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-