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The long-term concentration of sulphur dioxide at Taj Mahal due to the Mathura Refinery
Atmospheric Environment Vol. 24B, No. 3, pp. 407-411, 1990
0957 1272/90 $3.00+0.00 Pergamon Press pie
Printed in Great Britain.
THE LONG-TERM CONCENTRATION OF SULPHUR DIOXIDE AT TAJ MAHAL DUE TO THE MATHURA REFINERY* P. GOYAL a n d M. P. SINGH Centre for Atmospheric Sciences, Indian Institute of Technology, Hauz Khas, New Delhi-110 016, India (First received 10 June 1987 and in final form 7 June 1990)
Abstract--There was controversy regarding the impact of the Mathura Refinery on the Taj Mahal. Mathura is about 40 km from Agra, where one of the major tourist attractions in India, the Taj Mahal, is located. It is a topic of vital concern that the question whether the quantity of sulphur dioxide released from refinery stacks, either individually or collectively with the amount released from the local sources, would damage the Taj Mahal. To provide answers to such questions preliminary estimates of long-term concentrations, during premonsoon, winter, monsoon and post-monsoon, were computed at distances of 40 km from the refinery. Coinparative studies have been made with different concentration formulae. The long-term concentrations in either season, individually or collectively with the local sources, do not appear to exceed the standards proposed by The Indian Standards Institution. Key word index: Stack, dispersion parameters, effluents, sensitivity, Mathura Refinery.
1. INTRODUCTION A large petroleum refinery has been situated at Mathura by the Indian Oil Corporation about 40 km upwind of Agra, which is the site of India's most important tourist attraction, the Taj Mahal. This refinery is situated northwest of Agra. Sulphur dioxide (SO2) has been identified as a major pollutant of refinery effluents. Sulphur dioxide is a toxic gas which, in sunlight, reacts with either atomic or molecular oxygen to form an acid, particularly when water vapour is present. This is dilute sulphuric acid which, over a long period, corrodes marble and other building materials. To have an idea of the possible quantity of pollutants and their effect on the Taj Mahal, the present study was undertaken to obtain long-term concentrations of sulphur dioxide during winter, premonsoon, monsoon and post-monsoon periods. Computations were made only for the northwest sector which was considered mainly responsible for transport of pollutants towards Agra. A look at the meteorological data of Mathura reveals the fact that most of the time wind blows from the northwesterly direction. Therefore, it is worth studying the impact of the Mathura Refinery on the Taj Mahal. A previous work by Raghavan et al. (1983) showed that a considerable amount of the SO2 concentration at the Taj Mahal is contributed by local sources from Agra. There is a substantial level of pollution of sulphur dioxide in the Agra region. The possible sources are all * This paper was presented at the International Conference on Tropical Micrometeorology and Air Pollution, New Delhi, India, 15-19 February 1988.
coal users comprising two power plants, a number of small industries--mainly foundries (approximately 250)--and a railway shunting yard. Even though the total amount of emission of sulphur dioxide from these sources may be small, on account of their proximity to the monument, their contribution to the air quality of the zone will be considerably high. In this study low wind speed and calm intervals have also been treated separately. The main objective of the present study is to assist in planning the protection for the Taj Mahal and other monuments. The present study is taken up to verify the claim that the refinery plays only a small role in affecting the Taj Mahal compared with local pollution from Agra. To investigate the effect of Mathura Refinery on the Taj Mahal, two different concentration formulae have been used in the present study.
2. MODEL CHARACTERISTICS The urban pollution models which permit quantitative determination of ambient air concentrations in relation to emission sources and meteorological conditions, are widely used in regulation and urban planning for impact analysis of existing or new sources and evaluation of control strategies. In the present study, the relative performance of the two different formulae are evaluated by comparing the concentration estimates with measured concentrations on the four season database at Mathura. The first formula (formula I) selected is the simple direct approach with a few assumptions. (1) At a range of 40 km, the pollution released from the refinery will have become reasonably well-mixed
407
408
P. GOYAL
and
throughout the mixing layer. Hence we do not need to concern ourselves with the plume rise formulae or 6, curves. We simply apply the conservation of mass which states that what is emitted must flow out of the box. (2) We assume that, at night, the pollution is emitted above the turbulent mixing layer and contributes nothing to the Taj Mahal concentrations. (3) The wind direction is northwesterly and the sector is 22.5”. It is generally observed that most of the plumes are contained within an angle of approximately 30”. Hence it is assumed that the sources which lie outside this sector do not contribute to the concentration at the receptor. For convenience and taking into account all 16 wind directions, the plume angle is taken as 22.5”. Continuity
Q = uhdC,
says
(1)
where
M. P. SINGH In addition, the following assumptions made.
(i) Flat terrain (ii) Turbulent diffusion in the downwind direction can be neglected compared to transport. (iii) Sulphur dioxide is chemically and physically inactive. Plume rise
It was also found in the present study that plumes coming from individual stacks do not interact with each other. Therefore the concentrations obtained from each stack are added up to obtain the net concentration of SOZ. The plume rise was obtained by Lutes et al. (1963). This required minimum data which are conveniently available at several meteorologial stations. The expressions for plume rise used in the present study are
Q = emission rate of eight stacks of refinery in g day-l
60+5H Ah= 7
h = mixing height
116 Ah = -
160 and Ah= Qi!,‘” averaged over day
where f=fraction of time that the wind blows from the northwest with speed u. The second formula (formula II) we used in this study is basically taken from Smith (1968) and Turner (1970). The long-term ground-level concentration for a period of a month or more can be computed by
where
Q;”
U
C = ground level concentration u = mean wind speed.
x(x, 0, z)=
Q:'"for unstable
3afQ f#J*s~z&s,Ux exp [
--
hZ 20: 1
and
neutral
stratification
d = 40 km, sin 22.5”
Ground-level concentration and night is given as
were also
(3)
4 = angular width of direction sector in degrees,
f = percentage frequency occurrence of winds in a particular direction, wind group and stability during the period of interest. h = effective stack height (m) a, = vertical dispersion parameters for an elevated source (m) Q = emission rate of SO, (pg s-i) u = mean wind speed at stack height (ms- ‘) x = distance downwind from the stack (m). It is assumed that the effluents are uniformly distributed in the horizontal within the sector. The Mathura Refinery is located on flat terrain.
U
for low winds and stable atmospheric conditions for stable atmospheres high wind speed.
and
Here, Ah is the plume rise, H is the physical stack height, Qi, is the stack heat emission rate and u is the mean wind velocity. Thus the effective stack height is calculated as h=H+Ah. MODEL evaluation
A computer program of formula II has been developed on HP-1000 at IIT Delhi to predict the monthly or the seasonal mean of sulphur dioxide concentrations for the city of Mathura. 3. INPUT
PARAMETERS
The present study requires the following input parameters. (a) Stack characteristics. Stack emissions from all eight stacks of the refinery are given in Table 1, taken from the IMD Report (1980). (b) Meteorological parameters. For evaluating the concentration contribution due to elevated sources, wind and stability frequencies are required. In addition, eZ, the vertical dispersion parameter for elevated sources as a function of stability is requied. The seasonal wind frequency Tables 2, 3, 4 and 5 were obtained from Interim Report No. 3 for the period January 1979-December 1980 for Mathura. The four seasons chosen for the present study are winter, pre-monsoon, monsoon and post-monsoon. Since, climatologically, Mathura is not different from Delhi, the monthly mixing heights for Delhi computed by Manju Kumari (1985) are directly used in the present study.
Long-term concentration of sulphur dioxide
409
Table 1. Emission rates of SO2 from all eight stacks of the refinery
Stack no.
Height of stack (m)
1 2 3 4 5 6 7 8
Emissions from refinery Rate of emission Heat emission of SO2 (/~gm -a) rate (MW)
80 40 60 60 80 62 80 116
It is seen that quite often the measured wind speed is less than 1 ms -1. It is well known that Gaussian models grossly overpredict concentrations under low wind speed conditions if the conventional values for a and b appropriate to each Pasquill's stability class are used. Also, contributions to long-term concentration during calm conditions are usually neglected. Draxler (1979) has defined a z in terms of k, the coefficient of eddy diffusivity for each Pasquill stability category az = 2x//~/t~. Thus, the dispersion parameter becomes a function of not only distance but also of the mean wind velocity. This form of the dispersion parameter has been used in the present study. The question of the calm intervals (mean wind speed < 1 m s - 1) remains. It is known that under such conditions the wind is very variable. Thus it is assumed in this study that all directions are equally probable and the mean wind speed associated with these periods is 0.5 m s - 1.
4.71 × 107 0.0806 x 107 0.0754 x 107 0.0754 × 10 7 5.91 X 10 7 0.247 × 10 7 1.87 x 107 8.47 x 107
62.4 12.4 2.6 2.6 18.5 3.9 0.8 33.0
Table 2. Winter wind frequencies (in per cent)
2 N NNE NE ENE E ESE SE SSE S SSW SW WSW W WNW NW NNW
9.5 0.8 1.2 0.9 2.6 0.9 1.2 0.5 0.6 0.4 1.0 2.4 5.3 5.6 6.0 4.6
Winter Wind speed classes (ms-1) 5 8.5 14 1.0 0.6 0.9 0.6 1.8 0.7 0.9 0.3 0.4 0.3 0.7 1.7 3.4 3.9 4.2 3.2
4.6 0.4 0.6 0.4 1.2 0.4 0.6 0.2 0.3 0.2 0.5 1.1 2.5 2.6 2.8 2.3
-0.0 0.1 0.1 0.1 0.3 0.1 0.2 0.1 0.1 0.5 0.1 0.3 0.6 0.7 0.7 0.6
19 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Table 3. Pre-monsoon wind frequencies (in per cent) 4. RESULTSAND DISCUSSION Computations were made with Mathura data in Equation (2) (formula I) and in Equation (3) (formula II) to obtain long-term ground-level concentrations of SO 2 at Agra, utilizing 2 years' wind data from Mathura. The present computations for formula I assume a single source of emission of SO 2 as 2.144 x 10 s #g s - 1 while the computations using Equation (3) assume multiple stacks. The long-term seasonal contribution of sulphur dioxide from the refinery at the Taj Mahal, Agra, is presented in Table 6. I M D have indicated that the increase in the long term seasonal concentration of sulphur dioxide at Agra on account of the refinery would be one microgram per cubic meter. Computation of formula II were better than computation compiled by formula I. The main reason of this discrepancy might be the effect of multiple stacks in formula II. In general, the predicted concentrations due to two different formulae are in reasonable agreement with I M D observed concentrations 1 # g m -3, although there is a tendency towards underprediction. It must
N NNE NE ENE E ESE SE SSE S SSW SW WSW W WNW NW NNW
2
Pre-monsoon Wind speed classes (ms-1) 5 8.5 14
19
3.2 2.3 1.4 2.8 1.8 1.2 0.8 2.2 1.3 0.7 0.7 2.5 2.7 4.7 5.3 3.4
24 1.7 1.1 2.1 1.4 0.9 0.6 1.7 1.0 0.5 0.5 1.9 2.1 3.6 3.9 2.6
0.2 0.1 0.0 0.2 0.1 0.l 0.1 0.l 0.0 0.0 0.0 0.1 0.0 0.9 0.0 0.0
2.2 1.6 1.0 2.0 1.3 0.8 0.6 1.6 0.9 0.5 0.5 1.8 1.9 3.3 3.7 2.4
0.0 0.4 0.3 0.5 0.3 0.2 0.2 0.4 0.2 0.4 0.1 0.5 0.5 0.9 1.0 0.7
be emphasized that the study using formula II is handicapped by a lack of field data under Indian conditions while using diffusion coefficients which are used in extra-tropical latitudes. It is not clear how far
410
P. GOYAL and M. P. SINGH Table 4. Monsoon wind frequencies (in per cent)
Wind dir. N NNE NE ENE E ESE SE SSE S SSW SW WSW W WNW NW NWN
2 0.5 1.0 1.0 1.9 4.8 1.9 2.4 1.6 1.9 1.5 2.8 4.1 1.9 1.4 0.9 0.4
Wind speed classes (ms-~) 5 8.5 14 0.4 0.8 0.8 1.6 3.4 1.6 2.0 0.8 1.6 1.2 1.9 8.4 1.6 1.1 0.8 0.3
0.5 4.0 1.0 1.9 4.8 1.9 2.4 1.6 1.9 1.5 2.3 4.1 1.9 1.4 0.9 0.4
0.3 0.5 0.5 0.9 2.3 0.9 1.1 0,5 0,9 0,7 1.1 2.0 0.9 0.6 0.4 0.2
19 0.1 0.1 0.l 0.2 0.5 0.2 0.2 0.1 0.2 0.2 0.2 0.4 0.2 0.1 0.7 0.0
~ O
O O
u~ .o~
~J o
O
u~
,7
u~
Table 5. Post-monsoon wind frequencies (in per cent) ..=
Wind dir. N NNE NE ENE E ESE SE SSE S SSW SW WSW W WNW NW NWN
2 4.2 2,8 2.5 3.7 3.9 1.7 2.3 3.1 3.3 2.6 2.7 5,9 7.1 6,2 7.7 7.9
Wind speed classes (ms- t) 5 8.5 14 0.9 0.8 0.5 0.8 0.8 0.4 0.5 0.7 0.7 0.6 0.8 1.3 1.5 1.4 1.7 1.7
0.7 0.6 0.4 0.6 0.6 0.3 0.4 0.5 0.5 0.4 0.6 0.9 1.1 1.0 1.2 1,3
0.3 0.2 0.1 0.2 0.2 0,! 0.1 0.2 0.2 0.2 0.2 0.3 0.4 0.4 0.4 0.5
19 0.9 0.1 0.0 0.I 0.1 0.0 0.0 0.0 0.0 0.0 0.7 0.1 0.1 0.1 0.1 0.1
~ o ~ 0
O "O
~ O
c5
c~
.o c5
u~
,, O
m
u
O
e 8
these values would be applicable in India, without further field experiments. One of the shortcomings of the present study is in the assumption of a stationary meteorological condition, i.e. the speed and direction of wind and atmospheric stability are considered constant during the transport of pollutants. The emission rate is one of the most important
O
e
.o
c5 ~e~ ~
.2 ,. NN
O
r..)
parameters in the model input. Because SO: emissions generally result from combustion of a fossil fuel, variation in fuel characteristics as well as load factors can cause uncertainty in quantifying the emissions. At s u b u r b a n stations such as Agra, point sources are significant only during the hours when the a t m o s p h e r e shifts from stable to unstable conditions. The different features between urban and s u b u r b a n sites reflect the differences in point source distribution. In suburban locations, the concentrations mostly come from large point sources, and in urban locations, the fluctuations
O
-o'~ =.~
~o Z
Long-term concentration of sulphur dioxide in concentration are more likely to be a response to the nearby small point sources. Despite these drawbacks and limitations, the main conclusions of the present study may be summarized as follows.
5. CONCLUSIONS SO2 has been taken as a parameter to evaluate the increase in atmospheric pollution in the Agra Zone caused by the Mathura Refinery. This is because SO2 is the lone polluting substance emitted by the refinery which can reach Agra. Even if it reaches Agra, it is only present in very small concentrations. For a distance of 4 0 k m (between Agra and Mathura) the results estimated using a direct simple approach and a mathematical model of Gaussian type are nearly the same. This concludes that, for such a long distance, the pollutants are so well-mixed in the atmosphere that dispersion parameters are no longer important. In consideration of the great distance between Mathura and Agra, the calculated values should be considered even more valid the longer the period to which they refer. This means that the most valid are the annual averages, less valid are the seasonal averages and even less significant are the short-term averages. The average mean annual theoretical concentration of SO 2 in Agra caused by the Mathura Refinery is very much reduced, i.e. 1.5-2.0/~gm -3. Analogously, the seasonal averages go from 0.5-1/~gm -3 (monsoon period) to 3/~gm -3 (winter). Therefore, it can be affirmed that the atmospheric pollution caused by the refinery does not constitute, except for improbably high levels of concentrations due to exceptionally bad meteorological conditions, a modifying element of the atmospheric situation of Agra, due to its extremely low levels of concentration which it could add to the already existing low levels. Therefore, in conclusion, since the concentration levels of SO2 pollutants taken into consideration are
411
very low, it can be taken for granted that the atmospheric pollution actually present in the Agra zone does not constitute a prevailing cause of alteration such as to increase notably the natural aging of the stone. For this reason, although keeping in mind the state of conservation of the stones and on the accumulation effect, it can be considered that the foreseen pollution levels will not form one of the main causes of deterioration of the monuments. It is necessary to remember that the annual increase of SO2 of 1.5-2.0/~g m - 3 is the result of theoretical calculations which, although carried out with due care, have necessarily large margins of uncertainty connected to the schematization taken for the meteorological parameters. Acknowledoements--The authors wish to thank Dr D. J.
Moore and Dr R. E. Britter for their valuable suggestions for the present work.
REFERENCES
Draxler D. R. (1979) An improved Gaussian model for long term average air concentration estimates. Atmospheric Environment 14, 597-601. I.M.D. Report (1980) The dispersal of pollutants from a refinery stack. Prepared by India Meteorological Department, New Delhi, September, 1980. Interim Report No. 2 (1979) Environmental impact of Mathura Refinery--observationalprogrammes for investigation of pollution by India Meteorological Department. Luces D. H., Moore D. J. and Spurn G. (1963) The rise of hot plumes from chimneys. Int. J. Air Wat. Pollut. 7, 473-500. Manju Kumari (1985) Diurnal variation of mean mixing depth in different months at Delhi. Mausam 36, 71-74. Ragfiavan Nirupama, Pramila Goyal and Swati Basu (1983) A Gaussian model for predicting SO2 concentration in the city of Agra. Atmospheric Environment 17, 2199-2203. Smith F. B. (1979) Recommended for prediction of airborne effluents. ASME IX, 86. Turner D. B. (1970) Workbook of atmospheric dispersion estimates. U.S. Dept. of Health Service, Washington, DC.
0957 1272/90 $3.00+0.00 Pergamon Press pie
Printed in Great Britain.
THE LONG-TERM CONCENTRATION OF SULPHUR DIOXIDE AT TAJ MAHAL DUE TO THE MATHURA REFINERY* P. GOYAL a n d M. P. SINGH Centre for Atmospheric Sciences, Indian Institute of Technology, Hauz Khas, New Delhi-110 016, India (First received 10 June 1987 and in final form 7 June 1990)
Abstract--There was controversy regarding the impact of the Mathura Refinery on the Taj Mahal. Mathura is about 40 km from Agra, where one of the major tourist attractions in India, the Taj Mahal, is located. It is a topic of vital concern that the question whether the quantity of sulphur dioxide released from refinery stacks, either individually or collectively with the amount released from the local sources, would damage the Taj Mahal. To provide answers to such questions preliminary estimates of long-term concentrations, during premonsoon, winter, monsoon and post-monsoon, were computed at distances of 40 km from the refinery. Coinparative studies have been made with different concentration formulae. The long-term concentrations in either season, individually or collectively with the local sources, do not appear to exceed the standards proposed by The Indian Standards Institution. Key word index: Stack, dispersion parameters, effluents, sensitivity, Mathura Refinery.
1. INTRODUCTION A large petroleum refinery has been situated at Mathura by the Indian Oil Corporation about 40 km upwind of Agra, which is the site of India's most important tourist attraction, the Taj Mahal. This refinery is situated northwest of Agra. Sulphur dioxide (SO2) has been identified as a major pollutant of refinery effluents. Sulphur dioxide is a toxic gas which, in sunlight, reacts with either atomic or molecular oxygen to form an acid, particularly when water vapour is present. This is dilute sulphuric acid which, over a long period, corrodes marble and other building materials. To have an idea of the possible quantity of pollutants and their effect on the Taj Mahal, the present study was undertaken to obtain long-term concentrations of sulphur dioxide during winter, premonsoon, monsoon and post-monsoon periods. Computations were made only for the northwest sector which was considered mainly responsible for transport of pollutants towards Agra. A look at the meteorological data of Mathura reveals the fact that most of the time wind blows from the northwesterly direction. Therefore, it is worth studying the impact of the Mathura Refinery on the Taj Mahal. A previous work by Raghavan et al. (1983) showed that a considerable amount of the SO2 concentration at the Taj Mahal is contributed by local sources from Agra. There is a substantial level of pollution of sulphur dioxide in the Agra region. The possible sources are all * This paper was presented at the International Conference on Tropical Micrometeorology and Air Pollution, New Delhi, India, 15-19 February 1988.
coal users comprising two power plants, a number of small industries--mainly foundries (approximately 250)--and a railway shunting yard. Even though the total amount of emission of sulphur dioxide from these sources may be small, on account of their proximity to the monument, their contribution to the air quality of the zone will be considerably high. In this study low wind speed and calm intervals have also been treated separately. The main objective of the present study is to assist in planning the protection for the Taj Mahal and other monuments. The present study is taken up to verify the claim that the refinery plays only a small role in affecting the Taj Mahal compared with local pollution from Agra. To investigate the effect of Mathura Refinery on the Taj Mahal, two different concentration formulae have been used in the present study.
2. MODEL CHARACTERISTICS The urban pollution models which permit quantitative determination of ambient air concentrations in relation to emission sources and meteorological conditions, are widely used in regulation and urban planning for impact analysis of existing or new sources and evaluation of control strategies. In the present study, the relative performance of the two different formulae are evaluated by comparing the concentration estimates with measured concentrations on the four season database at Mathura. The first formula (formula I) selected is the simple direct approach with a few assumptions. (1) At a range of 40 km, the pollution released from the refinery will have become reasonably well-mixed
407
408
P. GOYAL
and
throughout the mixing layer. Hence we do not need to concern ourselves with the plume rise formulae or 6, curves. We simply apply the conservation of mass which states that what is emitted must flow out of the box. (2) We assume that, at night, the pollution is emitted above the turbulent mixing layer and contributes nothing to the Taj Mahal concentrations. (3) The wind direction is northwesterly and the sector is 22.5”. It is generally observed that most of the plumes are contained within an angle of approximately 30”. Hence it is assumed that the sources which lie outside this sector do not contribute to the concentration at the receptor. For convenience and taking into account all 16 wind directions, the plume angle is taken as 22.5”. Continuity
Q = uhdC,
says
(1)
where
M. P. SINGH In addition, the following assumptions made.
(i) Flat terrain (ii) Turbulent diffusion in the downwind direction can be neglected compared to transport. (iii) Sulphur dioxide is chemically and physically inactive. Plume rise
It was also found in the present study that plumes coming from individual stacks do not interact with each other. Therefore the concentrations obtained from each stack are added up to obtain the net concentration of SOZ. The plume rise was obtained by Lutes et al. (1963). This required minimum data which are conveniently available at several meteorologial stations. The expressions for plume rise used in the present study are
Q = emission rate of eight stacks of refinery in g day-l
60+5H Ah= 7
h = mixing height
116 Ah = -
160 and Ah= Qi!,‘” averaged over day
where f=fraction of time that the wind blows from the northwest with speed u. The second formula (formula II) we used in this study is basically taken from Smith (1968) and Turner (1970). The long-term ground-level concentration for a period of a month or more can be computed by
where
Q;”
U
C = ground level concentration u = mean wind speed.
x(x, 0, z)=
Q:'"for unstable
3afQ f#J*s~z&s,Ux exp [
--
hZ 20: 1
and
neutral
stratification
d = 40 km, sin 22.5”
Ground-level concentration and night is given as
were also
(3)
4 = angular width of direction sector in degrees,
f = percentage frequency occurrence of winds in a particular direction, wind group and stability during the period of interest. h = effective stack height (m) a, = vertical dispersion parameters for an elevated source (m) Q = emission rate of SO, (pg s-i) u = mean wind speed at stack height (ms- ‘) x = distance downwind from the stack (m). It is assumed that the effluents are uniformly distributed in the horizontal within the sector. The Mathura Refinery is located on flat terrain.
U
for low winds and stable atmospheric conditions for stable atmospheres high wind speed.
and
Here, Ah is the plume rise, H is the physical stack height, Qi, is the stack heat emission rate and u is the mean wind velocity. Thus the effective stack height is calculated as h=H+Ah. MODEL evaluation
A computer program of formula II has been developed on HP-1000 at IIT Delhi to predict the monthly or the seasonal mean of sulphur dioxide concentrations for the city of Mathura. 3. INPUT
PARAMETERS
The present study requires the following input parameters. (a) Stack characteristics. Stack emissions from all eight stacks of the refinery are given in Table 1, taken from the IMD Report (1980). (b) Meteorological parameters. For evaluating the concentration contribution due to elevated sources, wind and stability frequencies are required. In addition, eZ, the vertical dispersion parameter for elevated sources as a function of stability is requied. The seasonal wind frequency Tables 2, 3, 4 and 5 were obtained from Interim Report No. 3 for the period January 1979-December 1980 for Mathura. The four seasons chosen for the present study are winter, pre-monsoon, monsoon and post-monsoon. Since, climatologically, Mathura is not different from Delhi, the monthly mixing heights for Delhi computed by Manju Kumari (1985) are directly used in the present study.
Long-term concentration of sulphur dioxide
409
Table 1. Emission rates of SO2 from all eight stacks of the refinery
Stack no.
Height of stack (m)
1 2 3 4 5 6 7 8
Emissions from refinery Rate of emission Heat emission of SO2 (/~gm -a) rate (MW)
80 40 60 60 80 62 80 116
It is seen that quite often the measured wind speed is less than 1 ms -1. It is well known that Gaussian models grossly overpredict concentrations under low wind speed conditions if the conventional values for a and b appropriate to each Pasquill's stability class are used. Also, contributions to long-term concentration during calm conditions are usually neglected. Draxler (1979) has defined a z in terms of k, the coefficient of eddy diffusivity for each Pasquill stability category az = 2x//~/t~. Thus, the dispersion parameter becomes a function of not only distance but also of the mean wind velocity. This form of the dispersion parameter has been used in the present study. The question of the calm intervals (mean wind speed < 1 m s - 1) remains. It is known that under such conditions the wind is very variable. Thus it is assumed in this study that all directions are equally probable and the mean wind speed associated with these periods is 0.5 m s - 1.
4.71 × 107 0.0806 x 107 0.0754 x 107 0.0754 × 10 7 5.91 X 10 7 0.247 × 10 7 1.87 x 107 8.47 x 107
62.4 12.4 2.6 2.6 18.5 3.9 0.8 33.0
Table 2. Winter wind frequencies (in per cent)
2 N NNE NE ENE E ESE SE SSE S SSW SW WSW W WNW NW NNW
9.5 0.8 1.2 0.9 2.6 0.9 1.2 0.5 0.6 0.4 1.0 2.4 5.3 5.6 6.0 4.6
Winter Wind speed classes (ms-1) 5 8.5 14 1.0 0.6 0.9 0.6 1.8 0.7 0.9 0.3 0.4 0.3 0.7 1.7 3.4 3.9 4.2 3.2
4.6 0.4 0.6 0.4 1.2 0.4 0.6 0.2 0.3 0.2 0.5 1.1 2.5 2.6 2.8 2.3
-0.0 0.1 0.1 0.1 0.3 0.1 0.2 0.1 0.1 0.5 0.1 0.3 0.6 0.7 0.7 0.6
19 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Table 3. Pre-monsoon wind frequencies (in per cent) 4. RESULTSAND DISCUSSION Computations were made with Mathura data in Equation (2) (formula I) and in Equation (3) (formula II) to obtain long-term ground-level concentrations of SO 2 at Agra, utilizing 2 years' wind data from Mathura. The present computations for formula I assume a single source of emission of SO 2 as 2.144 x 10 s #g s - 1 while the computations using Equation (3) assume multiple stacks. The long-term seasonal contribution of sulphur dioxide from the refinery at the Taj Mahal, Agra, is presented in Table 6. I M D have indicated that the increase in the long term seasonal concentration of sulphur dioxide at Agra on account of the refinery would be one microgram per cubic meter. Computation of formula II were better than computation compiled by formula I. The main reason of this discrepancy might be the effect of multiple stacks in formula II. In general, the predicted concentrations due to two different formulae are in reasonable agreement with I M D observed concentrations 1 # g m -3, although there is a tendency towards underprediction. It must
N NNE NE ENE E ESE SE SSE S SSW SW WSW W WNW NW NNW
2
Pre-monsoon Wind speed classes (ms-1) 5 8.5 14
19
3.2 2.3 1.4 2.8 1.8 1.2 0.8 2.2 1.3 0.7 0.7 2.5 2.7 4.7 5.3 3.4
24 1.7 1.1 2.1 1.4 0.9 0.6 1.7 1.0 0.5 0.5 1.9 2.1 3.6 3.9 2.6
0.2 0.1 0.0 0.2 0.1 0.l 0.1 0.l 0.0 0.0 0.0 0.1 0.0 0.9 0.0 0.0
2.2 1.6 1.0 2.0 1.3 0.8 0.6 1.6 0.9 0.5 0.5 1.8 1.9 3.3 3.7 2.4
0.0 0.4 0.3 0.5 0.3 0.2 0.2 0.4 0.2 0.4 0.1 0.5 0.5 0.9 1.0 0.7
be emphasized that the study using formula II is handicapped by a lack of field data under Indian conditions while using diffusion coefficients which are used in extra-tropical latitudes. It is not clear how far
410
P. GOYAL and M. P. SINGH Table 4. Monsoon wind frequencies (in per cent)
Wind dir. N NNE NE ENE E ESE SE SSE S SSW SW WSW W WNW NW NWN
2 0.5 1.0 1.0 1.9 4.8 1.9 2.4 1.6 1.9 1.5 2.8 4.1 1.9 1.4 0.9 0.4
Wind speed classes (ms-~) 5 8.5 14 0.4 0.8 0.8 1.6 3.4 1.6 2.0 0.8 1.6 1.2 1.9 8.4 1.6 1.1 0.8 0.3
0.5 4.0 1.0 1.9 4.8 1.9 2.4 1.6 1.9 1.5 2.3 4.1 1.9 1.4 0.9 0.4
0.3 0.5 0.5 0.9 2.3 0.9 1.1 0,5 0,9 0,7 1.1 2.0 0.9 0.6 0.4 0.2
19 0.1 0.1 0.l 0.2 0.5 0.2 0.2 0.1 0.2 0.2 0.2 0.4 0.2 0.1 0.7 0.0
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Table 5. Post-monsoon wind frequencies (in per cent) ..=
Wind dir. N NNE NE ENE E ESE SE SSE S SSW SW WSW W WNW NW NWN
2 4.2 2,8 2.5 3.7 3.9 1.7 2.3 3.1 3.3 2.6 2.7 5,9 7.1 6,2 7.7 7.9
Wind speed classes (ms- t) 5 8.5 14 0.9 0.8 0.5 0.8 0.8 0.4 0.5 0.7 0.7 0.6 0.8 1.3 1.5 1.4 1.7 1.7
0.7 0.6 0.4 0.6 0.6 0.3 0.4 0.5 0.5 0.4 0.6 0.9 1.1 1.0 1.2 1,3
0.3 0.2 0.1 0.2 0.2 0,! 0.1 0.2 0.2 0.2 0.2 0.3 0.4 0.4 0.4 0.5
19 0.9 0.1 0.0 0.I 0.1 0.0 0.0 0.0 0.0 0.0 0.7 0.1 0.1 0.1 0.1 0.1
~ o ~ 0
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these values would be applicable in India, without further field experiments. One of the shortcomings of the present study is in the assumption of a stationary meteorological condition, i.e. the speed and direction of wind and atmospheric stability are considered constant during the transport of pollutants. The emission rate is one of the most important
O
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parameters in the model input. Because SO: emissions generally result from combustion of a fossil fuel, variation in fuel characteristics as well as load factors can cause uncertainty in quantifying the emissions. At s u b u r b a n stations such as Agra, point sources are significant only during the hours when the a t m o s p h e r e shifts from stable to unstable conditions. The different features between urban and s u b u r b a n sites reflect the differences in point source distribution. In suburban locations, the concentrations mostly come from large point sources, and in urban locations, the fluctuations
O
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Long-term concentration of sulphur dioxide in concentration are more likely to be a response to the nearby small point sources. Despite these drawbacks and limitations, the main conclusions of the present study may be summarized as follows.
5. CONCLUSIONS SO2 has been taken as a parameter to evaluate the increase in atmospheric pollution in the Agra Zone caused by the Mathura Refinery. This is because SO2 is the lone polluting substance emitted by the refinery which can reach Agra. Even if it reaches Agra, it is only present in very small concentrations. For a distance of 4 0 k m (between Agra and Mathura) the results estimated using a direct simple approach and a mathematical model of Gaussian type are nearly the same. This concludes that, for such a long distance, the pollutants are so well-mixed in the atmosphere that dispersion parameters are no longer important. In consideration of the great distance between Mathura and Agra, the calculated values should be considered even more valid the longer the period to which they refer. This means that the most valid are the annual averages, less valid are the seasonal averages and even less significant are the short-term averages. The average mean annual theoretical concentration of SO 2 in Agra caused by the Mathura Refinery is very much reduced, i.e. 1.5-2.0/~gm -3. Analogously, the seasonal averages go from 0.5-1/~gm -3 (monsoon period) to 3/~gm -3 (winter). Therefore, it can be affirmed that the atmospheric pollution caused by the refinery does not constitute, except for improbably high levels of concentrations due to exceptionally bad meteorological conditions, a modifying element of the atmospheric situation of Agra, due to its extremely low levels of concentration which it could add to the already existing low levels. Therefore, in conclusion, since the concentration levels of SO2 pollutants taken into consideration are
411
very low, it can be taken for granted that the atmospheric pollution actually present in the Agra zone does not constitute a prevailing cause of alteration such as to increase notably the natural aging of the stone. For this reason, although keeping in mind the state of conservation of the stones and on the accumulation effect, it can be considered that the foreseen pollution levels will not form one of the main causes of deterioration of the monuments. It is necessary to remember that the annual increase of SO2 of 1.5-2.0/~g m - 3 is the result of theoretical calculations which, although carried out with due care, have necessarily large margins of uncertainty connected to the schematization taken for the meteorological parameters. Acknowledoements--The authors wish to thank Dr D. J.
Moore and Dr R. E. Britter for their valuable suggestions for the present work.
REFERENCES
Draxler D. R. (1979) An improved Gaussian model for long term average air concentration estimates. Atmospheric Environment 14, 597-601. I.M.D. Report (1980) The dispersal of pollutants from a refinery stack. Prepared by India Meteorological Department, New Delhi, September, 1980. Interim Report No. 2 (1979) Environmental impact of Mathura Refinery--observationalprogrammes for investigation of pollution by India Meteorological Department. Luces D. H., Moore D. J. and Spurn G. (1963) The rise of hot plumes from chimneys. Int. J. Air Wat. Pollut. 7, 473-500. Manju Kumari (1985) Diurnal variation of mean mixing depth in different months at Delhi. Mausam 36, 71-74. Ragfiavan Nirupama, Pramila Goyal and Swati Basu (1983) A Gaussian model for predicting SO2 concentration in the city of Agra. Atmospheric Environment 17, 2199-2203. Smith F. B. (1979) Recommended for prediction of airborne effluents. ASME IX, 86. Turner D. B. (1970) Workbook of atmospheric dispersion estimates. U.S. Dept. of Health Service, Washington, DC.