 1.3 (±0.2), 15.1 (±2.2), and 46.4 (±7.0) g d‐1 AU‐1 for PM2.5, PM10, and TSP, respectively. The PM10 findings are roughly twice as high as those reported from other dairy studies with different climatic conditions and/or housing types, but are of similar magnitude as those from a study with similar conditions, housing, and emission rate calculation technique.

Particulate matter (PM) emissions from agricultural operations are an important issue for air quality and human health and a topic of interest to government regulators. PM emission rates from a dairy in the San Joaquin Valley of California were investigated during June 2008. The facility had 1,885 total animals, including 950 milking cows housed in free-stall pens with an open-lot exercise area, and 935 dry cows, steers, bulls, and heifers housed in open lots. Point sensors, including filter-based aerodynamic mass samplers and optical particle counters (OPC), were deployed at select points around the facility to measure optical and aerodynamic particulate concentrations. Simultaneously, vertical PM concentration profiles were measured both upwind and downwind of the facility using lidar. The lidar was calibrated to provide mass concentration information using the OPCs and filter measurements. Emission rates were estimated over this period using both an inverse modeling technique coupled with the filter-based measurements and a mass-balance technique applied to lidar data. Mean emission rates calculated using inverse modeling ( ± 95% confidence interval) were 3.8 ( ± 3.2), 24.8 ( ± 14.5), and 75.9 ( ± 33.2) g d -1 AU -1 for PM 2.5 , PM 10 , and TSP, respectively. Mean emissions rates based on lidar data were 1.3 ( ± 0.2), 15.1 ( ± 2.2), and 46.4 ( ± 7.0) g d -1 AU -1 for PM 2.5 , PM 10 , and TSP, respectively. The PM 10 findings are roughly twice as high as those reported from other dairy studies with different climatic conditions and/or housing types, but are of similar magnitude as those from a study with similar conditions, housing, and emission rate calculation technique.

Ground based remote sensing technologies such as scanning lidar systems (light detection and ranging) are increasingly being used to characterize ambient aerosols due to key advantages (i.e., wide area of regard (10 km2), fast response time, high spatial resolution (<10 m) and high sensitivity). Scanning lidar allows for 3D imaging of atmospheric motion and aerosol variability. Space Dynamics Laboratory at Utah State University, in conjunction with the USDA-ARS, has developed and successfully deployed a three-wavelength lidar system called Aglite to characterize particles in diverse settings. Aglite generates near real-time imagery of particle size distribution and size-segregated mass concentration in addition to the ability to calculate whole facility emission rates. Based on over nine years of field and laboratory experience, we present concentration and emission rate results from various measurements in military and civilian deployments.