On dispersion above a forest-Measurements and methods.

UNLABELLED: Data collected over a mixed conifer/deciduous forest at the U.S. Department of Energy's Savannah River Site in South Carolina using sonic anemometry reveal that on-site and real-time measurements of the velocity component standard deviations, σv and σw, are preferred for dispersion modeling. Such data are now easily accessible, from the outputs of cost-effective and rugged sonic anemometers. The data streams from these devices allow improvements to conventional methodologies for dispersion modeling. In particular, extrapolation of basic input data from a nearby location to the site of the actual release can be facilitated. In this regard reliance on the velocity statistics σv and σw appears to be preferred to the conventional σθ and σϕ. In the forest situations addressed here, the uncertainties introduced by extrapolating initializing properties (u, θ, σθ, and σϕ, or alternatively, σv and σw) from some location of actual measurement to some nearby location where an actual release occurs are similar to those associated with the spread of the plume itself and must be considered in any prediction of the likelihood of downwind concentration (exposure) exceeding some critical value, i.e., a regulatory standard. Consideration of plume expansion factors related to meander will not necessarily cause predicted downwind maxima within a particular plume to be decreased; however, the probability of exposure to this maximum value at any particular location will be reduced. Three-component sonic anemometers are affordable and reliable, and are now becoming a standard for meteorological monitoring programs subject to regulatory oversight. The time has come for regulatory agencies and the applied dispersion community to replace the traditional discrete sets of dispersion coefficients based on Pasquill stability by the direct input of measured turbulence data. IMPLICATIONS: The continued endorsement of legacy Pasquill-Gifford stability schemes is presently under discussion among professional groups and regulatory agencies. The present paper is an attempt to introduce some rationality, for the case of a forested environment.

Estimating background precipitation quality from network data.

Assessments of the relative merits of alternative acid-rain control strategies revolve around considerations of potential benefit per unit effort and/or cost. A question that often arises concerns the changes in deposition that would follow if all industrial (or societal) emissions were eliminated, in which case precipitation chemistry would be dominated by emissions from natural sources. Estimates of the 'natural background' of precipitation chemistry can be based on (a) measurements made at distant locations, (b) reducing emissions to zero in numerical simulations, or (c) examinations of existing data. Each alternative is flawed because (a) of the assumption that natural emissions in one location are like those in another, (b) no existing model contains descriptions of chemical processes involving all of the chemical species of importance, and (c) all contemporary data records or relevance are affected by precisely the emissions we wish to reduce. Here, the third alternative is explored in detail, using event precipitation chemistry data from North America. The analysis reveals a background pH level that varies from site to site, but always lies in the range 5.0-5.3.

Dry deposition of O3, SO2, and HNO3 to different vegetation in the same exposure environment.

Agricultural meteorological modeling techniques are used to investigate the relative and absolute dry deposition fluxes of SO2 (as sulfur), HNO3 (as nitrogen) and O3 to large fields of maize, soybeans, and alfalfa exposed in conditions as measured in northern Illinois, central Pennsylvania, and eastern Tennessee. For HNO3, the differences in seasonal deposition rates among the three types of plant species are small. Within the same environment, the soybean canopy has the potential to receive substantially more gaseous dry deposition of SO2 and O3 than the maize and alfalfa (which are about the same), as a result of lower stomatal resistance and consequently higher deposition velocities. Deposition differences among the sites are small except for the case of SO2, for which deposition rates estimated for northern Illinois are nearly double those at the other locations. The high SO2 deposition at the northern Illinois location is a consequence of the higher air concentrations observed there.

Sensitivity and uncertainty studies of the CRAC2 computer code.

We have studied the sensitivity of health impacts from nuclear reactor accidents, as predicted by the CRAC2 computer code, to the following sources of uncertainty: (1) the model for plume rise, (2) the model for wet deposition, (3) the meteorological bin-sampling procedure for selecting weather sequences with rain, (4) the dose conversion factors for inhalation as affected by uncertainties in the particle size of the carrier aerosol and the clearance rates of radionuclides from the respiratory tract, (5) the weathering half-time for external ground-surface exposure, and (6) the transfer coefficients for terrestrial foodchain pathways. Predicted health impacts usually showed little sensitivity to use of an alternative plume-rise model or a modified rain-bin structure in bin-sampling. Health impacts often were quite sensitive to use of an alternative wet-deposition model in single-trial runs with rain during plume passage, but were less sensitive to the model in bin-sampling runs. Uncertainties in the inhalation dose conversion factors had important effects on early injuries in single-trial runs. Latent cancer fatalities were moderately sensitive to uncertainties in the weathering half-time for ground-surface exposure, but showed little sensitivity to the transfer coefficients for terrestrial foodchain pathways. Sensitivities of CRAC2 predictions to uncertainties in the models and parameters also depended on the magnitude of the source term, and some of the effects on early health effects were comparable to those that were due only to selection of different sets of weather sequences in bin-sampling.