Meteorological data

Meteorological data which may be of interest for the design and the construction are  

Although not a direct input parameter for the design of reclamation works, wind is an important parameter describing the physical site conditions (i.e, seasonal variations, storm behaviour) and is the basic input information required in deriving 

Percentage of occurrence of wave height (m) in rows versus mean wave period (s) in columns 

Time- and spatial varying air or barometric pressure data are used in combination with wind fields to derive extreme water levels by means of numerical storm surge modelhng. 

Sudden changes in barometric pressure readings observed during reclamation works are indicators for weather changes and may therefore be a relevant monitoring parameter during the works. 

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Adequate support from the facility staff is absolutely essential. The facility staff must help the analysis team gather pertinent documents (e.g., PSilDs, procedures, software descriptions, material inventories, meteorological data, population data) and must describe current operating and maintenance practices. The facility staff must then critique the logic model(s) and calculation(s) to ensure that the assumptions are correct and that the results seem reasonable. The facility staff should also be involved in developing any recommendations to reduce risk so they will fully understand the rationale behind all proposed improvements and can help ensure that the proposed improvements are feasible. Table 12 summarizes the types of facility resources and personnel needed for a typical QRA. 

In addition to short-term emission estimates, normally for hourly periods, the meteorological data include hourly wind direction, wind speed, and Pasquill stability class. Although of secondary importance, the hourly data also include temperature (only important if buoyant plume rise needs to be calculated from any sources) and mixing height. 

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). 

In its simplest form, a model requires two types of data inputs information on the source or sources including pollutant emission rate, and meteorological data such as wind velocity and turbulence. The model then simulates mathematically the pollutant s transport and dispersion, and perhaps its chemical and physical transformations and removal processes. The model output is air pollutant concentration for a particular time period, usually at specific receptor locations. 

Seeing the success of the UNAMAP BBS, EPA s Office of Air Quality Planning and Standards started a BBS for information on regulatory models in June 1989. This has expanded to a BBS called TTN, Technology Transfer Network. This BBS, in Durham, NC, is reached on (919) 541-5742 and the system operator on (919) 541-5384. A part of this BBS called SCRAM, Support Center for Regulatory Air Models, contains model FORTRAN codes, model executable codes for use on personal computers, meteorological data, and in some cases model user s guides. Much of the information is downloaded in "packed" form, and software to unpack the files must also be downloaded from the bulletin board. 

One free software package worth downloading is WRPLOT View, which is a fully operational wind rose Windows program for your meteorological data. WRPLOT View is the logical replacement for the popular U.S. EPA DOS utility WRPLOT (this second program is also available at the site and is noted below). WRPLOT View s main features are ... 

AERMOD AERMOD is the next generation air dispersion modeling system and consists of 3 components - AERMOD (air dispersion model), AERMET (meteorological data preprocessor) and AERMAP (terrain preprocessor). A brief overview of the model can be found in the mod-desc.txt file which can be downloaded from the site. 

STAR The STAR program summarizes National Weather Services (NWS) meteorological data, by generating joint frequencies of 6 wind speeds, 16 wind directions, and 6 stability categories for the station and time period desired. 

Table 6. Meteorological Data and Stability Classes Used in Calculations.

Visit http //ncardata.ucar.edU/datasets/ds464.0/MASTER and/or Infor wunderground.com. Become familiar with the types of meteorological data and formats that you can download in. 

Collects, processes, displays, and reports air quality and meteorological data. Requires Data Genera Corp. MicroECLIPSE processor. 

Meteorological data processing. Prepares data in a suitable format for input in models. 

Primarily models chemical releases to the air. Includes a chemical database and map editor and is capable of mapping concentration isopleths. Allows real-time meteorological data input. 

Annual meteorological data from designated regional stations. 

CRAC determined the consequences of a reactor accident using meteorological data for six reactor sites. Each site was taken to represent an entire region, and all of the 68 sites of the first 100 reactors were assigned to one of these six regions. Wind. speed and stability for each of the six sites was assumed to be representative of the entire region out to a distance of 500 miles. Wind direction because with so many sites, the wind direction was assumed random, but the population dish ibution for all 68 sites was used. 

About ten sources of meteorological data were used, each assumed to be representative of a region in the vicinity of the plant. 

The dominant internal event accident scenarios were used in conjunction with conservative source terms (100% of the core melts, releasing 100% of the noble gases, 100% nf iodine and cesium, and 1% solids), and )ecific meteorological data to estimate e consequences to be well below the lOCFRlOO siting guidelines. 

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. 

The problem of unknown amounts of air leakage in the cold season in an industrial hall can be calculated by multizone airflow models during the whole year with local meteorological data. 

Weather data for a number of years should be assembled for each community being studied. Particular attention should be given to such natural disasters as hurricanes, earthquakes, and floods, which often can be predicted from meteorological data. In certain locations these catastrophic events must be assumed to be probable and this increases construction costs. E.xtremely cold weather often hampers process plant operation and requires special construction features to protect equipment from freezing. Predominantly warm weather permits cheaper construction but may also reduce the efllcicncy of the labor force. 

Design wet bulbs can be determined from published meteorological data for the area concerned. The difficulty is deciding how to relate the annual coverage to the tower performance at any given time. 

Overview. Figure 10 shows, in simplified form, the activities, inputs and outputs involved in running HSPF, from a typical user s point of view. The first phase involves copying input time series, such as meteorological data, from sequential files (cards, tape, disc) to the Time Series Store (TSS). This is sometimes done in a single run but in most practical situations, where data have to be gathered from diverse sources and gaps have to be patched, several runs are made. 

Pesticide) Alachlor Lombardia Region (Northern Surface water Italy) - Meteorological data - Application rate - Active ingredient lost by drift - Percentage of active ingredient lost by runoff [53]... 

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]. 

We have designed and built a microprocessor-based Data Acquisition System for radon research that is currently being used for field studies. Among other things the system will be used to monitor radon levels in conjunction with other meteorological data in a controlled space over relatively long periods of time. 

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