Aerosol Chemistry and Aerosol Chemistry and Climate change and Climate change and public health at an Indo public health at an Indo Gangetic Plain in IndiaGangetic Plain in India

RANJIT KUMAR RANJIT KUMAR and and K. MAHARAJ KUMARI K. MAHARAJ KUMARI

DAYALBAGH EDUCATIONAL INSTITUTE, DAYALBAGH EDUCATIONAL INSTITUTE, DAYALBAH, AGRADAYALBAH, AGRA--5. 5. EE--MAIL: rkschem@rediffmail.comMAIL: rkschem@rediffmail.com

Climate change has been Climate change has been seen in the form of seen in the form of --

Global warmingGlobal warminghotter summer for longer periodhotter summer for longer periodshorter but extreme cold in wintershorter but extreme cold in winterDroughtDroughtFlood Flood Change in rain patternChange in rain patternWater scarcityWater scarcityIncrease in number of diseasesIncrease in number of diseases

Climate changeClimate changeClimate change may be due : Climate change may be due : -- to natural internal processes or to natural internal processes or -- to external forcing, including changes in to external forcing, including changes in solar radiation and volcanic eruptions, or solar radiation and volcanic eruptions, or -- to persistent humanto persistent human--induced changes in induced changes in atmospheric composition or inatmospheric composition or in land useland use. .

The composition of the atmosphere -- its gases and particles -- plays a critical role in connecting human welfare with global and regional changes because the atmosphere links all of the principal components of the Earth system.

Aerosol particlesAerosol particles

Atmospheric aerosol particulates play an Atmospheric aerosol particulates play an important role in radiative forcing and important role in radiative forcing and climate changeclimate changeresponsible for visibility impairment and responsible for visibility impairment and have significant implications on human have significant implications on human health health associated with acid deposition and, associated with acid deposition and, therefore, effects on terrestrial and therefore, effects on terrestrial and aquatic ecosystems aquatic ecosystems

airborne particulates may be generated airborne particulates may be generated by a variety of sources, e.g. natural sea by a variety of sources, e.g. natural sea spray or wind blown dust, anthropogenic spray or wind blown dust, anthropogenic activities such as fuelactivities such as fuel--combustion, combustion, industrial processes, transportation and industrial processes, transportation and solid waste disposal solid waste disposal aerosols consist of many different types aerosols consist of many different types of particles (e.g. sea salt, mineral dust, of particles (e.g. sea salt, mineral dust, fly ash and biogenic particles). fly ash and biogenic particles).

Aerosol physical and optical properties Aerosol physical and optical properties depend on which type of they are. For depend on which type of they are. For example, the sulfate aerosols are example, the sulfate aerosols are considered to result in a negative considered to result in a negative radiative forcing that leads to a cooling radiative forcing that leads to a cooling of the Earth surface. of the Earth surface. By contrast, soot, or black carbon is an By contrast, soot, or black carbon is an effective absorber of solar radiation effective absorber of solar radiation and therefore has a warming effect. and therefore has a warming effect. The chemical constituents of aerosol The chemical constituents of aerosol play important role in radiative effects play important role in radiative effects of aerosol and impacts on public of aerosol and impacts on public health..health..

Cities act as sources of aerosol and are Cities act as sources of aerosol and are likely to be important on a regional likely to be important on a regional scale. scale.

Urban aerosol is a topic of current interest Urban aerosol is a topic of current interest because of the climate change caused by because of the climate change caused by aerosol, and because of rapidly increasing global aerosol, and because of rapidly increasing global urban populations urban populations The effects of urban aerosols outside their city The effects of urban aerosols outside their city of origin are many and varied. of origin are many and varied. Aerosol deposit on land downwind of cities, on Aerosol deposit on land downwind of cities, on agricultural and potentially sensitive ecosystems, agricultural and potentially sensitive ecosystems, modify the chemical and radiative properties of modify the chemical and radiative properties of the downwind atmosphere and alter the regional the downwind atmosphere and alter the regional cloud precipitation, depending upon their cloud precipitation, depending upon their number, composition and size distribution number, composition and size distribution

In order to trace down the pollution sources and determine the extent of the anthropogenic contribution, a fundamental study of the chemical composition and mass size distribution of atmospheric particulates is required

IndoIndo--gangetic planegangetic planeThe case study is focusing on the Indian part of the Indo-gangetic plains (21°45 to 31°0 N lat. and 74°15 to 91°30 E long.), which cover an area of ~650,000 km2, roughly 21% of the total area of India. The indo gangetic plains are home to 40% of India's population, being comprised of the states of Punjab, Haryana, Uttar Pradesh (UP), Bihar and West Bengal.

Experimental SitesExperimental Sites

Sample collection, preparation Sample collection, preparation and preservationand preservation

Particulate matter– Samples were collected by Kimoto (CPS-

105, Japan) size segregated impactor a flow rate of 1000 L m-1 using Whatman 41 filter paper as collecting surfaces

- extracted in 100 ml E-pure water on electrical shaker for 1 hr., filtered and supernatant was preserved for analysis.

SoilTopsoil from different places close to

sampling site was collected, air dried and sieved through a 60 mesh sieve, 1 g sieved soil extracted with deionised water, filtered through whatman filter paper, divided into two parts, preserved as dry deposition samples and stored in refrigerator

Meteorological ParametersTemperature, relative humidity, solar

radiation, wind direction and wind speed were monitored by Battery operated WDL 1002 Data Logger system

Table: Data of meteorological parameters during the study period.

MonthsMonths TemperatureTemperature((°°C)C)

Relative Humidity (%)Relative Humidity (%) Solar radiation Solar radiation (w/m(w/m22))

Wind speedWind speed(km h(km h--11))

WDWD

Min.Min. Max.Max. Avg.Avg. Min.Min. Max.Max. Avg.Avg. MinMin MaxMax Min.Min. Max.Max. Avg.Avg.

JanJan 7.97.9 18.118.1 13.013.0 6868 9696 8282 1.21.2 7.57.5 1010 1515 12.512.5 NW, NW, NN

FebFeb 10.110.1 22.622.6 16.316.3 4949 9090 69.569.5 1.51.5 8.38.3 1010 1515 12.512.5 W, W, NWNW

MarMar 15.415.4 29.429.4 22.422.4 3939 8282 60.560.5 1.71.7 9.09.0 1515 2020 17.517.5 WW

AprApr 22.522.5 36.836.8 29.629.6 2121 5858 39.539.5 1.81.8 9.19.1 1010 2828 19.019.0 NWNW

MayMay 28.628.6 38.538.5 33.533.5 2929 5959 4444 2.02.0 9.79.7 2222 3030 26.026.0 W, W, NWNW

JunJun 27.927.9 34.334.3 31.131.1 5656 8282 6969 1.91.9 9.89.8 2020 3030 25.025.0 NWNW

JulJul 26.926.9 31.831.8 29.429.4 7171 9292 81.581.5 1.61.6 7.57.5 1515 2525 20.020.0 E, E, SWSW

AugAug 26.726.7 32.432.4 29.529.5 6666 9090 7878 1.31.3 5.35.3 1010 1515 12.512.5 WW

SepSep 25.125.1 33.533.5 29.329.3 5050 8585 67.567.5 1.41.4 6.66.6 1515 2020 17.517.5 WW

OctOct 20.620.6 31.731.7 26.126.1 4444 8484 6464 1.51.5 8.48.4 77 1010 8.58.5 NWNW

NovNov 14.014.0 25.825.8 19.919.9 4747 8585 6666 1.61.6 7.07.0 1010 1010 1010 N, N, NWNW

DecDec 8.88.8 20.520.5 14.714.7 5959 9191 7575 1.21.2 6.26.2 33 1010 6.56.5 NE, NE, NN

Analysis:

- Major anions (F-, Cl-, NO3- and SO4

2-) Major cations (Na+, K+, Ca2+ and Mg2+) in particulate matter and soil and HNO3 in gas phase were analyzed by Dionex DX-500 Ion Chromatograph using 5.5 mM NaOH as eluent at a Flow rate 1 ml min-1

- NH4+ was analyzed by colorimetricall

using UV-visible spectrophotometer

Mean of suspended particulate matter (SPM) (Mean of suspended particulate matter (SPM) (µµg mg m--33) and its water) and its water-- soluble major ions (neq msoluble major ions (neq m--33))

SPMSPM FF-- ClCl-- NONO33 -- SOSO44

22-- NaNa++ KK++ CaCa2+2+ MgMg2+2+ NHNH44 ++

Total mass Total mass conc. conc.

228.9228.9 20.020.0 64.2264.22 21.1221.12 57.0857.08 19.1319.13 15.1215.12 60.560.5 100.0100.0 127.22127.22

Conc. in fine Conc. in fine modemode

135.6135.6 9.69.6 33.5233.52 15.015.0 33.5433.54 8.698.69 9.239.23 29.029.0 42.542.5 79.4479.44

Conc. in Conc. in coarse coarse modemode

92.492.4 10.310.3 30.730.7 6.126.12 23.5423.54 10.4310.43 5.895.89 31.531.5 57.557.5 47.7747.77

% Conc. in % Conc. in fine modefine mode

59.2559.25 48.348.3 52.252.2 7171 58.858.8 45.545.5 6161 47.947.9 42.542.5 62.462.4

% Conc. in % Conc. in coarse coarse mode mode

40.7440.74 51.751.7 47.847.8 3939 41.241.2 54.554.5 3939 52.152.1 57.557.5 37.637.6

MMD (MMD (µµm)m) 4.14.1 4.94.9 4.84.8 3.443.44 4.44.4 5.455.45 3.783.78 5.05.0 5.65.6 3.83.8

The mean value of SPM is 228.9 The mean value of SPM is 228.9 µµg mg m--33

with approximately 41% in coarse mode with approximately 41% in coarse mode The sum of concentration of waterThe sum of concentration of water--soluble soluble major ions 12.24 major ions 12.24 µµg mg m--33

Because of unmeasured organic and Because of unmeasured organic and carbon soot, which come out in significant carbon soot, which come out in significant amount from vehicles, diesel engine amount from vehicles, diesel engine generating sets which are present at very generating sets which are present at very high level high level The concentration of NHThe concentration of NH44

++ is highest Mgis highest Mg2+2+

> Cl> Cl-- > Ca> Ca2+2+ > SO> SO4422-- > NO> NO33

-- > F> F-- > Na> Na++ > > KK++

Log normal mass size distribution of SPM Log normal mass size distribution of SPM and water soluble componentsand water soluble components

FF--, NO, NO33-- and Naand Na++ show show unimodalunimodal and and

KK++, Ca, Ca2+2+, Mg, Mg2+2+, NH, NH44++, , ClCl--, and SO, and SO44

22--

show bimodal distributionshow bimodal distribution

The components with high MMD (> The components with high MMD (> 2.0 2.0 µµm) are produced by natural m) are produced by natural sources whereas those with low sources whereas those with low MMDsMMDs (< 2.0 (< 2.0 µµm) are produced from m) are produced from man made sources.man made sources.

Ionic balance (Ionic balance (neqneq mm--33) b/w total ) b/w total cationscations and totaland total anion (TCanion (TC--TA) in fine and coarse fraction of SPM TA) in fine and coarse fraction of SPM

Mode TC TA TC-TA (SO42-+NO3

-)/NH4+

Total 321.9 151.93 169.97 0.62

Fine 168.8 86.58 82.22 0.64

Coarse 153.1 65.22 87.88 0.62

# Difference between sum of cation and sum of anions in fine mode is 82.2 neq m-3 while in coarse mode is 87.9 neq m-3

# This anion deficit may be due to unanalyzed HCO3- and

CO32- ions

# Indicates alkaline nature of atmosphericparticulate

Fig. % contribution of each ion towards the Fig. % contribution of each ion towards the total watertotal water--soluble components soluble components

SPM is higher in monsoon followed by summer and winter SPM is higher in monsoon followed by summer and winter The high loading of SPM in monsoon may be due to high wind speedThe high loading of SPM in monsoon may be due to high wind speed and and atmospheric instability atmospheric instability The low loading of SPM in winter may be due to calm conditions. The low loading of SPM in winter may be due to calm conditions. As a result As a result dispersion of local emissions and lifting up of soil particles idispersion of local emissions and lifting up of soil particles is suppressed and s suppressed and loading of SPM was minimum loading of SPM was minimum

Table: Summary statistics of the TSPM and its water soluble chemical components (µg m-3) during SALC-IIDecember 2004.

Species Mean Standard Deviation

Minimum Maximum

TSPM 441.2 241.2 60.8 1004.6

F- 0.4 0.64 0.11 3.93

Cl- 9.7 7.34 .37 36.97

NO3- 19.9 15.29 0.31 63.03

SO42- 17.3 11.51 0.65 47.03

Na+ 4.7 3.48 1.33 11.37

K+ 6.5 2.61 1.74 11.98

Ca2+ 4.9 1.40 1.91 8.44

Mg2+ 4.5 1.89 0.16 9.75

NH4+ 20.5 5.85.8 15.515.5 30.230.2

Industrial ResidentialLocation Annual mean conc. Location Annual mean conc.

Present Study (Dayalbagh, Agra)

441.2

DIC Nunhai, Agra 492 Gandhi Maidan, Patna 610

Talkatora, Lucknow 431 Deputy Ka Parao, Kanpur 492

Town Hall, Delhi 425 Kidwai Nagar, Kanpur 492

Alwar, Rajasthan 418 Siri Fort, Delhi 367Jharia, Bihar 408 Hazratganj, Lucknow 363

Mettupalayam, Pondichery

389 Nizamudin, New Delhi 362

DIC Udaipur, Rajasthan 358 Janakpuri, New Delhi 343

Rita S. Mach Ludhiana, Punjab

343 Police Barracks Visakhapatnam

336

Shahdara, Delhi 313 Rehional Office Bodla, Agra

335

Milk Plant Ludhiana, Punjab

308 Hamidia Road, Bhopal 335

Table . A comparison of TSP level of (µg m-3) present study with other ten locations having highest concentration of suspended particulatematter in India.

Pre-foggy days Post foggy daysMean S.D. Mean S.D.

TSPM 574.1 164.8 334.7 243.7F- 0.35 0.18 0.49 0.9Cl- 9.7 7.9 6.9 5.65NO3

- 15.2 13.4 24.26 16.1SO4

2- 14.9 9.3 20.0 13.2Na+ 7.1 3.4 2.24 0.77K+ 8.2 2.0 4.7 1.9Ca2+ 5.3 1.3 4.6 1.5Mg2+ 4.8 1.4 3.9 2.2NH4

+ 14.5 6.8 25.5 10.5

Table . Mean and standard deviation of TSPM and their chemical constituents in foggy and post foggy days.

Table 6. Correlation matrix of major ions of aerosols during study period.

Species F- Cl- NO3- SO4

2- Na+ K+ Ca2+ Mg2+ NH4+

F- 1

Cl- 0.12 1

NO3- 0.48** -0.14 1

SO42- 0.37* 0.16 0.52** 1

Na+ 0.33 0.55** -0.28 -0.08 1

K+ 0.35* -.50** -0.35 -0.11 0.69** 1

Ca2+ 0.13 0.34 0.12 0.19 0.26 0.23 1

Mg2+ 0.09 0.06 0.19 0.33 0.05 0.09 0.70** 1

NH4+ 0.190.19 0.260.26 0.380.38 0.220.22 0.060.06 0.220.22 0.59**0.59** 0.57*0.57* 1

* - Signif. p= 0.05 ** - Signif. p= 0.01Correlation matrix reveals good correlation between Ca2+ and Mg2+ (r = 0.70)

indicates their origin from similar sources. Significant correlation of F- with NO3- (r

= 0.48), with SO42- (r = 0.37) and with K+ (r = 0.35) indicates their contribution

from similar sources, however, extent of their correlation are different.Cl- shows significant correlation with Na+ (r = 0.55) and K+ (r = 50).NO3

- has good correlation with SO42- (r = 0.52) probably due to their similar

anthropogenic origin.

Table 7: Factor matrix of data set. Species Factor I Factor II Factor III Communality

TSPM 0.77 0.22 0.13 0.66

F- 0.38 0.52 0.36 0.54

Cl- 0.78 -0.07 0.24 0.67

NO3- -0.20 0.76 0.36 0.75

SO42- 0.067 0.79 0.22 0.68

Na+ 0.69 -0.32 0.29 0.67

K+ 0.77 -0.41 0.08 0.76

Ca2+ 0.52 0.33 -0.69 0.86

Mg2+ 0.39 0.40 0.71 0.82

NH4+ 0.620.62 0.350.35 0.050.05 0.780.78

Eigen value 2.89 2.07 1.47

Pct. of Var. 32.1 23.0 16.4

Cum. Pct. 32.1 55.1 71.5

Factor I accounts 32.1% of the total variance, includes mainly Ca2+, Mg2+, Cl-, K+, and Na+ and has been attributed to soil and vegetative emissions.

Factor II accounts 23.0% of the total variance grouped mainly F-, NO3- and

SO42- may be contributed by industrial and vehicular emissions.

Factor III accounts 16.3% and includes Na+ and F+ and NO3- to little extent

may be attributed to intermingling.