Estimating Ammonia Emissions from Livestock Operations Using Low-Cost, Time-Averaged Concentration...
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Transcript of Estimating Ammonia Emissions from Livestock Operations Using Low-Cost, Time-Averaged Concentration...
Kira Shonkwiler and Jay Ham
Department of Atmospheric Science, Colorado State University
Department of Soil and Crop Sciences, Colorado State University
Estimating Ammonia Emissions Using Low-cost, Time-averaged Concentration Measurements
Objectives
• Adapt diffusive NH3 samplers for weather-based conditional sampling
• Field test at beef feedlots and dairies
• Estimate pen NH3 emissions using an inverse model
Radiello Diffusive/Passive Samplers
• Pros– Widely used for NH3 (e.g.,
AMoN network)– Inexpensive, Simple
• Cons– Cumulative – Conc. affected by wind
dir. /speed, stability, …– No Stationarity over
sample period
•
www.nescaum.org/documents/mac/mac-committee...3/rury-amon.pdf/
Conditional Samplers
• Robotic mechanism exposes samplers when a given set of user-defined weather conditions exist– Min. Wind speed– Wind Direction Range– Time of Day, others
• Wireless Sensor Net– Synoptic sampling– Xbee
Actuator Control
``
Linear Actcuator
Acrylic Tube
Cap
Spacer
Vertical Adapter
Radiello Diffusive Sampler
Foam
Acrylic Disc
Hall Effect Sensor
Control Cable
Spacer
Clevis
Clevis
PlungerMagnet
Hall Effect Cable
Arduino Shield Stacks andDatalogger Module
Weather-Based Sampling
Under automated control, samplers were exposed to the air for a total of 3.5 to 4 days during a 14 day sampling period.
Field Testing: Feedlot
Feedlot25,000 Head
700 m
North
South
West Lot
Base
Pasture
Prevailing Wind
Average concentration for each deployment (Oct 2012 – Feb 2013)
Inverse Modeling
Know average concentration, wind characteristics, and site layout…
Can infer emissions
Inverse Model
Weather Data
Source Geometry and
Roughness
Concentration Data Emissions
FIDES
Flux Interpretation by Dispersion Exchange over Short-range (FIDES)
Inverse model (inputs: u* and L)
Solves the advection-dispersion equation
Uses concentration (𝑪𝜶) from a location (x, z) to estimate source strength of a different location (xs, zs)
Loubet et al., 2001; 2010
Cbgd is the constant background concentration
S is the source strength D is a dispersion function
𝑪𝜶 (𝒙 , 𝒛 )=𝑪𝒃𝒅𝒈+∫𝑺 ( 𝒙𝒔 , 𝒛 𝒔 )𝑫 ( 𝒙 , 𝒛 /𝒙𝒔 , 𝒛 𝒔)𝒅𝒙 𝒔
FIDES
Applied successfully in Europe(Loubet et al., 2001; 2009; 2010)
NH3 concentrations measured with high-speed instrumentation
Work at CSU is first attempt at modeling NH3 emissions from time-averaged data (i.e., the conditional passive samplers)
Model Output – Emissions
Average emissions for each deployment cycle (Oct 2012 – Feb 2013)
Decrease in volatilization from surface during winter
Average temperature (above) and wind speed (below) for each deployment period.
Temperatures during the 2012 – 2013 winter (green line) were much higher than the 15-year normal (red line)
Mean wind speeds varied little over each period
Model Output – Emissions
Histogram (frequency distribution) of output emissions from FIDES
Log-normal distribution, 92% of values fall between 20 – 100 mg m-2 s-
1
Model Output – Emissions
Emissions summary
Average Emissions: 4.7 g m-2 d-1; 96.5 g head-1 d-1
Percent of Fed-Nitrogen emitted as NH3 averaged 53%
Conclusions
Emissions decreased throughout the winter as temperature decreased
Predicted emissions have a log-normal distribution
Average model output was 20 – 100 mg m-2 s-1
Emissions averaged 96.5 g head-1 d-1 and 4.7 g m-2 d-1
53% of Fed N emitted to air as NH3
Next steps Compare to continuous NH3 measurements (e.g.,
boreal laser Todd et al., 2008; mobile sampling)
References1. Fdfs
Thank You!