Measurements of level-crossing statistics of concentration fluctuations in plumes dispersing in the atmospheric surface layer

The statistics of level crossings and local extremes in concentration fluctuations in plumes dispersing in the atmosphere have been investigated. A set of concentration fluctuation tracer experiments has been utilized to measure the statistical propertics of the upcrossing interval (inter-arrival time between consecutive concentration bursts), excursion duration (persistence or width of concentration bursts), and concentration amplitude (difference between the maximum and minimum concentrations between successive upcrossings) with respect to a range of concentration crossing levels. In particular, the effect of downwind distance and atmospheric stratification on the level-crossing statistics has been studied in detail. It is shown that the effect of increasing atmospheric stability on level-crossing statistics is similar to the effect of increasing distance from the source in the sense that level-crossing statistics of concentration fluctuations in stable stratification resemble those in neutral stratification, but at a greater downwind distance. It is also found that the distribution of the interval between consecutive upcrossings of a concentration level, as well as the duration of an excursion across a concentration level, can be approximated by a lognormal distribution, whereas the distribution of the concentration amplitude is best characterized by a gamma distribution. Some implications of these results for the modeling of level-crossing statistics of concentration fluctuations are discussed.     

The vertical structure of concentration fluctuation statistics in plumes dispersing in the atmospheric surface layer

This paper describes a study of the vertical structure of concentration fluctuations in a neutrally buoyant plume from an elevated point source in slightly convective to moderately stable meteorological conditions at ranges of between 12.5 and 100 m for a range of source heights between 1 and 5 m. Observations were made of concentration fluctuations in a dispersing plume using a vertical array of sixteen very fast-response photoionization detectors placed at heights between 0.5 and 16 m. Vertical profiles of a number of concentration statistics were extracted, namely, mean concentration, fluctuation intensity, intermittency factor, peak-to-mean concentration ratio, mean dissipation rate of concentration variance, and various concentration time and length scales of dominant motions in the plume (e.g., integral macro-scale, in-plume mid-scale and Taylor micro-scale). The profiles revealed a similarity to corresponding crosswind profiles for a fully elevated plume, but showed greater and greater departure from the latter shapes once the plume had grown in the vertical so that its lower dege began to interact progressively more strongly with the ground. The evolution of the concentration probability density function at a fixed range, but with decreasing height from the ground, is similar to that obtained at a fixed height but with increasing distance from the source. Concentration power spectra obtained at different heights all had an extensive inertial-convective subrange spanning at least two decades in frequency, but spectra measured near the ground had a greater proportion of the total concentration variance in the lower frequencies (energetic subrange), with a correspondingly smaller proportion in the higher frequencies (inertial-convective subrange). It is believed that these effects result from the increased mean shear near the surface, and blocking by the surface. The effect of enhanced shear-induced molecular diffusion on concentration fluctuations is examined.     

Recurrence statistics of concentration fluctuations in plumes within a near-neutral atmospheric surface layer

This study examines the statistical properties of the concentration derivative, , for a dispersing plume in a near-neutrally stratified atmospheric surface layer. Towards this goal, the probability density function (pdf) of , and the conditional pdf of given a fixed concentration level, , have been measured. These pdfs are found to be modeled well by a generalizedq-Gaussian (gqG) distribution with intermittency exponent,q, equal to 0.3 and 3/4, respectively. These results highlight the strong intermittency effect (patchiness) of the small-scale concentration eddy structures in the plume. The distribution of time intervals between successive high peaks in the squared derivative process, x², is found to be well approximated by a power-law distribution, implying that occurrences of these high peaks are much more clustered than would be predicted by a Poisson or shot-noise process. The results are used to improve models for the joint pdf of and , and for the expected number of upcrossings per unit time interval of a fixed concentration level that have been proposed by Kristensenet al. (1989). The predictions of the improved models are in accord with observations, and suggest that the intercorrelation between and must be explicitly incorporated if good estimates of the upcrossing intensity are to be obtained.     

Conditional concentration statistics for surface plumes in the atmospheric boundary layer

A set of concentration time series from ground-level plumes in the atmosphere has been used to generate conditionally sampled (zeros ignored) plume concentration statistics. These have been compared and contrasted with corresponding unconditionally sampled statistics. It is found that conditional statistics are much less sensitive to the location of the receptor (relative to the mean plume) and to averaging time. Indeed, most of the variation apparent in unconditionally sampled statistics (both explained and unexplained) resides in the intermittency, the fraction of non-zero readings.The data are used to test three commonly used models for the concentration frequency distribution. At the simplest level of modelling, it is assumed that conditional statistics are invariant; then the data are best represented by a clipped-normal distribution. However, an exponential distribution is only slightly conservative and has the advantage of simplicity. A log-normal distribution is clearly not supported by the data. With this simple approach the intermittency remains unspecified and this is a serious deficiency.More advanced modelling must account for the residual variation in conditional statistics, which implies a relationship between these statistics and the intermittency. Although there is evidence for such a relationship in the data, it is not adequately represented by any of the distribution models considered.     

Multiscaling properties of concentration fluctuations in dispersing plumes revealed using an orthonormal wavelet decomposition

The dynamical characteristics of concentration fluctuations in a dispersing plume over the energetic and inertial-convective range of scales of turbulent motion are studied using a multiscale analysis technique that is based on an orthonormal wavelet representation. It is shown that the Haar wavelet concentration spectrum is similar to the Fourier concentration spectrum in that both spectra exhibit an extensive inertial-convective subrange spanning about two decades in frequency, with a scaling exponent of -5/3. Analysis of the statistical properties (e.g., fluctuation intensity, skewness, and kurtosis) of the concentration wavelet coefficients (i.e., the concentration discrete detailed signal) suggests that the small scales are always more intermittent than the large scales. The degree of intermittency increases monotonically with decreasing scale within the inertial-convective subrange, reaching a plateau at the very small scales associated with the beginning of the near-dissipation subrange. The probability density function (pdf) of the concentration discrete detailed signal displays stretched exponential tails with an intermittency exponent (tail slope) q that increases as ^a , where is the scale or dilation and a is a power-law exponent that is dependent on downwind distance, plume height, and stratification strength with typical values in the range from about 0.25 to 0.35. It is shown that the concentration variance cascade process requires a phase coherency of eddies between different scales at the small-scale end of the inertial-convective subrange.The variation of the concentration wavelet statistics with height above the ground is investigated. The increased mean shear near the ground smooths the fine-scale plume structure for scales within the inertial-convective subrange, producing a weaker spatiotemporal intermittency in the concentration field compared to that measured higher up in the plume. The pdf of the concentration detailed signal at a fixed scale possesses less elongated tails with decreasing height z. The intermittency exponent q is found to decrease roughly linearly with increasing z.Finally, the results of the wavelet decomposition are combined to provide a conceptual model of the turbulent transport, stirring, and mixing regimes in a dispersing plume. The implications of the results for contaminant texture in a plume are discussed.     

Microscale temperature fluctuations in the atmospheric surface layer

Microscale temperature fluctuations were measured at 2 m above a grassy surface. The temperature-derivative spectrum was in general agreement with earlier results but the bump at nondimensional wavenumbers higher than 0.02 was not as pronounced as has been observed. The Obukhov-Corrsin constant for the one-dimensional temperature spectrum was evaluated to be 0.92 ± 0.05, consistent with recent results. The effects of instability and the vertical variation of temperature variance and kinetic energy dissipation are postulated to explain some of the difference with other spectra.     

Spatial coherence of temperature fluctuations in the atmospheric surface layer

Simultaneous temperature fluctuations have been measured along directions both parallel and orthogonal to the wind direction in the atmospheric surface layer. Ensemble-averaged temperature distributions associated with the ramp-like feature observed in instantaneous temperature traces indicate that the average duration of the ramp is approximately independent of height. Application of Davenport's geometric similarity of coherence of temperature fluctuations yields approximate estimates for the spatial extent of the structure characterized by the ramp. The longitudinal extent is approximately 12 times the vertical extent and 17 times the lateral extent.     

Precipitation effects on aerosol concentration in the atmospheric surface layer

The effects of wintertime and summertime precipitation on the mean (semiannual, seasonal, and monthly) concentration of aerosol particles of different sizes in the atmospheric surface layer are analyzed on the basis of the data of 15-year measurements of atmospheric aerosol in the town of Dolgoprudny (20 km from the center of Moscow). It is demonstrated that a statistically significant negative correlation between the aerosol particle concentration and the precipitation is observed for monthly mean values only and is absent for semiannual and seasonal means. The analysis of individual cases of precipitation corroborated the conclusion on their low impact on the aerosol concentration in the surface layer. In winter, the aerosol concentration decrease is observed within a narrow particle size interval of 0.03?C0.1 ??m and amounts to not more than 30% during several hours. A scavenging effect of summertime precipitation manifests itself in a wider size interval of 0.03?C1.0 ??m but does not exceed 10?C20% and is of short-term nature. The limited effects of precipitation on the surface aerosol are explained by the proximity to the underlying surface being a permanent aerosol source.     

On characteristics of wind direction fluctuations in the surface layer

It is shown that the ratio of standard deviation of lateral velocity to the friction velocity, /u _*, and therefore wind direction fluctuations, are sensitive to mesoscale terrain properties. Under neutral conditions, /u _* is almost 40% larger in rolling terrain than over a horizontal surface. In the lee of a low mountain, the fluctuations may be 2.5 times as strong as over horizontal terrain. In contrast, vertical velocity fluctuations are little influenced by mesoscale terrain features.Now with Air Weather Service, Offutt AFB, Omaha, Nebraska.     

The vertical profile of concentration fluctuations in near-surface plumes

Field experiments on concentration fluctuations have frequently measured horizontal cross-sections of fluctuation statistics through plumes at fixed heights near the surface, but have not considered the effect of height above the ground in any detail. A set of tracer experiments designed to measure vertical profiles of concentration fluctuations in plumes, with a range of source heights, is described, and profiles of statistics are presented. Considerable variation of the statistics with both source and detector height is found. Near the surface, fluctuation intensity is a minimum and the time and length scales of the fluctuations are greatly increased. Profiles are consistent with the idea that concentration fluctuations near the surface are like those higher up at a greater distance from the source. Lowering the source height reduces the fluctuation intensity at all heights, and also alters the form of the concentration PDF. Results may be explained by the reduced length scale of sheargenerated turbulence near the surface causing enhanced small-scale mixing, which rapidly smooths out much of the fine structure with the plume.     

Accuracy of moments of velocity and scalar fluctuations in the atmospheric surface layer

A detailed accuracy analysis is presented for moments, up to order four, of both velocity (horizontal u and vertical w) and scalar (temperature and humidity q) fluctuations, as well as of the products uw, w and wq, in the atmospheric surface layer. The high-order moments and integral time scales required for this analysis are evaluated from data obtained at a height of about 5 m above the ocean surface under stability conditions corresponding to Z/L \- –0.05. Measured moments and probability density functions of some of the individual fluctuations show departures from Gaussianity, but these are sufficiently small to enable good estimates to be obtained using Gaussian instead of measured moments. For the products, the assumption of joint Gaussianity for individual fluctuations provides a reasonable, though somewhat conservative, estimate for the integration times required. The concept of Reynolds number similarity implies that differences in integration time requirements for flows at different Reynolds numbers arise exclusively from differences in integral time scales. A first approximation to the integral time scales relevant to atmospheric flows is presented.     

Thermal plumes and turbulence spectra in the atmospheric boundary layer

Experimental observations on the temperature and wind fields above flat grassy terrain have been obtained with an instrumented 92-m tower during intervals of strong insolation about midday. The turbulence characteristics of the air confirm that free convection prevailed at heights between 16 and 48 m, with some tendency for departure at higher levels. The spectra of temperature and vertical velocity contain gaps at wave numbers in the range 0.01–0.025 m^–1. These are attributed to natural thermal plumes that act as sources of extra energy input to the Kolmogorov-Obukhov-Corrsin scheme of turbulence in or at the low-wave number limit of the inertial subrange. Modified forms of the K-O-C spectral laws for thermally unstable air are derived which agree with the observed spectra over the whole range of wave numbers examined, and which contain the spectral gap at wave numbers corresponding to the thermal plume diameters.     

The effects of source size on concentration fluctuations in plumes

The effects of source size on plume behaviour have been examined in a 1.2 m wind tunnel boundary layer for isokinetic sources with diameters from 3 to 35 mm at source heights of 230 mm and at ground level. Experimental measurements of mean concentration and the variance, intermittency and probability density functions of the concentration fluctuations were obtained. In addition, a fluctuating Gaussian plume model is presented which reproduces many of the observed features of the elevated emission. The mean plume width becomes independent of source size much more rapidly than the instantaneous plume width. Since it is the meandering of the instantaneous plume which generates most of the concentration fluctuations near the source, these are also dependent on source size. The flux of variance in the plume reaches a maximum, whose value is greatest for the smallest source size, close to the source and thereafter is monotonically decreasing. The intermittency factor reaches a minimum, whose value is lowest for the smallest source, and increases back towards one. Concentration fluctuations for the ground-level source are much less dependent on source size due to the effects of the surface.     

Review of some basic characteristics of the atmospheric surface layer

Some of the fundamental issues of surface layer meteorology are critically reviewed. For the von Karman constant (k), values covering the range from 0.32 to 0.65 have been reported. Most of the data are, however, found in a rather narrow range between 0.39 and 0.41. Plotting all available atmospheric data against the so-called roughness Reynolds number, % MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-yqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaaeOuaiaabw% gadaWgaaWcbaGaaeimaaqabaGccqGH9aqpcaWG1bWaaSbaaSqaaiaa% cQcaaeqaaOGaamOEamaaBaaaleaacaaIWaaabeaakiaac+cacqaH9o% GBaaa!3FD0!\[{\rm{Re}}_{\rm{0}} = u_* z_0 /\nu \] or against the surface Rossby number, % MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-yqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaaeOuaiaab+% gadaWgaaWcbaGaaeimaaqabaGccqGH9aqpcaWGhbGaai4laiaadAga% caWG6bWaaSbaaSqaaiaaicdaaeqaaaaa!3DF1!\[{\rm{Ro}}_{\rm{0}} = G/fz_0 \] gives no clear indication of systematic trend. It is concluded that k is indeed constant in atmospheric surface-layer flow and that its value is the same as that found for laboratory flows, i.e. about 0.40.Various published formulae for non-dimensional wind and temperature profiles, _m and _h respectively, are compared after adjusting the fluxes so as to give % MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-yqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaam4Aaiabg2% da9iaaicdacaGGUaGaaGinaiaaicdaaaa!3AC6!\[k = 0.40\] and % MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-yqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaWaaeWabeaaii% GacqWFgpGzdaWgaaWcbaGaamiAaaqabaGccaGGVaGae8NXdy2aaSba% aSqaaiaad2gaaeqaaaGccaGLOaGaayzkaaWaaSbaaSqaaiaadQhaca% GGVaGaamitaiabg2da9iaaicdaaeqaaOGaeyypa0JaaGimaiaac6ca% caaI5aGaaGynaaaa!4655!\[\left( {\phi _h /\phi _m } \right)_{z/L = 0} = 0.95\]. It is found that for % MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-yqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaWaaqWabeaaca% WG6bGaai4laiaadYeaaiaawEa7caGLiWoacqGHKjYOcaaIWaGaaiOl% aiaaiwdaaaa!3F72!\[\left| {z/L} \right| \le 0.5\] the various formulae agree to within 10–20%. For unstable stratification the various formulations for _h continue to agree within this degree of accuracy up to at least % MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-yqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaamOEaiaac+% cacaWGmbGaeyisISRaeyOeI0IaaGOmaaaa!3BC9!\[z/L \approx - 2\]. For _m in very unstable conditions results are still conflicting. Several recent data sets agree that for unstable stratification % MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-yqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaaeOuaiaabM% gacqGHijYUcaaIXaGaaiOlaiaaiwdacaWG6bGaai4laiaadYeaaaa!3E0D!\[{\rm{Ri}} \approx 1.5z/L\] up to at least % MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-yqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaeyOeI0Iaam% OEaiaac+cacaWGmbGaeyypa0JaaGimaiaac6cacaaI1aaaaa!3C8D!\[ - z/L = 0.5\] and possibly well beyond.For the Kolmogorov streamwise inertial subrange constant, _u , it is concluded from an extensive data set that % MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-yqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaeqySde2aaS% baaSqaaiaadwhaaeqaaOGaeyypa0JaaGimaiaac6cacaaI1aGaaGOm% aiabgglaXkaaicdacaGGUaGaaGimaiaaikdaaaa!4178!\[\alpha _u = 0.52 \pm 0.02\]. The corresponding constant for temperature is much more uncertain, its most probable value being, however, about 0.80, which is also the most likely value for the corresponding constant for humidity.The turbulence kinetic energy budget is reviewed. It is concluded that different data sets give conflicting results in important respects, particularly so in neutral conditions.It is demonstrated that the inertial-subrange method can give quite accurate estimates of the fluxes of momentum, sensible heat and water vapour from high frequency measurements of wind, temperature and specific humidity alone, provided apparent values of the corresponding Kolmogorov constants are used. For temperature and humidity, the corresponding values turn out to be equal to the true constants, so % MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-yqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaeqOSdi2aaS% baaSqaaiaadgeaaeqaaOGaeyisISRaeqOSdiMaeyisISRaaGimaiaa% c6cacaaI4aGaaGimaaaa!4074!\[\beta _A \approx \beta \approx 0.80\]. For momentum, however, the apparent constant % MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-yqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaeqySde2aaS% baaSqaaiaadwhacaWGbbaabeaakiabgIKi7kaaicdacaGGUaGaaGOn% aiaaicdaaaa!3E18!\[\alpha _{uA} \approx 0.60\].Based on an invited paper presented at the EGS Workshop Instrumental and Methodical Problems of Land Surface Flux Measurements, Grenoble 22–26 April, 1994.     

The horizontal distribution of space correlation coefficients of wind fluctuations in the atmospheric surface layer

The horizontal distribution of space correlation coefficients of wind fluctuations was investigated in the atmospheric surface layer. The observational network of wind sensors was arranged to form a two-dimensional extension in the horizontal plane. The shape of the distribution of the correlation coefficients was approximated by a group of concentric ellipses; streamwise and lateral integral scales were estimated as 75 m and 25 m, respectively. Taylor's frozen eddy hypothesis was tested using streamwise and time integral scales.     

Characterization of concentration fluctuations of a surface plume in a neutral boundary layer

We describe a new high-resolution sampling technique which can be used to measure concentration fluctuations simultaneously at several points in space. The technique has been used to measure the probability distribution function as a function of the detector location relative to a continuous and steady source. Results are compared to previous experiments and theoretical predictions. The spectra of the concentration fluctuations are analyzed and their behaviour as a function of downwind distance from the source is described.     

The exponential probability density function and concentration fluctuations in smoke plumes

Observations of 1-s average concentration fluctuations during two trials of a U.S. Army diffusion experiment are presented and compared with model predictions based on an exponential probability density function (pdf). The source is near the surface and concentration monitors are on lines about 30 to 100 m downwind of the source. The observed ratio of the standard deviation to the mean of the concentration fluctuations is about 1.3 on the mean plume axis and 4 to 5 on the mean plume edges. Plume intermittency (fraction of non-zero readings) is about 50%; on the mean plume axis and 10%; on the mean plume edges. A meandering plume model is combined with an exponential pdf assumption to produce predictions of the intermittency and the standard deviation of the concentration fluctuations that are within 20%; of the observations.