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Atmospheric Environment 39 (2005) 4999–5012

www.elsevier.com/locate/atmosenv

A field experiment on turbulent concentration fluctuationsof an atmospheric tracer gas in the vicinity of a

complex-shaped building

J.M. Santosa,�, R.F. Griffithsb, I.D. Robertsc, N.C. Reis Jr.a

aDepartamento de Engenharia Ambiental, UFES, Av. Fernando Ferrari s/n, 29.060-970 Vitoria, ES, BrazilbEnvironmental Technology Centre, School of Chemical Engineering and Analytical Science, The University of Manchester, UK

cDefence Science & Technology Laboratories, Porton, UK

Received 10 November 2004; received in revised form 28 April 2005; accepted 11 May 2005

Abstract

This work investigates the turbulent flow and dispersion of atmospheric contaminants in the vicinity of an isolated

building. Field experiments were carried out to measure the fluctuating concentration time-series on the walls of a

complex-shaped building, and to investigate the influence of atmospheric stability and building dimensions on certain

statistics of the concentration distribution on the walls of the building. Meteorological conditions varied from neutral to

unstable. The measurements were conducted for two different wind directions (west and south, corresponding

respectively to directions normal and parallel to the long axis of the building). The experiments were performed in flat

terrain with uncut vegetation. The gas detectors used were photo ionisation detectors (PIDs) with a response time of

approximately 1/50 s. Sixteen such detectors were deployed, with 14 located on the building walls, and 2 on the roof.

The analysis presented here is for the 14 detectors on the walls. Statistical parameters of the concentration time-series

and the wind flow are presented, including mean and standard deviation. Intermittency and concentration fluctuation

intensity are also presented. Results were analysed based on the turbulent structures of the fluid flow around the

building. The experimental work revealed that the atmospheric stability conditions significantly influenced the

concentration levels on the external walls of the building, except on the windward wall. It was also revealed that mean

conditional concentration values on the walls were significantly influenced by the ratio between building width and

height.

r 2005 Published by Elsevier Ltd.

Keywords: Field experiments; Building effects; Concentration fluctuation; Stability conditions

1. Introduction

The presence of a building profoundly alters the

atmospheric turbulent flow structure in a region of the

flow, which depends on the building dimensions. The

e front matter r 2005 Published by Elsevier Ltd.

mosenv.2005.05.005

ing author. Fax: +5527 3335 2648.

ess: janemeri@npd.ufes.br (J.M. Santos).

building not only disturbs the mean wind field, but also

increases the local turbulence by generating a large

amount of shear stress in the flow. These effects

considerably modify the local pattern of pollutant

dispersion. The wind flow approaching the building

depends on the atmospheric conditions, since the

velocity and temperature profiles and turbulent proper-

ties are determined by the prevailing stability conditions.

ARTICLE IN PRESSJ.M. Santos et al. / Atmospheric Environment 39 (2005) 4999–50125000

The atmospheric stability conditions can assist or

suppress the vertical turbulent transport according to

the density stratification (buoyancy forces). These

atmospheric conditions can vary from a strongly

unstable atmosphere with a deep mixed boundary layer

that promotes the contaminant spreading, to a stably

stratified boundary layer that damps the vertical mixing

of contaminants. Thus, in order to understand the

atmospheric flow and dispersion around a building, it is

necessary to include the effects of atmospheric stability.

There is a considerable amount of work in the

literature about field and wind tunnel experiments on

atmospheric flow and dispersion around single buildings

(for example, Ogawa et al. (1983a, b); Jones and

Griffiths (1984); Higson et al. (1994); Saathoff et al.

(1995) and Higson et al. (1996)) and more recently

researchers have investigated dispersion over building

arrays and urban areas (for example, Macdonald et al.

(1997); Mavroidis and Griffiths (2001); Allwine et al.

(2002); Yee and Biltof (2004)). There has been great

interest in numerical simulations of both configurations

(for example, Zhang et al. (1996); Meroney et al. (1999);

Sada and Sato (2002); Cheng et al. (2003)) due to

advances in turbulence models, numerical tools and

high-performance computers. However, comparatively

little work has been concerned with investigations under

different stability conditions and complex-shaped build-

ings. In fact, there is little field experimental work, no

wind tunnel experiments and no numerical simulations

of the atmospheric flow under unstable stratification

with an obstacle present. In the case of wind tunnel

investigations, it is only recently that wind tunnel

facilities that are capable of simulating the unstable

atmosphere have been built. Thus, the majority of

studies investigating the effects of atmospheric stratifi-

cation on the flow and dispersion around a building are

concerned with near-neutral stratified conditions. Only

very recently, a few works studying unstable conditions

in the atmosphere have been reported in the literature,

such as Mavroidis et al. (1999, 2003), but these are

mainly focussed on dispersion around cubic-shaped

buildings. The ratio between building width and height

can strongly influence the fluid flow and dispersion

patterns, since a wider obstacle can cause the contami-

nants to be more dispersed. The concentration levels

seen on the walls of the building can thus be strongly

affected by the building dimensions.

This work extends the previous studies, by investigat-

ing the turbulent flow and dispersion of atmospheric

contaminants in the vicinity of an isolated complex-

shaped building, in neutral and unstable atmospheric

conditions. Field experiments were carried out to

measure the concentration fluctuations on the walls of

a complex-shaped building, and to analyse the influence

of atmospheric stability and building dimensions on the

mean and fluctuation intensity of concentrations on the

walls of the building. The results also reveal the

progressive reduction of the fluctuation intensity as the

measurement location progresses from windward to

leeward locations in the flow paths around the building.

2. Experimental details

Field experiments were conducted at Dugway Proving

Ground, 85 miles south west of Salt Lake City in Utah,

USA. The experiments were conducted during August

1998 at different times of the day in order to collect data

for distinctly different stability conditions. This region

reliably experiences unstable atmospheric conditions

during daytime.

The experiments involved placing a source of propy-

lene gas at a fixed distance from the building and using

gas detectors (photo ionisation detectors—PIDs) to

measure concentration time-series close to the walls

and on the roof of the building. Fig. 1 presents a view of

the building used in the trials and shows a schematic

representation of the site, indicating the location of the

gas source and the PIDs. The xyz co-ordinate system is

specified here, respectively, as the along wind direction,

the lateral and vertical directions. The source was

located upwind at a distance of about 3.5 building

heights (x ¼ 3:5Hb) from the face of the building, at a

height of 0.5Hb. The source released propylene gas

through an open-ended pipe of about 1 cm diameter

with a flow rate of 50 lmin�1.

The terrain where the experiments were conducted is

flat for many kilometres to the west and south of the

building, with some hills at about 1–2 km to the east and

north. In order to avoid the influence of these hills on

the wind profile, the experiments were conducted only

when the wind was blowing from the west or the south,

to guarantee that the wind profile was similar to a

boundary layer flow. The vegetation is low patchy grass

(maximum height 15 cm) and the terrain roughness is

about 10mm calculated from the velocity profile in

neutral stability.

2.1. Gas monitoring and method of analysis

Concentration measurements were made by sampling

using a number of digital fast-response PIDs. This

instrument has a response time corresponding to about

50Hz. It continuously samples the ambient air at a flow

rate of 1 lmin�1 and this air stream is exposed to a high-

energy ultra-violet light, which ionises molecules having

ionisation energy levels at or below the lamp photon

energy. The gas tracer is selected to be such that it will be

detected. The release rate of the tracer gas is set to

ensure that the signal due to tracer gas is far in excess of

any ionisable species that may be present as a back-

ground. The gaseous constituents of air are not ionisable

ARTICLE IN PRESS

4.55

1.85

5.80

4.55

2.75

3.40

5.20

1.45

2.80

2.55

3.05

1.55

2.25 3.55

0.85

9.10

2.906.10

0.850.851.60

3.103.002.90

2.5510.45

7.25

Sonic anemometer (3 vertical positions)

Source

PID

PID (2 or 3 vertical positions)

South wind

direction

West wind

direction

12

31a

10

13

14

1211

14

9

8

7

13

455a

5b6

N

E

W

SN

E

W

S

(a) (c)

(d)

(b)

(e)

Fig. 1. (a) Schematic representation of the site, (b) photograph of the building used in the experiments at Dugway Proving Ground

(view looking from SSW), (c) top, west and south views (clockwise) of the building and detector locations on the building surfaces, (d)

a schematic representation of the detector locations and numbering on the building surfaces—perspective view looking from SE—and

(e) perspective view looking from NW.

J.M. Santos et al. / Atmospheric Environment 39 (2005) 4999–5012 5001

at the photon energy level used. The instrument

response is such that at low concentrations (in the range

up to approximately 800 ppm) the output signal is nearly

linearly proportional to the concentration of the

contaminant gas, and the tracer gas release rate is

chosen to ensure that the instrument is operating in this

range. The ions formed are collected on an electrode

system providing an electrical field, producing an ion

current that is a measure of tracer gas concentration.

The ion current is amplified and converted to a voltage

signal whose value is close to proportional to the gas

concentration. The instruments are calibrated regularly

during the field campaign by exposure to metered

concentrations of tracer gas in the ambient air, thereby

providing calibration data to convert the output voltage

to equivalent gas concentration. This procedure ensures

that any non-linearity in instrument response is properly

allowed for in the data acquisition.

By applying a baseline correction (in which the slowly

varying baseline signal was removed from the data) and

the calibration curves of the instruments (using the

calibration measurements conducted during the trials as

described above), the voltage signals recorded by the

acquisition system were converted to concentration

values (ppm). This data conversion produced time series

of concentration, to which an averaging time of 1 s was

then applied in order to reduce the file sizes. Further-

more, the basic 50Hz data were not required for this

study, since the investigation is concerned with processes

that can adequately be analysed using longer averaging

times (1 s or more). For the purposes of this study, the

1 s-averaged data contain sufficient information about

fluctuations of concentration due to turbulent eddies.

Thus, the mean concentration, the deviation of the

measured values in relation to the mean and other

statistical parameters were calculated using the 1 s-

averaged data.

In order to obtain information about turbulent

fluctuations from the data, it is important to analyse

concentration fluctuation values in relation to the levels

ARTICLE IN PRESSJ.M. Santos et al. / Atmospheric Environment 39 (2005) 4999–50125002

of the mean concentration, since a certain absolute value

of fluctuation can represent a relatively large fluctuation

if the mean value is low or a relatively small fluctuation

if the mean is high. Thus, concentration fluctuation

intensity, i, is presented as the ratio of the standard

deviation to the mean concentration.

A detector will experience periods of zero concentra-

tion due to pockets of clean air brought into the plume

by the small-scale atmospheric turbulence and due to the

large-scales of turbulence that will cause the plume to

meander. The term intermittency is used to describe this

characteristic of the concentration time series. Although

this characteristic appears, at first, as a simple idea, the

literature contains several definitions of intermittency.

Chatwin and Sullivan (1989) discussed this topic and

proposed a definition that was suitable for both

theoretical and practical applications. Here, for consis-

tency with other field work in which intermittency has

been measured (for example, Higson et al., 1994;

Mavroidis and Griffiths, 2001), the definition adopted

is that the intermittency is the proportion of the

concentration time series for which the concentration

is at or below a threshold value, which in this case is the

nominal zero concentration. Complete statistics are

calculated using the whole data record (including zero

concentrations), whilst conditional statistics refer only

to those portions greater than a threshold (i.e., excluding

zero concentrations).

Another important parameter is the cumulative

frequency, which represents the cumulative distribution

function (cdf) of a concentration time series. As

illustrated in Figs. 4–6, the cdf gives the proportion of

concentration readings which are below a given con-

centration (expressed as the ratio between the instanta-

neous and mean concentration values), and provides the

following information: (a) the concentration fluctuation

intensity which is indicated by the slope of the central

part of the curve (the lower the intensity the steeper the

gradient); (b) intermittency, which is indicated by the

intercept on the vertical axis; and (c) the ratio between

peak and mean obtained from the value where the cdf

reaches 1.

2.2. Meteorological instrumentation and method of

analysis

Meteorological data were acquired using three ultra-

sonic anemometers located in a vertical array (z ¼ 0:44,0.88 and 1.76Hb) at a distance of 30m west of the

building (Fig. 1a). These instruments provided three

orthogonal components of the velocity vector of the

wind and the speed of sound in air at a frequency of

20Hz. Since the speed of sound is related to the air

temperature, temperature at these locations can be

deduced from the measurement. The ultrasonic anem-

ometer measurements were complemented by measure-

ments of ambient pressure, humidity and temperature

provided by a meteorological station located within

500m of the building.

2.3. Averaging time

The averaging time was chosen based on the time

scale of turbulence in the near-wake of the obstacle,

which is of the order of Hb/Ub (where Ub is the wind

speed at one building height). This time scale is about 1 s

for these experiments, since the wind speed is higher

than 2.5m s�1. Mavroidis et al. (2003) pointed out that a

minimum averaging time is required to obtain stable

repeatable data, due to the randomness of the turbulent

fluctuations. However, it is important to note that as the

averaging time increases the variations of mean wind

speed and direction start to affect the measurements

more intensely. In fact, the authors point out that eddy

scales beyond about 10–20 times the obstacle size are not

distinguishable as turbulence related to the obstacle, but

as variations in mean wind speed and direction. In this

sense, it is desirable to consider an averaging time long

enough to be representative of the process, but avoiding

large variations of the mean wind speed and direction.

According to these authors, this can be achieved by

using an averaging time of the order of hundreds of Hb/

Ub. Thus, in this work, the time series of 1 s-averaged

data are averaged over a number of periods of 5min.

Over the whole period of the campaign, seven basic

episodes of 5min were selected for analysis and were

chosen from episodes when the mean wind direction

(averaged over the 5min period) was normal to the

building wall within 7101 and the wind speed was

greater than 2m s�1. Table 1 shows the meteorological

data averaged over the 5min period for the chosen

scenarios, except the coefficient of variation, which was

calculated as the ratio between standard deviation and

mean of the ten 30-s values of Richardson-flux number

(Rif ) in order to enable the examination of its variability

during the 5min periods.

3. Results and discussion

This section presents the results obtained from the

selected episodes. The analysis is carried out in two sub-

sections that describe, firstly, the influence on concen-

trations of the building dimensions, and then the

influence of atmospheric stability.

3.1. Concentration distribution and the influence of

building dimensions

As stated earlier, experiments were carried out for

wind impinging on the longer wall of the building (west

wind direction) and wind impinging on the shorter wall

ARTICLE IN PRESS

Table 1

Chosen scenarios and their meteorological parameters

Exp. Windward wall /

stability

Speed

(m s�1)

y (1) sy L (m) u�(m s�1)

Rif CVbT (1C) TKEa

(m2/s2)

1 Short wall/neutral 6.15 180.7 8.30 �50.84 0.57 �5.90� 10�2 �9.42 41.25 1.38

2 Short wall/neutral 5.31 182.4 12.33 �54.14 0.54 �5.54� 10�2 �1.72 41.54 1.53

3 Long wall/neutral 4.61 267.1 14.53 �24.87 0.47 �1.21� 10�1 �6.93 42.90 1.41

4 Long wall/neutral 2.79 261.4 17.42 �43.69 0.54 �6.87� 10�2 �1.95 42.10 1.43

5 Long wall/extremely

unstable

2.48 265.1 21.38 �0.98 0.15 �3.07� 10+0�1.51 40.36 1.28

6 Long wall/slightly

unstable

2.86 264.43 16.78 �14.31 0.33 �2.09� 10�1 �5.88 42.03 1.16

aTKE represents the turbulent kinetic energy of the incident flow.bCV represents the coefficient of variation (calculated as the ratio between standard deviation and mean) of the 10 30-s values of Rif

during the 5min-period selected for analysis.

J.M. Santos et al. / Atmospheric Environment 39 (2005) 4999–5012 5003

of the building (south wind direction). In the first

configuration, the ratio between the building width and

height (Wbwest/Hb) is 5.35 and in the second configura-

tion this ratio (Wbsouth/Hb) is 1.34, where Wb

west and

Wbsouth denote the length of the west and south walls of

the building, respectively.

Fig. 2 presents the normalised mean concentration on

the building walls, which is expressed as o� ¼

CUbH2b=Q � 106 (where C is the concentration in

ppm, Ub is wind speed at the building height, Hb is the

building height and Q is the volumetric flow rate emitted

from the source). Fig. 2a and b present the concentra-

tion distribution on the building walls for the west wind

direction (Exp. 3 and 4, neutral stability) and for the

south wind direction (Exp. 1 and 2, neutral stability),

respectively. The corresponding results for unstable

conditions are presented in Fig. 2c, and are discussed

in Section 3.2.

The source is located such that the plume dimension

reaching the obstacle is less than or comparable to the

building width. There is a clear indication from the

experimental data that, in general, the means are higher

for the plume reaching the shorter windward wall

(Figs. 2a and b). The region of the flow disturbed by

the building is smaller when the flow is impinging on the

shorter wall, thus the plume is less spread and higher

concentration values occur. Given this behaviour on the

windward wall, these higher concentrations would be

expected to persist in the subsequent passage around the

building, and this is shown in Fig. 2, where the

concentrations on the leeward and lateral walls are in

general greater in the south wind configuration than in

the west wind configuration.

In all cases the maximum value of concentration is

seen on the windward wall. Fig. 2a shows that when the

wind direction is within a few degrees of normal to the

building wall this maximum is seen on the central

detector on the windward wall and that the mean

concentration decreases steadily with lateral distance

from this central position. However, in the case of Exp.

4 the maximum concentration on the windward wall is

displaced from the central to the neighbouring detector.

This is consistent with the wind direction in this case,

which (at 261.41) is close to the 101 limit of the selection

criterion. In Fig. 2b the maximum is on the windward

wall, but as only one detector is located on this wall, the

lateral behaviour is not apparent.

The mean values of concentration on the leeward wall

are nearly uniform and comparable to the minimum

values measured on the windward wall. It is interesting

to note that although the concentration values on the

leeward wall are nearly uniform, concentration values

for detectors 8 and 9 (in Fig. 2a) are noticeably different,

since they are just beside the step-shaped structure on

this wall.

It can be seen in Fig. 2a that the mean concentrations

on the left lateral walls are also lower than the windward

wall maximum, and nearly constant. This may be related

to the turbulent structures on these walls. These lateral

and leeward walls are characterised by a boundary layer

separation, producing recirculation zones where there

are high levels of turbulent kinetic energy, but with a

relatively small length scale, since these zones are mainly

generated by mechanical forces. In Fig. 2b the concen-

trations on the right lateral wall are less than the value

on the windward wall, but are not uniform. In spite of

the fact that these regions are fairly well mixed, there is

considerable complexity on the longer walls given their

stepped shape.

The turbulence characteristics can be observed in

more detail in Figs. 3–5, which show concentration

fluctuation intensity (Fig. 3) and the cdf’s on the

building (Figs. 4 and 5). Figs. 3a and b show that the

concentration fluctuation intensity is nearly uniform on

each of the building walls, except for detectors 11 and 12

on the windward wall and for the detector 9 on the

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0 0.5 10.00

0.20

0.40

0.60

0.80

1.00

ω*

(con

ditio

nal -

5 m

in a

vera

ging

)

11 12

12

3

0 0.5 1

4 56

0 0.5 1

10

0 0.5 1

7 89

Exp. 3Exp. 4

windward wall left lateral wall right lateral wallleeward wall

windward wall left lateral wall right lateral wallleeward wall

windward wall left lateral wall right lateral wallleeward wall

0 0.5 10.00

0.20

0.40

0.60

0.80

1.00

ω *(c

ondi

tiona

l - 5

min

ave

ragi

ng)

10

Exp. 2Exp. 1

0 0.5 1

1112

1 23

0 0.5 1

7

8

9

0 0.5 1

4 5 6

South wind direction

West winddirection

0 0.5 1

d/Lwest

0.00

0.20

0.40

0.60

0.80

1.00

ω*

(con

ditio

nal -

5m

in a

vera

ging

)

11 12

1

23

Exp. 6Exp. 5

0 0.5 1

d/Lnorth

4 5 6

0 0.5 1

d/Lsouth

10

0 0.5 1

d/Least

d/Lwest d/Lnorthd/Lsouth d/Least

d/Lwest d/Lnorth d/Lsouthd/Least

7 89

West winddirection

(a)

(b)

(c)

Fig. 2. Conditional normalised mean concentration in (a) neutral conditions for source located upwind of the centre of the long face of

the building (W Exp. 3, J Exp. 4), (b) neutral conditions for source located upwind of the centre of the short face of the building (WExp. 2,J Exp. 1), (c) unstable conditions for source located upwind of the centre of the long face of the building (J Exp. 5,W Exp. 6).

J.M. Santos et al. / Atmospheric Environment 39 (2005) 4999–50125004

ARTICLE IN PRESS

(a)

(b)

(c)

0 0.5 1

d/Lwest

0.0

1.0

2.0

3.0i

(con

dito

nal-

5 m

in a

vera

ging

)11

12

12 3

0 0.5 1

d/Lnorth

4 5 6

0 0.5 1

d/Lsouth

10

0 0.5 1

d/Least

d/Lwest d/Lnorthd/Lsouth d/Least

d/Lwest d/Lnorth d/Lsouthd/Least

7 8

9

windward wall left lateral wall right lateral wallleeward wall

windward wall left lateral wall right lateral wallleeward wall

windward wall left lateral wall right lateral wallleeward wall

0 0.5 10.0

1.0

2.0

3.0

i(c

ondi

tona

l-5

min

ave

ragi

ng)

10

0 0.5 1

11 121 2 3

0 0.5 1

4 5 6

0 0.5 1

78

9

South wind direction

West winddirection

0 0.5 10.0

1.0

2.0

3.0

i(c

ondi

tiona

l-5

min

ave

ragi

ng)

11

12

12 3

0 0.5 1

4 5 6

0 0.5 1

10

0 0.5 1

7 8

9

West winddirection

Fig. 3. Conditional concentration fluctuation intensity in (a) neutral conditions for source located upwind of the centre of the long face

of the building (W Exp. 3, J Exp. 4), (b) neutral conditions for source located upwind of the centre of the short face of the building

(W Exp. 2, J Exp. 1), (c) unstable conditions for source located upwind of the centre of the long face of the building (J Exp. 5, WExp. 6). & Higson et al. (1996) with plume width comparable to L, ’ Higson et al. (1996) with plume width less than L.

J.M. Santos et al. / Atmospheric Environment 39 (2005) 4999–5012 5005

ARTICLE IN PRESS

0 2 4 6 8 10

0

0.2

0.4

0.6

0.8

1

0 1 2 3 4 5

0

20

40

60

80

0 1 2 3 4 5t (mins)

0

20

40

60

80C

(pp

m)

0 2 4 6 8 10C/Cmean

t (mins) C/Cmean

0 2 4 6 8 100 1 2 3 4 5t (mins) C/Cmean

t (mins) C/Cmean

t (mins) C/Cmean

0

0.2

0.4

0.6

0.8

1

Con

ditio

nal c

df

C (

ppm

)

Con

ditio

nal c

df

C (

ppm

)

Con

ditio

nal c

df

C (

ppm

)

Con

ditio

nal c

df

C (

ppm

)

Con

ditio

nal c

df

0

0.2

0.4

0.6

0.8

1

0

20

40

60

80

0 2 4 6 8 100

0.2

0.4

0.6

0.8

1

0 1 2 3 4 50

20

40

60

80

0 2 4 6 8 100

0.2

0.4

0.6

0.8

1

0 1 2 3 4 50

20

40

60

80

West winddirectio n

1

53

10

8

(a)

(b)

(c)

(d)

(e)

Fig. 4. Time series and conditional cdf’s in neutral conditions for source located upwind of the centre of the long face of the building.J Higson et al. (1996), — Exp. 3 and - - - - Exp. 4: (a) sensor 1, (b) sensor 3, (c) sensor 5, (d) sensor 8 and (e) sensor 10.

J.M. Santos et al. / Atmospheric Environment 39 (2005) 4999–50125006

ARTICLE IN PRESS

0 2 4 6 8 10C/ Cmean

0

0.2

0.4

0.6

0.8

1

0

0.2

0.4

0.6

0.8

1

0

0.2

0.4

0.6

0.8

1

0

0.2

0.4

0.6

0.8

1

Con

ditio

nal c

df

0 2 4 6 8 100 1 2 3 4 5

0

20

40

60

80

0 1 2 3 4 5t (mins)

C/ Cmeant (mins)

C/ Cmeant (mins)

C/ Cmeant (mins)

0

20

40

60

80

C (

ppm

)

Con

ditio

nal c

df

C (

ppm

)

Con

ditio

nal c

df

C (

ppm

)

Con

ditio

nal c

df

C (

ppm

)

0 2 4 6 8 100 1 2 3 4 5

0

20

40

60

80

0 2 4 6 8 100 1 2 3 4 5

0

20

40

60

80

South wind direction

1

810 5

(a)

(b)

(c)

(d)

Fig. 5. Time series and conditional cdf’s in neutral conditions for source located upwind of the centre of the short face of the building.J Higson et al. (1996), — Exp. 1 and - - - - Exp. 2: (a) sensor 10, (b) sensor 1, (c) sensor 5 and (d) sensor 8.

J.M. Santos et al. / Atmospheric Environment 39 (2005) 4999–5012 5007

leeward wall for the west wind configuration due to the

complex and asymmetric shape of the building. These

Figures also indicate that the distributions of concentra-

tion fluctuation on the windward, leeward and lateral

walls display a very similar pattern for the two building/

source orientations in relation to the wind direction,

ARTICLE IN PRESSJ.M. Santos et al. / Atmospheric Environment 39 (2005) 4999–50125008

with larger values on the windward wall, smaller values

on the leeward wall, and intermediate values on the

lateral walls. This is consistent with the progressive

reduction of intermittency by the action of the shear and

small-scale turbulence generated by the interaction of

building with the flow. On the windward wall the mean

intermittency (average value between all sensors on the

windward wall) is 0.05 for Exp. 1 and 2, and 0.05 for

Exp. 3 and 4, while for the leeward walls mean

intermittency is zero for all experiments. This can also

be understood in terms of large values of fluctuation

intensity being related to the large-scale upstream

turbulent motion, and small values being associated

with the small-scale local turbulent motion. Further-

more, the concentration in the recirculation region

behind the building will display a significant decay time

(Mavroidis et al., 1999), since the contaminants are

partially ‘‘trapped’’ in this region. This behaviour tends

to buffer the intense concentration fluctuations.

In order to evaluate the influence of the building

shape, the results presented here are compared with field

experimental data obtained by Higson et al. (1996). Both

experimental investigations used complex-shaped, but

not identical, buildings. Therefore, a comparison be-

tween these two sets of data can indicate the influence of

changes in building shape on the distribution of

concentration and related statistics on the obstacle

walls. Higson et al. (1996) carried out experimental

investigations at Altcar Rifle Range (England) on

dispersion around an isolated rectangular obstacle with

an L-shaped ‘‘penthouse’’ added on the roof. The

building dimensions are similar to those of the building

used in the work presented here. A tracer gas was

released upwind of the building (x ¼ 4:07 and 12.20Hb)

and concentrations were measured using a PID detector

system with response time of approximately 1 s. The

experiments were undertaken under near neutral atmo-

spheric stability conditions paying attention to the

fluctuating components of concentration for the purpose

of comparing the concentration distribution measured in

the field with those measured in experiments conducted

in a wind tunnel. Higson et al. (1996) have used

conditional statistics to enable comparison between field

and wind tunnel data and avoid evaluating two sets of

data with different intermittency, which would be

meaningless. Thus, conditional average and fluctuations

were used in the present work to allow for the

comparison with the field experiments carried out by

Higson et al. Moreover, the data for this analysis were

previously chosen from the whole experiment for which

the intermittency was low.

There is a similarity between the results obtained in the

field experiments carried out by Higson et al. (1996) and

those reported here, which can be seen in Figs. 3a and b.

The fluctuation intensity values obtained in this work are

higher than those obtained by Higson et al. (1996), except

on the leeward wall where the values are comparable. In

fact, there are more similarities in the case with the wind

impinging on the shorter wall; the levels of fluctuation

intensities are quite similar in this case.

Figs. 4 and 5 present the progression of the cdf shapes

around the building using two different runs (Exp. 3 and

4 in Fig. 4 and Exp. 1 and 2 in Fig. 5) to illustrate the

representativeness of the sample selected.

Fig. 4b presents the cdf for the sensor at the left

corner of the windward wall for the present experiments

and for the experiments performed by Higson et al.

(1996). It can be seen that the shapes of the cdf’s are

remarkably similar. The same tendency can be observed

in Figs. 5a and c, which also present a comparison

between the cdf0s for the present experiments and for the

experiments performed by Higson et al. (1996). This fact

may indicate that the differences in the building shape

between these two configurations do not significantly

affect the cumulative distribution frequency of concen-

tration fluctuations on the building walls.

It is clear from the time series and the shapes of the

cdf’s presented in Figs. 4 and 5 that there is significantly

more fluctuation intensity on the windward wall than on

the leeward wall. The progressive steepening of the slope

of the central portion of the cdf0s indicates a gradual

reduction of the fluctuation intensity as the measure-

ment location progresses from windward to leeward via

the lateral wall, i.e. via the two sensor sequences 1, 3, 5, 8

and 1, 10, 8. Furthermore, on the leeward wall, the

values of concentration peak divided by the mean are

lower due to lower velocities and high levels of turbulent

kinetic energy in the region downwind of the obstacle (in

comparison with the free upstream flow). As discussed

previously, these features may indicate a considerable

variation in the turbulence length scale, due to shear

generated turbulence.

The cdf’s obtained for the two different building

orientations (Figs. 4 and 5) analysed are quite similar

despite the fact that the mean concentration is higher for

the case where the shorter wall is normal to the wind.

The time series presented shows clearly that the

turbulence scales on the windward and leeward walls

do not vary according to the ratio between building

width and height, which implies that the concentration

fluctuation intensity on the building walls is more

influenced by the building height than by the width for

the configurations studied. Thus, it is suggested that the

building height is the characteristic dimension determin-

ing the dominant size of the scales of turbulent eddies

close to the obstacle. Despite the values of concentration

fluctuation intensity presented by Higson et al. being,

for all detectors, lower than those reported here, the

shapes of the cdf’s shown in Figs. 4 and 5 are similar for

both field experiments. This can be understood to mean

that the characteristic behaviour of dispersion on the

different walls of the obstacle was not strongly

ARTICLE IN PRESSJ.M. Santos et al. / Atmospheric Environment 39 (2005) 4999–5012 5009

influenced by the slightly different building shape in the

two experiments.

3.2. Atmospheric stability

According to Robins (1994), in strongly convective

conditions, the high levels of atmospheric turbulence

significantly modify the flow and dispersion features

generated in the vicinity of an obstacle. Moreover, in

strongly stable conditions (Frp2:5), the reattachment ofthe flow on the top and lateral sides of the building is

enhanced and that dramatically changes the concentra-

tion field (Snyder, 1994). Thus, it seems that there is a

range of atmospheric conditions, centred upon neutral

conditions, outside of which the vertical structure of

temperature significantly affects the dispersion of con-

taminants in the vicinity of the obstacle.

In this section the concentration measurements

obtained under unstable atmospheric conditions are

presented, which correspond to Exp.5 and 6 described in

Table 1. Exp.5 is characterised by a very small negative

Monin–Obukhov length (�0.98), which corresponds to

an extremely unstable condition on a Pasquill–Gilford

classification scheme, while Exp. 6 has a Monin–Obu-

khov length equal to �14.31, which corresponds to a

slightly unstable condition. Fig. 2c shows that the mean

concentration levels are markedly smaller than the

values obtained for neutral conditions with similar

building orientation in relation to the wind (Fig. 3a),

especially for Exp. 5 (extremely unstable). This may be

related to an enhanced degree of atmospheric dispersion

before the plume reaches the windward face of the

building. On the other hand, the concentration fluctua-

tion intensity presented in Fig. 3c is not significantly

different from the values obtained for neutral conditions

with similar building orientation. In fact the fluctuation

intensity is only marginally larger on some sensors,

especially on the lateral walls of the building.

Fig. 6 shows the concentration time series and cdf’s

for different detector positions on the building surface

(detectors 1, 5, 8 and 10). The concentration time series

are markedly different from the time series under neutral

conditions for a similar building orientation (Fig. 4).

Although the mean concentration values are smaller for

the unstable cases, as shown in Fig. 2, there are

significant higher concentration peaks. It can be seen

that the unstable time series exhibit much larger

intermittency. While for the neutral cases the mean

intermittency on the windward wall is 0.05, tending to

zero at the leeward wall, the mean intermittency on the

windward wall is 0.12 for Exp. 5 (extremely unstable

condition) and 0.07 for Exp. 6 (slightly unstable

condition), also tending to zero on the leeward wall.

This is probably related to the presence of turbulent

motions of larger scales for the more unstable condi-

tions. It is important to remember that the data

presented here were selected according to the criteria

stated in Section 2.3 for wind direction (7101 from

normal) and the wind speed (42m s�1). Therefore, the

intermittency of the concentration data is related to the

meandering due to the larger scales of turbulence rather

than to the meandering due to the changing direction of

the mean wind.

The cdf0s related to the time series of each sensor are

presented on the right of Fig. 6. The maximum

concentration (C/Cmean) lies beyond the scale presented,

but the graphs have been shown on the same scale as the

one used in Figs. 4 and 5 to emphasise the differences/

similarities between the distributions. As for the experi-

ments under neutral conditions, the time series and cdf

shapes show that there is significantly more fluctuation

intensity on the windward wall than on the leeward wall.

The progression in the slope of the central portion of the

cdf0s indicates a gradual reduction of the fluctuation

intensity as the measurement location progresses from

windward to leeward via the lateral wall, i.e. via the two

sensor sequences 1, 5, 8 and 1, 10, 8. In spite of the

differences in the time series, the conditional cdf0s

exhibit comparable shapes. The slopes of the cdf0s for

unstable and neutral conditions display very similar

behaviour. In fact, this corresponds to the fluctuation

intensity values presented in Fig. 3, where the values

obtained for neutral and unstable conditions were

approximately the same.

The main difference in the cdf0s presented is in the

value of the peak to mean ratio. While for the neutral

cases the maximum values of peak to mean ratio

observed in the cdf0s are 12.3, 4.31, 1.86 and 9.24 (for

the windward, left lateral, leeward and right lateral

walls, respectively), the values for the experiment under

unstable conditions (Exp. 6) were 14.7, 3.76, 2.55 and

11.7, and for the experiment under extremely unstable

conditions (Exp. 5) they were 14.2, 7.17, 3.23 and 22.03.

These values indicate a significant increase in the peak to

mean ratio under unstable conditions. Even inside the

recirculation region behind the building, which is

considered to be a well-mixed region, the peak to mean

ratio presents relatively high values. Again, this effect is

probably related to the presence of turbulent motions of

larger scales for the more unstable conditions.

4. Conclusions

Field experiments were carried out to measure the

fluctuating concentration time series on the walls of a

complex-shaped building, and to investigate the influ-

ence of atmospheric stability and building dimensions

on certain statistics of the concentration distribution on

the walls of the building. The experiments were

performed in flat terrain with uncut vegetation. Meteor-

ological conditions varied from neutral to extremely

ARTICLE IN PRESS

0 1 2 3 4 5t (mins)

0

40

80

120

160

C (

ppm

)

0 2 4 6 8 10C/ Cmean

t (mins) C/ Cmean

t (mins) C/ Cmean

t (mins) C/ Cmean

0

0.2

0.4

0.6

0.8

1

Con

ditio

nal c

df

C (

ppm

)

Con

ditio

nal c

df

C (

ppm

)

Con

ditio

nal c

df

C (

ppm

)

Con

ditio

nal c

df

West winddirection

0 2 4 6 8 100

0. 2

0. 4

0. 6

0. 8

1

0 1 2 3 4 50

20

40

60

80

0 2 4 6 8 100

0. 2

0. 4

0. 6

0. 8

1

0 1 2 3 4 50

20

40

60

80

0 2 4 6 8 100

0. 2

0. 4

0. 6

0. 8

1

0 1 2 3 4 50

20

40

60

80

(a)

(b)

(c)

(d)

Fig. 6. Time series and conditional cdf’s in unstable conditions for source located upwind of the centre of the long face of the building.

— Exp. 5 and - - - - Exp. 6: (a) sensor 1, (b) sensor 5, (c) sensor 8 and (d) sensor 10.

J.M. Santos et al. / Atmospheric Environment 39 (2005) 4999–50125010

unstable. The experimental work carried out on the

complex building revealed that the mean conditional

concentration on the walls was significantly influenced

by the building orientation in relation to the wind

direction. There is a clear indication from the experi-

mental data that: (1) the mean concentration and

concentration fluctuations on the windward wall are

higher than on the other three walls; (2) the concentra-

tions on all walls are higher when the shorter wall faces

the wind. The region of the flow disturbed by the

ARTICLE IN PRESSJ.M. Santos et al. / Atmospheric Environment 39 (2005) 4999–5012 5011

building is smaller when the flow is impinging on the

shorter wall, thus the plume is less spread and higher

concentration values occur. Concentration fluctuation

intensity is nearly uniform on each of the building walls,

and the distributions of concentration fluctuations on

the windward, leeward and lateral walls are comparable

for both Wb=Hb ratios analysed.

Comparison with the work published by Higson et al.

(1996), which also studies atmospheric dispersion

around an isolated building, indicated that although

the fluctuation intensity of the gas tracer concentration

carried in the incoming flow was larger in this study, the

values of concentration fluctuation intensity on the

other building walls were comparable. This behaviour

was also observed in the comparisons of the cdf’s for the

concentrations on each building wall, which displayed a

remarkably similar shape. This can be understood to

mean that the characteristic behaviour of dispersion on

the different walls of the obstacle was not significantly

affected by the slightly different building shapes used in

the two experiments.

The changes in the fluid flow pattern, together with

the greater degree of plume spreading before impinge-

ment on the obstacle, produce lower mean concentration

levels under extremely unstable conditions. Concentra-

tion fluctuation intensity displayed a consistent pattern

in neutral conditions, with larger values on the wind-

ward wall, smaller values on the leeward wall, and

intermediate values on the lateral walls. This pattern was

also displayed in extremely unstable conditions, though

with slightly less consistency. Values of conditional

fluctuation intensity on the building walls were not

significantly influenced by atmospheric stability condi-

tions, but the effect of intermittency due to large-scale

turbulent motion on unstable conditions was clearly

observed. The main effect of the atmospheric stability

was related to values of peak to mean concentration

ratio observed on the building walls, which exhibited a

considerable increase under unstable conditions.

Acknowledgements

The authors would like to acknowledge the sponsor-

ship of the CNPq (the Brazilian Government Agency for

Technological Development and Scientific Research).

The authors also would like to acknowledge the

Meteorology Division, Dugway Proving Ground, Utah,

USA, and staff of DSTL, Porton, UK for enabling Dr

Santos to participate in the field experiments.

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