2014 journal article
Modeling of ammonia dry deposition to a pocosin landscape downwind of a large poultry facility
AGRICULTURE ECOSYSTEMS & ENVIRONMENT, 185, 161–175.
author keywords: Ammonia; Dry deposition; Bi-directional flux; Resistance modeling; Animal facility
UN Sustainable Development Goal Categories
11. Sustainable Cities and Communities
(Web of Science)
13. Climate Action
(Web of Science)
Source: Web Of Science
Added: August 6, 2018
A semi-empirical bi-directional flux modeling approach is used to estimate NH3 air concentrations and dry deposition fluxes to a portion of the Pocosin Lakes National Wildlife Refuge (PLNWR) downwind of a large poultry facility. Meteorological patterns at PLNWR are such that some portion of the refuge is downwind of the poultry facility 52%, 66%, 57%, and 50% of time during winter, spring, summer, and fall, respectively. Air concentrations and dry deposition rates are highest in the northeasterly direction from the facility, consistent with prevailing wind patterns. Dry deposition rates along the axis of highest concentrations are 10.1 kg N ha−1 yr−1 at the refuge boundary closest to the facility, decreasing to 5.4 kg N ha−1 yr−1 1.5 km further downwind and continuing to decrease non-linearly to a deposition rate of 1.4 kg N ha−1 yr−1 8–10 km downwind. Approximately 10% of the refuge model domain receives ≥3.0 kg N ha−1 yr−1 as dry NH3 deposition. Depending on the definition of the background air concentration, annual nitrogen loading to the refuge from background NH3 dry deposition and NH3 dry deposition associated with elevated concentrations downwind of the facility is between 41% and 79% higher than background dry NH3 deposition alone. Relative to the total N deposition budget for the refuge, which includes all nitrogen compounds, total background N deposition plus NH3 dry deposition associated with elevated concentrations downwind of the facility is, correspondingly, 6–10% greater than background total N deposition alone. From a process standpoint, predicted fluxes are most sensitive to uncertainty in the parameterization of the cuticular resistance.