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IndianInstituteofTropicalMeteorologyMinistryofEarthSciencesGovernmentofIndia

EXECUTIVESUMMARY

SAFAR-HIGH-RESOLUTION(400mx400m)GRIDDEDEMISSIONSINVENTORYFOR

PUNE,PIMPRIANDCHINCHWADREGIONS

Air pollution research is increasingly becoming a topic of immediate interest due to its close

linkages with Human health and ecosystem. Unlike several other irreversible processes,

anthropogenic sources (human-made) can be inverted as a major cause of air quality

deterioration.Whenthelocalconcentrationsofairpollutantsexceedaspecificthresholdlimit,it

canharmthehealthofhumanbeings,plantsandanimals.Mostofthemega-citiesworldwideare

experiencing the deterioration of air quality. The various natural and anthropogenic sources

accountforenvironmentalpollutantemissionsload.Theanthropogenicemissionisontherise.

EmissionInventoryisacomprehensivelistingbylocalsourcesofairpollutantemissionsandthe

numberofairpollutantsreleasedintotheairduetoaspecificprocessinaparticulargeographic

regionduringa specificperiod. It isoneof themost critical factors required forairpollution

forecastingmodelsandmeteorologicalinputtoforecasttheairqualityandframethemitigation

strategy.Qualityofforecastingdependsontheaccuracyandreliabilityofemissionestimation.

Emission inventories could also be used for air quality management and formulating

environmentalpolicy.

Emission inventory development is an area of current interest but a complex process due to

numerous,diverseandwidelydispersedemissionsourcesinPuneregion.Regioncoversmultiple

megapolis likePune,PimpriandChinchwad(includesPMC,PCMC,KCB,PCB,DCB&adjoining

region),calledas“PuneMetropolitanRegion(PMR)”intherestofthisreport.Thewidespread

campaign requires a vast amount of ultra-high-resolution activity data, emission factors, and

knowledgeoffundamentalscientificprocesses.Anextensivescientificfieldcampaignhasbeen

carriedoutinPMRbyinvolvingmorethan200studentvolunteersfromdifferentcollegesalong

withSPPUforseveralmonthsjointlyorganizedbyIITMandSPPU.Anorientationworkshophas

beenarrangedforthevolunteers.Totalcampaigncovered~250,000hoursofdatacollection.The

campaign'smainfocuswastogeneratemissingprimarydata,validatesomeuncertainsecondary

data,andcollecttheavailablesecondarydata.Thefinalproductdeliveredwasahighresolution

(400mx400mgrid)griddedemissioninventoryofeightcrucialairpollutants(PM2.5,PM10,NOx,

CO,SO2,BC,OC,VOCsasNMVOCs).EmissionsinventoryisdevelopedforthePMR-regionof50km

x50km.Duringthecampaign,followingactivitydataandrelevantinformationrelatedtomajor/

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minorsourcesfrom26differenttargetshavebeencollectedaspartofanelaborateexerciseina

missionmode.

PMR is rapidly growing region of India, experiencing remarkably high vehicular density. The

trafficvolumehasbeencalculatedusingclickcountersondifferentmajorandminorroadsofthe

studyarea.Thecurrentcampaignhascoveredmore than200primaryandminorroads from

MunicipalCorporationlimitsandfringeareas.

Todeveloptheemissioninventory,abottom-upapproachhasbeenadopted.TheGeographical

InformationSystem(GIS)basedstatisticalmodeldevelopedbySAFARearlierhasbeenusedto

prepare high-resolution gridded emission inventory. The emissions of PM10 and PM2.5 from

various sources alongwith relative%shareof various sources are given inTable-a. Current

emissionestimates(Gg/Yr)inthePMRregionfordifferentpollutants,namely,BC,OC,NOx,CO,

SO2,andVOCsfortheyear2019-20aregiveninTable-b.

Table-a:AbsoluteEmission(Gg/yr)andRelativesectoralshareofPM2.5&PM10Emissions

forYr2019-20

PM2.5 PM10Sources Emissions(Gg/Yr) SectoralShare Emissions(Gg/Yr) SectoralShareTransport 21.2 45.6% 21.8 25.2%Industrial 11.3 24.4% 20.6 23.8%Residential* 06.0 12.9% 10.8 12.4%WBRDust 02.9 06.2% 27.2 31.4%Other# 05.0 10.8% 06.2 07.2%Total 46.4 ---- 86.6 ----

* Residential Sector -Residential cooking, Slum, Trash. Burning, Cow Dung, Street Vendor, Household,Woodburning,etc.#OtherSector-MSWPlants,MSWOpenBurning,Crematory,Aviation,IncenseStick,BrickClams,etc.WBRDust-WindBlownRe-suspendedDust

Table-b:AbsoluteEmissioninGg/YrofDifferentPollutantEmissionsfromDifferent

sectorsYr2019-20

Sector(Gg) BC OC NOx CO SO2 VOCsTransport 3.18 4.93 162.69 194.05 30.27 146.82Industry 2.31 4.76 45.21 5.03 157.72 26.29Residential* 1.33 2.708 6.94 65.67 1.97 16.125Other# 0.65 3.10 7.17 28.10 1.61 1.20

7.47 15.50 222.01 292.85 191.57 190.44* Residential Sector -Residential cooking, Slum, Trash. Burning, Cow Dung, Street Vendor, Household,Woodburning,etc.#OtherSector-MSWPlants,MSWOpenBurning,Crematory,Aviation,IncenseStick,BrickClams,etc.WBRDust-WindBlownRe-suspendedDust

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Figure-a:RelativeContributionofPM2.5&PM10Emissions

Figure-b:GeographicaldistributionofPM2.5&PM10Emissions

Sectoral share illustrates – transport and vehicular movement induced re-suspended dust

accounted for >50% of the particulate load (Figure-a). Residential and industrial contribute

identicalforPM10andPM2.5.ParticulateconcentrationhavespatiallydistributedalloverthePMR

region (Figure-b).Denselypopulated central areashaveaccounted forhigher emissions.The

transportbeingprominentsource,foundtobespreadallacrossthestudyregion.Northernareas

arecharacterizedwithanindustrialclusteralongwithassociatedresidencesandeateries.Some

green cover i.e. hills, cantonment, university, gardens – spread across the region curtails the

pollutionatsomeextent.Outofcitylimits,predominantlyEasternandnorthernparthavemajor

statehighwayswithheavytraffic.

EmissionsGrowthfrom2012-13to2019-20:Thepercentagegrowthofemissionsofvarious

pollutantsduringsevenyearperiodhasbeenestimatedwhichisfoundtobehighlysignificant.

The%growthin2019-20ascomparedto2012-13isfoundtobe81.3%forOC,72.8%forNOx,

69.8%forVOCs),and30.2%forSO2.(Table-c)TheoverallincreaseintheemissionsofPM10and

Transport45.6%

Industry24.4%

Residential12.9%

Others10.8%

WindBlownDust(WB)6.2%

SectoralPM2.5 EmissionShare

Transport25.2%

Industry23.8%

Residential12.4%

Others7.2%

WindBlownDust(WB)31.4%

SectoralPM10 EmissionShare

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PM2.5 overPMRregion,which includesPune,Pimpri andChinchwad region, from2012-13 to

2019-20isfoundtobe61%and70%respectively.Puneisamixoflanduseprovince,ranging

fromcommercial,residential,agricultural,reservedforestsandwaterbodies.Giventheextensive

reformsinanindustrialsector,itmanagedtocontroltheemissionsleadingtomoderategrowth.

VehiclesremainthemajorcontributorofPM2.5emissions,followedbyindustries.

Table-c:PercentChangeinPM10&PM2.5EmissionsduringPast7yrs(Yr2012-13to

Yr2019-20)

SECTORS PM10 PM2.5Transport ↑87.9% ↑91.0%Industrial ↑33.8% ↑32.9%Residential* ↑107.7% ↑57.9%WBRDust ↑49.5% ↑38.1%Other# NA$ NA$Total ↑61.3% ↑70.0%

* Residential Sector -Residential cooking, Slum, Trash. Burning, Cow Dung, Street Vendor, Household,Woodburning,etc.#OtherSector-MSWPlants,MSWOpenBurning,Crematory,Aviation,IncenseStick,BrickClams,etc.WBRDust-WindBlownRe-suspendedDust$Manysourcesnewlyaddedsonotappropriatetoshowgrowth.

-GufranBeigSAFAR-India,IITM,Pune