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Meteorological data parameters

Pasquill (11) advocated the use of fluctuation measurements for dispersion estimates but provided a scheme "for use in the likely absence of special measurements of wind structure, there was clearly a need for broad estimates" of dispersion "in terms of routine meteorological data" (p. 367). The first element is a scheme which includes the important effects of thermal stratification to yield broad categories of stability. The necessary parameters for the scheme consist of wind speed, insolation, and cloudiness, which are basically obtainable from routine observations (Table 19-3). [Pg.301]

Data Acquisition and Parameter Estimation determines frequencies of the initiating events, component unavailability and probabilities of human actions were estimated from plant history. If insufficient, generic values were used including generic data from the nuclear industry (IAEA, 1988). In addition meteorological data and data on the population distribution around the plant were gathered and processed. [Pg.447]

In order to achieve that an environmental fate model is successfully applied in a screening level risk assessment and ultimately incorporated into the decisionmaking tools, the model should have computational efficiency and modest data input. Moreover, the model should incorporate all relevant compartments and all sources of contamination and should consider the most important mechanisms of fate and transport. Although spatial models describe the environment more accurately, such models are difficult to apply because they require a large amount of input data (e.g., detailed terrain parameters, meteorological data, turbulence characteristics and other related parameters). Therefore, MCMs are more practical, especially for long-term environmental impact evaluation, because of their modest data requirements and relatively simple yet comprehensive model structure. In addition, MCMs are also widely used for the comparative risk assessment of new and existing chemicals [28-33]. [Pg.50]

The Monin-Obukhov length L can also be estimated from conventional meteorological data by first evaluating the parameter a (Fulle, 1975) ... [Pg.256]

Recent precipitation parameters common to Indiana have been used to establish the experimental criteria ( ). These included such data as acid content, meteorological data and conditions, chemical composition of the precipitation, etc. Only one degradation parameter was focused upon the cause and effect interaction of pure in leaching structural materials common in Indiana, including bronze, marble, and Indiana limestone. Quantitative data on the contribution of can then be selectively isolated from the overall effects of the complex environmental matrix. With this initial step, the effects of further matrix components (whether cations, anions, or compounds), acting both individually and/or syner-gistically, can then be pursued. [Pg.286]

The final output for the atmospheric model is the radon concentration at a defined distance from the source, in each wind direction and in the dominant wind direction, where is considered to be located the receptor. For the hydrological model the final outputs are the radium concentration in the well water and the corresponding cumulative rate of radium transported to the well after the time considered. Local meteorological data, namely wind velocity and frequency, was used for simulating the dispersion in each octant direction. These data was obtained from a local automatic meteorological station (INAG 2004). The dominant wind direction is NW. The unknown parameters were estimated from available data. [Pg.473]

Parameter (surface meteorological data) (upper air meteorological data)... [Pg.161]

Dispersion models calculated downwind vapor concentrations based on actual, 24-hour, groundlevel and upper-air meteorological data from 61 cities (including one each in Alaska and Hawaii) over a 5-year period. The nuxlels approximated atmospheric conditions at over 40.000 U.S. hypotlietical incident sites derived from truck-fatal accident locations in tlie same 5-year period. A sensitivity study indicated heavy gas effects on vapor plume dispersion were minimal for the incident release sizes considered when compared to uncertainty in other input parameters. Data also showed nighttime atmospheric... [Pg.833]

Climate and Environmental Factors. The biomass species selected for energy appHcations and the climate must be compatible to faciUtate operation of fuel farms. The three primary climatic parameters that have the most influence on the productivity of an iadigenous or transplanted species are iasolation, rainfall, and temperature. Natural fluctuations ia these factors remove them from human control, but the information compiled over the years ia meteorological records and from agricultural practice suppHes a valuable data bank from which to develop biomass energy appHcations. Ambient carbon dioxide concentration and the availabiHty of nutrients are also important factors ia biomass production. [Pg.30]

All meteorological parameters should be recorded to assist in understanding the relevance of the results and their comparison with other data. [Pg.54]

From equation (3.13) we can deduct a rough approximation of the location where maximum ground-level concentration occurs. It is argued that the turbulent diffusion acts more and more on the emitted substances, when the distance from the point source increases therefore the downwind distance dependency of the diffusion coefficients is done afterwards. If we drop this dependency, equation (3.13) leads to xmax=34,4 m for AK=I (curve a) and xmax=87,7 m for AK=V (curve b), what is demonstrated in fig n The interpolated ranges of measured values are lined in. Curve a overestimates the nondimensional concentration maximum, but its location seems to be correct. In the case of curve b the situation is inverted. Curve c is calculated with the data of AK=II. The decay of the nondimensional concentration is predicted well behind the maximum. Curve d is produced with F—12,1, f=0,069, G=0,04 and g=l,088. The ascent of concentration is acceptable, but that is all, because there is no explanation of plausibility how to alter the diffusivity parameters. Therefore it must be our aim to find a suitable correction in connection with the meteorological input data. [Pg.122]

Clearly, environmental chamber studies are very useful tools in examining the chemical relationships between emissions and air quality and for carrying out related (e.g., exposure) studies. Use of these chambers has permitted the systematic variation of individual parameters under controlled conditions, unlike ambient air studies, where the continuous injection of pollutants and the effects of meteorology are often difficult to assess and to quantitatively incorporate into the data analysis. Chamber studies have also provided the basis for the validation of computer kinetic models. Finally, they have provided important kinetic and mechanistic information on some of the individual reactions occurring during photochemical smog formation. [Pg.880]

We thank the Cincinnati Station of the U. S. Weather Bureau for making data available to us, and David Smith of this laboratory for discussing the effect of meteorological parameters. [Pg.453]


See other pages where Meteorological data parameters is mentioned: [Pg.239]    [Pg.123]    [Pg.95]    [Pg.41]    [Pg.161]    [Pg.12]    [Pg.44]    [Pg.52]    [Pg.247]    [Pg.128]    [Pg.428]    [Pg.284]    [Pg.183]    [Pg.8]    [Pg.91]    [Pg.95]    [Pg.372]    [Pg.32]    [Pg.381]    [Pg.349]    [Pg.32]    [Pg.985]    [Pg.986]    [Pg.36]    [Pg.605]    [Pg.605]    [Pg.16]    [Pg.46]    [Pg.64]    [Pg.259]    [Pg.106]    [Pg.56]    [Pg.57]    [Pg.464]    [Pg.58]    [Pg.162]   
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