ta ala Ee ae saliccoAiatRS Tellci Hct ete Se dee
*
aoa
TABLE62.
SEASON: MARCHSAPRIL«MAY
DEGREES |
PAND 3
BAKO 3
BANG.2
BAND
BARC 3
FEET
j
1
3
2
2
3
3
3
3
3
32
3
3
DES F
1
.
J7CCO-#*e8| 4- 7 [ AD- a9
[7COP-sese|
46- 7 | BO- 99
Tt207 seee _4-_7_§ 80-99
"7000-*ee2|
@-t2 | 10- 19
}7ToGG-#*e8{
g-12 | 10- 19
BAKO 3 |7€20-e*ee)
BAKC
BAKD
BAND
BAND
BAND
BAKD
BANC
BAND
BAND
BAND
BAND
«KT
1
|
CST
MIN
~ boa
|
[|
{
|
|
OL6
0,03
OC
O7L3
O415
STATION: TAM
25
0.0
0.93
0,0
O-L4
49.20
*
PERIOD OF OATAS JAN 101966 ~ DEC 3151967
PERCENTILE VALUES OF SO2Z(PPMI CONCENTRATIONS
50
75
90
95
98
99°
«MAX
0.90
0.0
9.09
9203
0,13
_t.
t
AAND
BAND
BAND
BAND
BAND
1
2
3
1
2
©6040
0403
06.0
O.16
0424
0.0
0603
0-0
Osl17
0234
0.0
4.03
0.0
O17
043%
0.0
0.93
O-.f
OL?
0.39
0.0
0.03
0.0
Gel?
0.440
0.0
0.03
0.0
0. iv
0.
0.0
09.03
0.0
M017?
Me40
6.0
0.0
6.0
0.0
0.05
9.0
| 0.03
[| 0.0
| 0.16
| O27
[|
1
{|
[
|
1
|
ft
|
§$
1
|
|
BAND
BAND
BAND
BAND
BAND
BAND
BAND
BAND
LD Ocll OelS 624
2 | Oc1T O.22 0629
9 } Oe2O Oel& Os19
L | Ocll O.t2 Oelt
2 $0.13 0.421 0.28
3 | Onl2 Onl8
1 | 0.02 0.02 0.95
2 | 0.03 DelS Oc19
0632
0639
0626
Oe22
0.36
Oedl
0483
0229
Oe22
0.39
Oe42
Oc84
od)
Oe22
0.57
Ooh2
0645
Oe32
(e22
0259
0.42
0.45
0-631
Ge22?
0.38
0.07
O22
9.09
Oe29
0.09
0646
0.10
0646
est
02646
| 0624
| 0.31
| 0.21
| G. 16
| 0629
| Ge2]
[ 0.05
| 020
0
| Oco8
| 0.15
1 0.1027
1 0.0974
| 0.0549
[6.0453
1 6.1191
[|0.0487
¢ 6.0204
# 0.0922
0.0652
10,0383
1 0.0642
0.0
9.0
0.0
0.0
O.0189
0.0756
0.0[ 0.0 {0.0
A
1 9
'
4
14
| 3
|
9
'
6
| BAND L $ 0.02
| BAND 2 1 0.07
0.92
Ge10
02605
Gel3
0.19
0418
Gell
O427
Gell
Oe28
Oolk
OF28
O-12
02.28
8-12 | 60- 69 { BAND 1 1 0.07
98-17 | 60- 69 | BAND 2 | 0.02
0498
0.06
O-12
0-10
Och
0.13
Oc16
0.18
Oel6
0226
O616
0226
0616
0.26
0416
0.26
06.06
0.07
0.02 1 0-11 1 06.0344 1
§
6.13 1 O-12 | 0.9604 | 14
BAND 3 [7CON-seee]
a-12 | To- 79 1 BAND 110.0
0.0
36
BAND 3 {[700f-*#8e{
9-12 £ TO- 79 | BAND 2 | 0.0% 0.05 O497
BAND 2 |7CCC-eeee] 8-42 1 7O- 79 | BAND 3_ 1 0,05 Oe07F 0.10
BAND 3 [7TCCO-*es#|
9-12 | 5O- 89 | BAND 1 10.0
9.0
£0.20
BANC 32 [7CCT—eeee| 9-12 | 80- 69 | BAND 2 10.0
040
0.0
BAND 2. 17CCO-s#48
BAND 3 | 7fCO-#ee8( 13-18 1 30- 39 | BAND 110.0
04.0
O-0
BAND 3 170CO-#eee] 13-18 | 30+ 39 | BAND 2 1 0415 0615 0615
BAND 32 [7CCO-*ee8/ 13-18 | 30- 39 | BAND 3 t OcO On0 O20
BAND 3 170€00-eee8{ 13-18 | 40- 49 | BAND 1 | 6.07 0.07 0.07
BANC 3 | 7COC-*eee| 13-18 | 40- 49 1 BAND 2 | 0.19 0.4.10 On10
BANG 3 17€CO-*8e8(13-15140-49|BAND 3 1 0,08 0.99 0-08
BAND 3 [7¢CC-#ees| 13-18 | 50- 59 | BAND 1 | 0.08 0.98 0.08
BARD 3 ([7C9¢-#eee] 13-18 | 5SO- 59 | BAND 2 10.0
06.9
060
BAND 3 17COC-*e¥8] 13-19 | 50- 59
BAND 3 1 7COC-*¥801 13-18 | 60- 69 | BAND 1 $0.0
000
G60
BAKO 3 {7CCO-##*e| 13-18 | 60- 69 1 BAND 2 1 0.0
O60
O60
BANC 3 |7C00-#e80/ 13-18 [ 60- 69 | BAND 3 } 0,05 0205 0,05
BAND 3 F7000-*eee{ 13-18 | 74 79 | BAND 1 1 O20
G60
O60
BakD 3 170 G0-eeee] 13-18 | TO- T9 | BAND 2 1 O-04 0.04 0.04
BAND 3 17000-9*e8) 13-18 | 7O0- 79 _] BAND3|] 0.0% 0605 O605
BAKD 3 |7C0Q0-*8e0}; 134-18 1 #O- 89 | BAND 1 | O4¢
0.9
0
BAND 3 |7090-*##8| 13-18 { 80- 89 | BAND 2 1 0.08 @.08 0.98
.. BAAD 3 L7CqOo-seee!/13-16|BO- 89 | BAND 3 1 9099 02609 0,09
BAND 3 17000-*e98| 19-24 | 40- 49 | BAND 2 $0.6
0.0
0.0
BANO 3 ([7000+#e8¢( 19-74 | 40- 49 | BAND 2 | 04.16 0216 Oc16
BAND 3 | 7OQ0-*e8e1 19-74 1 40- 49 1BAND. 32 [ 050
O49
Oe
BAND 3 17000-*#80| 19-24 | 50- 59 | BAND L | 0.0
9.0
0.0
BAND 3 | 7GG0-*ee8/ 19-24 | 56- 59 | BAND 2 10.0
0.0
0e0
0.09
Del?
0.9
O60
O60
0210
Oel4
0.0
O06
9260
Os12
Oek4
0.6
O60
066
GelZ
Ool15S
6.0
O60
ah
Gel2
0215
0.6
0.9
6.0
6212
0.15
0.0
£6.20
6.0
0.046
Qs ae
O40
0425
060
0.08
Oo12
0,08
6.08
0.0
O60
0625
000
0.08
Galt
0,08
0.08
O40
O60
0225
O50
0.08
Ool4
0,08
0.08
0.40
OF-0
0425
GeO
6.08
Ool#
0.08
0.08
060
O.6
0425
O10
0.08
O.14
0.08
6.08
6-0
O60
0.40
0.07
050
O.07
0.05
6.0
6.08
0.09
O66
Oc16
O40
0.0
0.0
O60
O49
0.08
O69
0.09
0.05
0.0
0.08
0.09
0.0
0.16
D000
a.0
G60
O20
O60
O08
O40
0.09
0.05
9.0
0.08
0,09
G£.0
O.16
O00
0.0
0.0
O40
0-60
0.08
O60
0.0%
0.05
0.0
0.08
0.09
O-60
O4.16
069
0.0
6.0
O40
8-0
0.08
0-6
0.09
0.05
O66
6.08
0.09
0-0
O.16
)
0.0
6.09
O00
0.25
OO
0.08
O14
0.08
0.086
0.06
&
O40
0.0
0.08
0,0
0.09
06.05
0.0
0.086
0.09
9.6
0416
0.9
6.0
G.0
6.0
0.0
5.0
0.03 | 0.07 | 0.0207
Qs o2
0.10 | 9.0395
6.0 {0.0
0:0 10.0 | 9.0
0.0
£06.0
0.0
0.0 f 0.20 1 0.0500
6.0 | 0,0 |0.06
6.0 { 0.07 | 0.0047
9.02 | 0.12 | G.0700
0.9
{ 5.08 } 0.0
6.6 [ 6.08 | 0.0
0.0 | 0.0 | 0.0
0,15 | 0.0141
0.0
{|
0-0 | 5.06
0,0 § 0.0 | 0.0
0.01 | 0.06 | 0.0122
O.0 | 6.0 { 6.0
6,02 | 0.06 | 6.0223
0.0 {6.05 J 9.0
6.0
$06.0 [| 0.0
0,0
| 0.78 | 0.0
0.0 | 6.09 | 5.0
6.0 [0.0
f 0.6
O60
| 0-16 | 0.0
0.0 |O00 $0.0
6.0
190.0 | 6.0
O.0 {0.0
| 0.0
6.6
0.03
6.69#=5.808.08#0.06 6.6 U.D 8.06 [5.59 TV.0
0.03 06.03 6.03 0.03 9.03 0.9
9.0 {| 0.03 | 3.0
BAND 3 |7CNO-**ee]
BARC 32 [7?ct0-*see{
20- 29
20- 29
20- 29
30- 39
30- 39
30- 39
o0- 69
469- 49
-_4&
| 50- 59
| 50- 59
1} MEAN ! ST DEV (FREO
O7S-25 95-75 t
9.42 0618 6.10
0.45 0.18 5.05
6.32 9.19 0.05
Oe22 010 06.00
0659 0.15 O.21
Ft6,08O,f1
6.19 6.05 0.02
0.46 0.09 0.22
6
9
0,08
Gell 9.07 6,01
0.28 0.09 6.16
BAND 3 [7oCC-*#*8|
|
£
|
|
|
|
|
|
we eee
|
|
)
|
|
g-12 | 1O- 19.1 BAND 3 J. 0.0 0.0 0.00.0 010000010
920.90.0
L7COC—e#ee(
8-12
|709h-seee(
6-12
L7CfC-seee!] 8-12
[7O0C-#eme( 8-12
|} 7CCO-**e8(
98-12
|7TCOO-**e#{
6-12
[7CO0-seee|
9-17
|7L30-#¢e|
8-12
|T7OCo-**ee{317CCC-ee#e,
9-12
170CO-*#e*|
e-12
mo te
Caadeetals,
TasuLatTion PREbicTION TECHNIQUE
_____. PRECIPITATION?NWO
WIND DIR{ CFILING [MIMO SP. Teme)| HoUR_
.
.
.
wae!
fee
de Val
giz | So- 5° | BANO 3 | 0.05.On
BARC 2 N7CCO-#eeel g-12 | BAND
=#e48
=
~
BAND 3 |7TO00Q-e90e0| 19-24 1 70- 79 | SAND 21 7 O60 46.0
BAND 3 17000-8e008{ 19-24 | 7O- 79 | BAND 2 { 0203 0.03
0.060
0.03
rates of dispersion and, consequently, the concentra-
tions observed downwind. The relations between the
meteorological variables and pollutant concentrations
are complex. Various techniques have been used for
depicting these relationships, such as multiple regres-
sion analysis or diffusion equations such as the Sutton
or Gaussian forms.
DESCRIPTION OF THE TABULATION PREDICTION TECHNIQUE
One way of demonstrating the relation between me-
teorological variables and pollutants is by arranging
combinations of relevant meteorological variables in
an ordered sequence and presenting the associated
probability distribution for each entry as shown in
Table 62. This procedure is referred to as the “Tabulation Prediction Technique” or the “Look-up Tech-
nique” and is based on hourly readings. For each com-
bination of meteorological variables the minimum
value, the 10, 25, 50, 75, 90, 95, 98, 99 percentiles, and
maximum value of SQ. concentrations are shown
o
| 9%
|] 9
| 16
f §
1 13
1 9
| 14
| 15
$13
| 4
| 11
7Del?0.060,03 1 0612 | 0.0441 | 10
9-10
0.01
oQ
0
G.£.0
9.10
0.0
9.091
6.02
0.0
6.0
9.0
6.0
04.0
0.0
0.02
6.0
6.03
0.0
0.0
0.0
0.9
6.6
0.0
9.0
0.0
6.0
0.01
9
0.07 {| 9.0098 |
oi3
6,0
5
0
1 13
| 6
on)
{
0
1
0
| 2
{ 0
{
3
|
2
|
4
T 1
on)
{_3.
{
9
a:
| 4
1 6
| 5
tot
t 90
t 4
on
fo
' 1
jf O_
1 o
{ 9
1
TF
' 1
Also presented are the mterquartile ranges, i.e., the
difference in SQ. concentration between the 75th and
25th percentiles, and that of the 95th and 75th percentiles. The number of cases observed for each combination of meteorological variables is shown in the
last column. To arrange combinations of meteorologi-
cal variables into an ordered sequence, each of the
selected variables must first be divided into appropri-
ate bands. For example, wind direction is grouped into >
three class intervals, time of day also into three, wind
speed into five, and so forth. A number is assigned to
each class interval of each variable. Thus any com-
bination of, let us say, five meteorological variables
corresponds to a five-digit number. If letters are assigned to each class of each variable, then any com-
bination would correspond to a five letter word. Since
the combinations of meteorological variables are ordered, it is possible to look up any combination just
as one would look up a namein a telephone book or a
word in a dictionary to obtain the probability distri-