Wind speed averages

The scope of the wind resource is widespread and less dependent upon latitude than other solar technologies. The accessible resource in the United States has been conservatively estimated to be capable of providing more than 10 times the electricity consumed therein. The intermittency of the wind resource, however, makes it impractical to base more than 10—20% of electricity generation on this resource until a suitable storage technology is developed. Wind is a very complex resource, existing in three dimensions, rather than the two associated with other solar resources. It is intermittent and strongly influenced by terrain effects. Moreover, there is a nonlinear (cubic) relationship between wind speed and power or energy available. This last factor is best illustrated by comparing good, excellent, and outstanding wind sites having average wind velocities of 5.5, 7.0, and 8.5 m/s, respectively. This 1.5-m/s difference results in the excellent site having 106% more available energy per unit than the good site for conversion to electricity the outstanding site has 269% more available energy than the good site.  [c.232]

Introduction Gas dispersion (or vapor dispersion) is used to determine the consequences of a release of a toxic or flammable material. Typically, the calculations provide an estimate of the area affected and the average vapor concentrations expected. In order to make this determination, one must know the release rate of the gas (or the total quantity released) and the atmospheric conditions (wind speed, time of day, cloud cover).  [c.2340]

Near-surface (within 10 m of the ground) meteorological instrumentation always includes wind measurements and should include turbulence measurements as well. Such measurements can be made at 10 m above ground by using a guyed tower. A cup anemometer and wind vane (Fig. 19- 7), or a vane with a propeller speed sensor mounted in front (Fig. 19-8), can be the basic wind system. The wind sensor should have a threshold starting speed of less than 0.5 m s an accuracy of 0.2 m s or 5%, and a distance constant of less than 5 m for proper response. The primary quantity needed is the hourly average wind speed. A representative value may be obtained from values taken each minute, although values taken at intervals of 1-5 sec are better.  [c.306]

What is the steady-state concentrahon derived from the box model for a 10-km city with average emissions of 2 x 10" g m s when the mixing height is 500 m and the wind speed is 4 m s  [c.344]

Using simplified techniques for estimating the concentrations from area sources, what is the annual average particulate matter concentration for a city with an average wind speed of 3.6 m s and area emission rate of 8 x 10 g s m"  [c.344]

Average Wind Speed and Frequency of Calms  [c.351]

Average wind speed 3.79 m s 3.26 m s  [c.351]

U = average wind speed, m/s t = time  [c.285]

Since U is a function of z, some mean value must be used. The appropriate value is the mean through the plume. However, the time-averaged wind speed at the stack height is commonly used. Often, even this value may not be known, in which case an estimate must be made. This estimate could be based on an assumed power law velocity profile such as  [c.286]

As noted earlier, the SCREEN model also contains the option to calculate maximum 24-hour concentrations for terrain elevations above stack height. A final plume height and distance to final rise are calculated based on the VALLEY model screening technique (Burt, 1977) assuming conditions of F stability (E for urban) and a stack height wind speed of 2.5 m/s. Stack tip downwash is incorporated in the plume rise calculation. The user then inputs a terrain height and a distance (m) for the nearest terrain feature likely to experience plume impaction, taking into account complex terrain closer than the distance to final rise. If the plume height is at or below the terrain height for the distance entered, then SCREEN will make a 24-hour average concentration estimate using the VALLEY screening technique devised by EPA.  [c.322]

This self-extracting EXE can be installed in Windows 95/98/Me, NT, or 2000. You will easily find this product on the main site page. Figure 14 shows a sample graphical printout from the program. Once executed, the program will link you to a meteorological Web site where you can download historical and current weather information for a region or city into a file for construction of the wind rose plots. You may also perform statistical analysis to ascertain trends on wind speed, direction, and seasonal variations. This type of information is obviously needed when you perform an air dispersion study (e.g., in assessing average conditions and worst case scenario dispersion calculations).  [c.327]

Atmospheric Conditions - Normal average wind speed, ambient air temperature, air density, relative humidity.  [c.283]

U. = Normal average wind speed, m/s, based on local meteorological conditions  [c.286]

The weather data are based on thousands of observations of wind speed, wind direction and atmospheric stability taken over the desired averaging interval at local weather bureau stations.  [c.358]

Similar behavior was observed for LNG clouds during both continuous and instantaneous tests, but average flame speeds were lower the maximum speed observed in any of the tests was 10 m/s. Following premixed combustion, the flame burned through the fuel-rich portion of the cloud. This stage of combustion was more evident for continuous spills, where the rate of flame propagation, particularly for LNG spills, was very low. In one of the continuous LNG tests, a wind speed of only 4.5 m/s was sufficient to hold the flame stationary at a point some 65 m from the spill point for almost 1 minute the spill rate was then reduced.  [c.149]

Wind turbines produce power by converting the force of the wind into torque. The power produced is a function of the wind energy flux (power), which, in turn, is a function of the air density multiplied by the wind velocity raised to the third power. Changes of air density with time at a particular site are negligible compared to the fluctuations in wind velocity. Meteorologists usually report wind speed as an average. To get the potential wind power, the average  [c.92]

The factor S2 takes account of the combined effect of ground roughness, the variation of wind speed with height above ground and the size of the building or component part under consideration. In conditions of strong wind the wind speed usually increases with height above ground. The rate of increase depends on ground roughness and also on whether short gusts or mean wind speeds are being considered. This is related to building size that take account of the fact that small buildings and elements of a building are more affected by short gusts than are larger buildings, for which a longer and averaging period is more appropriate.  [c.18]

Particulate Matter. In the air pollution field, the terms particulate matter, particulates, particles, and aerosols (qv) are used interchangeably and all refer to finely divided sohds and hquids dispersed in the air. The original EPA primary standards were for total suspended particulates, TSP, the weight of any particulate matter collected on the filter of a high volume air sampler. On the average, these samplers collect particles that ate less than about 30—40 )Tm in diameter, but collection efficiencies vary according to both wind direction and speed. In 1987, the term PM q, particulate matter having an aerodynamic diameter of 10 )Tm or less, was introduced. The 10-)Tm diameter was chosen because 50% of the 10-)Tm particles deposit in the respiratory tract below the larynx during oral breathing and the fraction deposited decreases as particle diameter increases above 10 )Tm. Because the NAAQS standard (see Table 3) was only enacted in 1987, currentiy available PM q data ate insufficient to determine trends. However, from 1979 to 1988 TSP emissions declined 22% and ambient concentrations decreased 20% (4).  [c.373]

The plume model describes continuous release of material. The solution depends on the rate of release, the atmospheric conditions, the height of the release above ground, and the distance from the release. In this case, the wind is moving at a constant speed u in the x direction. The equation for the average concentration for this case is (Crowl and Louvar, 1990, p. 142)  [c.2343]

The changeover is obtained by measuring the average power generated during a particular time period, say, one minute or so, rather than the speed of the wind. When this average power falls below a preset level the machine changes over to the lower speed windings and vice versa. Due to the unpredictable nature of the wind speeds, this may require frequent changeovers and may affect the reliability of a double-speed system.  [c.160]

Pollution roses are constructed by plotting either the average concentration for each direction or the frequency of concentrations above some particular concentration. Pollution roses for two pollutants at two times of the year are shown in Fig. 21-10, with wind frequencies by two speed classes  [c.359]

It is appropriate to consider the differences between manual tasks and process industries (see Section while assessing the exposure, and to perform air sampling so that it also can support planning of engineering control. Because of steep concentration gradients, breathing zone sampling must be performed when investigating manual tasks. A worker often performs several tasks, and the exposure may be very different during different tasks. Therefore, all major tasks done by the worker should be studied under various conditions. If the position of the local exhaust is not fixed, its influence should also be examined. The time-weighted average (TWA) concentration is obtained using the lengths of various tasks as the weights. It is common practice to determine the TWA of a working day (shift). Since the health effects usually depend on long-term average exposure level, this should also be estimated. Past exposures are often very difficult to assess because working conditions and methods may have been changed. However, the present (e.g., annual) average exposure level can be estimated by asking the worker how much time he/she spends on average (e.g., during the past year) for various tasks and use these as weights. For example, if we want to assess a construction painter s exposure to organic solvents, we must first list all tasks in which solvent-based paints are used. The exposure during painting depends mainly on the size of the surface painted (or on paint consumption rate), the room volume, and the ventilation. Since  [c.321]

The study by Hol worth (2) also examined several other parameters in addition to mixing height. For example, because pollutants are diluted by the wind and mixing height limits the vertical dispersion of pollutants, Holzworth used the radiosonde data to determine the average wind speed through the mixing height for each season and annually. Figure 21-6 shows the distribution of mean annual wind speed averaged through the afternoon mixing layer.  [c.356]

Fig. 21-6. Mean annual wind speed averaged through the afternoon mixing layer. Speeds are in meters per second. Source Adapted ftom Holzworth (2). Fig. 21-6. Mean annual wind speed averaged through the afternoon mixing layer. Speeds are in meters per second. Source Adapted ftom Holzworth (2).
The principal framework of empirical equations which form a basis for estimahng concentrations from point sources is commonly referred to as the Gaussian plume model. Employing a three-dimensional axis system of downwind, crosswind, and vertical with the origin at the ground, it assumes that concentrations from a continuously emitting plume are proportional to the emission rate, that these concentrations are diluted by the wind at the point of emission at a rate inversely proportional to the wind speed, and that the time- averaged (about 1 h) pollutant concentrations crosswind and vertically near the source are well described by Gaussian or normal (bell-shaped) distributions. The standard deviations of plume concentration in these two directions are empirically related to the levels of turbulence in the atmosphere and increase with distance from the source.  [c.296]

In estimating seasonal or annual concentrations from point or area sources, shortcuts can generally be taken rather than attempting to integrate over short intervals, such as hour-by-hour simulation. A frequent shortcut consists of arranging the meteorological data by joint frequency of wind direction, wind speed, and atmospheric stability class, referred to as a STability ARray, STAR. The ISCLT (16) is a model of this type and is frequently used to satisfy regulatory requirements where concentrations averaged over 1 year (but not shorter averaging times) or longer are required. Further simplification may be achieved by determining a single effective wind speed for each stability-wind direction sector combination by weighting 1/u by the frequency of each wind speed class for each such wind direction-stability combination. Calculations for each sector are made, assuming that the frequency of wind direchon is uniform across the sector.  [c.327]

Data for one full year (1964) for Nashville, Tennessee, and Knoxville, Tennessee, 265 km (165 mi) apart, were compared to determine the extent to which the frequencies of various parameters were similar. Knoxville is located in an area with mountainous ridges oriented southwest-northeast Nashville is situated in a comparahvely flat area. The data available are the number of hours during which each of 36 wind directions (every 10° azimuth) occurred, the average wind speed for each direction, the number of hours of each Pasquill stability class for each direchon, and the mean annual wind speed.  [c.350]

Because of the slight difference in average wind speed, one might expect this to cause a greater frequency of both stable and unstable condihons at  [c.350]

The Maplin Sands tests were reported by Blackmore et al. (1982) and Hirst and Eyre (1983). Quantities of 20 m LNG and refrigerated liquid propane were spilled on the surface of the sea in the Thames estuary. The experimental program consisted of both instantaneous and continuous releases. The resulting vapor cloud dispersion and the subsequent combustion of the clouds was observed by instrumentation deployed on 71 floating pontoons (Figure 5.2). On the masts of 20-30 selected pontoons, 27 wide-angle radiometers (to measure average incident radiation) and 24 hydrophones (to measure flame-generated overpressures) were mounted. Another two special pontoons provided platforms for meteorological instruments. The instruments provided vertical profiles of temperature and wind speed up to 10 m above sea level, together with measurements of wind direction, relative humidity, solar radiation, water temperature, and wave height.  [c.147]

An estimate is required of the total hydrocarbon concentration 300 meters downwind of an expressway on an overcast day with wind speed 4 m/s. Tlie expressway runs norlli-south and the wind is from tlie west. Tlie measured traffic flow is 8000 vehicles per hour during tlris rush hour, and the average speed of the velucles is 40 mph. At tlris speed tlie average vehicle is expected to  [c.388]

The most powerful hurricanes (called Categoi y. S ) have sustained winds exceeding 248 km/hr. In general, hurricanes move slowly vdth the average wind speed of the troposphere. When these hurricanes strike land, they bring a devastating combination of high winds, torrential rain, and a storm surge. The storm surge is an uplifting of the water level resulting from an air pressure drop and wind-driven water the most powerful hurricanes have a storm surge exceeding 18 feet (5.5 m). Hurricane Gilbert, a massive Categoiy 5 hurricane in 1988, dominated about 20 percent of the entire global Intertropical Convergence Zone, causing the cloudiness in the zone outside the storm to dissipate. Hurricane Andrew, which devastated South Florida in 1992, was also a Categoiy 5 hurricane.  [c.89]

The three micrometeorological methods [Fourier Transform Infrared Spectroscopy (FTIR), Tunable diode laser spectroscopy (TDL), and gas chromatography (GC)] all gave measurements over essentially the same area of the field using the flux-gradient technique, and Figure 13 shows the good agreement obtained between the methods, with emission fluxes in the range 0-140 ng Nm s h However, the chamber results also shown on Figure 13 gave much larger fluxes of 140-350ng Nm s a difference which is hard to explain in terms of systematic differences between methods. There was strong evidence that the difference results from the large spatial variability in NjO emission and the associated hot-spots in the held which lay outside the footprint of the micrometeorological equipment. " The experiment demonstrates that a variety of micrometeorological methods may all yield broadly similar fluxes, and that these average fluxes are at the held scale. However, the comparison with chamber methods illustrates some of the difficulties in comparisons at different scales. In the case of chamber measurements, it is necessary to use large numbers of chambers to overcome spatial heterogeneity in emissions, yet to compare with the micrometeorological methods correctly the footprint of the field in which the chambers are placed (which varies with wind direction, speed and atmospheric stability) must be integrated in the same way for both techniques. In practice, this is an extremely demanding task which, for emissions of NjO and NO, may only be achieved within a substantial range of uncertainty ( + 20-25%). As such, the data in Figure 13 represent progress but with more chambers (or a more fortunate wind direction) could have been better by a factor of 2.  [c.79]

See pages that mention the term Wind speed averages : [c.76]    [c.69]    [c.300]    [c.309]    [c.327]    [c.150]    [c.393]    [c.73]   
Macmillan encyclopedia of energy Volumes 1,2,3 (2001) -- [ c.93 ]