Modeling of dispersion of air pollutants in the atmosphere is one of the most important and challenging scientific problems. There are several natural and anthropogenic events where passive or chemically active compounds are emitted into the atmosphere. The effect of these chemical species can have serious impacts on our environment and human health. Modeling the dispersion of air pollutants can predict this effect. Therefore, development of various model strategies is a key element for the governmental and scientific communities. We provide here a brief review on the mathematical modeling of the dispersion of air pollutants in the atmosphere. We discuss the advantages and drawbacks of several model tools and strategies, namely Gaussian, Lagrangian, Eulerian and CFD models. We especially focus on several recent advances in this multidisciplinary research field, like parallel computing using graphical processing units, or adaptive mesh refinement.
Abstract. Improved data on biosphere-atmosphere exchange are fundamental to understanding the production and fate of ammonia (NH 3 ) in the atmosphere. The GRAMINAE Integrated Experiment combined novel measurement and modelling approaches to provide the most comprehensive analysis of the interactions to date.Major intercomparisons of micrometeorological parameters and NH 3 flux measurements using the aerodynamic gradient method and relaxed eddy accumulation (REA) were conducted. These showed close agreement, though the REA systems proved insufficiently precise to investigate vertical flux Correspondence to: M. A. Sutton (ms@ceh.ac.uk) divergence. Grassland management had a large effect on fluxes: emissions increased after grass cutting (−50 to 700 ng m −2 s −1 NH 3 ) and after N-fertilization (0 to 3800 ng m −2 s −1 ) compared with before the cut (−60 to 40 ng m −2 s −1 ).
Abstract. Ammonia exchange fluxes between grassland and the atmosphere were modelled on the basis of stomatal compensation points and leaf surface chemistry, and compared with measured fluxes during the GRAMINAE intensive measurement campaign in spring 2000 near Braunschweig, Germany. Leaf wetness and dew chemistry in grassland were measured together with ammonia fluxes and apoplastic NH + 4 and H + concentration, and the data were used to apply, validate and further develop an existing model of leaf surface chemistry and ammonia exchange. Foliar leaf wetness which is known to affect ammonia fluxes may be persistent after the end of rainfall, or sustained by recondensation of water vapour originating from the ground or leaf transpiration, so measured leaf wetness values were included in the model. pH and ammonium concentrations of dew samples collected from grass were compared to modelled values.The measurement period was divided into three phases: a relatively wet phase followed by a dry phase in the first week before the grass was cut, and a second drier week after the cut. While the first two phases were mainly characterised by ammonia deposition and occasional short emission events, regular events of strong ammonia emissions were observed during the post-cut period. A single-layer resistance model including dynamic cuticular and stomatal exchange could describe the fluxes well before the cut, but after the cut the stomatal compensation points needed to numerically match Correspondence to: J. Burkhardt (j.burkhardt@uni-bonn.de) measured fluxes were much higher than the ones measured by bioassays, suggesting another source of ammonia fluxes. Considerably better agreement both in the direction and the size range of fluxes were obtained when a second layer was introduced into the model, to account for the large additional ammonia source inherent in the leaf litter at the bottom of the grass canopy. Therefore, this was found to be a useful extension of the mechanistic dynamic chemistry model by keeping the advantage of requiring relatively little site-specific information.
Abstract. Commonly, the micrometeorological parameters that underline the calculations of surface atmosphere exchange fluxes (e.g. friction velocity and sensible heat flux) and parameters used to model exchange fluxes with SVATtype parameterisations (e.g. latent heat flux and canopy temperature) are measured with a single set of instrumentation and are analysed with a single methodology. This paper evaluates uncertainties in these measurements with a single instrument, by comparing the independent results from nine different institutes during the international GRAMINAE integrated field experiment over agricultural grassland near Braunschweig, Lower Saxony, Germany. The paper discusses uncertainties in measuring friction velocity, sensible and latent heat fluxes, canopy temperature and investigates the energy balance closure at this site. Although individual 15-min flux calculations show a large variability between the instruments, when averaged over the campaign, fluxes agree within 2% for momentum and 11% for sensible heat. However, the spread in estimates of latent heat flux (λE) is Correspondence to: E. Nemitz (en@ceh.ac.uk) larger, with standard deviations of averages of 18%. The dataset averaged over the different instruments fails to close the energy budget by 20%, significantly larger than the uncertainties in the individual flux corrections. However, if the largest individual turbulent flux estimates are considered, energy closure can be achieved, indicating that the closure gap is within the spread of the measurements. The uncertainty in λE feeds results in an uncertainty in the bulk stomatal resistance, which further adds to the uncertainties in the estimation of the canopy temperature that controls the exchange. The paper demonstrated how a consensus dataset was derived, which is used by the individual investigators to calculate fluxes and drive their models.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.