Chapter Ill Air Quality Indices: A Brief...

Chapter - Ill

Air Quality Indices: A Brief Review

Air Quality monitoring is carried out to determine the air quality. status and the

'effectiveness' of the air pollution control programme in a given environment. It is a

complex procedure to evaluate the status of overall air pollution since the pollutants have

synergistic interactions among themselves and have adverse effects on the living beings.

Hence the combined and individual airpollution indices (now called Air Quality Indices)

are required for the planners and decision-makers.

A typical air pollution index is an interpretative technique, which transforms complex data

on measured atmospheric pollutant concentrations into a single number or set of numbers in

order to make the data more meaningful and understandable. An "Air Quality Index" may

be defined as a scheme that transforms the (weighted) values of individual air pollution

related parameters (for example, CO concentration or visibility) into a single number or set

of numbers (Fig. 3.1). In most elaborate form, an Air Quality Index combines many

pollutants in some mathematical expression to arrive at a single number for air quality.

Parameter

Parameter X

Parameter X

Parameter

____. Index

Fig. 3.1: Air Pollution Index (API) calculation (Thorn and Ott, 1976).

The purpose behind Air Pollution Index (API) is only to indicate the Ambient Air Quality

of an individual city, geographical region, or the country as a whole. Further this aggregate

measure. should be understandable to a layman or the general public.

[3.1] Development of AQI

Air Quality Index is an integral part of the Environmental Quality Index (EQI). It may be

said that the first Environmental Quality Index developed was the health index (Lohani,

1984). This health index was based on the degree of human sufferings. In 1960's the

National Wildlife Federation (NWF) organisation of U.S. started developing EQI and it

gained a national picture. The· categories included in the EQI were soil, timber, wildlife,

minerals, water and air. The seventh category, living space, was add~d in 1970 (Kimball,

1973).


The idea behind the Air Quality Index is not new to the present world. The information

from Encyclopaedia Britannica ( 1966, Vol.2) describes the following myth "The Sumerians,

creators of the world's first cuneiform system of writing, had thousands of gods, but four

were particularly significant: Enlit (the god of Air), Enld (the god of water), Ninhursaga

(the earth goddess), and An (god ofthe sky). If we regard the first three as representing the

three major components of the environment, and the fourth as giving a bird's eye-view of

the others, we have a succinct description of the parts of the Environmental Quality Index,

4500 years old" (Sanderson, 1977).

Air Quality Index, which was known as Air Pollution Index (Shenfeld, 1970; Thomas et al.,

1971 ), has been developed and disseminated by many agencies. There are problems of

constructing Air Quality Indices as most of them have considered only one or a few aspects

of overall air quality (Shenfield, 1970; Bisselle et al., 1972; Leblanc and Rao, 1972;

Thomas, 1972).

The hierarchical structure of Air Quality Index (Fig. 3.2) is designed to take account of

three major aspects of air quality (lnhaber, 1975). First, the index of specific pollutants is

derived from physical measurements of particular pollutants like sulphur dioxide, carbon

monoxide and so on in many large urban areas. Secondly, an inter-urban Air Quality Index

can describe air quality around the urban areas. This is primarily obtained by measuring the

visibility at airports, which are generally located at some distance from the centre of cities.

, Finally, the air quality in the vicinity of large industries where the index is obtained by

evaluating the effect of particular pollutant on surrounding vegetation, soil, water and

wildlife in the countryside (Inhaber, 1975; Lohani, 1984). As physical measurements

become difficult in industrial areas, the industrial emission index is calculated on the basis

of estimated emission of particular air pollutant (Babcock, 1970; Babcock and Nagda,

1972). These indices are reported in varying formats and grouped into different categories

depending on time, space, etc.

[3.2] Categories ofAQI

The Air Quality Indices can be grouped into two categories: the short-term indices and the

long-term indices.

Short-term Indices-: The local air quality could be investigated by these indices. These

are used more frequently and widely. by the local and state pollution control agencies in US.


Daily changes in air pollution levels are inferred and disseminated to inform the general

public (Thorn and Ott, 1976). The short-term indices include the extreme value index (EVI),

Ontario Air Pollution Index (OAPI), Oak Ridge Air Quality Index (ORAQI), Green's Index,

etc.

Long-term Indices-: These are used to evaluate changes in air quality of a number of

places across a country or region over a period of several years. The sole purpose of these

indices is to assess the effectiveness of enforcement policies in improving air quality (Thorn

and Ott, 1976). Examples of long-term indices are Mitre Air Quality Index (MAQI),

Pollution Index (PINDEX) etc.

Fig. 3.2: Schematic diagram of Air Quality Index (lnhaber, 1975).

Index of industrial emission (mainly

rural)

The literature on air pollution indices has previously focussed on the development of long

term indices. Little emphasis was given to the short-term indices. A brief account of some

of these indices (short-term and long-term) is given below.

(a) Green's Index

It is one of the earliest air pollution indices, which was proposed by Marvin Green in 1966

(Green, 1966). This index was based on two variables: sulphur dioxide and smoke shade.

Each pollutant was placed on the same numerical scale, i.e., from zero to 100. The scale


was divided so that fof each pollutant with an index of 25 would be the desirable level, 50

would be the alert level and 100 would be the extreme or intolerable level. The 'alignment

chart' (Fig. 3.3) prepared by Green relates the air pollution index scale from zero to 100 to

specific pollutant concentrations.

EXTREME LEVE L-1.50

L

1'11 41 ,... 1'11 1/1 . c:: 11! 4>

u

1.00 Eo.oo 0. o.aeo

L :::l ...... ao.oz

0.01J

100 90 so .'i'O

10.0-EXTREME LEVEL

8.0

6,0

4.0

-ALERT LEVEL

Fig. 3.3: The alignment chart prepared by Green.

For S02 and smoke shade a power function was used to relate the pollutant concentrations

to the index scale. The functions were given as

For S02

(3.1)

For Smoke Shade,

h = 26.6 [coh]0575 (3.2)


Where, [S02] ~ the concentration of S02

[ coh] ~ the concentration of smoke shade

A Combined Index, I, was calculated by taking the average of sub indices of specific

pollutants:

1=11+12 2

(b) Ontario Air Pollution Index (OAPI)

(3.3)

In 1970, Government of Ontario, Canada developed this air pollution index (API) which

was intended both to provide the public with daily information about air quality levels and

to trigger control actions during air pollution episodes (Babcock and Nagda, 1971 ).

The Ontario API included two pollutant variables, Coefficient of Haze (COH) and S02 and

used linear sub index functions:

For COH, l1 = 30.5 X1

For S02 (ppm), h = 126 X2

(3.4)

(3.5)

The pollutant variables X1 and X2 were both 24- hour running average concentrations of

COH and S02 respectively. The aggregate function was:

API= 0.2 (11 +h) 1.35 (3.6)

An API value less than 32 was considered ''acceptable" air quality. A value of greater than

50 was considered as an indicator for the curtailment of some air pollution sources.

(c) Oak Ridge Air Quality Index (ORAQI)

ORAQI, developed in 1971, is based on the 24-hour average concentrations of five air

pollutants: carbon monoxide, nitrogen dioxide,· ozone, suspended particulate matter and

sulphur dioxide (Babcock and Nagda, 1971). Each sub index is calculated as the ratio of the

observed pollutant concentration to its respectiye standards:

(3.7)

The ORAQI aggregation function is non-linear:


[

5 ]1.37 ORAQI = 5.7x ~I; (3.8)

It also ignores the meteorological parameters.

(d) MITRE Air Quality Index (MAQI)

MAQI is based on the secondary National Air quality Standards (NAAQS) of US. It uses '

the data of more recent 12 months to depict the quarterly changes in air quality. The index is

calculated as the square root of the sum of squares in five NAAQS pollutants (CO, S02,

N02, 0 3 and SPM) in US (Thorn and Ott, 1976). Each sub index, in tum, is the square root

of the sum of squares of the normalised pollutant concentrations. The normalised pollutant

concentrations are calculated by dividing the mean pollutant concentration by the standards

for several different averaging times. The sub indices, mentioned above, are then aggregated

in the following manner:

(3.9)

Where, MAQI = MITRE Air Quality Index

Ii =air quality sub-index for pollutant i.

The sub indices for the MITRE Air Quality Index are determined as follows:

I1: Carbon Monoxide

Where: I1 =Carbon Monoxide sub-index

X8 = concentration of CO (maximum 8-hr value)

Ss = 8-hour NAAQS (= 9 ppm)

X1 =concentration of CO (maximum 1-hr value)

S1 = 1-hour NAAQS (= 35 ppm)

c)= 1 ifX1 > = S1, 0 otherwise

(3.10)


h : Sulphut Dioxide

(3.11)

Where,. h ~ Sulphur dioxide sub-index

Xa ~ Annual (or Daily) arithmetic mean observed concentration of S02.

Sa~ Annual (or Daily) secondary standard value

X24 ~ Maximum observed 24-hours concentration of S02.

S24 ~ 24-hour (or 1-hour) secondary standard

X3 ~ Maximum observed 3- hour concentration of S02.

S3 ~ 3-hour secondary value (0.5ppm).

81 = 1 if X24 ;:::: s24

82 = 1 if x3 ;:::: s3

13: Nitrogen Dioxide

I = Xa 3 s

a

(3.12)

Where, 13 ~Nitrogen dioxide sub-index

k Ozone

Where,

Xa ~Annual (or Daily) arithmetic mean observed concentration ofN02.

Sa~ Annual (or Daily) secondary standard value ofN02

(3.13)

14 ~Ozone sub-index

X0 ~ Maximum observed 1-hour concentration of 0 3.

S0 ~ 1-hour secondary value (0.08) of 03


Is: Suspended Particulate Matter

Where, Is ~ Suspended Particulate Matter Index

Xa ~ Average SPM concentration in 24-hours

Sa ~ Secondary value of SPM

X24 ~ SPM concentration (maximum in 24 hours)

S24~ Secondary NAAQS value

(3.14)

This method gives an indication for an index value of at least one if any pollutant included

in the computation exceeds its standard value. A grey area is found between 1 and 3 where

each pollutant concentration may or may not exceed its standard. This implies that each

indicator is required to be inspected to determine if a standard has been exceeded. Values ·

greater than 3 give the impression that at least one standard has been exceeded.

The () factor gives an added emphasis to a violation of NAAQS. Further () coefficient is

used to eliminate the pollutant concentrations from Index calculation if it is below their

respective standards. This typical picture prevents eclipsing (Thorn and Ott, 1976).

This index (MAQI) was developed by using five different pollutants without taking the

meteorological variables into the account. .

(e) Extreme Value Index (EVI)

EVI is a modified form of MAQI. It was intended to reflect the frequency of air pollution

events rather than the maximum values, which formed the basis of MAQI (Thorn and Ott,

1976). EVI used "accumulated extreme" values by summing all periods when the

concentrations exceeded NAAQS ofU. S. Mathematically, EVI is given as:

( 2 2 2 2 )1/2

EVI = Ic +I0 +IT +Is

Where, EVI~ Extreme Value Index

Ic ~ CO sub index

10~ 03 sub index

(3.15)

[ill

•) Ir~ TSP sub index

Is~ S02 sub index


The sub indices were calculated with "accumulated extremes" values substituting for

maximum concentration values in the MAQI sub index equations.

EVI has included only four (CO, S02, 03 and TSP) of the five MAQI pollutants. It also

ignores the meteorological parameters.

(f) Pollution Standards Index (PSI)

In 1976 USEPA developed PSI to serve as a national uniform air pollution index for USA.

The index includes five pollutants: CO, N02, 03, TSP and S02. A sixth index is calculated

as TSP x S02. Each sub index is derived from a segmented linear function of averaged -

time concentrations. PSI is calculated as follows. The observed concentrations of all

pollutants are taken on the horizontal axis and their sub indices are taken along the vertical

axis in a graph. The PSI is· then reported by reading the appropriate maximum value of the

six sub indices. Mathematically it is expressed as:

I= max (Ii, h, ... , I6) (3.16)

Where, I = Pollutant Standards Index

I1-6 =Sub indices for each pollutant.

The pollutant ~esponsible for the maximum sub index is called the "critical pollutant" and is

reported along with the index. The structure of PSI allows for the easy incorporation of

additional pollutant sub indices in the future if desired but without meteorological variables.

(g) Inhaber's Air Quality Index

This Air Quality Index, developed specially for Canada (Inhaber, 1975), was composed of

three sub indices: a specific pollutant index (SPI) (Isp ), Inter-urban air quality (IAQ) and

industrial air emissions (IAE). The five indicators for the SPI were: sulphur dioxide (S02),

particulate matters (P), haze (H), carbon monoxide (CO), ozone (03) and nitrogen dioxide

(NOx). The SPI was calCulated by the following formula:

(3.17)

Where, Ism - Sub index for Sulphur dioxide

lp- Sub index for.Particulate matter

IH - Sub index for Haze

leo- Sub index for Carbon monoxide

lm - Sub index for Ozone

1No2 - Sub index for Nitrogen dioxide


These sub indices are calculated as follows.

leo = ~[( C cs IS cs )2 +S x( C' o IS CI )2 ] (3.18)

Where, Ccs- the maximum observed 8-hour concentration of CO.

Scs - 8-hour secondary standard value ( 9 ppm or, 1 0,000 11g/m3)

CCI- Maximum observed remove1-hour concentration.

SCI- 1-hour secondary standard value (35 ppm)

S = 1 ifCCI2: SCI,

= 0 if CCI< Sc1

Jso 2= ~[(csaiSsa )2 +S1x(C c24 IS 524 )2 +S 2 x(Cs3 IS 53 )2] (3.19)

Where,

I = Cna N02 S

na

Where,

Csa - Annual arithmetic mean of observed concentration of S02

Ssa- Annual secondary standard value (0.02 ppm)

Cs24- Maximum observed 24-hour concentration of S02

Ss24- 24-hour secondary standard (0.1 ppm)

Cs3 -Maximum observed 3-hour concentration of S02

Ss3- 3-hour secondary standard value (0 .5 ppm)

S 1 = 1 if Cs24 2: Ss24, and 0 otherwise . \

S2 =1 ifCs3 2: Ss3, and 0 otherwise

(3.20)

Cna- Annual arithmetic mean observed concentration ofN02

Sna- Annual secondary standard value (0.05 ppm)


Col I ozone=S

01

Where, Co1- Maximum obse:rved 1-hour concentration of ozone.

So1-l-hour secondary standard value (0.08ppm)

(3.21)

The sub indices for the remaining pollutants (Ip and IH) were calculated by using the formula:

Where, n - Number of weekly readings per station in a month

Cn- weekly observations in Jlg I m3

The IAE sub index was calculated by the following formula:

(3.22)

Where, Ec =Weight of the industrial emissions in a given county.

P c = Population of that county.

E1 =Total nationwid~ weight of the emission

P1 =The national population.

The IAQ index was based on visibility readings at airports.

IAQ = Vm

2VAP (3.24)

Where, V FN - average visibility for the two far northern stations and

V AP- average visibility for other airports in Canada.

An airport having a same average visibility as the far northern stations had IAQ = 0.05.

The overall Air Quality Index was calculated by:

1 . = 5 x 181' + 3 x I AQ + 2 x I AE

(

2 2 2 J 0

" 10 (3.25)


(h) Air Quality Index

The emission data on carbon mbnoxide, particulates, and sulphur dioxide were used to

evaluate the air quality of 29 metropolitan areas in the U.S. The overall index is calculated

from a weighted sum of the sub indices assigned to each of the three pollutants: CO, TSP

and S02 (Ott, 1978). The equation for calculating the index is given as:

3

AQI= LWJ; ;~I

Where, AQI ~Air Quality Index of the metropolitan area

I 1 ~ estimated CO sub index

h~ estimated TSP ·sub index

I3~ estimated so2 sub index

wi~ weight assigned to pollution type i.

It is limited by the following assumptions:

(3.26)

1. The urban area is square with the wind always parallel to one of its sides.

2. The sources emit continuously and are evenly distributed over the urban area.

3. Meteorological conditions remain at a constant stability throughout the year.

Hence its applicability is very limited. But it can be of use in the cities where less air quality

data are available.

(i) Pindex

Pindex is a combined pollution index designed to estimate total environmental pollution

(Lohani, 1984 ). It is widely used for assessing air pollution. Each contaminant is weighted

by dividing its concentration by the ambient air quality standard set for that particular

pollutant. The Pindex combines the weighted concentrations of air pollutants such as

particulate matter, sulphur dioxides, nitrogen oxides, carbon monoxide, hydrocarbons,

oxidants, solar radiation and with terms representing the particulate-sulphur oxides

synergisms as shown in Fig. 3.4 (Lohani, 1984). A correction factor is applied to get the

true concentration of nitrogen oxides, hydrocarbons and oxidants as the nitrogen oxides,

hydrocarbons and incidental solar radiation contributes to formation of oxidants.

The PINDEX equation may be applied to long-term ambient air quality data. It may also

applied to emission data from specific source categories such as transportation, industry,

power plants, space heating, and refuse combustion (Thorn and Ott, 1976).


Original concentrations (!J.g/m3)

Particulate matter

Sulphur dioxide

Nitrogen oxides

Solar radiation

Oxidant

Hydrocarbons

Carbon monoxides

Excess hydroca~bons

Fig. 3.4: Pindex Calculation Scheme (Lohani, 1984).

Concentrations corrected by tolerance factors

Particulate matter

Synergism

Sulphur dioxide

Nitrogen oxides

Oxidant

Hydrocarbons

Carbon monoxide

G) Air Quality Index by U.S.E.P.A.

The following steps are used to calculate the AQI (Federal Register, 1999):

Pindex

(1) Identify the highest concentration among all the monitors within each reporting area

and truncate the pollutant concentration to one more than the significant digits used

to express the level ofNAAQS for that pollutant.

(2) Find tw,? breakpoints that contain the concentration by using Table 3.1. Use the

following equation to calculate the Index

lp = !Hi -fw ( ) ------ Cp-BPw +lw

BPH; -BP.w (3.27)

Where, lp = the index value for pollutant, P


Cp = the truncated concentration of pollutant, P

BPHi = the breakpoint that is ~ Cr

BPw = the breakpoint that is ~ Cr

IHi =the AQI value corresponding to BPHi

lw =the AQI value corresponding to BPw

(3) Round the index to the nearest integer

(4) If the concentration is equal to a breakpoint, then the index is equal to the

corresponding iQ.dex value given in Table 3.1. Otherwise calculate the index from

the formula given in equation (3 .19).

(5) If the concentration is larger than the highest breakpoint in Table3.1 then you may

use the last two breakpoints in Table 3.1 when equation is applied.

(6) The index value ,for each measured pollutant is calculated and the highest producing

index value is selected for AQI.

Table 3.1: Breakpoints for AQI

Equal these AQis 0 3 (ppm) 0 3 (ppm) PMzs PMw CO (ppm) S02 (ppm) N02 (ppm) AQI Category

8-hr 1-hr(IJ (~g/m3) (~g/m3) 0-0.064 ......... 0-15.4 0-54 0-4.4 0-0.034 (2) 0-50 Good 0.065- ........... 15.5-40.4 55-154 4.5-9.4 0.035-0.144 (2) 51-100 moderate 0.084 0.085- 0.125- 40.5-65.4 155-254 9.5-12.4 0.145-0.224 (2) 101- Unhealthy 0.104 0.164 150 for Sensitive

I Group 0.105- 0.165- 465.5-150.4 255-254 12.5-15.4 0.225-0.304 (2) 151- Unhealthy 0.124 0.204 200 0.125- 0.205- •r5o.5- 355-424 15.5-30.4 0.305-0.604 0.65-1.24 201- Very 0.374 0.404 250.4 300 Unhealthy

(3) 0.405- 4250.5- 425-504 30.5-40.4 0.605-0.804 1.25-1.64 301-0.504 3'50.4 400

(3) 0.505- 4350.5- 505-604 40.5-50.4 0.805-1.004 1.65-2.04 401- Hazardous 0.604 500.4 500

Areas are generally reqmred to report the AQI based on 8-hour ozone values. However, there are small number of areas where an AQI based on 1-hour ozone values would be more precautionary. In these cases, in addition to calculating the 8-hour ozone index value, the 1-hour ozone index value may be calculated, and the maximum of the two values reported. 2 N02 has no short-term NAAQS and can generate an AQI only above an AQI value of200 3 8-hour 0 3 values do not define higher AQI values ( :2: 301). AQI values of 301 or higher are calculated with 1-hour 0 3 concentrations. 4 If a different SHL for PM2 5 is promulgated, these numbers will change accordingly.

(k) Revised Air Quality Index Model (RAQI)

It was developed by Cheng et al., (2004) in Taiwan by taking the entropy function of

Shannon (North et al., 1983) and PSI (Pollutant Standard Index) values of PM10, 0 3, S02,

COandN02.

The index is given as:


5

~ Av [1] [ . ] L,.j daily J Av S . Max I ,I , ... ,!

RAQ'] = ~ f [J J J ] J=l aanual dmly ( [ I 2 5 ]) (3.28) lVlax I' 2, ••• , 5 ( ~ X ( [ D Av ~ Av . [I] Sdaily Max /1,/2, ... ,/5

L,.j dally J

annual j=l

Where:

S ~ Entropy

I~, h, ... , Is ~PSI values of PM10, 03, S02, CO and N02,

The first factor, Max [I1, h, ... , Is), is the maximum operator function representing the

largest value of each sub-index.:

The second factor is the background arithmetic mean index value of five pollutants. It is

given by:

5

"Av [1] L,.j daily J j=l (3.29)

Av [t Av daily [I 1]] annual ;-I

Here the numerator represents the sum of the daily arithmetic averages of the sub-index.

The denominator is the annual average multiplied by the sum of the daily averages.

The third factor represents the background arithmetic mean entropy index value. It is given

as:

Av 1s, .1 (Max[I,,/ 2, ••• ,/5DJ annual t uai Y .

S daily (Max[! ,,I 2, ... ,/ 5 D (3.30)

Here the numerator is the average daily entropy times the yearly average. The denominator

is the Log10 of each sub-index and the daily average ofthe entropy function.

The index predicts the air quality in long terms only.

(1) Factor Analysis Index

Here each of then variables is described linearly in terms of m new uncorrelated common

factors F1, F2, .... , Fn and unique factor Uj G = 1, 2, ..... , n).

(3.31)

Where,


Yj => A standardised form of a variable with known data.

Ajm => Factor loadings or weight for each factor.

Uj => A unique factor.

bj => A unique factor weight.

(3.32)

The variables entering into each function, Fm, are unknown and are related in unknown (but

not ne~essarily linear) ways. The equations relating the functions themselves are linear.

Each function makes a contribution to the sum of the variances of the variables, and in

general a few of the func~ions will account for a large amount of the total variance. The

factor analysis technique provides values for the constants, Ajm, called loadings, which ' .

represent the extent to which each specific function is related to Yj. Once the factor loadings

or weights for each variables are determined, the initial set of statistics can ·be aggregated

through the determination of factor scores into a single index in which each variable is

weighted proportionally to its involvement in a pattern. The greater the involvement, the

higher is the weight. For example, an index 11, constructed from the first factor loadings

may be expressed as

(3.33)

·Where, ~ is the eigenvalue for the first factor.

In this study (Lohani, 1980), the meteorological variables were ignored. This method was

earlier applied to annual air pollution data of Taiwan. Comparisons were made between the

Factor Analysis Index (F AI) and Pindex Index (PI). The rating obtained by both the method

was exactly the same. But F AI showed a wider range, which indicates that it is a better

approach.

In the present work the above methodology has been modified to incorporate the

meteorological variables (which were ignored in the previous studies) along with the

pollutant parameters. This method is discussed in detail in Chapter- V.

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Chapter Ill Air Quality Indices: A Brief...

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