Meteorological conditio ns

I
METEOROLOGICAL CONDITIONS IN NORTHERN INDIA AND
AIR ~ POLLUTION DISPERSION MODELLING
By
Dr. G-D. Agc^r.wal, Technical Advisor
Envirotech Instruments (P) Ltd., New Delhi.
INTRODUCTION
substainable Development the Key to Environmental
Protection: For developing countries like India, it can
never be a question of choosing between environment and
development - the nation stands to lose if one were to
be chosen at the cost of the other. The interests of
the nation lie only in planning development in a manner
that it shall not harm or adversely affect our natural
resources or environmental quality in either the short
or in the long rui and shall in other words be sust-
ainable.
Modelling the Key to planning for Substainable
Development: As would be obvious, all planning involves
some assessment or prediction of future. Ensuring that
the proposed projects or activities shall be
sustainable and shall not affect environmental quality
in the long run requires reliable prediction of future
impacts. And such prediction shall need to be well-
quantified to help decide the extents to which
development can be sustained by a local environment and
also to decide appropriate technologies, designs and
polluti on-control or amelioration measures. An EIA
(Environmental Impact Assessment) without quantitative
modelling of cause-effect relationships is little mor-
than a set of apprehensions or platitudes.
Pollutant Dispersion Modelling Key to Air Quality
Management: Thus the most important tool to ambient
air-quality management in India to ensure that human
activities do not deyrade air-quality that start

2
adversely affecting ecological or other sensitive
interests, becomes mathematical modelling of the
dispersion or spread of the pollutants in the
atmosphere. In the absence of reliable modelling of
such dispersion, decisions on site clearance of
proposed projects, fixing of emission limits, design of
stacks and of pollution control equipments shall all
either be oversafe (and hence, in a way, development
restrictive) or undersafe (and hence shall damage
environmental quality). For rational and optimal
decisions, it is absolutely imperitive to develop
models that shall provide practically reliable air-
quality predications.
1.4 Meteorology the Most Critical Factor:
Meteorology being the science that defines all physical
characteristics of the atmosphere including all forms
and factors of it's movement and the spread of
pollutants, - modelling of such spread becomes
intrinsically dependent not only on having reliable and
appropriate meteorological data but also on having a
good practical understanding of the meteorology of the
area. It is not adequate for environmental scientists,
.particularly those involved with air-quality-management
or with carrying out EIAs for air-polluting activities,
to collect data from the meteorological department, IMD
or to refer to IMD for advice but to understand the
behaviour themselves so as to correctly decide the data
needs. And when necessary, these scientists/engineers
have to be able to make appropriate meteorological
measurements themselves.
1.5 This paper discusses some meteorological behaviours
observed during environmental studies in the plains of
northern India and their relevance to mathematical
modelling of dispersion of air pollutants. It brings
out the need for intensive collection of appropriate
location-specific meteorological data as also of use
of models that have been validated on field under
Indian Conditions.

3
2.2 On a first look one may feel that the only meteorolo-
gical parameter involved in the equation is u, the
average wind speed. But soon one would realise that
both yy and Jz. very much depend on meteorological
conditions that control atmospheric dispersivities. In
fact all the different models proposed (100 or more in
number) are merely efforts to obtain better estimates
of y and z under the complex meteorological controlling-1
*
factors and/or to account for in a realistic manner,
the variations in ^ and^z from point to point and from
moment to moment. Most models classify the meteoro-
logical conditions controlling the dispersivities into
a number of Stability Classes and then provide
equations to compute^y and for each Stability-Class.
The most popular classification has been the 6-class
passquill-Gifford-Turner (1,2) system, later extended
by Holz-worth (3) to add a seventh G stability-class to
the original A to F.
2.3 The effective height, He, is not the physical height of
the stack but has to include the plume-rise due to
thermal and inertial factors. Plume rise again depends
on meteorological factors including wind speed, ambient
temperature and atmospheric stability.
2.4 Even the coordinates x and y are not independent of
meteorology, since the average down-wind direction
decides the x-axis, and any change in wind direction
shall change the coordinates of all points and in turn
also affectyy,y~z and all other terms.
2.5 Overall one could say that all terms in the basic model
equation depend on meteorological data, except the rate
of emission Q, and the vertical coordinates z.
Obviously the reliability of modelling results becomes
very intimately related to obtaining appropriate and
reliable meteorological data.

BASIC AIR-DISPERSION MODELS AND METEOROLOGICAL DATA
NEEDED
While the number of mathematical models proposed for
predicting ground level incremental pollutant
concentrations from particular emissions would run
considerably over a hundred, 95% or more of these
essentially revert to a Gaussian equation, the general
form of which in case of single steady-state continuous
point source of emission is
- y 2
C(x,y,z,He) = 0 e 2 fv?
2 " . v.ffjz
(z-He)2
-(z+He)2
2.-^2 r 7
v -j
1
I
J
,-Wherc. He = Effective height of the stack emission
above G.L.
x,y,z = Coortinates taking the foot of the stack
or the projection of the point of
emission on G.L. as the origin and thf*
average downwind direction as the x
axis; the cross-wind horizontal
direction becomes y axis and the
vertical the z axis.
Q = Mass rate of pollutant emission (s^i
grams /sec) .
u = The average wind-speed
= Lateral dispersion/spread or plume at a
distance x downwind from origin.
Vertical dispersion/spread of plume at a
distance x downwind from origin.
C(x,y,z,He)= Incremental pollutant concentrations at
the point x,y,z due to emissions
released at a height He above origin or
o , o , o .
P

5
2.6 Meteorological data needed
modelling shall include:
for pollutant-dispersion
a. Average Wind Direction to define coordinates
b. Average Wind-speed to provide u
c. Atmospheric Stability to determine / , z and
class He
d. Ambient Temperature : to calculate He
e. Atmospheric Temperature : to calculate He, or to
Lapse Rate determine stability i
some models
f. Incoming solar rediation : to determine "stability
and out-going earth's Class" in some models
re-radiation
All models need (a), (b) and (c) above, while some also
need (d) (e) and (f)
2.7 All meteorological characteristics keep varying from
moment to moment and taking long-time average values
for wind-direction, wind-speed, atmospheric-stability
or even ambient temperature shall be meaningless as the
inter-relationships are not arithmatic or straight line
ones but are very complex. The most reliable approach
may be to take sets of values corresponding to small
specific time periods, compute pollutant concentra-
tions for these small periods and then integrate these
for longer periods, as necessary. Very short initial
averaging periods become impractical due to effort and
cost involved. Practical approach would be to collect
data for 30/60 minute averaging period and either to
carry out computations individually for each such
period and then integrate, or to generate frequency
distributions .for Wind speed-direction-stability
combinations, termed" Stability Wind-roses" and work on
the basis of these. The second approach saves computer
time,but cannot be as reliable or informative as the

6
first particularly if variations and peak concentra-
tions are to be evaluated. And these should always be
of interest even if standards do not talk about them.
Another major question is as to where these wouiJ be
done. Wind-speeds know to vary with height as dcas
temerature and lapse rate and as was ovserved in our
stuides in northern India, even wind direction.
(See Tables 2 & 3). In such a case what point these
characteristics (wind-direction, wind-speed, ambient
temperataure) should relate to? obviously the most
critical would be the values of these parameters at
the point(and height) of pollutant emission though an
idea of variations with height wouil also be desirable
even if not essential.
While parameters like wind-direction,wind-speed amient
temperature and even lapse-rate are easily understood
and their method of determmination well known,
definition and determination of stabliityclasses.
On which so much depends is a much more hazy area. A
preliminary discussion of the simpler approaches is
given is Section 4.
THERMAL STRATIFIICATION AND MIXING HEIGHTS
A considerably complicting facator in modelling
pollutant dispersion is the thermal stratification
existing of the atmosphere, particularly in the ground
layer. Differential heating/ cooling of the different
layers results, in density stratifications, the most
critical of which beacome thermal inversions where
warm layers sitting over colder ones act almost as
flexible lids and block vertical diffusion/dispersion
across them. The inversion occuring close to the
ground surface almost each night and per-down periods,
caused by the back radiation from heated earth-surface

7
and buildiny structures are termed "yround-based
inversion" and very significantly affect pollutant -
dispersions and consequent environmental impacts. The
understanding and characterisation of these inversions
is absolutely essential to any meaninyful modelling of
pollutant dispersions, (see Fig.l)
3.2 By acting as sort of Flexible lids, to block vertical
dispersion, inversions limit the height of the
atmosphere to which it could be considered a mixed
fluid medium. The constrained heights within which
mixing is allowed to take place are termed "Mixiny
Heiyhts" of the atmosphere. It should be obvious that
pollutants discharged within the "mixiny heiyht" zone
shall disperse only within this zone, while those
discharyed above the level of "mixiny heiyht" shall not
come to the yround untill the inversion breaks.
3.3 Conventional pollutant-dispersion modelliny takes
thermal stratification and consequent "mixiny heiyhts"
into account in three ways:
a. Accountiny for these in selection of the
"stability-class".
b. Limitiny maximum plume-rise to (mixiny heiyht-
physical stack heiyht) when the physical stack
top is within the mixiny zone.
c. Limitiny maximum z to mixiny heiyht when the
emission is released within the mixiny zone.
Better and more exact accountiny of thermal strati-
fication in modelliny shall be hiyh'ly desirable even if
rather complex.
3.4 Indian Meteoroloy ica.l Department carries out
measurements of thermal stratifications at selected

8
meteorological stations daily at 5.30 hrs morning and
evening by a technique called "Radio-Sonde". The
technique involves release of a hydrogen-filled ballon
into the atmosphere carrying sensors and transmitter?-;
to signal temperature, pressure, humidity etc. as the
baloon rises up in the atmosphere, thus providing the
thermal structure of the atmosphere. The exact
position of the baloon is tracked by sensitive
instruments at all moments. From the data, the
lapse-rates of different layers and the mixing heiyht
for the time of measurement are obtained. The values
are then extrapolated for other timings of that day.
Such tests are extremely costly, need very sophisti-
cated instrumentation and are not possible for location
of pollutant sources. One has to accept data from
nearest IMD station to be applicable which is rarely
true. A major weakness of "Radio-Sonde" technique and
the data provided by it is that is provides thermal
structure only beyond the lowest 300-400 m above ground
And it is only these lowest 300-400 m that are most
important from air-pollution modelling point of view.
3.5 An alternative shall be to use a tethered hydrogen-
filled baloon carrying an appropriate thermistor cabled
to an instrument on the ground. The baloon can be
lowered/raised to different • heights and the thermal
structure at different times of the day obtained. The
study can be conducted at the sites of proposed
emission sources, or close to existing sources. Some
typical shapes obtained , during Envirotech studies are
given in Fig.l. Although theoretically there is no
limitation, in practice it shall be difficult to use
this method above 100-150 m height above ground. The
method is not automatic and is suite cumbersome.
Capital costs are low but cost of baloons and of
hydrogen supply make operational costs sizeable.

9
3.6 An instrumental technique called "SODAR" is a more
practical alternative. The technique uses longitudinal
(ultra-sound) waves transmitted through a special
antenna and the waves reflected by various atmospheric
non-homoyenuities monitored and interpreted. The
instrumentation now developed and available in India
from National Physical Laboratory New Delhi provides a
continuous picture of stratification and other
atmospheric structures. A typical plot is shown in
Fig.2. From this the mixing heiyhts can be easily
computed. The mixing heights near the J.K. Cement Plant
at Nimbahera, Rajasthan, the first industrial house in
India to commission such environmental studies in India
for parts of recent • months are yiven in Fig 3. The
installation shall cost around Rs.10 lakhs and operating
costs shall be about Rs.'l.O lakh /Year. Thus the method
is not cheap but the information provided by it are
invaluable.
4. DETERMINATION OF STABILITY CLASS.
4.1 As had been discussed in Section 2, determination of
the Stability status or class is essential step in all
pollution-dispersion modelling. There are a number of
alternative methods proposed and used for selecting
"Stability Class" applicable at a particular location
at a Particular time. Some of these are briefly
discussed below:
a. Turner's Table: The simplest method is to use
Turner's Table as given in Table-1 which needs
only average wind-speed and some qualitative
information about solar radiation/cloud cover.
Being very simple and needing very little data, it
is almost the universally adopted method in India.
b. Wind speed nd In-coming/Out-goiny radiation: This
is an improvement over Turner's Table by replacing
the qualitative day/night and solar-radiation/

10
cloud-cover data by actually measurement radiation
data .
Richardson Number Method: Richardson number, or
Bulk Richardson Number Ri, is defined as
R i = g O / z) where y is the acceleration due to
gravity, o the ambient potential temperature, o/ z
the gradient of potential temperature with height
and u/ z the gradient of average wind velocity
with height. Negative Values of Ri indicate
unstable and turbulent atmosphere, larger the
numberical value more the unstability. Zero value
of Ri indicates neutral atmosphere and positive
values "Stable" conditions. Higher the value,
higher the stability.
Slade's Approach (4.5): This uses the
wind-direction fluctuation range over an hour to
compute surface turbulance, o, and the Pasquill's
Stability Class (A to F) is assigned based on the
Value of o.
Stability Length Approach: Stability Length, L,
absolute
the Von
constant
specific
energy and u*, the shear velocity is given by* _
u =( - ) 1/2, being the eddy shear stress.
Dr.Swadas in his Ph.D Thesis (6) described a
method to compute L from , the standard
deviation of wind-direction fluctuations. For
was defind by Monnin - Ob ikhov as below:
L = -u*3
R (q) (H)
1 Cp
L = - u *3 Where T is the
K(g ) (H) temperature.
T p
g the acceleration due to gravity, k
Karman constant CP the specific heat at
pressure, the density of air, H the

11
neutral (or adiabatic) atmosphere, L becomes
infinte, it is negative for unstable conditions
and positive for stable conditions, the numerical
values indicating the extent of stability or
in-stability.
f. SODAR Method: The SODAR plots can also be used to
determine Stability class.
g. There could be other approaches also involving
other micrometeorological characteristics. In fact
there can probably be no micrometeorological
parameter which is not related to Stability Class
and perfact determination of stability appears an
impossible task.
. Table 2 shows some typical Stability Classes as
determined by two different methods. -
4.2 The above discussion would make it abundantly clear
that determining the Stability Class is by far the most
critical, the most difficult and the most doubtful and
hazy step in the entire modelling exercise.
5 . C U R R E N T P R A C T I C E O F O B T A I N I N G M E T E O R O L O G I C A L D A T A
5.1 The most common current practice of consultants and
other agencies involved with EIAs or predicting air
„ pollutant dispersions for other purposes is to obtain
meteorological data from IMD publication such as the
30-years average or "normals" for various parameters
published in book-worm (7). The tables in this
publication provide monthly average frequency
distributions for the morning and evening times for
wind directions divided in 16 sectors and also the
percentage of calm periods. They also yive the average
number of days in the month with wind speeds above 20
km pH. Obviously these data are not adequate to plot

12
wind-roses, to select stability classes or to carry out
any dispersion modelling by any method whatever.
On special arrangement, and on payment, IMD provides
wind-speed and direction-recorder data that can be used
to compile wind-roses. Data on cloud-cover, solar-
radiation, mixing heights etc. can also be obtained
from IMD on special arrangement. However all these data
are for the locations where IMD operates Met-Stations,
with appropriate instrumentation. Thus Radio-Sonde
measurements are carried out only at some 20 stations
spread around the country. Also the wind data is
recorded at 10 m height above G.L.
In many cases, often to satisfy requirements laid down
by Pollution Control Boards, Departments of Environment
and other regulatory agencies, large industrial
establishments (or their consultants) set up weather
monitoring stations. These stations conventionally
include facilities to record temperature, humidity,
pressure, wind speed and wind-direction. Measurements
of lapse-rates, velocity-gradients, solar-radiation or
mixing heights are rarely done.
SHORTCOMINGS OF CURRENT METEOROLOGICAL FRAMEWORK
The shortcomings or lacunae in the meteorological data
currently used (or made available) for dispersion
modelling can be grouped as below:
a. Applicability for the location and height of the
emission source and dispersion area.
b. Parameters needed but usually not done or
available.
c. Reliability, frequency and format of data.

13
6.2 Applicability of Data of Nearest IMD Station: IMD
stations are located at a few selected cities generally
at air-ports. Air-ports are almost always in plain-open
terrain, 15-20 kms or even more from the cities. Thus
while these stations shall provide reliable data on
regional meteorology, they shall not apply to built up,
habitated or industrial areas. The differences between
the met-dta for the Palam Air-port and the Safdarjang
Air-port, the two stations maintained in Delhi and
barely 20 kms apart, shall amply prove this point. How
justified would it be to use Palam data for Panipat,
Karnal, Meerut or Moradabad if it does not hold for
Saf-darjang? And in such a case how meaningful it would
be to carry -out modelling exercises using data from-
far-away IMD stations, separated by undulating
landscape.
6.3 Applicability of IMD Radio-Sonde Data: Besides the fact
of such data being non-applicable due to intervening
distance and terrain separating the point of interest
from the rather sparsely distributed Radio-Sonde
stations, the "mixing-height" and "inversion" data
available has another problem - Radio-Sonde is blind to
the 300-400m surface layer closest to the ground. Since
in air-quality management, it is the layers closest to
the ground that are most important, the "Radio-Sonde"
data is near-useless so far as pollutant-dispersion
modelling is concerned. Desired instrumentation in this
area shall be "SODAR" which can sense layers from 50 to
2000m from GL.
6.4 Applicability of Wind data taken at 10m Height:
Traditionally wind-speed and direction data are
monitored at 10m height above G.L. by DMD as also all
consultants and other agencies. Recording data at this
standard height helps meteorologists compare the wind-
status of different locations. However, the 10m height
data has no relevance to air quality modelling or

14
management. Again in traditional practice one assumes
that wind-direction does not change with height while
wind-speed increases as one goes up, varyiny with
height according to a power-law. Monitoring by
Envirotech at several locations in Northern Indian
plains (including locations in Rajasthan, M .P., U.P.,
Bihar and Assam) have shown that none of the above
.hold, particularly- under conditions of stable
atmosphere and low mixing heights which happen to be
the most critical conditions from air-guality
management point of view. Some recent data from
Nimbahera Rajasthan, given in table 2 and 3 amply
demonstrate it. Thus for meaningful pollution-
dispersion modelling, wind speed and direction
measurements should be done as close as possible to the
height of the emission cource, and not at the standard
10m height.
6.5 Parameters needed for Reliable Stability Classi-
fication: As discussed in Section 4, the weakest link
in dispersion-modelling is the "Stability Class" and
the normal method of determining stability using
turners table is not very reliable. Table 3 gives the
Stability Classes for Nimbahera as determined using
Turner's Table as also those based on Richardson
Number. Obviously Stability Class based on Richardson
Number or on Stability Length or mixing height should
better represent the actual state of the atmosphere
than that based on general judgements or even actual
measurements on incoming or* nett rediation.
7. CHOICE OF DISPERSION MODELS
7.1 ISI/Bureau of Indian Standards suggested the use of
Pasqu.ill-Gif ford and Mc-ElRoy' s models for flat and
undulating terrains respectively in IS-8829. The
choice was guided by the simplicity of the models than
any validation for Indian conditions. Unfortunately

15
it were termed only a "Guideline", there has been
little effort to' validate the models on field and the
models have been applied as Gospel Truth in most
modelling exercises. This should not be allowed to
continue, without adequate validation on field.
7.2 During the past decade, USEPA and other agencies in the
developed countries have developed a number of new
models, e.g. PEM-I, PEM-II, CDM etc. each suited to
handle a particular situation. Package computer-
programmes for these models are paraded as panacea for
modelling needs, are sold for high costs and are used
by consultants as "Statussymbols" and for winning jobs.
Obviously none of these can be considered better than
Pasquill-Gifford or Mc-Ebroy's, until these are
validated on field under Indian conditions-such as a
very large percentage of calm period, very low mixing
heights etc. The same can be said about the various
plume-rise models.
7.3 Currently the best bet seems to be to use - IS: 8829
procedures and in parallel also the models and approach
developed by Prof. M.P. Singh and his group at the
Centre of Atmospheric Sciences, IIT, New Delhi. The
latter though so far not tested under many field
situations, has been especially developed in India,
for Indian conditions, and the limited validation
exercises so far indicate this to be better than other
models tried by the Centre.
8 . SUMMERY AND RECOMMENDATIONS
In summary the following recommendations are made:
(i) Meteorological data should be collected at site.
Modelling on basis of data from the nearest IMD
station is meaningless and may be used only for
preliminary estimates.

16
(ii) Wind data, both speed and direction and
temperature need to be measured at a height as
close to the height of emission as possible. This
implies use of a tall mast and it should be
possible to also measure the parameters at 10m
height and/or some other heights by installing
additional sensors without too large an increase
in cost. The advantages of this will be to
compute Richardson numbers and also much better
overall understanding.
(iii) If logger based instrumentation is used, such as
WM-200, one can directly get hourly average wind-
speed, wind-direction and temperatures as also the
provide additional alternatives for selecting
stability class or using models that need such
data. Two sets of sensors to give these 5
parameters (speed, direction, temperature, jfu and
^ 0) at two different heights on a single mast-
should give enough meteorological data to try
alternate approaches to stability selection and
modelling (it may be mentioned that humidity or
pressure measurements would be unnecessary cost
increases and even radiation recording shall be
much more "costly than the advantage it can
provide).
(iv) If funds permit, installing and operating a SODAR
at the site shall be highly desirable. For large
projects it should be a must.
(v) Several alternative models should be tried and the
one giving the -best field validation for the
particular site or similar conditions should be
adopted.
standard deviations. These can
(vi) A lot of field research is needed in this critical

1?
T A B L E - I
IS 1 8829 - 1978
t a b l e i pasquill stability classes
( Clou.U 3.3.1 )
Suaificr Wind
Speid (it 10m )
Day TIKI IN8OL>
S i r o n g M o d e r a t e S l i g h t
(1) (2) (3) (<)
rr.; i
LeU than 2 A - B B
,,' . , 2 A - B B C
,, 4 B B - C C
,. 6 C C - D D
More than 6 C D D
NIOHT TIME Conditions
8 Clout
Cover
(61
Thin Overcast J> 3,8 Cloud-
or < 4/8
Cloud Cover
(5) .
A
— Extremely unstable
B — Moderately unstable
C — Slightly unstable
E F
D ' E
D D
D D
D — Neutral '
E — Slightly stable
F — Moderately stable
C-a1
' F
°r { A
~B ) U,C
°C
J »"«! B similarly proceed for D — C and
-h^r.tyVc'le^l^^ol^devi^ 'm
P' i e s the amount of incoming solar radiation
' - U g h . * i n s o l a t i o n r e L . T " " 3 5 a " d ^ T h c ' ' < « > " * '
respectively Cr ,0 !
°Ur of
than 60° and less than 35*
IS I 8829 - 1978
2
O
in
cr
UJ
ex
ul
< 2
(_J UJ
^ o
ll
CO
en
UJ
CL
ts>
5 '
<i •
o _
f ~ u
zc ll
o Ll
" UJ
> O
t> o

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LOCV £ S £ s £ N Ai£ NN£ £/Vt A/A£ £ . S £ N £ K'_s A1
2{CV /,'A£ • S U N £ £ N N E A A £ A' IV S
LltL'
£ S E 'siv' e • N N E N N E £ N t A/E S E s S U
£ A E IV'Siv' £ E S E N N £ £ N t N £ s S i- E
2<i00 £ S E J K- E
i
£ MN E E N t
i
E N £ £ N't"
i
s IE

NIMBAHERA ( R A J A S T H A N ) MARCH 6,91 B O K A J A N ( A S S A M ) J [ J N E 2 6 , 6 8
T Y P I C A L A T M O S P H E R I C THERMAL P R O F I L E S MONITORED BY ENVIROTECH
FIG.- 1

Meteorological conditio ns

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