Research Journal of Environmental and Earth Sciences 3(3): 234-248, 2011
ISSN: 2041-0492
© Maxwell Scientific Organization, 2011
Received: November 27, 2010
Accepted: January 07, 2011
Published: April 05, 2011
Assessment of Atmospheric and Meteorological Parameters for Control of
Blasting Dust at an Indian Large Surface Coal Mine
1
1
S. Roy, 1G.R. Adhikari, 1T.A. Renaldy and 2T.N. Singh
National Institute of Rock Mechanics, Champion Reefs, Kolar Gold Fields - 563 117,
Karnataka, India
2
Indian Institute of Technology, Bombay, Powai, Mumbai-400076, India
Abstract: The aim of the study was to assess the atmospheric and meteorological parameters for the control
of blasting dust. Dust generated due to blasting at large surface coal mines causes air pollution in and around
the mining area. The dispersion of blasting dust depends on prevailing atmospheric and meteorological
conditions. A Sound Detection and Ranging (SODAR) was installed at the mine site to monitor atmospheric
conditions in four seasons. Over 2000 sodar echograms were examined and classified into six categories as
rising layers, thermal plume (free), ground based layer (spiky top), spiky top layer (clear weather), flat top layer
(calm cold), and ground based stratified and multiple layers. Dot echo structures in the echograms were also
observed during rainfall. From sodar echograms, unstable and stable periods were identified. Pasquill stability
classes were evaluated by echograms and mixing heights. An automatic weather station was also installed at
the site to monitor meteorological parameters as wind speed, wind direction, temperature, humidity, solar
radiation and rainfall. Simple correlations as well as multiple regression analysis of meteorological parameters
with mixing height show that solar radiation has strong influence on mixing height. The nearby villages that
are likely to be affected by blasting dust can be protected by planting trees perpendicular to the wind direction
as indicated by windrose diagrams. Dispersion factors, the product of mixing height and wind speed, were
calculated for all the seasons. It was suggested that blasting should be conducted during the period when the
dispersion factor is maximum so that the impacts of blasting dust on the environment can be minimised.
Key words: Blasting dust, dispersion factor, meteorological parameters, mixing height, Sodar, stability classes
Considering the increasing trend of surface mining and
the growing scale of operation of individual mines, it is
essential to assess the dust generated due to blasting and
to adopt suitable control measures.
The generation of blasting dust depends mainly on
the source parameters like blast details, rock and
explosives characteristics (Hagan, 1979). But the
dissipation of blasting dust in vertical and lateral
directions depends basically on atmospheric and
meteorological conditions. The height of the atmospheric
boundary layer or mixing height governs vertical mixing
of the atmospheric pollutants (Aron, 1983; Beyrich, 1997;
Aksakal, 2001; Eresmaa et al., 2005). Pollutants
discharged into the atmosphere are also affected by the
meteorological conditions prevailing in the atmospheric
boundary layer (Spurr, 1978) because meteorological
factors cause atmospheric dispersion of air pollution
(Karppinen et al., 2001). Therefore, a comprehensive
study of atmospheric boundary layer and meteorological
conditions was conducted at a large opencast coal mine to
suggest suitable methods to minimise the impact of
blasting dust on the environment.
INTRODUCTION
Surface coal mining contributes to about 70% of the
total coal production in India. It has an edge over
underground coal mining in terms of production,
productivity and safety. However, surface mining causes
adverse impacts on the environment. Blasting, which is
one of the major operations at surface mines, is associated
with environmental hazards such as ground vibration, air
overpressure, flyrock and dust (Dick et al., 1986;
Adhikari, 2001). Even though blasting is a short-lived
phenomenon, the dust generated due to the use of
explosives in rock fragmentation at large mines cause air
pollution, particularly when a cluster of large mines are
operating in the same coalfield (Roy et al., 2010, 2011).
If the blasting dust is ignored in each of the mines, the air
quality in that coalfield is likely to be deteriorated, which
may have serious consequences on human health.
Previous studies have attempted to assess and control
air pollution caused by various mining operations such as
drilling, loading, hauling and crushing. Very little work
has been conducted on blasting dust and its management.
Corresponding Author: S. Roy, National Institute of Rock Mechanics, Champion Reefs, Kolar Gold Fields - 563 117, Karnataka,
India. Tel: +918153-275000; Fax: +918153-275002
234
Res. J. Environ. Earth Sci., 3(3): 234-248, 2011
The pulse width of 100 ms duration and 2250 Hz of
operating frequency was used in the sodar. The pulsed
signal was amplified in power amplifier for an acoustic
pressure of 126 dB and transmitted through an acoustic
transducer placed at the focus of a 1.2 m diameter
parabolic fiber glass dish inside the acoustic antenna of
1.98 m height. The repetition rate for the acoustic wave
signal was set at 4 s for the range of 640 m with a
resolution of 17 m. The acoustic metallic shields were
lined by high density glass wool. The backscattered
signals were received by the same antenna and amplified
through a remote preamplifier. The amplified signal of
about 80 dB, after proper filtration of the additional noise,
was fed to the data acquisition card placed in sodar CPU.
Finally, backscattered energy were recorded and
displayed in real time in the form of echograms as a
function of height and time. The data was stored in the
digital format and echograms were processed
online/offline. The horizontal and vertical axis of
echograms indicates the height (m) and time (h)
respectively. On top of the display screen, a menu bar
appears for data acquisitions. Among the functions,
“offline data reader” is used to see echograms already
saved in the sodar CPU and by using “generate mixing
height averages” function, hourly mixing height/plume
height is generated in excel format (Operational
Manual, 2008).
MATERIALS AND METHODS
Description of the site: Dudhichua project, Northern
Coalfields Limited, Singrauli, Madhya Pradesh, India was
selected for this study. It is one of the largest opencast
coal mines of India and is surrounded by ten large
opencast coal mines. The mine produced 13.27 million
tonne (Mt) coal in the year 2008-09 and removed 34.36
Mm3 of overburden using 18990 t explosive. It is having
an area of 8.68 km2 and located in the central part of
Moher basin of Singrauli Coalfields. The mine is situated
between latitudes 24º7!30" and 24º10! N and longitudes
82º40! and 82º42!30" E. The area is undulating with an
average elevation of 325 m above MSL. It is at a distance
of 63 km by road from Renukut in Uttar Pradesh and 18
km from Singrauli railway station in Madhya Pradesh.
The general strike in Dudhichua block is NW-SE and
the dips are 1 in 20 to 1 in 25 (2 to 3º) towards north-east.
The lithology consists of mainly soil, sandstone and coal.
This mine was developed in ten benches including three
in coal and seven in overburden. Large blasts are
regularly conducted both in coal and overburden benches
using huge quantities of explosives, thus increasing the
potential for dust hazards in and around the mine. The site
mixed emulsion explosives are used as an explosive. The
main mining and transport equipment are electric shovels,
draglines, dumpers, dozers, etc.
Installation and operation of weather monitoring
station: An Automatic Weather Station of Lawrence &
Mayo (India) Pvt. Ltd. was installed at the time office
building of the mine. This weather station consists of a
data acquisition unit, sensors for wind speed, wind
direction, air temperature, humidity, solar radiation and
rainfall. The portable digital data bank is a part of the data
acquisition unit, which automatically records the data at
an interval of one minute. This station is operated by
mains-cum-battery power supply. At the time of power
failure, the battery is charged by the solar panel, which
ensures uninterrupted power supply.
Installation of sodar and its principle of operation:
SODAR stands for sound detection and ranging. A tri-axis
monostatic (back-scattering) sodar, manufactured by
Global Environmental Technologies, New Delhi, India,
with a technical know-how of the National Physical
Laboratory, New Delhi, India, was installed at the project
office building of Dudhichua project. Sodar was operated
continuously for 24 h in post-monsoon (OctoberNovember), winter (January-February), summer (AprilMay), and monsoon (August-September) for a period of
26, 21, 26 and 27 days respectively during 2008 and 2009.
It works on the principal of acoustic backscattering
and emits a series of chirps or beeps at a fixed frequency.
The sodar uses sound or acoustic waves of a well defined
audible frequency for investigating the atmospheric
boundary layer. An acoustic pulse transmitted into the air
experiences backscattering from small temperature
inhomogeneities (with a size in the order of the wave
length). The acoustic waves as they propagate interact
with atmospheric regions of wind and temperature
fluctuations and get scattered. The backscattered acoustic
signals are received back by the same antenna in the sodar
and suitably processed to produce sodar echograms. The
travel time between emission and reception determines
the height the signal represents. It provides three
dimensional (height, time and intensity) pictorial view
(echograms) of the dynamics of thermal structures in real
time.
RESULTS AND DISCUSSION
Categorisation of sodar echograms: Over 2000 sodar
echograms recorded at the mine site for different seasons
were analysed and classified into different categories.
Though there were some variations in the echogram
structures, the observed echograms in general could be
broadly classified into six categories as shown in Fig. 1.
Figure 1a shows the rising echograms which occur in
the morning some time after sunrise. The rising
echograms indicate transition from stable to unstable
conditions. Such echograms were observed late in winter
than in other seasons. The incoming solar radiations
gradually erase the ground based temperature inversion
layer. With continuous solar heating, the layer starts
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Res. J. Environ. Earth Sci., 3(3): 234-248, 2011
Stratified layer
Spiky top layer
Thermal plume (free)
Rising layer
(b)
(a)
Spiky
Top
Layer
Spiky top
layer
(clear
w eather)
Ground based layer ( spiky top)
Rising Layer
(c)
(d)
Decrease in Thermal Plume
Flat top layer (calm cold)
after 3 pm
Ground based stratified layer
Therm al Plume (Free)
(f)
(e)
Thermal Plum e (Free)
Dot echo structures due to rain
Ground based multiple layers
(g)
(h)
Fig. 1: Typical sodar echograms at the mine site
rising, indicating the transfer of heat, momentum and
energy from the earth’s surface (Singal et al., 1997;
Nilsson et al., 2001; Choudhury and Mitra, 2004). In
winter, convection period started late due to low surface
heating (Myrick et al., 1994).
Figure 1b exhibits the thermal plume (free) types of
echograms which were observed during the day time i.e.
strong convection periods up to 15:00 IST (Indian
Standard Time). Thermal plumes (free) or convective
conditions are caused by turbulence in the unstable
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Res. J. Environ. Earth Sci., 3(3): 234-248, 2011
Table 1: Onset, dissipation and duration of convective activity at the mine site in different seasons
Season
Onset time (h)
Dissipation time (h)
Post-monsoon
0800
1700
Winter
0900
1700
Summer
0800
1800
Monsoon
0800
1800
condition (temperature decreases with height) and
its strength become maximum in the afternoon
(Singal et al., 1997) or at noon (Nilsson et al., 2001) and
then decreases with the fall in solar heat flux
(Singal et al., 1997; Nilsson et al., 2001). The strong
convection period is followed by weak convection, which
persists till sunset.
Tall spiky top layers were observed (Fig. 1c) in the
evening. Often the presence of winds during temperature
inversion is responsible for this type of structures.
Under this situation, the wind tends to cause
instability in temperature inversion layers (Choudhury and
Mitra, 2004). Small spiky and flat top layers (Fig. 1d, e)
were found during clear and calm weather after midnight.
When the heating due to radiation stops in the evening,
cooling of earth surface establishes a stable boundary
layer (Mayer, 2005). Owing to large radiative cooling at
ground surface, a nocturnal stable boundary layer forms
after sunset and persist throughout the night
(Nilsson et al., 2001). Very stable situations are usually
associated with clear nocturnal skies and weak winds or
with the advection of warm air over a much cooler surface
(Mahrt, 1999). Spiky top layers are formed due to small
scale wind turbulence (Singal et al., 1997) whereas flat
top layers are formed on clear nights (associated with very
light wind conditions) (Choudhury and Mitra, 2004) due
to emission of infrared radiations from the ground.
Singal et al. (1997) observed flat top layers under slight
or no wind conditions during night time. The thickness of
these layers may increase with time.
Ground based stratified and multiple layers
(Fig. 1f, g) also occurred after midnight when temperature
increases with height. Light wind conditions or
advection are responsible for these types of layers
(Singal et al., 1997; Beyrich, 1997). Katabatic winds
during the radiative cooling of ground also form layered
structures (Garcia et al., 2007).
Some vertical lines that can be seen in echograms are
due to noise caused by intermittent movements of coal
loaded wagons. Similar vertical lines in the echograms
have been reported
due
to
traffic noise
(Holmgren et al., 1975).
All echograms were similar to one or other types as
mentioned above except during the rain. Typical
echograms during the rainfall are shown in Fig. 1h, which
are called dot echoes structures (Gera and Singal, 1990)
representing clusters of water vapour in which turbulence
is generated owing to the mixing of temperature and
humidity inhomogeneities (Singal et al., 1985). In the dot
type echograms, it is difficult to detect any structure due
to the noise caused by the rainfall.
Duration of convective activity (h)
09
08
10
10
Assessment of stability periods using sodar echograms:
Based on the observations of sodar echograms, onset and
dissipation time of convective boundary layer was found.
Table 1 shows that onset time of convective boundary
layer is late by an hour in winter than in other seasons. As
the days are shorter in winter, the duration of convective
period is the minimum in this season. The dissipation time
for post-monsoon is same as for winter but it is late by
one hour for summer as well as monsoon. The duration of
convective activity is the lowest in winter. Depending on
seasons, there was variation in onset and dissipation time
and hence duration of convective activity. The convective
activity during day time determines the atmospheric
boundary layer’s diluting capability for pollutants (Gera
and Saxena, 1996).
The duration of convective activity is called unstable
period while remaining hours are called stable period. The
relative occurrence of unstable and stable periods in
different seasons was determined (Fig. 2). The occurrence
of unstable period was the lowest in winter and
corresponding stable period was the highest in this season
compared to other seasons.
Mixing height: Mixing height is defined as the height of
the layer adjacent to the ground over which pollutants
enter into this layer get mixed up by convection or
mechanical turbulence within one hour (Beyrich, 1997;
Seibert et al., 2000). It is a fundamental parameter that
characterizes the structure of the lower atmosphere and
determines the volume available for dispersion of
pollutants by convection or mechanical turbulence and
has its applications in environmental monitoring and
prediction of air pollution and weather forecasting
(Aron, 1983; Beyrich, 1997; Seibert et al., 2000; Aksakal,
2001; Eresmaa et al., 2005; Garcia, 2007; Baars et al.,
2008; Zhou et al., 2009). Higher the mixing height the
higher is the volume available for the dispersion of
pollutants and vice versa. The stable boundary layer is
indeed quite shallow compared to convective boundary
layer or unstable boundary layer (Nieuwstadt and
Duynkerke, 1996). The structure of the atmospheric
boundary layer is determined by various processes
(turbulence, radiation, baroclinity, advection, divergence
and associated vertical motion, etc.) which influence the
vertical profiles and turbulent atmospheric parameters in
a different way especially in the stable boundary layer
(Beyrich, 1997).
The ground based horizontal layer gives the inversion
height or the mixing height of stable atmospheric
boundary layer, which were directly read from the sodar
echograms. However, under unstable atmospheric
boundary layer conditions associated with thermal
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Res. J. Environ. Earth Sci., 3(3): 234-248, 2011
80
Relative occurrence (%)
Unstable period
Stable period
60
40
20
0
Post monsoon
Winter
Summer
Monsoon
Fig. 2: Seasonal variation in unstable and stable periods at the mine site
1600
Post-monsoon
Winter
Mixing height (m)
1200
Summer
Monsoon
800
400
Stable boundary layer
Stable boundary layer
Unstable boundary layer
0
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Time (h)
Fig. 3: Seasonal variation in mixing height at the mine site
convection i.e., during daytime, when the plumes are not
capped by a stable layer; mixing height was
evaluated using an empirical relation developed by
Singal et al. (1997) based on correlation studies of
simultaneous sodar observations of thermal plumes and
radiosonde observations made by Indian Meteorological
Department. Following relation was used to compute the
height of unstable atmospheric boundary layer
(Singal et al., 1997; Operational Manual, 2008).
y = 4.24*x + 95
15:00 IST, the mixing height starts decreasing due to
lower heating of the ground. The majority of mixing
heights during transition phase (stable to unstable and
vice versa) were within 400 m in all the seasons. Even
during weak convection, which occurred before sunset,
the mixing height was also within 400 m. The highest
mixing height during convection period was 1499, 1364,
1126 and 1032 m in monsoon, post-monsoon, winter, and
summer respectively. Mixing heights were highest
between 12:00 IST and 14:00 IST due to highest
convection during this period in all the seasons
(Myrick et al., 1994; Singal et al., 1997).
(1)
where, y is the mixing height (m) for unstable
atmospheric boundary layer, x is the depth of the sodar
measured thermal plumes (m).
Figure 3 shows hourly variation in mixing height for
different seasons. Mixing height is low during nocturnal
stable boundary layer in winter. In general, it is high in
between 12:00 IST and 14:00 IST in all the seasons. After
Evaluation of stability classes: Atmospheric stability is
one of the essential parameters for air quality studies.
Pasquill (1961) classified it into six classes from A to F in
terms of increasing order from very unstable (A),
moderately unstable (B), slightly unstable (C), neutral
(D), slightly stable (E) to moderately stable (F). The
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Res. J. Environ. Earth Sci., 3(3): 234-248, 2011
Table 2: Sodar based stability classification scheme (Operational Manual, 2008)
Sodar structural details
Mixing/inversion height
Thermal plumes ( free)
No limit
>800 m
400 m < MH <800 m
< 400 m
Thermal plumes
Capping layer height
(with capping layer)
NO structure (blank)
Zero
Ground based layer
(Flat/spiky top)
No limit
Flat/ spiky top layer
Height <150 m
(Clear/ fair weather)
>150 m
Flat top layer
Height <100 m
(Calm cold/ foggy conditions)
>100 m
Ground based stratified/ Elevated /
No limit
multiple layers or wavy layers
Rising layer(with thermal plumes
Height <400 m
beneath it)
>400 m
Note: MH = mixing height
ABL stability
Unstable
Unstable
Stability class
A,B or C
A
B
C
C
Neutral
D
Stable
E or F
E
F
E
F
F
Highly stable
Transitional
phase stable to
unstable
Table 3: Stability class for different periods of the day at the mine site in different seasons
Post-monsoon
Winter
Summer
------------------------------------------------------------------------------------------------------------Time (h)
Class
Time (h)
Class
Time (h)
Class
00:00-08:00
F
00:00-09:00
F
00:00-08:00
F
08:00-09:00
C
09:00-10:00
C
08:00-09:00
C
09:00-15:00
A
10:00-15:00
A
09:00-15:00
A
15:00-17:00
C
15:00-17:00
C
15:00-18:00
C
17:00-00:00
E
17:00-00:00
E
18:00-00:00
E
C
B
Monsoon
---------------------------------------Time (h)
Class
00:00-08:00
F
08:00-09:00
C
09:00-15:00
A
15:00-18:00
C
18:00-00:00
E
source using Pasquill-Gifford curves (Gifford, 1961;
Singal et al., 1997). These coefficients are required to
calculate emission rate at the mine for known
concentration of dust and corresponding wind
speed using modified Pasquill and Gifford formula
(Peavy et al., 1985).
presence of class A indicates strong mixing whereas
E or F gives rise to poor dispersion (Canter, 1977;
Dobbins, 1979). The stability classes can be determined
based on mixing heights and sodar echograms (Gera and
Saxena, 1996; Singal et al., 1997).
Using sodar echograms, corresponding mixing
heights and the information given in Table 2, stability
classes for the mine site condition were determined. In all
the seasons, classes A, B and C were found during
convection periods of the days. In the evening, class E
was considered due to low infrared radiation and tall
spiky layers. After midnight, mixing heights greater than
100 m and flat or almost flat echograms indicated class F.
Class D was absent as no echogram structures (blank) or
zero mixing height were observed. Table 3 summarises
stability classes for different periods of the day for
different seasons. Class A was predominant during 10:0015:00 IST in winter and during 9:00-15:00 IST in all other
seasons. These periods fall under strong convection
period of the day. Class C was predominant during weak
convection period of the day i.e. at 09:00-10:00 IST in
winter and at 08:00-09:00 IST in all other seasons. Class
C also found at 15:00-17:00 IST for post-monsoon and
winter, and at 15:00-18:00 IST for summer and monsoon.
Class E was found in the evening and F in the morning in
all the seasons.
The Pasquill stability classes can be used to
determine the horizontal and vertical dispersion
coefficients as a function of downwind distances from the
Influence of meteorological parameters on mixing
height: Meteorological parameters such as, wind speed,
wind direction, surface temperature, humidity, solar
radiation and rainfall can affect the mixing height.
Therefore, the influence of these parameters on mixing
height was studied.
The meteorological data generated for each season
were analysed. Though the number of monitoring days for
meteorological parameters compared to operation periods
of the sodar was more in some seasons, only those
meteorological data corresponding to mixing height were
considered for analysis. The hourly average values of
meteorological parameters and mixing height for different
days of different seasons were calculated separately.
Hence hourly data for each season was used for analysis.
Wind speed and direction: The change of wind direction
and speed with time at a particular site can be presented
diagrammatically in the form of a wind rose. A wind rose
diagram consists of a series of lines emanating from the
centre of a circle and pointing in the direction from which
the wind blows. It shows the prevailing wind direction
239
Res. J. Environ. Earth Sci., 3(3): 234-248, 2011
N
N
10%
8%
4.0%
3.2%
6%
2.4%
4%
1.6%
0.8%
W
E
2%
W
E
Wind speed (m/s)
>=2.1
Resultant vector
233 deg – 57%
Resultant vector
211 deg – 43%
0.5-2.1
Calms: 81.64%
S
(a) P os t mons oon
Wind speed (m/s)
>=2.1
0.5-2.1
Calms: 76.22%
S
(b) W inter
N
N
10%
8%
10%
8%
6%
6%
4%
4%
2%
W
2%
W
E
Wind speed (m/s)
>=2.1
Resultant vector
168 deg – 61%
S
0.5-2.1
Calms: 48.75%
Wind speed (m/s)
>=2.1
Resultant vector
186 deg – 66%
(c) S ummer
E
S
0.5-2.1
Calms: 64.51%
(d) Mons oon
Fig. 4: Windrose diagrams for different seasons at the mine site
and speed. The length of the bar for a direction indicates
the percent of time the wind comes from that direction.
The percentage of time for velocity is shown by the
thickness of the direction bar. The circle marked in the
centre of the wind rose indicates the percent of time
covered for calms with very low wind velocities.
Wind rose diagrams (Fig. 4) were plotted for all
seasons using hourly data of wind speed and direction
with the help of ISC-AERMOD View software version
5.9. The level of frequencies (%) is mentioned on each
circle through which frequency for each direction can be
assessed.
In post-monsoon, the wind speed and direction at the
mine site are shown in Fig. 4a which indicates that the
greatest percentage of wind blew from WSW at a speed
of up to 2.1 m/s and occasionally from ESE beyond 2.1
m/s. The calm conditions prevailed 81.64 % of the time.
In winter (Fig. 4b), the highest percentage of winds was
from ESE at a speed up to 2.1 m/s. The calm conditions
were 76.22% of the time. In summer (Fig. 4c), the
percentage of winds was the highest from E but the
percent of wind speed up to 2.1 was the highest from S.
The wind also blew more than 2.1 m/s from other
directions. The calm period was 48.75% of the time in
this season. In monsoon (Fig. 4d), the highest percentage
of wind was from SSE. The wind also blew from different
directions beyond 2.1 m/s in this season. The percentage
of calm condition was 64.51%.
The calm condition was the highest in post-monsoon
and the lowest in summer indicating the wind blew more
in summer and less in post-monsoon. As per the Beaufort
scale, the wind velocities from 0.45 to 5.4 m/s come under
light wind category (Spurr, 1978). The low wind speeds
are associated with elevated pollution levels
(Papanastasiou et al., 2007). At the mine, blasting dust
moves away from the mine towards the downwind
direction. If the wind direction is constant, the area
remains exposed to high pollutant levels. As the direction
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Res. J. Environ. Earth Sci., 3(3): 234-248, 2011
10000
10000
Winter
Mixing height (m)
Mixing height (m)
Post-monsoon
1000
100
y = -671.4x2 + 1467.5x + 326.5
R = 0.75
10
0.00
0.20
0.40
0.60
Wind speed (m/s)
N = 26
0.80
1000
100
y = -343.25x2 + 1111.5x + 230.1
R = 0.69
10
0.00
1.00
0.40
0.60
0.80
Wind speed (m/s)
1.00
10000
10000
Monsoon
Mixing height (m)
Summer
Mixing height (m)
0.20
N = 21
1000
100
y = -220.83x 2 + 775.1x + 18.5
R = 0.66
10
0.00
0.50
N = 26
1.00
1.50
Wind speed (m/s)
1000
100
y = 3836.3x2 - 3274.7x + 917.3
R = 0.91
10
0.20
2.00
0.40
0.60
0.80
Wind speed (m/s)
N = 27
1.00
1.20
Fig. 5: Correlation of wind speed with mixing height in different seasons
10000
10000
Mixing height (m)
Mixing height (m)
Post-monsoon
1000
100
y = -0.0712x2 + 25.799x - 1666.6
N = 26
1000
100
2
y = -0.088x + 31.064x - 2089.9
R = 0.52
R = 0.30
10
180
220
240
Wind direction (0)
260
150
N = 21
200
250
Wind direction (0)
300
10000
Summer
Monsoon
1000
100
y = -0.1152x2 + 37.444x - 2590.8
R = 0.20
10
100
10
100
Mixing height (m)
Mixing height (m)
10000
200
Winter
150
200
Wind direction (0)
N = 26
1000
100
y = -0.0575x2 + 17.965x - 775.5
R = 0.30
10
100
250
150
200
N = 27
250
300
Wind direction (0)
Fig. 6: Correlation of wind direction with mixing height in different seasons
changes, pollutant disperse over a large area causing
lower concentrations over the exposed area. The
predominant wind directions in different seasons can help
in the design of greenbelts of fast growing trees to
minimize the environmental impacts of the mining
activities including blasting dust.
Good correlation of wind speed with mixing height
for different seasons (Fig. 5) shows the influence of wind
speed on mixing height. Using SPSS software version
13.0, the significant level of correlation coefficients was
checked and it was found that correlations are statistically
significant at 5% level of significance for all the seasons.
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Temperature (0C)
50
Post-monsoon
Winter
Summer
Monsoon
40
30
20
10
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Time (h)
Fig. 7: Hourly variation in temperature in different seasons
10000
10000
Winter
Mixing height (m)
Mixing height (m)
Post-monsoon
1000
100
y = 0.9391x2 + 12.748x - 286.5
N = 26
R = 0.54
1000
100
y = -1.2549x2 + 84.258x - 739.2
R = 0.44
15
20
25
Temperature
12
30
10000
Summer
1000
100
y = -1.8189x2 + 167.52x - 3178.1
R = 0.49
N = 26
10
27
31
16
(0C)
Mixing height (m)
Mixing height (m)
10000
N = 21
10
10
35
39
28
32
Monsoon
1000
100
y = 16.437x2 - 706.42x + 7549.5
10
25
43
20
24
Temperature (0C)
Temperature (0C)
R = 0.68
27
29
Temperature (0C)
N = 27
31
Fig. 8: Correlation of temperature with mixing height in different seasons
These results agree with those published by
Singal et al. (1997) and Zhou et al. (2009).
Using the monitored data, wind direction was
plotted against mixing height for different seasons and
analysed (Fig. 6). No significant correlations were
observed due to limited variation in wind direction.
surface temperature controls the occurrence of
atmospheric convection; hence it strongly affects the
mixing height (Zhou et al., 2009).
Hourly variation in temperature for different seasons
is shown in Fig. 7. Obviously, the temperature was the
highest in summer and the lowest in winter. The
temperature in the morning than in the evening might be
the reason for higher inversion.
Figure 8 shows the correlation of temperature with
mixing height for different seasons. The correlations for
different seasons are statistically significant at 5% level of
Temperature: The convective boundary layer height
rises and falls during the day time depending on the
increase and decrease of surface temperature due to solar
heating of the ground (Gera et al., 1990). The variation in
242
Res. J. Environ. Earth Sci., 3(3): 234-248, 2011
100
Humidity (%)
80
60
40
Post-monsoon
Winter
Summer
Monsoon
20
0
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Time (h)
Fig. 9: Hourly variation in humidity in different seasons
10000
10000
Mixing height (m)
Mixing height (m)
Post-monsoon
1000
100
y = -0.047x2 - 6.2142x + 1048
R = 0.44
N = 26
Winter
1000
100
y = -0.083x2 - 0.0531x + 640.6
R = 0.37
30
40
50
60
70
Humidity (%)
80
20
90
30
40
50
60
Humidity (%)
70
80
10000
10000
Monsoon
Mixing height (m)
Summer
Mixing height (m)
N = 21
10
10
1000
100
y = -0.3546x2 + 7.042x + 554
R = 0.43
10
15
25
35
Humidity (%)
1000
100
y = 0.8682x2 - 185.33x + 9915.4
R = 0.66
N = 26
N = 27
10
45
70
55
75
80
85
90
95
Humidity (%)
Fig. 10: Correlation of humidity with mixing height in different seasons
significance indicating influence of temperature on
mixing height. Similar results were also obtained by
Zhou et al. (2009).
monitored, mixing height was plotted against humidity
(Fig. 10). The coefficients are significant at the 5% level
of significance except winter indicating influence on
mixing height.
Humidity: Figure 9 shows the hourly variation in
humidity in different seasons. Obviously, humidity was
the highest in monsoon and the lowest in summer.
Rainfall might be the reason for the higher humidity in
monsoon whereas the higher temperature in summer
might be the reason for lower humidity.
Humidity plays a dominant role in affecting mixing
height (Beyrich, 1997; Zhou et al., 2009). Using the data
Solar radiation: The highest solar radiation was observed
in monsoon and the lowest in winter (Fig. 11). The
presence of dust particles decrease the solar radiation in
the atmosphere (Prendez et al., 1995) whereas dust is
cleansed by washing out process during rainy season
(Stern, 1968), which may be attributed to the highest solar
radiation in monsoon.
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Res. J. Environ. Earth Sci., 3(3): 234-248, 2011
Solar radiation (w/m 2)
1.40
Post-monsoon
Winter
Summer
Monsoon
1.20
1.00
0.80
0.60
0.40
0.20
0.00
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Time (h)
Fig. 11: Hourly variation in solar radiation in different seasons
10000
10000
Winter
Mixing height (m)
Mixing height (m)
Post-monsoon
1000
100
y = 2574.6x 2 - 98.554x + 299.8
R = 0.94
10
0.00
0.20
0.40
100
y = 3262.8x 2 - 730.25x + 272.5
R = 0.93
N = 26
0.60
Solar radiation
1000
10
0.00
0.80
0.40
0.60
0.80
Solar radiation (w/m2)
(w/m2)
10000
10000
Monsoon
Mixing height (m)
Summer
Mixing height (m)
0.20
N = 21
1000
100
y = 1420.2x 2 - 207.04x + 183.1
R = 0.94
10
0.00
0.20
0.40
0.60
N = 26
0.80
1000
100
y = 878.27x2 - 156.73x + 237.8
R = 0.95
N = 27
10
0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40
1.00
Solar radiation (w/m2)
Solar radiation (w/m2)
Fig. 12: Correlation of solar radiation with mixing height in different seasons
Figure 12 shows the correlation of solar radiation
with mixing height. The correlations are statistically
significant at 1% level of significance indicating the
strong influence of solar radiation on mixing
height. The results are in agreement with those of
Myrick et al. (1994).
rainfall in monsoon is shown in Fig. 13. Using the
monitored data of monsoon, mixing height was plotted
against rainfall (Fig. 14). Variations in rainfall at different
periods of the days might have led to variations in
infrared cooling of the earth. This could be the reason of
insignificant influence on mixing height.
Rainfall: During the investigation period, there was no
rain in post-monsoon, winter and summer. Therefore, no
graphs were plotted for these seasons. The recorded
Multiple regression analysis of data: Multiple
regression analysis was carried out using the SPSS
software version 13.0 to study the combined influence of
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Res. J. Environ. Earth Sci., 3(3): 234-248, 2011
1.60
1.40
Rainfall (mm)
1.20
1.00
0.80
0.60
0.40
0.20
0.00
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Time (h)
Fig. 13: Hourly variation in rainfall in monsoon
10000
Mixing height (m)
Monsoon
1000
100
y = -712.48x2 + 1334.1x + 165.9
R = 0.40
10
0.00
N = 27
0.40
0.80
1.20
1.60
Rainfall (mm)
Fig. 14: Correlation of rainfall with mixing height in monsoon
2000
y = 0.8162x + 85.1
R = 0.90
Predicted mixing height (m)
1600
1200
800
400
0
0
400
800
1200
1600
Measured mixing height (m)
Fig. 15: Correlation between predicted and measured values of mixing height
meteorological parameters on mixing height. A total of 96
sets of data, consisting of 24 sets for each season, were
used to derive the following empirical equation:
where, MH is the mixing height (m), X1 is the wind speed
(m/s), X2 is the wind direction (0), X3 is the temperature
(0C), X4 is the humidity (%), X5 is the solar radiation
(w/m2) and X6 is the rainfall (mm).
The value of multiple correlation coefficient (R) in
Eq. (2) is 0.90, which p-value is below 0.01 indicating
MH = 1.474 – 190.476*X1 + 1.169*X2 – 0.407*X3 +
0.757*X4 + 1274.113*X5 – 378.922*X6 (2)
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Res. J. Environ. Earth Sci., 3(3): 234-248, 2011
Dispersion factor (m 2/s)
1600
Post-monsoon
1200
Winter
Summer
Monsoon
800
400
00
:0
0
-0
02
1:
00
:0
0
-0
04
3:
00
:0
0
-0
06
5:
00
:0
0
-0
08
7:
00
:0
0
-0
10
9:
00
:0
0
-1
12
1:
00
:0
0
-1
14
3:
00
:0
0
-1
16
5:
00
:0
0
-1
18
7:
00
:0
0
-1
20
9:
00
:0
0
-2
22
1:
00
:0
0
-2
3:
00
0
Time (h)
Fig. 16: Dispersion factor at different times of the day in different seasons
15:00 IST. It was the normal practice in the mine that the
blasting operations are carried out during the shift change
so that the loss of productive time can be minimised.
Although the blasting time was fixed by some other
considerations, it coincides with the period of maximum
dispersion factors in winter and summer. However, it
would be beneficial if blasting operations are rescheduled
during 12:00-13:00 IST in post-monsoon and monsoon.
Dispersion factor is the lowest in the winter season.
Hence the pollutants in the atmosphere cause greater
impact to the environment in winter than in any other
season.
Knowledge of dispersion factor has practical
applications in controlling air pollution. For this purpose,
emissions from high air polluting sources of mining
activities can be confined to 10:00-15:00 IST.
the statistically significant correlation at a 99%
confidence level. The coefficients (1274.113 and 378.922) are statistically significant at the 1% level of
significance. Simple as well as multiple regression
analysis shows that sodar radiation has strong influence
on mixed height.
Figure 15 shows the plots of predicted and measured
values of mixing height. Good correlation between the
predicted and measured values indicates that Eq. (2) can
be used at the mine site to estimate the effect of
meteorological parameters on mixing height.
Determination of dispersion factor: Mixing height and
wind speed are the two most important parameters for
vertical and horizontal dispersion of air pollutants at a
given time. The product of mixing height and wind speed
is called dispersion factor (Trindade et al., 1980), which
is an indicator of atmosphere’s dispersive capability
(Masters, 2000).
From the known mixing height and wind speed,
dispersion factors were computed for the mine site
condition. Figure 16 shows the dispersion factor at
different periods of the day for different seasons. The
dispersion factor is high during 10:00-15:00 IST for all
the seasons. It is the highest in summer and the lowest in
winter. The knowledge of dispersion factor at different
times of the day at the mine can be used as a tool for
control of air pollution due to blasting. For effective
control of blasting dust, blasts at the mine can be
scheduled, when the dispersion factor is maximum i.e., in
between 12:00-13:00 IST in post-monsoon and monsoon
and in between 13:00-14:00 IST in other two seasons.
During the monitoring period, most of the blasts at
the mine were conducted during 13:00-14:00 IST i.e.,
during the change of shifts. Under unavoidable
circumstances, blasts were also conducted during 14:00-
CONCLUSION
Thermal plumes (free) occurred during the day time
whereas spiky, flat, stratified and multiple layers formed
during the night time. Rising layers were observed during
transition phase in the morning some time after sunrise.
Dot echo structures were found during rainfall.
Echograms provided real-time information about onset
and dissipation times of convective and stable boundary
layers.
The mixing height was the highest during 12:00 IST
and 14:00 IST in all the seasons. Stability classes A, C, E
and F was predominant at different times of the day for all
the seasons. These classes can be used to know dispersion
coefficients for calculation of emission rates for different
mining activities including blasting dust.
The predominant wind direction as indicated by
windrose diagrams for different seasons can be used to
minimise the impacts of blasting dust by planting fast
246
Res. J. Environ. Earth Sci., 3(3): 234-248, 2011
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growing trees perpendicular to blasting dust plume
towards habitations.
Varying degree of simple correlations of
meteorological parameters with mixing height was
established, the highest being with solar radiation.
Multiple regression analysis of data indicated the
combined influence of meteorological parameters on
mixing height. It also established that solar radiation has
dominant influence. The developed statistical model can
be used at the mine site to compute mixing height.
Dispersion factor was high during 10:00-15:00 IST
for all the seasons but for effective control of blasting
dust, blasts at the mine can be scheduled during 12:0013:00 IST in post-monsoon and monsoon and during
13:00-14:00 IST in other two seasons. Results of the
study will also be useful for control of dust due to other
mining activities.
ACKNOWLEDGEMENT
This research study is a part of Ph. D. work of the
principal author. The financial support from the Ministry
of Coal, Government of India through Central Mine
Planning & Design Institute Limited, Ranchi is gratefully
acknowledged. We are also thankful to the management
of Dudhichua project, Northern Coalfields Limited for
providing necessary facilities during the field study. The
authors are thankful to the Director, National Institute of
Rock Mechanics, for his permission to publish this paper.
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