Department of Chemistry

Dr. B. R. Ambedkar Agra University

Email: ataneja5@hotmail.com

People spends most of their time indoors yet the majority of pollution

concentration data is based on measurements conducted outdoors in one

and more central monitoring sites

HAP is responsible for 6.0 % of the total national burden of disease, 1.04

million premature deaths and 31.4 million disability adjusted life

years(DALYS) in India(South Asia)

IAP has been linked to three MDGs (Millennium development goals) out

of eight goals earmarked by UN

GOAL 4 : REDUCED CHILD MORTALITY

GOAL 5: IMPROVE MATERNAL HEALTH

GOAL 7: ENSURE ENVIRONMENTAL SUSTAINABILITY

• Indoor Air Pollution is the term used to describe the amount of

contaminants in the air inside a building.

• The National Health and Medical Research Council (NHMRC)

defines the indoor air as “air within a building occupied for at least

one hour by people of varying states of health.” This can include the

office, classroom, transport facility, shopping center, hospital and

homes.

• Indoor air quality can be defined as “the totality of attributes of

indoor air that affect a person’s health and well-being.”

INDOOR AIR QUALITY

OUTDOOR AIR QUALITY

NATURAL SOURCES

BUILDING MATERIALS

SOURCES

ACTIVITIES RELATED SOURCES

CONTENTS OFF-GASING

SOURCES

GROUND WATER QUALITY

MOBILE

TRANSPORTATION

SOURCES

ENERGY

GENERATION

SOURCES

MANUFACTURING

SOURCES

NATURAL

SOURCES VAPOR

INTRUSION

HVAC SYSTEMS SOURCES

India faces the dual problem of air pollution at rural and urban fronts.

India is undergoing rapid urbanization and industrialization and indoor air

quality is strongly influenced by motor vehicles and industrial sources outdoors

as well as smoking and gas cooking indoors.

In urban area fuel usage patterns are complex and differ by socioeconomic

status. Household energy decisions are shaped by income , social expectations

and fuel availability.

Balakrishnan et al. Environmental Health 2013 12:77 doi:10.1186/1476-069X-12-77

Weighted state estimates for

average 24 hr kitchen area

concentrations of PM2.5 for all

solid- fuel-using households in

India (Note: Solid-fuel-using

households include both urban and

rural households. State estimates

are weighted by the percentages of

rural, urban households using solid

cook fuels as the primary fuel,

respectively.

• In UP state 62.5 percent of rural households use firewood as the primary fuel for cooking, 12.3 percent

use crop residue as the primary cooking fuel, and 10.9 percent use dung.

Households by primary fuel used for cooking Percentage

Fuel Type Total Rural Urban

Firewood 49.0 62.5 20.1

Crop residue 8.9 12.3 1.4

Cowdung cake 7.9 10.9 1.7

Coal, Lignite, Charcoal 1.4 0.8 2.9

Kerosene 2.9 0.7 7.5

LPG/PNG 28.5 11.4 65.0

Electicity 0.1 0.1 0.1

Bio-gas 0.4 0.4 0.4

Any other 0.5 0.6 0.2

No cooking 0.3 0.2 0.5

Note: LPG = Liquefied Petroleum Gases; PNG = Piped Natural Gas. Source: India Census 2011

•In 1993-94 as many as 78% households in rural India used biomass as cooking fuel and in 2009-10,

76% used this fuel. Therefore in this period when urban India moved to LPG(from 30% to 64%) rural

India remained where it was. National sample Survey office (NSSO) { Down to Earth, Feb 16-

28,2014}

Concentration: 10-100 times NAAQS: Dung> crop residues> wood

Composition: Complex mixture;

Gases: CO, NOx, SO2 etc.

VOC: Benzene, toluene, xylene etc.

PAH: Benzo(a)pyrene, Benz-anthracene

Heavy metals: Pb, Fe, Cd, Zn, Ni

Particulate Matter: Of different size and composition

Exposure: High- short duration (2-4 hrs/day)

The health effects are the impact of this complex mixture

rather than a particular pollutant

(Chittranjan National Cancer Institute, Kolkata)

• ALRI

• Lung function impairment

• Numerical, structural and functional alteration of Alveolar Macrophage

• Sputum cytology alterations

• Nuclear anomalies- biomarker of Genotoxicity

• Heamatological and metabolic alteration

• Immune alterations (vulnerable to infections)

Some of these alterations are reversible and proper intervention measures can

prevent the Development of irreversible diseases like COPD and cancer

Exposure to biomass fuel emissions in rural women cause significant increase in:

• Pollutant levels are often greater than outdoors.

•Many pollutant sources.

oInfilteration and accumulation of outdoor air.

oLimited air volume and poor air mixing.

• Severe problem in developing countries

oNon chalance

oLesser attention paid by the authorities

1. How can we quickly and cheaply identify households likely to have

the highest exposures?

- How can we create refined regional and national exposures

profiles with a minimal amount of air sampling

- How do differences in housing/ventilation affect exposures?

- Can household characteristics be used to predict exposures?

2. What should be done to reduce exposure?

- What are possible strategies to reduce exposure?

- Choosing interventions that are cost-effective?

Challenges

• A national “clean household” promotion program: low-cost alterations in

houses and cooking locations, combined with effective public education on

the associated health benefits, could reduce Indoor Air Pollution exposure to

much safer levels for many poor families.

•12th five year plan…urban areas to meet the air quality standards by 2017

•12th plan highlights need for epidemiological studies

•Planning commission working on environmental performance index to

incentives state for environment performance through budgetary allotment

No action for indoor air pollution

National Health Research Policy – will this address health concern related to air

pollution

•Studies on Indoor/Outdoor Relation of Air Quality in Residential Homes. 2004-2006

(DST).

•Size and Chemical Composition Distribution of Particulate Matter in Different

Indoor Microenvironment. 2007-2010 (DST).

•Distribution of Particulate and Vapour phase Polycyclic Aromatic Hydrocarbons in

Residential Microenvironment and assessment of their related Carcinogenic

Potencies 2009-2012. (UGC).

•Emissions and Formation of Fine Particles from Hardcopy Devices: The cause of

Indoor Air Pollution. (Case Study).

•Studies on Indoor Air Pollution in Classroom of Schools Located in Different

Microenvironments, Ph.d (2008-2011).

•Fine Particle and Its Elemental Bioavailability, The Potential Health Risk of

Exposure in Domestic Homes Located in Different Micro-environments (2012).

•Chemical and Morphological Composition of Fine Particulate Matter in Low-

Middle- and High-Income Neighborhoods in Agra city (2012).

1. Exposure to IAP is a complex function of energy, housing and behavioral factors. Diverse

set of energy use, housing and exposure patterns exists.

2. Indoor activities that generate pollutants include the use of gas or kerosene stoves and

wood/cow dung for heating, cooking, cleaning and the use of a variety of consumer

products. The density of human occupancy with people tending to spend more time

indoors in the winters than in the summer combined with inadequate ventilation also can

play important role in determining air quality.

3. All the gaseous pollutants were found well within permissible limits. Only short term

exposure seems to exceed the limits for few minutes. However PM10 (at all sites)

concentrations exceeded the permissible limit of 100 µgm-3 suggested by WHO.

4. Our results also indicate that particulate concentration their physical and chemical

characterization should be focused upon as they may offer higher reliability for

predicting health impacts.

To provide quantitative Information on the level of PM10, PM2.5 and PM1.0 in

typical microenvironment (domestic homes) located on roadside, urban and

rural areas

Characterization of Particulate Matter in terms of Major Elements and ions

To compare indoor and ambient particulate levels as a part of the task of

source apportionment

To investigate the extent to which certain indoor pollution sources influence

the quality of indoor air in domestic homes

Size and Chemical Composition Distribution of Particulate Matter in

Different Indoor Microenvironment. 2007-2010 (DST ).

Selection of Homes on the

basis of Locations

Household level survey

to obtain data of house-

hold characteristic, behavior

factors, activity diary

Sampling indoors/outdoors,

real time series data for

PM10, PM2.5 & PM1.0 particulate

average data

Temp, humidity, wind speed

and wind direction

Meteorological parameters

Determined (Metrological

data logger WM 251 Envirotech)

CO2 concentrations( time

series data and Ventilation rate

YES 205 & 206 IAQ monitors

Roadside, Urban & Rural

Questionnaire

Hindi as well as in English

Grimm IAQ Monitor

Low Volume Samplers

Medium Volume Samplers

(Envirotech)

Conditioning and weighing of filter papers

(GF/A &Teflon 47mm diameter )

Metals ( Pb, Zn, Fe, Ni, Mn, Cu, Cr)

Anions & Cations (F- ,Cl-, NO3

-, SO42-, NH4

+ ,Na+, K+,Ba2+ ,Ca2+, Mg2+)

Ion Chromatography (Dionex 2000) & AAS

EmissionMode)

Seasonal Variations linking to

meteorological changes & CO2 concentration

Statistical Analysis, I/O ratios, Correlation

Analysis, Source Apportionment

Suggestions and Report Submission

Acid

Extraction

Water

Extraction

AAS Perkin

Elmer

Awareness

Seasonal Trends of Particulate Matter in indoor and outdoor environments at

three sites

• Concentrations of Particulate matter in all three different locations (i.e. Roadside, urban

site & rural) were found to be highest in the winter season followed by summer and rainy

seasons.

• The trends of particulate mass concentration during the sampling duration:

•PM10 roadside>rural>urban indoors as well as outdoors

•PM5.0 roadside>rural>urban indoors as well as outdoors

•PM2.5 rural>roadside>urban indoors and roadside>rural>urban for outdoors

•PM1.0 roadside>rural>urban indoors as well as outdoors.

•On comparing the annual average PM10 & PM2.5 concentration with new NAAQS, it was

found to be 3-4 times higher indoor as well outdoor and on comparing with WHO our

results exceeded 10-13 times and 12-16 times for PM10 and PM2.5 outdoor, whereas indoor

concentration ranged between 9-12 and 11-16 times during the sampling duration.

PM2.5: 10 μg/m3 annual mean

(35, 25, 15)

25 μg/m3 24-hour mean

(75,50, 37.5)

PM10: 20 μg/m3 annual mean

(70, 50, 30)

50 μg/m3 24-hour mean

(150, 100, 75)

New

40 μg/m3 annual mean

60 μg/m3 24-hour mean

60 μg/m3 annual mean

100 μg/m3 24-hour mean

UNANALYSED PERCENTAGE

SIZE SITE INDOOR OUTDOOR

PM10 ROADSIDE 51.20 40.50

RURAL 48.47 37.99

URBAN 46.93 34.23

Total 48.75 37.63

PM2.5 ROADSIDE 34.29 42.16

RURAL 28.49 38.10

URBAN 28.45 30.79

Total 29.92 37.09

PM5 ROADSIDE 21.00 22.51

RURAL 26.20 33.31

URBAN 29.34 22.19

Total 25.58 27.66

Total ROADSIDE 28.19 38.46

RURAL 29.73 37.19

URBAN 31.44 30.63

Total 29.91 35.70

• In Indoors in winter season at roadside it was 1.01 , 1.70 times, in rural

site it was 2.0, 2.28 times whereas at urban site the concentrations were

1.25 and 2.05 times than summer and rainy seasons respectively.

• At outdoors, at roadside the concentrations were 1.56 times, 2.28 times

more, whereas at rural site it was 1.56 times, 2.39 times higher. While at

urban site it was 1.35 and 1.91 times higher in winter season than in

summer and rainy seasons.

• Higher concentrations of chemical constituents outdoors in winter

season can be due to low wind speed and high humidity in comparison to

other season, so the removal of aerosol particles is reduced by dispersion.

• At indoors due to increased Human activities and more space heating

during this season increases particulate concentration which is composed

of several chemical constituents.

ROADSIDE INDOORS ROADSIDE OUTDOORS

RURAL INDOORS RURAL OUTDOORS

URBAN INDOORS URBAN OUTDOORS

PCA identified following contribution of sources at sampling

microenvironments which explains 76% to 88% of source

contribution:

• Higher probability of suspension in the atmosphere and a longer residence

time.

• More than 90% of the mineral particles deposited in airway sites of the

human being had aerodynamic(or mean) diameters less than 2.5µm.

• Prevalence of allergy related diseases( Epidemic of 21st century).

• A higher surface area per unit volume than larger particles increases the

capability to adsorb compounds some of which are potentially

carcinogenic.

Sampling Sites Sizes Mean IN µgm-3 Mean OUT µgm-3

Roadside PM2.5

PM1.0

PM0.5

PM0.25

137.93 ± 55.75

117.09 ± 46.05

68.17± 6.76

8.55 ± 3.60

202.95 ± 54.18

177.20 ± 49.97

99.15 ± 14.63

9.29 ± 7.49

Rural PM2.5

PM1.0

PM0.5

PM0.25

173.03 ± 55.03

133.26 ± 48.41

96.02 ±54.82

8.56 ± 12.05

178.32 ± 45.50

153.62 ± 43.63

73.69 ± 45.93

6.58 ± 3.94

Urban PM2.5

PM1.0

PM0.5

PM0.25

135.55 ± 42.15

102.92 ± 39.11

38.38 ± 23.06

6.35 ± 7.44

156.40 ± 52.96

136.31 ± 57.25

71.88± 16.67

6.38 ± 6.75

• The trends of particulate mass concentration indoors were rural>roadside>urban and for

outdoors were roadside>rural>urban

• PM2.5 values were 7-10 higher than WHO standards.

• The average I/O ratios for PM2.5, PM1.0, PM0.5 and PM0.25 in roadside and rural areas were

close to or above 1.00 and less than 1.00 for urban areas

Ionic ratio is ∑ cations (equivalent mass) / ∑ anions (equivalent mass)

• Box plots are drawn to link the I/O ratios in the roadside, urban and rural

houses with different activities like cooking medium, different oils used for

cooking and other activities like smoking and incense burning.

• House using clean fuel like L.P.G (Liquefied Petroleum Gas) have lower I/O

ratios in comparison to houses using fuel like wood, cow dung cakes, kerosene

etc.

• Activities like smoking and incense burning in indoors also contribute more to

fine particle concentrations than coarse particles.

• These exposure activities were found more in common in rural houses

followed by roadside and urban houses.

• Average ionic I/O ratios are found to

be above 1 in PM2.5 rural and roadside

areas whereas for urban areas were less

than 1.

• At the rural site Cl-, S042-,, Mg2+, Na+ &

Ca2+ have higher I/O ratios

• At roadside site F− ,Cl- & NO3- and at

urban site Ba2+ and Mg2+ have higher

loading

-20.00

0.00

20.00

40.00

60.00

CO

NC

EN

TR

AT

ION

(µg/m

3)

ELEMENTS

URBAN RURAL ROADSIDE

•At urban site, elemental concentration is in the order as follows: Al>Cu>Ba>As.

•Elemental concentration at rural site followed the order: Al>Fe>Ba>Mn=Co>Cu=As>Pb.

•Elemental concentration at roadside followed the trend: Al>Fe>Ba>As>Mn>Pb>Cu

•The largest source of airborne aluminum containing particulates is the flux of dust from soil.

• The major anthropogenic sources of aluminum containing particulate matter include coal

combustion and care products like cosmetics and hair sprays (Lantzy et al., 1997).

•Pb was detected at roadside and its probable sources are lead based paints(Jonathan et al.,

2003), soil and dust(Young et al., 2002).

ELEMENTS Cu

(µg/m3)

Mn

(µg/m3)

Fe

(µg/m3)

Ba

(µg/m3)

Pb

(µg/m3)

Al

(µg/m3)

SOLUBLE FRACTION 0.027 0.014 0.661 0.104 0.207 29.284

INSOLUBLE FRACTION 1.841 0.511 49.192 27.432 0.526 475.250

% BIOAVAILABILITY 1.45 2.67 1.33 0.38 28.24 5.80

Bioavailability of Elements in PM2.5

% Bioavailability= (Soluble fraction *100)/ Total Fraction

•The bioavailability of elements is identified with their mobility, which is defined as the

water solubility of their compounds. The soluble metal fraction was extracted using

0.01M ammonium acetate solution (AA) at pH 7 to simulate the neutral lung

environment.

• The total concentration of all elements in PM2.5 was 589.93 (µg/m3), in which the

soluble fraction which simulates the neutral lung environment at pH 7 is 5.1%.

•Extractable fraction which contributed bioavailability was as Pb (28.28%), Al (5.80%),

Mn (2.67%), Cu (1.45%), Fe (1.33%) and Ba (0.38%).

•Elemental bioavailability in PM2.5 followed the trend as: Pb>Al>Mn>Cu>Fe>Ba.

•Particle size and chemical compositions of PM are crucial factors for human

health since the efficiencies of inhalation, respiratory deposition, and

bioavailability are dependent upon these factors.

•It is important to consider the differences in trace metal solubility from a

bioavailability perspective because the predominant exposure pathway for

airborne particulates to humans is through the air/lung interface.

•Elemental bioavailability in PM2.5 followed the trend as:

Pb>Al>Mn>Cu>Fe>Ba.

•Lead is reasonably anticipated to be human carcinogen. It exists in various

inorganic and organic forms, which affect its environmental fate, transport and

bioavailability. Therefore the potential carcinogenic risk posed by Pb and Cu

and the non carcinogenic risk posed by Mn, Ba and Al via inhalation.

Variable Parameters Low-Income Middle-Income High-Income

PM2.5

(µg/m3)

M 46.7 39.2 25.6

Morn Noon Even Morn Noon Even Morn Noon Even

54.3 23.2 64.5 39.1 20.4 57.2 21.0 16.2 50.3

Md 32.9 25.0 21.8

S. E. 4.4 4.1 2.3

Skew 3.3 2.6 3.1

95% C. I. 38.1-55.5 31.1-47.3 20.9-30.2

The average mass concentration of PM2.5 in low-income group homes was 46.7 μg/m3 which was 19.3%

higher than middle-income group homes (39.1 μg/m3) and 82.6% higher than high-income group homes (25.6

μg/m3).

In low-income group homes, the highest average fine particulate matter (PM2.5) concentration was recorded

in the evening hours (1800-2100 hours) (18.7% higher than morning hours) followed by morning hours

(0700-1000 hours). In middle-income group homes, evening concentration was 46.2% higher than morning

hours. In high-income group homes the evening concentration was 139.5% higher than morning hours and

211.3% higher than afternoon hours (1200-1400 hours).

In low- middle- and high-income group homes cooking may be the major contributing factor in variation of

PM2.5 concentration in evening and morning hours

CHEMICAL AND MORPHOLOGICAL COMPOSITION OF FINE PARTICULATE

MATTER IN LOW- MIDDLE- AND HIGH-INCOME NEIGHBOURHOODS INAGRA

Low-Income Group < Rs 5000/month, Middle Income Group < Rs 50,000/month, High Income Group> Rs 70000/month

Elemental and Morphological Analysis

Low-Income Middle-Income High-Income

Low Income Middle Income High Income

Shapes of

Particles

Branched spherical, nearly

spherical, cluster, and flaky

shaped

Spheres, cluster, flaky,

irregular, near sphere and

tubular shaped particles.

Particles are reticular, flaky,

cluster, and irregular shaped

Elements &

Their

Percentage

Distribution

C (49%) > F (42%) > O (5%) >

Si (1%) > Na (1%) > Al (1%) >

Mg (1%)

F (59%) > C (34%) > O (3%) >

Al (2%) > Si (1%) > Na (1%)

F (65%) > C (29%) > O (3%) >

Si (2%) > Al (1%)

Possible

Sources

Biomass fuel burning,

Cooking on unvented mud

stoves, Smoking (C-O) [Hand

et al., 2005; Alexander et al.,

2008; Cong et al., 2009], Coal

Burning, Pesticides, Brick

Kiln (F) [Hyunn et al., 1991;

Schauer, 2003; Lonati and

Giugliano, 2006; Ikezawa et al.,

2011], Mineral dust ((Si-Na),

Aluminosilicates (Al-Si-O))

[Shao et al., 2007], Talc (Mg-

Si or Mg-Al-Si) [Conner et al.,

2001].

Incense Burning, Mosquito

Repellent/Coil/Spray,

Insecticides (F) [Lonati and

Giugliano, 2006; Ikezawa et al.,

2011] , Cooking (C-O) [Murr

and Bang, 2003], Dusting,

Cleaning (Soil-related

component like Na, Si, and

Al) [Murr and Bang, 2003],

Building material viz.,

cement, bricks glass, ceramics

and clays (Si-O) [Cong et al.,

2009], Soil delivered

aluminosilicates (oxides of Al

and Si with varying amounts

of Na) [Pachauri et al., 2013]

Pest (pesticides/insecticides)

control performed few days

before the study and regular

floor polishing [Safai et al.,

2005], Outside Contamination

from Industries using Coal,

Diesel generators and garbage

burning (F) [Webber, 2009],

Cooking (C-O), Cleaning,

Crustal Sources

(Aluminosilicates having

oxides of Al and Si)

[Slezakova et al., 2008].

Besides all these sources in all the three income group homes viz., low- middle- and high-income group

homes, presence of large concentration of carbon and fluorine particles may be attributed to matrix effect

and coming from PTFE filter paper [Ikezawa et al., 2011]

Low temperature biofuel combustion has the potential to result in higher emissions

of PAHs than high-temperature industrial sources.

PAHs emission factors from wood combustion in small-scale space heating

stoves exceeds those from furnace oil combustion

Thus

It is important to reveal the abundance, distribution and potential sources of PAHs in

the Indoor air both in aerosol and in the vapor phase

Distribution of Particulate and Vapour phase Polycyclic Aromatic Hydrocarbons

in Residential Microenvironment and assessment of their related Carcinogenic

Potencies 2009-2012. (UGC )

Why PAHs

In a screw top vial, add

Dichloro Methane for extraction

Filters, front & back sections of

XAD extracted separately

BS/BSD, Lot Blank, Field

Blank (QA/QC)

Transfer of Filtrate to

sampler vial

Shaking of vial (2 min) &

settle for 30 min

Analyzed by GC/MS

XAD tubes and

filter paper at ambient temperature

Extraction and Analysis

KITCHEN LIVING OUTDOOR

NAP 676.25±379.08 687.57±285.46 472.92±135.83

2MNAP 162.65±75.12 181.75±91.45 139.92±113.89

1MNAP 125.53±36.04 121.91±66.26 94.52±44.27

BPHY 78.79±4.97 70.97±22.07 49.86±8.34

2,6DMNAP 60.31±21.69 48.24±13.32 40.86±21.67

ACY 58.69±29.83 45.34±13.05 21.3±10.42

ACE 25.48±4.87 29.49±5.97 14.77±1.94

DBF 44.72±8.33 31.33±13.13 22.53±7.60

FLU 35.05±10.34 31.25±16.49 21.49±6.12

PHE 55.1±20.45 44.93±22.40 31.62±9.89

ANT ND 29.75±9.00 38.02±18.63

CAR 34.45±1.90 ND ND

FLT 14.55±1.83 19.77±3.59 12.8±2.19

PRY 11.31±1.03 16.69±1.45 14.44±4.59

B(a)A 7.87±1.52 9.81±2.92 ND

CHR 7.23±1.16 ND

B(b)F 8.92±1.83 6.31±1.57 ND

B(K)F 5.74±1.97 11.73±0.53 ND

B(e)P 5.14±0.45 11.49±1.22 ND

B(a)P 8.11±2.92 12.34±4.07 ND

I(123-CD)P ND ND ND

DBA ND ND ND

B(ghi)P 7.17±0.76 19.88±7.81 ND

MEAN 71.65 75.29 75.00

MEDIAN 29.96 29.75 31.62

TOTAL 1433.16 1430.62 975.09

URBAN

PAHs

AVERAGE CONCENTRATION OF PAHS IN (ng/m3)

KITCHEN LIVING OUTDOOR

NAP 832.57±385.02 793.41±128.37 855.49±312.22

2MNAP 303.9±30.18 160.45±66.16 254.11±76.05

1MNAP 139.76±59.47 134.45±34.79 179.21±49.36

BPHY 94.07±7.06 93.93±64.34 107.42±64.99

2,6DMNAP 93.26±8.69 88.45±35.89 77.73±34.35

ACY 73.35±7.45 55.06±6.20 94.44±8.36

ACE 15.26±9.81 4.29±1.03 28.04±11.69

DBF 55.68±30.10 42.83±22.51 46.18±3.72

FLU 28.76±3.42 16.18±3.04 36.91±3.32

PHE 38.43±3.09 22.98±7.84 57.72±8.14

ANT 13.8±2.24 40.37±6.29 17.58±1.20

CAR 22.9±4.12 ND 70.41±1.18

FLT 19.51±5.94 17.98±0.59 26.07±11.46

PRY 17.03±5.60 16.77±3.43 28.64±8.52

B(a)A 19.27±2.64 22.77±6.50 14.96±5.46

CHR 13.47±5.34 28.36±5.18 15.49±6.46

B(b)F 13.65±1.04 36.55±7.47 34.95±4.22

B(K)F 8.1±1.4 16.58±3.07 11.15±5.32

B(e)P 13.24±7.36 11.76±4.56 11.92±8.10

B(a)P 7.62±1.81 18.18±8.23 14.03±3.14

I(123-CD)P ND ND 13.83±4.36

DBA ND ND ND

B(ghi)P 9.2±4.65 3.41±1.10 11.68±4.41

MEAN 87.28 81.24 91.27

MEDIAN 19.51 25.67 31.79

TOTAL 1832.94 1624.86 2008.05

PAHsROADSIDE

Among all the PAHs Naphthalene and its methyl substituted derivatives was found

dominating at all sites homes in indoor and outdoor environment and it ranged from 40.86

to 855.49 ng/m3 and their percentage contribution range was 20 – 56%

While the concentrations of TPAHs at urban site homes ranged from 5.14 – 687.57 ng/m3

(indoors), 12.8 – 472.92 ng/m3 (outdoors). At roadside the TPAHs concentration in indoor

air ranged from 4.29 – 832.57 ng/m3 and in outdoor it ranged from 11.15 – 855.49 ng/m3,

whereas at rural site it ranged from 12.80 – 645.83 ng/m3 and 16.64 – 720.33 ng/m3 in

indoor and outdoor environment respectively.

Comparison between sites showed higher concentrations at roadside both indoors and

outdoors due to affect of vehicular emissions.

CONCLUSIONS

The gas particle partitioning of PAHs revealed that naphthalene and its methyl derivative

with biphenyl and dibenzofuran were all found in gaseous phase followed by some semi

volatile compounds such as acenaphthylene, acenapthene, fluorene and phenantharene.

whereas in particulate phase all higher molecular weight PAHs such as chrysene,

benzo(a)antharacene, benzo(b,)fluoranthene, benzo(k)fluoranthene benzo(e)pyrene,

benzo(a)pyrene, indeno(123cd)pyrene and benzo(ghi)perylene were abundant with some

semivolatile compounds.

The contribution of gaseous phase PAHs was 49.39 - 56.09% and in particulate phase it

was 20.44 - 36.43% at all three locations.

A significant difference in total PAHs concentration in indoor and outdoor air was also

observed among the seasons. The concentrations of PAHs were found more in winter

months of season (November-January). They were 1.34 to 4.88 times higher in winter

season than summer and rainy seasons.

Immediate

IAQ of a house located in different microenvironment is known. Activity linked exposure

can also be seen.

Long Term

The underlying biological causes of the health effects of particles exposure are not clear,

thus their chemical characteristic will serve as reference to elucidate particle toxicity

The data generated will also give an idea on distribution of size fractionated particles

which is needed to identify the regions and populations where investigations need to be

focused such as engineering and dissemination approaches for improved stoves, fuels,

ventilation and behavior that reliably and economically reduce exposures

Models can be build in future to trace elements and ions to their potential emission sources,

if elemental signatures are provided

These measurements will help to work for consistency between emission standards and air

quality standards and develop a better understanding of particle formation and post formation

processes

1. To gain quantitative information of coarse and fine particulate matter in

the classrooms of different schools located in different

microenvironment i.e. roadside schools and in residential areas.

2. To characterize sedimented dust in terms of major elements and ions in

the classrooms of schools situated in different areas.

3. To analyze the seasonal variations in indoor particulate concentration and

sedimented dust concentration i.e., winter and summer and link it to

meteorology conditions.

4. To access the exposure of particulates and their related toxicity to school

children.

•PM concentration were found higher at roadside than at residential schools

•Coarse particles PM10 shows high elevation in indoors i.e. indoor activities

largely influence indoor levels.

•The heavily polluted area at roadside marks higher trends for PM levels.

•Schools at residential area were higly influenced by localized activities of a

particular monitoring area, leading to higher levels of I/O ratios of PM

•School dust was mostly found enriched with Fe and Zn , followed by Mn, Pb,

Cu, Ni, Cr and Cd.

•These indicate contamination of regional soil dust with vehicular activities,

welding soldering and burning activities.

Pettenkofer (1858):

“If there is a pile of manure in a space, do

not try to remove the odor by ventilation.

Remove the pile of manure.”