Suitability and uncertainty of two models for the simulation of ammonia dispersion from a pig farm located in an area with frequent calm conditions. (February 2015)

• Record Type: Journal Article
• Authors: Theobald, Mark R.; Sanz-Cobena, Alberto; Vallejo, Antonio; Sutton, Mark A.
• Is Part Of: Atmospheric environment. Volume 102(2015)
• Page Start: 167
• Page End: 175
• Publication Date: 2015-02
• Subjects: Ammonia emissions -- Atmospheric dispersion modelling -- Uncertainty analysis; Air -- Pollution -- Periodicals; Air -- Pollution -- Meteorological aspects -- Periodicals; 551.51
• DOI: 10.1016/j.atmosenv.2014.11.056
• Languages: English
• ISSNs: 1352-2310

Abstract

Abstract: We used two atmospheric dispersion models (ADMS and AERMOD) to simulate the short-range dispersion of ammonia emitted by two pig farms to assess their suitability in situations with frequent calm meteorological conditions. Simulations were carried out both using constant and temporally-varying emission rates to evaluate the effect on the model predictions. Monthly and annual mean concentrations predicted by the models at locations within one kilometre of the farms were compared with measured values. AERMOD predicted higher concentrations than ADMS (by a factor of 6–7, on average) and predicted the atmospheric concentrations more accurately for both the monthly and annual simulations. The differences between the concentrations predicted by the two models were mainly the result of different calm wind speed thresholds used by the models. The use of temporally-varying emission rates improved the performance of both models for the monthly and annual simulations with respect to the constant emission simulations. A Monte Carlo uncertainty analysis based on the inputs judged to be the most uncertain for the selected case study estimated a prediction uncertainty of ± a factor of two for both models with most of this due to uncertainty in emission rates. Highlights: Two dispersion models are compared for a site with frequent calm conditions. Modelled ammonia concentrations around a pig farm are compared with measurements. Model uncertainty due to input uncertainty is approximately a factor of 2. The largest contribution to prediction uncertainty is uncertainty in emission rates. Differences in model performance are mainly due to periods with low wind speeds.