Indoor Air Quality of Houses Located in the Urban Environment of Agra, India

Indoor Air Quality of Houses Located in theUrban Environment of Agra, India

Ajay Taneja, Renuka Saini, and Amit Masih

School of Chemical Sciences, Department of Chemistry, St. Johns College, Agra, India

Increased concern over the adverse health effects of air pollution has highlighted theneed for air-pollution measurements, especially in urban areas, where many sourcesof air pollutants are normally monitored outdoors as part of obligations under the Na-tional Air Quality Strategies. Very little is known about air pollution indoors. In fact,the largest exposure to health-damaging indoor pollution probably occurs in the de-veloping world, not in households, schools, and offices of developed countries wheremost research and control efforts have been focused to date. As a result much of thehealth impacts from air pollution worldwide seem to occur among the poorest andmost vulnerable populations. The authors in their earlier studies have confirmed theimportance of ambient air in determining the quality of air indoors. In this study anobservation of air quality indoors and outdoors of domestic homes located in an ur-ban environment from October 2004 to December 2005 in Agra, north central India, isperformed. The purpose of this study was to characterize the indoor/outdoor (I/O) rela-tionship of airborne pollutants and recognize their probable source in all three seasons,that is, winter, summer, and rainy season. Concentrations of SO2, NO2, CO2, Cl2, H2S,NH3, RSPM, and PAH were monitored simultaneously and I/O ratios were calculated.In order to investigate the effect of seasonality on indoor and ambient air quality, winterto summer and winter to monsoon average ratios were calculated. It is apparent thatthere is a general pattern of increasing levels from monsoon to summer to winter, andsimilarly from outdoor to indoor air. Regressions analysis had been done to furtherinvestigate the influence of outdoor air-pollutant concentrations on indoor concentra-tions. The most probable categories of sources for these pollutants have been identifiedby using principal-component analysis. Indoor air pollution is a complex function ofenergy housing and behavioral factors. On the basis of this study and observations,some interventions are also suggested.

Key words: indoor air quality; urban environment; indoor/outdoor relationship; India

Introduction

Indoor air quality (IAQ) is a complex issue,much more so than any single environment is-sue. There are hundreds of pollutants that ef-fect IAQ and thousands of sources. Researchindicates that more than 900 contaminants arepresent in indoor environments,1 depending onthe particular operation and activities, whichoccur with in the specific environments. The in-door environment in any building involves the

Address for correspondence: Ajay Taneja, School of Chemical Sci-ences, Department of Chemistry, St. Johns College, Agra, [email protected]

interactions of a set of factors that are constantlychanging. A healthy indoor environment is onethat promotes the comfort, health, and well-being of the occupants. In it the air is free ofsignificant levels of contaminants and odors.

Over the past two decades there has been arapid increase in urbanization and industrial-ization in many cities of India. With this hascome a dramatic increase in the number ofresidences, office buildings, and manufacturingfacilities, together with an increase in both thenumber and density of motor vehicles. The ur-banization process has both positive and nega-tive effects on IAQ in many cities of the world.2

People spend most of their time indoors; yet, the

Ann. N.Y. Acad. Sci. 1140: 228–245 (2008). C© 2008 New York Academy of Sciences.doi: 10.1196/annals.1454.033 228

Taneja et al.: Indoor Air Quality in Homes 229

majority of data on the concentrations of pol-lutants are based on measurements conductedoutdoors, in one or more control monitoringsites. Outdoor pollutant concentrations maynot be reliable indicators of indoor and per-sonal pollutant sources.3 Assessment of risk tothe community resulting from exposure to air-borne pollutants should ideally include mea-surements of concentration levels of pollutantsin the microenvironment where people spendtheir time. However, due to the multiplicityof different microenvironments, it is usuallynot possible to conduct measurements in allof them. “My home is my castle” is a familiarquotation originated from a rule of law stated inthe 17th century by the English jurist EdwardCoke, when he maintained the right to assumeddefense of private homes. Today there are newthreats in the homes that must be defended bymore sophisticated methods. One such threat isexposure related to poor indoor environment,which has given strong evidence of pronouncedeffects on our health.4–7

Principally, pollutants found in urban ar-eas are from short-range sources, includingpollution from vehicles exhaust, combustion,standby generators, process-plant discharge,construction, demolition, and kitchen exhaust.There can be large variations in concentra-tions over the buildings (houses), with high peakvalues found in houses, and very rapid short-term fluctuations in space and time over peri-ods of seconds. There may also be a slower,more diffuse component of the exposure, attime scales of minutes; on one or more housefacades.8 Understanding the relationship be-tween indoor and outdoor pollutant concen-tration under different environmental condi-tions is of importance for improving exposureestimates and, in turn, for developing efficientcontrol strategies to reduce human exposure,and thus health risk, as the largest exposuresprobably occur in the developing world, notin household, schools, and offices of developedcountries where most research and control ef-forts have focused to date.9

Recently in April 2007, WHO published thefirst-ever country-by-country estimates of theburden of disease due to indoor air pollution.10

These estimates can assist national decisionmakers in the health, environment, energy, andfinance sectors to set priorities for preventiveaction. In the 21 worst effected countries—Afghanistan, Angola, Benin, Burkina Faso,Burundi, Cameroon, Chad, Congo, Eritrea,Ethiopia, Madagascar, Malawi, Mali, Maurita-nia, Niger, Pakistan, Rwanda, Senegal, SierraLeone, Togo, and Uganda—approximately 5%of death and disease is caused by indoorair pollution. In 11 countries—Afghanistan,Angola, Bangladesh, Burkina Faso, China,Congo, Ethiopia, India, Nigeria, Pakistan andTanzania—indoor air pollution is to blame fora total of 1–2 million deaths a year. Globally,reliance on solid fuels is one of the 10 most im-portant threats to public health. The burden ofdisease, due to indoor air pollution from solid-fuel use for the year 2002 is shown in Table 1 forthe just-mentioned countries and some othercountries of the developing world.11 More than72% of Indian households, as reported in the2001 census, still use unprocessed biomass astheir primary cooking fuel.12 In rural areas,this figure is approximately 90%. As a result,India bears one of the largest burdens of dis-ease due to the use of unclean household fuels.13

According to a WHO comparative-risk study,exposure to smoke from household use of solidfuels is responsible for the premature deaths ofapproximately 400,000 women and children inIndia every year or 28% of all deaths causedby indoor air pollution in developing countries.Table 2 shows major sources and health effectsof indoor air pollution. Continuing with ourearlier studies14–16 in this central semiarid areaof India, where the data of IAQ is scarce andthe problem is less understood, the present workaims to determine the relationship between in-door and outdoor concentrations of pollutantsin domestic houses of urban areas. The datagenerated are expected to help the evolutionof complete benefits of interventions, identify

230 Annals of the New York Academy of Sciences

TABLE

1.

Cou

ntry

-by-

Cou

ntry

Estim

ates

ofth

eBu

rden

ofD

isea

seD

ueto

Indo

orA

irPo

llutio

n

Perc

enta

geA

LR

Ide

aths

CO

PDde

aths

Lun

gca

ncer

Perc

enta

geof

ofpo

pula

tion

attr

ibut

able

attr

ibut

able

deat

hsat

trib

utab

leT

otal

deat

hsT

otal

DA

LYs

natio

nalb

urde

nof

usin

gto

solid

-fue

luse

toso

lid-f

uelu

seto

coal

use

attr

ibut

able

toat

trib

utab

leto

dise

ase

attr

ibut

able

toC

ount

ryso

lidfu

els

(<5

year

s)(≥

30ye

ars)

(≥30

year

s)so

lid-f

uelu

sea

solid

-fue

luse

solid

-fue

luse

Afg

hani

stan

>95

22,7

0012

00-

23,9

0083

,230

04.

9A

ngol

a>

9521

,170

870

-22

,000

74,7

000

5.9

Ban

glad

esh

8932

,330

13,6

20-

45,0

001,

316,

400

3.6

Bur

kina

Faso

>95

2083

065

0<

1921

,500

738,

300

8.5

Chi

na80

20,5

4034

2,45

017

,720

380,

700

3,20

4,90

01.

5C

ongo

8547

024

0<

1070

018

300

1.2

Eth

iopi

a>

9550

,320

6410

-56

,700

1,79

0,80

04.

9In

dia

8225

1,56

015

5,25

034

040

7,10

010

,646

,500

3.5

Indo

nesi

a72

3130

12,1

60-

15,3

0032

0,80

00.

7M

alay

sia

<5

<10

20-

<10

030

00

Mya

nmar

>85

11,5

9030

70-

14,7

0046

9,20

03.

2N

epal

8148

2026

80-

7500

204,

400

2.7

Nig

eria

6770

,390

85,7

0-

79,0

002,

591,

500

3.8

Paki

stan

8151

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18,9

80<

1070

,700

2,05

7,40

04.

6Ph

ilipp

ines

4555

2014

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100

1.6

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anka

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nd72

1850

2710

-46

0095

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0.8

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ted

Rep

ublic

ofT

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nia

>95

25,0

5024

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27,5

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4

Vie

tNam

7026

2078

1015

010

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157,

100

1.2

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bia

8713

8051

0-

1900

50,9

000.

6

aT

heto

tald

eath

sat

trib

utab

leto

solid

use

wer

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unde

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dm

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tbe

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lto

the

sum

ofA

LR

I,C

OPD

,and

lung

canc

erde

aths

.A

LR

I,ac

ute

low

erre

spir

ator

yin

fect

ions

;CO

PD,c

hron

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stru

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s,da

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just

able

life

year

s.


TABLE 2. Major Sources and Health Effects of Indoor Air Pollutants

Pollutants Indoor sources Health effects

CO Kerosene and gas heaters, wood,coal stoves, smoking

Formation of carboxyhemoglobin reduces oxygenintake of blood, headache, shortness in breath(immediate effect)

Nitrogen oxides Kerosene, diesel, wood, coal outdooractivities, infiltration

Chronic lung diseases, cardiovascular diseases,hypertension, skin irritation, eyes irritation, cough(immediate effect)

SO2 Kerosene, diesel, coal, outdooractivities, infiltration

Respiratory diseases (immediate effect)

RSPM (PM10) Wood, peat, biomass, heavy oil,diesel, outdoor activitiesinfiltration

Affects respiratory tracts and embedded into alveoli,carrier of many secondary pollutants andcarcinogenic trace elements, lung cancer (cumulativeeffect)

Chlorine Drycleaners, phenyl, cleaningcooking

Nose and throat infection, chest pain, pulmonaryedema, burn the eyes and skin causing permanentdamage (immediate effect)

CO2 Metabolic activity, combustionactivities, motor vehicles

Surrogate index of ventilation

Polycyclic aromatichydrocarbons

Fuel combustion, oil burning,tobacco smoke

Carcinogenic, mutagenic (cumulative effect)

priority issues for researchers, and policymak-ers. A better understanding of other factorsis also necessary, apart from household fuelchoices, to develop exposure atlases for par-ticular regions or nations.

Experimental Methods

Site Description

Agra, the city of Taj (27◦10′ N 78◦2′ E) is lo-cated in the north central part of India, about204 km south of Delhi in the Indian state of U.P.Agra is one of the most famous tourist spots ofthe country. The city, situated on the west bankof river the Yamuna, is known world over ashome to a wonder of the world, the Taj Mahal.A part of the great northern Indian plains, Agrahas a tropical climate. The climate during sum-mer is hot and dry with temperature rangingfrom 32◦ to 48◦C. In winter the temperatureranges from 3.5◦ to 30.5◦C. The downwardwind is south-southeast 29% and northeast 6%of the time in summer, and it is west-northwest9.4% and north-northwest 11.8% of the time in

winter. The atmospheric pollution load is high,and because of the downward wind, pollutantsmay be transported to different areas mainlyfrom an oil refinery situated in Mathura (50 kmfrom the center of Agra City). Agra has about1,316,177 total population and population den-sity is about 21,148 per sq. km17 with 386,635vehicles registered and 32,030 generator sets.18

In Agra, 60% pollution is due to vehicles.19

Three highways cross the city. Vehicular traf-fic on these highways is high (105 vehicles perday).

In the present study, monitoring was carriedout both inside and outside 20 houses from Oc-tober 2004 to December 2005. Ten houses wereselected in the areas, which were typical ur-ban colonies, and 10 houses were selected fromthe roadside colonies lying adjacent to nationalhighways or having high-volume traffic (Fig. 1).Concentrations of indoor CO2, CO, NO2, NO,SO2, Cl2, H2S, NH3, and PM10 were mea-sured in the living room where the people spentmost of their time, whereas outdoor measure-ments were done at the rooftop of the house.During the measurement of these pollutants,meteorological parameters were also recorded.


Figure 1. Map showing urban and roadside sites of Agra. (In color in Annals online.)

Indoor and outdoor concentration levels of allthese pollutants were simultaneously measuredfor a period of 8 hours a day. On a particu-lar day, full-day sampling of indoor and out-door for all 20 houses was done. This samplingtime covered activities for the entire day in-side houses, such as prayer, cleaning, makingof food, as well as outdoor activities when thetraffic was low and high, the use of generatorsfor tube wells, and sweeping. In urban areaswe have old types of houses, which have park-ing garages inside or beneath the houses due tolack of space, and the outdoor environment hasshopping complexes and small markets, but lesstraffic. On the roadside we have modern typesof houses, as they have been built recently; usu-ally their environment is of high traffic duringthe night and morning, with both heavy andlight motor vehicles and less greenery. All pol-lutants, that is, CO, NO2, NO, SO2, were mea-sured by a portable YES-205 multigas monitor(Young Environmental Systems Inc., VantageWay, Delta, BC, Canada). CO2 was measuredby a portable YES-206 Falcon IAQ moni-tor, oxides of nitrogen (NOx), SO2, and NH3

were also measured and compared by the im-pinger method (spectrophotometer method) us-

ing handy samplers. Particulate matter (PM10)and particulate polycyclic aromatic hydrocar-bons (PAHs) were collected for both inside andoutside the house using handy samplers andrespiratory dust sampler, respectively.

Results and Discussion

Table 3 shows the average monthly concen-trations of pollutants monitored indoors as wellas outdoors at urban and roadside sites. Con-centrations of pollutants CO2, CO, NO2, andH2S were higher in indoors, whereas NH3 washigher outdoors at urban locations. No definitetrends were observed for SO2 and Cl2. Res-pirable suspended particulate matter (RSPM)(PM10) were higher outdoors in urban areas,whereas in roadside and rural locations it washigher indoors. In order to investigate the effectof seasonality on indoor and ambient air qual-ity, winter to summer and winter to monsoon,average ratios were calculated, and the resultsare shown in Table 4. It is apparent that thereis a general pattern of increasing levels frommonsoon to summer to winter and similarlyfrom outdoor to indoor air.


Indoor/Outdoor Ratios

I/O concentrations can vary largely due toa large number of factors (including location,building design, and different activities). I/Oratios are also being explored to see the effectof the outdoor environment on the indoor en-vironment; these ratios are shown in Table 5.The I/O ratios for CO2 were found to beclose to 1, whereas CO, NO2 the I/O ratioswere significantly greater than 1 at both loca-tions, implying additional indoor sources. TheI/O ratio for PM10 was >1 at roadside loca-tions, but <1 in urban locations. For Cl2 it wasnear to 1 in both urban and roadside locations.The I/O ratio for NH3 was found to be <1 atroadside locations, but >1 in urban locations.The SO2 I/O ratio was >1 in urban locationsand was 1.0 for roadside locations. These ratios(I/O) being mostly higher than 1 clearly indi-cates a pattern of the indoor levels of the targetpollutants being higher than those outdoors.These monthly I/O variations were found tobe higher in terms of gaseous pollutants SO2

and CO in urban areas, NO2 and CO at road-side locations. The RSPM monthly mean I/Oratio also significantly varied at both locations.Thus, while the ambient air may have a pre-dominantly influence on the levels of most in-door air constituents, activities and materialsfound indoors were shown in this study to con-tribute significantly to indoor pollution in mostof the instances.

Full-Day Variation duringDifferent Seasons

Summer Season

At the urban and roadside sites, full dayand night monitoring was done once a monththroughout the year. Full-day variationsmean monitoring of pollutants around theclock (24 h), which covers all the indoorand outdoors activities taking place in a day.Figures 2, 3, and 4 show full-day variationfor gaseous pollutants CO2, CO, NH3, NO2,and SO2 in a house at both the sites, where

average maximum concentration of pollutantswere found in different seasons. Figure 2Aexplains full-day variation at a urban house;CO2 levels are constant, with two very smallpeaks of CO during the morning and evening.NO2 marks its presence throughout the day;NH3 concentrations were found to be highduring noontime. Figure 2B for a roadsidehouse also has similar trends, having onemajor difference, that is, these sites hadlots of vehicular emission, includingafter9.00 PM when heavy diesel vehicles are al-lowed inside the city, which results in peaks ofCO and CO2, but settles down after some time.

Winter Season

Figure 3A illustrates a more or less constantindoor CO2 concentration, with peaks of COthat are believed to be due to household ac-tivities; NO2 and SO2 show their presencethroughout the day. The figure shows full-dayvariation of NO2 and NO, ranging between 0.1and 0.8 ppm (average 0.29 ppm) and between0.1 and 0.5 ppm (average 0.2), respectively,whereas low concentrations of NH3 were alsoobserved during early morning and evening.Figure 3B shows the indoor concentrationswhere two peaks dominated all the pollutants;one is in the morning and other during night.During these times of day, indoor activities areat its maximum. CO2 and CO concentrationsparticularly are seen to have maximum valuesbetween 9:00 PM and 10:00 PM.

Rainy Season

Figure 4A and 4B show full-day variationat urban and roadside houses during this sea-son. Though the outdoor concentrations arelow due to a washout effect, they still have apositive impact at urban and roadside houses.CO2 concentration is constant, but has twosmall peaks with that of CO. Cl2 and H2S alsoshow their presence in this season, which is be-lieved to be due to outdoor sources because ofwaterlogging, overflow of drains due to heavyrain.


TABLE

3.

Ave

rage

Mon

thly

Con

cent

ratio

nsof

Pollu

tant

sat

Urb

anan

dRo

adsi

deSi

tes

Poly

cycl

icar

omat

icSO

2C

O2

Cl 2

NO

2C

OH

2S

NH

3R

SPM

hydr

ocar

bons

(ppb

)(p

pm)

(ppm

)(p

pb)

(ppm

)(p

pm)

(ppb

)(μ

gm

−3)

(ng

m−3

)

Mon

ths

IO

IO

IO

IO

II

OI

OI

OI

O

Ru

ral

hou

ses

Oct

40.

900.

3737

236

60.

10.

17.

864.

690.

80.

60.

20.

118

.613

5-

--

-N

ov4

0.83

4.19

388

398

0.2

0.2

42.3

20.6

1.1

0.8

0.2

0.1

--

230

315

1.2

1.0

Dec

46.

523.

7139

238

60.

40.

452

.325

.61.

80.

90.

20.

335

.225

.331

842

81.

91.

3Ja

n5

23.4

20.3

398

372

0.3

0.2

8.11

5.59

1.6

0.8

0.3

0.2

20.9

21.2

496

569

2.8

2.4

Feb

510

.62.

5038

436

80.

60.

65.

713.

391.

00.

40.

30.

4-

-24

725

22.

42.

0M

ar5

19.6

0.70

351

481

0.2

0.2

9.89

36.7

0.9

0.8

0.2

0.1

10.6

43.7

101

198

1.6

1.0

Ap

r5

9.27

1.45

487

451

0.1

0.1

0.07

0.13

1.4

1.0

0.2

0.2

-42

.1-

--

-M

ay5

2.57

3.50

476

382

0.1

0.1

11.6

16.9

1.6

0.3

0.1

0.1

--

--

--

Jun

50.

480.

2042

936

60.

80.

45.

024.

490.

90.

50.

10.

9-

--

--

-Ju

l5

0.40

0.41

456

347

0.1

0.4

0.19

5.44

1.4

0.5

0.2

0.2

26.5

21.0

7915

91.

21.

7A

ug

52.

592.

7135

143

70.

20.

17.

856.

931.

10.

90.

90.

129

.562

.3-

--

-Se

p5

11.6

6.18

487

475

0.2

0.1

8.91

4.39

0.6

0.4

0.3

0.2

22.3

32.9

--

--

Oct

52.

753.

6045

847

20.

20.

35.

9210

.63

0.8

0.6

0.2

0.1

20.6

45.1

--

--

Nov

522

.59.

3241

838

70.

50.

447

.619

.41.

00.

90.

40.

420

.623

.6-

--

-D

ec5

36.4

12.5

497

473

0.3

0.2

54.6

27.0

10.

90.

50.

20.

221

.627

.5-

--

-A

veer

age

10.0

4.77

422

410

0.28

0.25

17.8

12.7

91.

120.

660.

260.

2445

.643

.60

245

320

1.85

1.5

Con

tinu

ed


TABLE

3.

Con

tinue

d

Poly

cycl

icar

omat

icSO

2C

O2

Cl 2

NO

2C

OH

2S

NH

3R

SPM

hydr

ocar

bons

(ppb

)(p

pm)

(ppm

)(p

pb)

(ppm

)(p

pm)

(ppb

)(μ

gm

−3)

(ng

m−3

)

Mon

ths

IO

IO

IO

IO

II

OI

OI

OI

O

Roa

dsi

de

site

sO

ct4

1.11

1.39

390

374

0.2

0.3

8.52

0.52

0.8

1.0

0.3

0.2

27.5

213

--

--

Nov

45.

502.

9447

939

70.

30.

344

.328

.61.

81.

30.

50.

2-

-28

316

61.

62.

1D

ec4

3.07

1.00

544

384

0.3

0.2

56.4

23.1

3.0

1.3

--

72.6

25.4

893

686

2.3

2.2

Jan

59.

474.

0152

341

90.

40.

39.

8310

.03.

21.

21.

20.

436

.720

.433

325

13.

43.

2Fe

b5

0.50

3.06

462

378

0.5

0.5

14.2

7.07

2.5

1.5

--

91.5

73.4

185

164

2.7

2.5

Mar

516

.70.

7747

432

40.

20.

13.

577.

481.

10.

90.

40.

363

.873

.792

188

1.9

1.1

Ap

r5

17.7

1.75

503

371

0.2

0.6

0.29

0.17

1.5

1.1

0.3

0.4

30.0

11.0

--

--

May

52.

225.

4546

734

20.

10.

313

.510

.90.

61.

10.

40.

4-

--

--

-Ju

n5

1.38

2.42

517

412

0.2

0.2

7.99

5.88

1.1

0.9

1.0

0.6

--

--

--

Jul

50.

430.

4635

933

10.

10.

20.

745.

010.

50.

90.

30.

454

.563

.024

824

71.

51.

0A

ug

52.

1914

.042

136

80.

60.

611

.97.

30.

71.

70.

20.

220

.938

.1-

--

-Se

p5

16.2

15.8

582

413

0.3

0.2

1.22

1.84

1.2

1.0

0.3

0.1

21.8

29.1

--

--

Oct

50.

961.

3754

847

20.

50.

45.

564.

222.

11.

20.

40.

222

.637

.4-

--

-N

ov5

0.84

16.9

538

488

0.4

0.3

34.0

16.3

33.

11.

00.

20.

322

.331

.7-

--

-D

ec5

-29

.358

355

90.

20.

244

.723

.33

3.0

0.9

0.2

0.1

24.4

30.5

--

--

Ave

rage

176.

749

240

20.

30.

317

.110

.11.

71.

10.

40.

2961

.353

.833

928

32.

22.

0


TABLE 4. Ratio of Mean Concentrations of Pollutantsa of Agra

Air-quality Polycyclic aromaticparameters SO2 NO2 CO2 CO Cl2 H2S NH3 RSPM hydrocarbons

A Indoor 2.91 4.36 0.97 0.93 1.40 2.00 1.98 3.19 1.29A Outdoor 7.36 0.95 0.95 1.00 1.75 0.93 0.56 1.97 1.62B Indoor 5.34 5.07 0.96 1.14 1.76 0.75 0.51 4.08 1.72B Outdoor 3.46 2.02 0.92 1.08 0.90 2.00 0.59 0.59 0.98

a(A) Winter to summer, and (B) winter to monsoon in urban areas.

TABLE 5. Indoor/Outdoor Ratios at Urban and Roadside Sites

Months SO2 NO2 CO2 CO H2S Cl2 NH3 RSPM

Rural housesOct 4 2.4 1.67 1.0 1.3 2.0 1.0 - 1.3Nov 4 0.19 - 0.9 1.3 1.6 1.0 - 0.7Dec 4 1.75 0.77 1.0 2.0 - 1.0 1.5 0.7Jan 5 1.15 1.45 1.0 2.0 1.3 1.5 0.2 0.8Feb 5 4.26 1.68 1.0 2.5 - 1.0 - 0.9Mar 5 - 0.26 0.7 1.1 2.0 1.0 0.02 0.5Apr 5 6.39 0.53 1.0 1.4 0.8 1.0 - -May 5 0.73 0.68 1.2 5.3 1.3 1.0 - -Jun 5 2.4 1.11 1.1 1.8 2.1 1.0 - -Jul 5 0.97 0.03 1.2 2.8 1.0 0.2 0.2 0.4Aug 5 0.92 0.12 0.8 1.2 1.0 2.0 1.5 -Sep 5 1.88 2.02 1.0 1.5 1.3 2.0 0.68 -Oct 5 0.76 0.55 1.0 13 2.0 06 0.45 -Nov 5 2.41 6.5 1.1 1.1 1.5 1.2 0.87 -Dec 5 2.9 - 1.0 1.8 0.5 1.5 0.78 -Average 2.07 1.36 1.00 1.89 1.41 1.13 0.68 0.75

Roadside housesOct 4 0.79 6.3 1.0 0.8 1.5 0.6 - 1.2Nov 4 1.87 1.25 1.2 1.3 2.5 1.0 - 1.7Dec 4 3.07 2.25 1.4 2.3 - 1.5 3.5 1.3Jan 5 2.36 0.98 1.2 2.6 3.0 1.3 1.5 1.3Feb 5 0.16 2.02 1.2 1.6 - 1.0 2.6 1.1Mar 5 - 0.46 1.4 1.2 1.3 2.0 0.3 0.4Apr 5 - 1.7 1.3 1.3 07 0330 - -May 5 0.40 1.23 1.3 05 1.0 03 - -Jun 5 0.57 135 1.2 1.2 1.6 1.0 - -Jul 5 0.93 0.14 1.0 0.5 0.7 0.5 0.8 1.0Aug 5 0.15 1.63 1.1 0.4 1.0 1.0 0.6 -Sep 5 1.02 0.66 1.4 1.2 3.0 1.5 0.74 -Oct 5 0.70 1.31 1.2 1.7 2.0 1.2 0.60 -Nov 5 0.04 0.63 1.1 3.1 0.6 1.3 0.70 -Dec 5 - - 1.0 3.3 2.0 1.0 0.8 -Average 0.86 1.67 1.2 1.53 1.39 1.03 1.37 1.14

Indoor/Outdoor Relationship

To further investigate relationships be-tween indoor and outdoor air quality, linearregressions was performed on the indoor ver-

sus outdoor concentrations of each pollutant atboth of the sites. Figures 5 and 6 show theserelationships for those homes where the maxi-mum concentration of the particular pollutantwas found during a season. The results shown


Figure 2. (A) Full-day variation of pollutants at an urban site during summer. (B) Full-dayvariation of pollutants at a roadside site during summer. (In color in Annals online.)

in the figure suggests that outdoor concentra-tions at the home are also good estimates ofindoor concentration of NO2 (winter (urban,r = 0.9702), monsoon (urban, r = 0.7107)), Cl2(winter (roadside, r = 0.778), summer (urban,

r = 0.808)), SO2 (winter (urban, r = 0.918)),and CO2 (winter (roadside, r = 0.801)). Neg-ative correlations were found for SO2 (sum-mer (roadside)) and H2S (monsoon (urban)),whereas it was less significant for CO (winter


Figure 3. (A) Full-day variation of pollutants at an urban site during winter. (B) Full-dayvariation of pollutants at a roadside site during winter. (In color in Annals online.)

(roadside, r = 0.6042), summer (urban, r =0.4947)), Cl2 (monsoon (roadside, r = 0.5357)),NH3 (winter (roadside, r = 0.5735), monsoon(urban, r = 0.4227)), CO2 (summer (roadside,r = 0.1625)), and H2S (winter (roadside, r =0.4706), summer (roadside, r = 0.6948)). It isimportant to note that the sample size used for

the univariate regression curves in this studywere relatively small (n = 30–34), and there is apossibility that the correlation coefficients weresignificantly effected by one or two extremelyhigh levels of data. For these reasons, interpre-tation of the correlation result should be takenas suggestive rather than definite.


Figure 4. (A) Full-day variation of pollutants at an urban site during rainy season. (B)Full-day variation of pollutants at a roadside site during rainy season. (In color in Annalsonline.)

Pearson Correlation Coefficient

To investigate the relation between indoorpollutant concentrations and the wind speedfor a dominant wind direction class interval,

the Pearson correlation coefficient betweenindoor pollutant concentration and wind speedwas calculated (Table 6). In the table positivecorrelations as marked in bold are observedfor SO2 (winter, summer), NO2 (winter), CO


Figure 5. Linear-regression curves between indoor and outdoor for their respective pollutants in homesof maximum concentration at urban site in different seasons (R2, r, and n are also shown). (In color in Annalsonline.)

Figure 6. Linear-regression curves between indoor and outdoor for their respective pollutants in homesof maximum concentration at roadside in different seasons (R2, r, and n are also shown). (In color in Annalsonline.)


(monsoon), NH3 (winter, monsoon), H2S (win-ter, summer, monsoon), Cl2 (winter), in urbanmicroenvironment, for roadside microenviron-ment SO2 (summer), NO2 (monsoon), CO(winter, summer, monsoon), NH3 (winter, sum-mer), Cl2 (winter, summer) showed positive cor-relation. The rest of the inverse relationshipbetween wind speed and the concentrations in-dicates that low wind speed favors the accu-mulation of pollutants (low wind speed is alsorelated to stable atmospheric conditions).

Factor Analysis

A varimax rotated factor analysis was per-formed to identify the main sources influenc-ing the concentration of the pollutants stud-ied at the sampling sites. In this statisticalmethod, a set of multiple intercorrelated vari-ables is replaced by a small number of linearlyindependent variables (factors) by orthogonaltransformations (rotations). This is achieved bydiagnosing the correlation matrix of the vari-able, that is, by computing their eigenvaluesand eigenvectors. Factor loadings obtained af-ter the rotation called varimax rotation givesthe correlation between the variables and thefactors. Each variable was also evaluated for itsKeiser–Mayer–Olvin value, which gives sam-pling adequacy, and data were included in thematrix only if it had eigenvalues greater than1. The varimax procedure was adopted for ro-tation of the factor matrix to transfer the initialmatrix into one that was easier to interpret.In the present study, the SPSS (version 11.0)20

computer software was used to perform factoranalysis.

Results obtained by varimax rotated factoranalysis are given in Table 7. The results inthe table have loading >0.5, because they aredeemed to be statistically significant. Factoranalysis of different pollutants from the indoorsmicroenvironment and outdoors for the road-side microenvironment has revealed five factorswith the eigenvalues > 1. These five sourceshave accounted for a total of 79.6% of the vari-ance in roadside environment. The first fac-

tor contributed 30.6% of the total variance,which contains pollutants; CO2, PAH, andtotal suspended particulate matter (TSPM).These point at probable combustion activitiesas the main source, which is the result of indoorcooking and the use of different types of oils. Italso focuses on the outdoor combustion of wasteon the roads. The second factor contributes to25.9% of the total variance, explaining loads ofNO2 and TSPM; vehicular emissions are themost probable source of them. The third fac-tor contributes 9.5% of the total variance; thisis related to dairy activities, which may be themain source of NH3. The next factor, whichcontributes 7.5% of the total contribution, isagain vehicular emission, as it is responsiblefor heavy loads of CO2, NO, and TSPM. Thelast significant factor, contributing 5.9% of totalvariance, indicates that loads of CO and SO2

may be due to the use of generators.The factor analysis of the pollutants mea-

sured both indoors and outdoors at houses lo-cated in an urban area reveals six factors witheigenvalues > 1 and contributes 85.3% of thetotal variance. The first and the most impor-tant factor that contains 25.06% of the totalvariance with a large loading of NO2, PAH,and TSPM may be because of the usage ofheavy diesel generators. At urban sites thereis an erratic supply of electricity, all the shop-keepers and the residents are forced to usethese heavy generators, which emit very harm-ful pollutants along with carcinogenic PAH.The second factor is contributed by 21.2%; theprobable source of this is biowaste, which in-cludes open wastes, manholes, animal wastes,and meat shops. The third factor at the urbansite is cooking activity, which emits loads ofCO2, CO, PAH, and TSPM. This factor con-tributes 14.6% of the total variance. The nextfactor represents 10.6% of the total variancewith heavy loads of NO and SO2, with inciner-ation being the probable source. The fifth fac-tor is responsible for Cl2 contributing 7.83%of the total variance. Here, cleaning activitiesseems to be the main source, and stems fromcleaning tiles and floors with different types


TABLE 6. Seasonal Pearson Correlation (R 2) Coefficient between Indoor Pollutants and Wind Velocityat Agra at Urban and Roadside Sites

DominantSeasons wind direction SO2 NO2 CO CO2 NH3 H2S Cl2 RSPM

UrbanWinter NW 0.541 0.746 −0.322 −0.254 0.989 0.893 0.835 0.126Summer SE 0.808 −0.134 −0.808 −0.825 0.082 0.707 0.121Monsoon E −0.226 0.089 0.609 −0.695 0.769 0.729 −0.279

RoadsideWinter NW −0.026 −0.865 0.563 −0.116 0.510 0.265 0.890 −0.36Summer SE 0.663 −0.708 0.553 0.120 0.805 0 0.816Monsoon E −0.119 0.546 0.919 −0.716 0.238 −0.957 −0.012

of media, such as bleaching powder, phenylsbleaching powder with CaCO3, and acids. Thesixth factor contributes 5.8% of the total vari-ance with the pollutants of CO and NO. Thisfactor can be interpreted as combustion activi-ties.

Conclusions and Recommendations

Several air-quality parameters were mea-sured simultaneously in order to develop a gen-eral profile of both indoor and outdoor air toassess the relationship between them in homeslocated in two different microenvironments,that is, urban and roadside in the Agra region.This study provides an example of systematicassessment and choice of indicator pollutantsin Agra where a diverse set of energy use, hous-ing, and exposure patterns exists and most ofthe developing cities world have similar typesof scenario. The main conclusions of the studyare:

(1) Exposure to indoor air pollution is a com-plex function of energy, housing, and be-havioral factors.

(2) Indoor activities that generate pollutantsinclude the use of different types of fuel forcooking and heating, cleaning, and the useof a variety of consumer products.

(3) The trend of increased indoor pollutionduring the winter months when com-

pared with the summer and monsoonmonths implies that several factors influ-ence tindoor air quality during the winter,including outdoor air and meteorologicalfactors. Such factors include indoor activ-ities, ventilation, and duration of humanoccupancy.

(4) Although the quality of the inside air, asdocumented in this study, was generallypoorer than the quality of air outdoors,the inside air was strongly influenced byother sources of pollution.

(5) Because no standards were available forinside air in India, the findings werecompared with available NIOSH21 andWHO22,23 standards (Table 8). All thegaseous pollutants were found to be withinpermissible limits. Only short-term expo-sure seemed to exceed the limits for afew minutes. Moreover PM10 concentra-tions exceeded the permissible limits sug-gested by WHO, making it an importantpollutant for assessing potential impactsof interventions. Thus, their physical andchemical characterization should be fo-cused on, as they may offer higher relia-bility for predicting health impacts.

Because the issue of IAQ is complex andrequires an interdisciplinary team to addressthem, an appropriate approach by the houseowner and consultant team is necessary to op-timize the quality of indoor air. From our study


TABLE

7.

Resu

ltsof

Fact

orA

naly

sis

with

Var

imax

Rota

tion

atU

rban

and

Road

side

Loca

tions

Urb

ansi

teR

oads

ide

site

Pollu

tant

sFa

ctor

1Fa

ctor

2Fa

ctor

3Fa

ctor

4Fa

ctor

5Fa

ctor

6Fa

ctor

1Fa

ctor

2Fa

ctor

3Fa

ctor

4Fa

ctor

5

Cl 2

outd

oor

1.35

8E−0

2−0

.147

−5.5

6E−0

24.

22E

−02

0.90

3−6

.95E

−02

0.45

5−0

.355

−0.3

50−2

90−0

.453

Cl 2

−0.1

72−0

.239

−0.1

74−4

.93E

−02

0.86

08.

78E

−02

--

--

-C

O2

indo

or−0

.283

−0.1

320.

860

2.25

E−0

23.

09E

−02

0.29

00.

773

−0.1

350.

336

0.3

6.95

E−0

2C

O2

outd

oor

0.12

1−4

.06E

−02

0.25

3−0

.315

−0.3

510.

699

−1.3

2E−0

20.

490

0.49

30.

579

4.61

E−0

2C

Oin

door

−0.2

04−0

.126

0.87

00.

208

−0.1

11−4

.8E

−02

0.83

3−0

.414

−0.1

81−0

.127

−6.4

8E−0

2C

Oou

tdoo

r0.

205

−0.1

600.

707

−8.5

−0.3

80−7

.6E

−02

0.12

3−1

370.

233

−6.5

1E−0

20.

871

H2S

−0.1

0700

.926

−0.1

342.

14E

−02

−0.1

111.

68E

−02

--

--

-H

2S

−.15

70.

926

−0.1

453.

5−7

.06E

−02

−3.1

E−0

2-

--

--

NH

3in

door

0.29

70.

818

−4.4

6E−0

2−0

.209

−0.1

77−8

.8E

−02

0.11

20.

325

0.83

40.

220

0.23

0N

H3

outd

oor

0.11

40.

945

-−0

.123

-−3

.2E

−02

5.28

4E−0

20.

194

0.85

00.

188

9.95

E−0

2N

O2

indo

or0.

949

--

-−7

.08

−9.7

7E−0

23.

452E

−20

0.95

00.

143

0.17

74.

81E

−02

NO

2ou

tdoo

r0.

931

--

-−0

.130

5.63

E−0

2−7

.42E

−03

0.93

10.

187

−4.4

9E−0

24.

32E

−02

NO

indo

or0.

375

−0.1

02−4

.34E

−02

0.50

8−4

.81E

−02

−0.2

35−2

.85E

−02

−3.9

7E−0

27.

781E

−02

2.73

8E−0

26.

18E

−02

NO

outd

oor

0.14

7-

0.14

30.

275

0.83

3−2

.85E

−02

−116

0.73

8−3

.96E

−02

PAH

indo

or0.

559

0.22

10.

691

0.14

2−0

.110

0.91

19.

725E

−02

−0.2

17−.

2.13

E−0

2PA

Hou

tdoo

r0.

875

0.17

0-

6.42

E−0

26.

6E−0

20.

192

0.86

03.

88E

−02

−0.2

320.

208

SO2

indo

or−3

.34E

−02

-0.

326

0.86

54.

87E

−02

0.38

30.

362

−0.4

830.

323

0.11

9SO

2ou

tdoo

r−1

.23E

−02

−0.1

15−2

.48E

−02

0.95

8−3

.2E

−02

4.05

E−0

25.

376E

−02

0.15

6−0

.323

7.76

3E−0

20.

661

TSP

Min

door

0.56

2−0

.163

0.76

24.

72E

−02

−7.8

E−0

20.

111

0.87

60.

485

0.14

40.

290

−2.0

0E−0

2T

SPM

outd

oor

0.87

6−0

.165

0.27

07.

97E

−02

−8.4

4E−0

20.

173

0.39

10.

619

0.30

80.

529

1.45

6E−0

2E

igen

valu

e5.

012

4.24

2.93

2.1

1.56

1.18

5.51

14.

674

1.71

21.

359

1.07

9T

otal

vari

ance

25.0

%21

.2%

14.6

%10

.6%

7.8%

5.8%

30.6

%25

.9%

9.5%

7.5%

5.9%

Prob

able

Die

sel

Bio

was

teC

ooki

ngIn

cine

ratio

nC

lean

ing

Com

bust

ion

Veh

icul

arIn

cine

ratio

nD

airy

Com

bust

ion

Aut

omob

ileso

urce

gene

rato

rsac

tiviti

esac

tiviti

esac

tiviti

esem

issi

ons

activ

ities

activ

ities

repa

irw

orks


TABLE 8. Threshold Limit for Airborne Contami-nants by National Institute for Occupational Safetyand Health and the World Health Organization

Time weighted averageconcentration (8-h workday)

Pollutant ppm μg m−3

CO 25 28,630NO2 3 5644.2SO2 2 5235.2CO2 1000 1799.6 × 103NH3 - -H2S - -PM10 - 100

(70,50,30,20)a

PAH - 0.001MeteorologicalParametersRH% 30–80Temperature, ◦C 25.5Air movement, ms−1 <0.3

aNew interim targets of annual mean which should beobtained in a stepwise manner.

and observations, four general categories of in-terventions have been identified that should betaken up to reduce indoor air pollution in urbanareas.

(1) Concerned city development authoritiesshould not allow the colonies to crop upadjacent to national highways or roadshaving heavy traffic.

(2) Behavioral changes in occupants shouldbe encouraged to reduce exposure, forexample, giving up incense burning dur-ing prayers, mosquito coil burning, and soforth

(3) Increase household ventilation at the timeof construction or modification, as the ma-jority of houses are naturally ventilated inthese parts of the world.

(4) Incentives for shifting to efficient andhigh-energy ladder fuels by the concernedgovernment agencies.

Moreover, the factors leading to adoption ofany the preceding suggestions at a household’slevel extend well beyond the technical and eco-

nomic to the the social, cultural, and perpet-ual. Therefore awareness through education,advertising, and other avenues directed at in-fluencing the behavior of occupants will alsoplay an important role in the near future.

Acknowledgments

The authors gratefully acknowledge the fi-nancial assistance received from the Depart-ment of Science and Technology, New Delhi(DST) Project No. SR/S4/AS: 228/03 for car-rying out this work. We also thank Dr. F.M.Prasad, Principal, and St. John’s College forhis encouragement, Dr. Ashok Kumar, Head,Department of Chemistry, St. Johns College,Agra, for providing us the necessary facilities,and Aditi Kulshrestha for the preparation ofthe manuscript.

Conflicts of Interest

The authors declare no conflicts of interest.

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Indoor Air Quality of Houses Located in the Urban Environment of Agra, India

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