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AirQualityIndex–AComparativeStudyfor
AssessingtheStatusofAirQuality
ARTICLE·APRIL2015
DOI:10.5958/2321-581X.2015.00041.0
CITATION
1
READS
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Availablefrom:NavneetKumar
Retrievedon:02February2016
Research J. Engineering and Tech. 6(2): April-June, 2015
1
ISSN 0976-2973 (Print) www.anvpublication.org
2321-581X (online)
RESEARCH ARTICLE
Air Quality Index – A Comparative Study for Assessing the Status of Air
Quality
Shivangi Nigam1*, B.P.S. Rao1, N. Kumar1, V. A. Mhaisalkar2
1CSIR-National Environmental Engineering Research Institute APC Division, CSIR-National Environmental
Engineering Research Institute, Nehru Marg, Nagpur-440020
2Head Environmental Engineering Department, VNIT, Nagpur
*Corresponding Author Email: s_nigam@neeri.res.in
ABSTRACT:
Air quality Index is a tool for identify the present scenario of air quality. Six different methods of estimating Air
quality Index (AQI) based on four pollutants synergistic effect viz., PM10, PM2.5, SO2 and NO2 were used to
compare the prevailing ambient air quality in the study region. The average concentration of PM10, PM2.5, SO2
and NO2 are in 82.59, 61.61, 27.19 and 3.92 µg/m3 in was observed in May June respectively. Similarly the
levels in June-July 2014 were observed as 57.96, 43.27, 14.24 and 2.54 µg/m3 respectively while the
concentration in July-August 2014 were found as 39.37, 32.89, 10.44 and 2.92µg/m3 respectively, in August-
September 2014 were 30.08, 32.53, 12.18 and 2.90 µg/m3 respectively and the levels in Sept-Oct 2014 were
found as PM10, PM2.5, SO2 and NO2 are in 93.66, 94.04, 23.39 and 6.85 µg/m3 respectively. Seasonal and daily
AQI calculation revealed that air quality status in the study region under various classes ranging from good,
moderate, satisfactory and unacceptable class for different AQI calculation.
KEYWORDS: Air Quality Index (AQI), Oak Ridge National Air Quality Index (ORAQI), Break Point
Concentration, SPSS-Factor Analysis, Nagpur.
1. INTRODUCTION:
Air Pollution is a complex mixture of gases, particles,
aerosols, water vapour which has originated due to
human development and other natural/anthropogenic
activities. Its close relation to human development,
complex structure containing infinite proportions of
particles and gaseous matrix makes it more challenging
towards its management. Air pollution management is lie
at the interface of science and public policy. These
decisions involve a number of stakeholders with
competing agendas and vested interests in the ultimate
decision.
Received on 11.02.2015 Accepted on 21.03.2015
©A&V Publications all right reserved
Research J. Engineering and Tech. 6(2): April-June, 2015 page 1-3
It is then appropriate to adopt formal methods for
consensus building to ensure transparent and repeatable
decisions. In this paper, different method for estimating
the Air Quality Index is evaluated as a tool for assessing
the impact of air pollution with a case study. Air Quality
Index (AQI) is such an indicator tool which is widely
used worldwide and in India since last 2-3 decades.
Essentially it is used for assessing the air pollution hot
spots in the region for delineating management and
concrete actions. The earlier version was mostly based
on exceedance to the compliances (health based) set for
a country’s ambient air for a time period.
Various AQI used in the country as well world over
include synergistic effect estimation based on mean of
the ratios of pollutant over guideline levels for a certain
time period. These can further be classified as AQIs
using various mean values viz., geometric, arithmetic
mean, weighted average, logarithmic mean and break
point concentration. Air Quality Index is the simplest
Research J. Engineering and Tech. 6(2): April-June, 2015
2
and widely used measure of measure of overall air
pollution of a region. More recently the breakpoint
concentration method of measurement of AQI was
proposed by CPCB which is for individual pollutants
AQI estimation followed by max of these as synergistic
level of AQI which may be used for decision making.
This was also adopted by China and is USEPA concept
of break point concentration level which they have
adopted since last decade for their development. The
pollutant with the highest AQI value determines the
overall AQI for that hour. The four pollutants measured
for the AQI are good indicators of daily air quality, but
are not the only air pollutants which may cause health
effects, such as air toxics pollutants. Additionally, the
AQI does not account for temperature or pollen levels,
which may increase sensitivity to air pollutants.
2. MATERIALS AND METHODS:
The real time Continuous air pollution monitoring is
undertaken at residential site NEERI, Nagpur by
Environment S. A. CAAMQS analyzer during May to
October 2014 with reference to PM10, PM2.5, SO2 and
NO2.
2.1 Study Area:
Nagpur (21◦15’N, 79◦08’E) is the Capital of
Maharashtra in the winter season. The district stretches
to almost 9897 sq km. Nagpur is surrounded by plateau
rising northward to the Satpura Range, Kanhan and
Pench rivers are the two important rivers of the district.
It is situated 274.5m to 652.7m above sea level and 28%
of the town is covered by forest. The city has a typical
seasonal monsoon weather which is normally dry.
Annual Average relative humidity (RH) is 60%. Annual
average temperature ranges from 33.2 to 17.1◦C with
average annual rain fall 112 mm.
2.2 METHODOLOGY:
To understand the temporal variation and episodic rise of
the air pollution in the study region, real time air quality
monitoring was carried out at residential site NEERI,
Nagpur (Figure 1). In the present study ambient air
quality was measured by Environment S.A CAAMS
Analyzer (Continuous Ambient Air Monitoring Station)
for fine particulate matter PM10, PM2.5, SO2 and NO2.
The fine particulate monitor of CAAMS works on
principle of Beta Attenuation Method for measuring and
analysis of the concentration of PM10 and PM2.5. Every
hour, a small C14 (Carbon -14 or Krypton 85) element
emits a constant source of high-energy electrons (known
as beta rays) through a spot of clean filter tape. UV
fluorescence method is used for SO2 monitoring. The UV
fluorescence method is based on the fluorescence
emission of light by SO2 molecules excited by UV
radiation. Chemiluminescence Analyzer is used for
measurement of oxides of nitrogen in air (NO2). The
calibration is undertaken by traceable standard reference
gas method.
2.2.1 Air Quality Index (AQI):
Now a day, it is important to the society to look for
Awareness of daily levels of air pollution.AQI is a tool
which is used to report the overall air quality status and
trends based on a specific standard. In India we are using
CPCB Standard for calculating air quality index or
environment pollution index. This index gives an idea
about the environmental status as air quality. And also
tells the general public to understand how clean or
pollute air is breathe daily.
Figure.1. Sampling Site at NEERI, Nagpur (Residential Area)
Research J. Engineering and Tech. 6(2): April-June, 2015
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Overall this index can be used to give meaningful
evaluation of air pollution to the common man. It also
helps to identify the air pollution control policies or
control equipment can reduce level of dominating
pollutant. AQI is representing the cumulative effect of
all the pollutant to show overall air quality status in
better way. The AQI of specific pollutant is derived
mainly from the physical measurement of pollutant like
PM10, PM2.5, NO2 and SO2 etc. In the present study, six
different methods were used to calculate ambient air
quality index.
Method I:
Air quality Index (AQI) is calculated based on the
arithmetic mean of the ratio of concentration of
pollutants to the standard value of that pollutant such as
PM10, PM2.5, NO2 and SO2. The average is then
multiplied by 100 to get the AQI index. AQI was then
compared with rating scale (Kaushik et al., 2006). For
individual pollutant AQI was calculated by the following
formula
=
∗100
Where
AQI = Air Quality Index
C= the observed value of the air quality parameters
pollutant (PM10, PM2.5, NO2 and SO2)
Cs= CPCB standard for residential Area (CPCB, 2009)
Method II:
In this procedure AQI is calculated by taking the
geometric mean of the ratio of concentration of
pollutants to the standard value of that pollutant such as
PM10, PM2.5, NO2 and SO2. AQI was then compared with
rating scale. (Ravikumar et. al., 2014)
Method III:
Oak Ridge National Air Quality Index (ORNAQI) is
used for the relative ranking of an overall air quality
status. Over all AQI was estimated by the following
mathematical equation developed by the Oak Ridge
National Laboratory (ORNL), USA is given below.
= [39.02
].
Air quality Index then measured and compared with
relative ORAQI values (Bhuyan et al. 2010).
Method IV:
Air Quality Index was done for combining qualitative
measures with qualitative concept of the environment.
The individual air quality index here is calculated as
follow:
= ( ∗
)
Where
AQI = Air Quality Index
W= Weighted of Pollutant
C= the observed value of the air quality parameters
pollutant (PM10, PM2.5, NO2 and SO2)
Cs= CPCB standard for residential Area (CPCB, 2009)
Method V:
Air Quality Index was done based on dose response
relationships of pollutants to obtain break point
concentration.(USEPA, 2006,CPCB 2014) The
individual air quality index for a given pollutant
concentration (Cs) as based on linear segmented
principle is calculated as
= [{ ( –)
( − )}∗(−)]+
Where
B
= Breakpoint conecntration greater or equal to given
Concentration
B
= Breakpoint conecntration smaller or equal to given
Concentration
I = AQI value corresponding to B
I = AQI value correspond to B
Finally;
AQI=Max (Ip) (where p=1, 2, 3…n; denotes n pollutants)
3. RESULT:
Data obtained from monitoring of ambient air at
Residential site is used to calculate the air quality index
(air pollution index) for critical parameter. Different AQI
were estimated for various months and varying results
were observed ranging from good to unacceptable for the
same set of data. This may be due to eclipsing effect of
the values used in the formulas. The statistical theory
behind these AQI makes it more prone to variations viz.
the use of means from simple arithmetic to logarithmic
and weighted averages to use of breakpoint
concentration as basis of estimation. As reported in
USEPA, CPCB, 2014, the breakpoint concentration
based AQI is more robust and can be used for decision
making. Accordingly, the AQI values are calculated
based on Break Point concentration for 24 hourly
averages for PM10, PM2.5, SO2 and NO2 concentrations
and are categorized as satisfactory to moderate during
the study period at the residential site.
Research J.
Figure 2. Variation in air quality index in the study area during May
Figure 3. Variation in air quality index in the study area during June
Figure 4. Variation in
air quality index in the study area during July
Research J.
Engineering and Tech. 6(2): April-June, 2015
4
Figure 2. Variation in air quality index in the study area during May
-June (2014)
Figure 3. Variation in air quality index in the study area during June
-July (2014)
air quality index in the study area during July
-August (2014)
Research J. Engineering and Tech. 6(2): April-June, 2015
5
The diurnal variation of different AQI has been shown in
figure 2, figure 3, figure 4, figure 5 and figure 6 for the
month of May-June, June-July, July-August, August-
September 2014 respectively .AQI values calculated for
PM10 is found in the Satisfactory, PM2.5 in Poor and NO2
and SO2 in Good category during May-June 2014. While
they were found as PM10: Satisfactory, PM2.5: Moderate
and NO2 and SO2 in Good category during June-July
2014. The AQI values calculated for PM10 is found in
Good category, PM2.5 in the Moderate, NO2 and SO2 is
coming in the range of Good in July-August 2014. AQI
values calculated for PM10 is coming in the Good, PM2.5
is coming in the Satisfactory, NO2 and SO2 is coming in
the range of Good in August-September. AQI values
calculated for PM10 is coming in the Satisfactory, PM2.5
is coming in the Poor, NO2 and SO2 is coming in the
range of Good in September-October 2014.
The overall Air Quality Index was found to fall under the
category of satisfactory to moderately polluted area
(figure.7).
Figure 5. Variation in air quality index in the study area during August-September (2014)
Figure 6. Variation in air quality index in the study area during September- October (2014)
Figure 7. Classification of air quality index i n the study area during study time
Research J. Engineering and Tech. 6(2): April-June, 2015
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Table 1: Classification of AQI used for Comparative Study
AQI
(CPCB,1994)
AQI
(Malaysia,1999)
AQI
(Wt. Avg.)
AQI (ORAQI) AQI
(USEPA, 2006)
AQI
(CPCB, 2014)
(AQI<100)
Good
(AQI<10)
Very Clean
(0≥AQI≤0.5)
Acceptable
(0≥AQI≤25) Clean (up to 50) Good (0-50) Good
(AQI>100)
Harmful
(10≥AQI<25) Clean (0.51≥AQI≤1)
Unacceptable
(26≥AQI≤50)
Light Air Pollution
(51-100) Moderate (51-100)
Satisfactory
(25≥AQI<50)
Fairly Clean
(1.01≥AQI≤2)
Alert
(51≥AQI≤75)
Moderately Polluted
(101-150) Unhealthy
for sensitive Groups
(101-200)
Moderately
polluted
(50≥AQI<75)
Moderately Polluted
(AQI≥2.01)
Significant
harmful
(76≥AQI≤100)
Heavy Air Pollution
(151-200) Unhealthy (201-300)
Poor
(75≥AQI<100)
Polluted
(AQI>100)
Severe Air Polluted
(201-300)
Very Unhealthy
(301-400)
Very Poor
(100≥AQI<125)
Highly Polluted
(301-500) Hazardous (401-500)
Severe
(AQI≥125)
severely Polluted
Figure 8. Percentage occurrences of four pollutants in the study area during study
In order to study the frequency and occurrence of
individual pollutant in diurnal variation study factor
analysis method through SPSS 13.0 software is used
(Anikender et al. 2011). The frequency of occurrence of
different pollutant has been shown in figure 8. It has
been observed that occurrence of particulate matter is
more as compared to other pollutant in all the seasons
from May to October 2014. PM10 is found more
polluting parameter as compared to PM2.5, SO2 and NO2
with variance of average as 62%.
Figure 9. CPCB 2014 Individual pollutant classification in the study area during study
Research J. Engineering and Tech. 6(2): April-June, 2015
7
Based on break point concentration, AQI of individual
pollutant has been shown in figure. 9. It has been
observed that Particulate matter (PM2.5) is satisfactory,
SO2 and NO2 is Good from May- October 2014. While
PM10 is to be appear in moderate to poor from May-
October 2014. This PM10 is factor which is the major
pollutant for causing the overall air quality reduction.
Source of PM10 may be thermal power plant, small-
medium scale industry and vehicle etc. PM10 may cause
lot of respiratory problem to human health (Ekpenyong
et. al. 2012).
Table 2: Correlation coefficient of four Pollutant using SPSS during May-July 2014
May-June(2014) June-July(2014)
PM
10
PM
2.5
NO
2
SO
2
PM
10
PM
2.5
NO
2
SO
2
PM
10
1 0.946 0.275 0.227 1 0.748 0.502 0.137
PM
2.5
0.946 1 0.365 0.197 0.748 1 0.417 0.099
NO
2
0.275 0.365 1 0.037 0.502 0.417 1 0.347
SO
2
0.227 0.197 0.037 1 0.137 0.099 0.347 1
Table 3: Correlation coefficient of four Pollutant using SPSS during July –September 2014
July-Aug(2014) Aug-Sept(2014)
PM
10
PM
2.5
NO
2
SO
2
PM
10
PM
2.5
NO
2
SO
2
PM
10
1 0.609 0.728 0.244 1 0.912 0.808 0.568
PM
2.5
0.609 1 0.570 0.004 0.912 1 0.826 0.618
NO
2
0.728 0.570 1 0.110 0.808 0.826 1 0.720
SO
2
0.244 0.004 0.110 1 0.568 0.618 0.720 1
Table 4: Correlation coefficient of four Pollutant using SPSS during September-October 2014
PM
10
PM
2.5
NO
2
SO
2
PM
10
1 0.964 0.461 0.452
PM
2.5
0.964 1 0.339 0.281
NO
2
0.461 0.339 1 0.181
SO
2
0.452 0.281 0.181 1
Correlation matrix has been made using Pearson
correlation coefficient with two tailed significant test.
Correlation coefficient Matrix has been shown in table 2,
table 3 and table 4. It has been observed that correlation
coefficient is very strong between PM10 to PM2.5 as
compared to other pollutant during May-October 2014
except July –August 2014.PM10 and PM2.5 may be due to
power plant /industrial emissions but further particulate
characterization study would strength the source
identification. During the July –August 2014, strong
correlation has been found between Particulate matter
(PM10) and NO2. This may be due to excessive rain and
less photochemical reaction between pollutants
(Analitiset al. 2006).
4. CONCLUSION:
Air quality Index can give clear view about ambient air
and critical pollutant mainly responsible for the quality
of air. The AQIs were calculated according to CPCB
break point concentration. The AQI study reveals that
particulate matter (mainly PM10) was mainly responsible
for maximum times in the residential site NEERI,
Nagpur. These also have identified that PM10 as the
dominant pollutant in the index value (pipalatkar et. al.
2012). Particulate Matter is causing serious worldwide
public health problem for residents because of their
synergetic action. We have to look for appropriate
pollution control and management plans like plantation
and green belt etc for the betterment of the civic life. The
use of this tool in decision making for development but
may involve risk as it does not clearly address the
temporal AAQ variation due to meteorology, land use,
ecosystem geology of the region and its impact,
population exposure (poor) who cannot afford air
conditioning comfort, chemical conversion and
synergistic effect particle/ gas combination leading to
smoke acid rain and other climate change phenomena,
health impact of raised AAQ due to agglomeration of
finer particle-gas and their synergistic combination on
health of exposed/poor under privilege population which
may defeat the purpose of inclusive
development(Anderson et. al. 2005, Pope et al. 2006).
5. ACKNOWLEDGEMENTS:
This study was carried out as part of the project funded
by Council of Scientific Industrial Research. The authors
are grateful to Director NEERI, Nagpur for according to
permission to publish this paper.
Research J. Engineering and Tech. 6(2): April-June, 2015
8
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