Chandra Venkataraman Department of Chemical from residential energy use Chandra Venkataraman Department of Chemical Engineering Indian Institute of Technology, Bombay TF HTAP Emissions

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  • Emissions from residential Emissions from residential energy useenergy use

    Chandra VenkataramanDepartment of Chemical EngineeringIndian Institute of Technology, Bombay

    TF HTAP Emissions Inventory and Future Projections Workshop

    October 18-20, 2006, Beijing

  • AcknowledgmentsAcknowledgments

    Organizers: for invitation / hospitality and defining workshop issues.

    Collaborators: Gazala Habib, Shekar Reddy, ShubhaVerma, Manish Shrivastava, Baban Wagh, IIT Bombay; Antonio Miguel, Arantza Fernandez, Sheldon Friedlander, UCLA; Tami Bond, UIUC; Jamie Schauer, U Wisc Madison.

    Funding Support: ISRO-GBP, MHRD.

  • The source of the problem (or problem with the source). Emitted pollutants of regional / global

    relevance. Inventory methodology. Uncertainties and their containment (more than

    mere reduction). Transport pathways South Asia. Recommendations.

    OutlineOutline

  • Energy use by sourceEnergy use by source

    12%

    25%

    62%

  • Energy consumed by households excluding transportation: includes cooking, home heating / air-conditioning, lighting and home appliances.

    Residential energy Residential energy

    Commercial energy accounting excludes about two billion people who rely on solid biofuels for residential energy.

    International energy outlook, 2006

    Residential energy use trends Includes:OilNatural GasElectricityCoal

  • The energy ladder: The energy ladder: emissions per meal cookedemissions per meal cooked

  • National Household Use of Biomass and Coal in 2000

  • Solid Solid biofuelsbiofuels for cookingfor cooking

  • Spatial scales of effectsSpatial scales of effects

  • Evidence of long range transportEvidence of long range transport

    120

    100

    80

    60

    40

    20

    cm-3

    Spatial distribution of black carbon containing particles with potassium from TOFMS (Guazzotti et al., 2003, JGR).

  • Particles (median aerodynamic diameters 0.5-1 m). Particle constituents (OC, BC, inorganic ions). Gases: CO, VOCs (ozone/PM precursors), N2O, CH4. Organics (gas and particle phase) hundreds of organic

    compounds including formaldehyde, benzene, polycyclic aromatic hydrocarbons, laevoglucosan (sugar anhydrides) substituted phenols, guaiacyl / syringyl compounds, sterols.

    Regional / global effects from long-range transport

    Air quality PM, VOCs, organics (POPs?). Visibility PM, BC, ions. Radiation / climate BC, OC, GHGs, extinction cross-

    section.

    Pollutants in Pollutants in biofuelbiofuel smokesmoke

  • Emissions inventory methodologyEmissions inventory methodology Activity levels (usually fuels) (kg day-1)

    Per capita usage, user population, fuel-mix.

    Technology divisionsDevices, efficiency (thermal and combustion).

    Emission factors (g kg-1)Pollutants of interest for each fuel-technology system.

    Spatial distribution and resolutionAppropriate proxy typically population.

    Temporal resolution and seasonal cycleFoods / fuels may vary with season.

  • Activity levels (kg day-1, national / distributed) Energy and fuel-use surveys : high uncertainty and low representative-

    ness for biofuels (kg capita-1 day-1). User population : not documented. Mix of fuels: not known in most cases.

    Uncertainties in fuel useUncertainties in fuel use

    Fuel-technology divisions Wood, dung, crop waste, mixed-fuels, ... Traditional open-combustion chamber, massive mud, bucket with grate, packed bed (rice husk),

  • Statewise cooking energy consumption from 6 fuel types (PJy-1)

    Specific cooking energy (MJ kg-1 of food cooked)

    Statewise cooking fuel use for 6 fuel types (Tgy-1)Statewise cooking fuel use for 6 fuel types (Tgy-1)

    Statewise average food items consumed (kgc-1m-1) (NSS, 2001)

    Cooking device efficiencies (%)

    Calorific value (MJ kg-1)

    Statewise rural and urban fraction of fuel user population for 6 fuel types (Fuelwood,

    dung-cake, crop waste, coal, LPG and kerosene) (NFHS, 2000)

    Statewise population using 6 fuel types

    Statewise rural, urban population (Census, 2001)

    Statewise end use energy (PJy-1) in four cooking process and 6 fuel types

    Statewise food items consumption in 4 cooking process (boiling, skillet-baking,

    leavened-baking, meat cooking)

    Uncertainty containment: activity levelsUncertainty containment: activity levels

  • Uncertainties in regional Uncertainties in regional biofuelbiofuel useuseFuelwood Dung-cake Crop waste

    Crop waste open burning Forest fire

    0 50 100 150 200 250 300

    278

    63

    37

    168

    39

    6%11%

    47%

    29%

    7%

    0 50 100 150 200 250 300Biomass burning (MTy-1)

    Bio

    mas

    s ty

    pe

    Biofuel combustion: 379-555 MTy-1

    Biofuels379 MTy-1

    Fuel mix: 73:17:10% of FW:DC:CW. Upper bounds derived, as + 95%CI, within factor of 1.5.Spatial variability on 25 km grid.

    Fuelwood278 MTy-1

    Dung-cake 63 MTy-1

    Crop waste 37

    MTy-1

  • Global Global biofuelbiofuel useuse

    0

    500

    1000

    1500

    2000

    2500

    3000

    3500

    4000

    1850 1875 1900 1925 1950 1975 2000

    biof

    uel c

    onsu

    mpt

    ion

    (Tg/

    yr)

    Industrial BiofuelsDomestic CharcoalDomestic DungDomestic CropsDomestic Fuelwood

    Courtesy David Streets, Argonne National Labs, USA

  • Emission factors : in laboratoryEmission factors : in laboratoryFuel-technology divisions

    Traditional single pot mud stove5-wood species, animal dung and

    10-crop waste typesDilution sampler

    Optimized for aerosol stabilizationMass of fuel, duct velocity,

    temperatures in combustion zone, duct and plenum recorded each minutePollutants

    PM2.5: Cyclone sampler.OC-BC: Thermal optical

    transmittance (S. California Particle Centre and Supersite).

    SO2, NO2, ions, trace elements and absorption (U Wisc, Madison, UIUC).

    Dilution sampler Burn cycle

    Multi-stream aerosol sampler

    AIHL Cyclone

    Equilibration cylinder

    Inlet for air

    Filter holders Cyclone outlet pipe

    Connection to PumpCritical Orifices for flow control

    Venkataraman et al. Science, 2005, 307, 1424-1426. Habib et al., in preparation, 2005.

  • Variability across fuels: PM emissionsVariability across fuels: PM emissions

    0 2 4 6 8 10 12 14 16

    Wood-LBR

    Wood-HBR

    Fibrous hollow stalks

    Woody stalks

    Straws

    Dried cattle manure

    Kerosene

    LPG

    Fireplaces

    Forest fire

    Diesel

    Sour

    ce c

    ateg

    orie

    s

    Emission factors (gkg-1)

    ECOCAssociated organic matterIonsTrace metal

  • Variability across fuels: Variability across fuels: Mass absorption crossMass absorption cross--sectionsection

    0 1 2 3 4 5 6 7 8

    Mass absorption cross section [m2(gPM2.5)-1]

    Wood-LBR

    Wood-HBR

    Fibrous hollow stalks

    Woody stalks

    Straws

    Dried cattle manure

    Kerosene

    LPG

    Fireplaces

    Forest fire

    Diesel

    So

    urc

    e c

    ate

    go

    ries

  • Do stoves measured in the field perform Do stoves measured in the field perform differently?differently?

    Emission Factors (mean +/- 1 st. dev.)

    0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0

    Honduras 2004 Traditional Stove - field data

    Honduras 2005 Improved Stove w/o chimney - fielddata

    Honduras 2005 Improved Stove with chimney - fielddata

    Aprovecho 2005 Trad. & impr. Cookstoves- lab data

    Brocard et al (1996) trad. African stoves -simcooking in field

    Zhang et al (2000) trad. & impr. Cookstoves in lab

    Venkataraman & Rao (2001) trad. & impr. woodstove in lab

    Smith et al (2000) trad. & impr. wood stoves - labtest

    Emission Factor (g/kg_wood)

    Previous WorkARACHNE results

    Yes, there is a big difference between lab and field measurements.

    Courtesy Tami Bond, University of Illinois, USA

  • Integrated uncertainties in pollutant emissionsIntegrated uncertainties in pollutant emissions

    BC Fuelwood: 137Ggy-1

    BC Dung-cake : 8 Ggy-1

    5 10 20 30 60 90kgkm2y-1

    5 10 20 30 60 90kgkm2y-1

    BC Crop waste : 19

    Ggy-1

    5 10 20 30 60 90kgkm2y-1

    Fuelwood Dung-cake Crop waste

    Fossil fuelForest fire

    Crop waste open burning

    0 20 40 60 80 100 120 140 160

    Fuelwood

    Dung-cake

    Crop waste

    BC emissions (Ggy-1)

    Bio

    fuel

    type

    Biofuel38%

    6%

    0 20 40 60 80 100 120 140 160

    Biofuel BC: 175-360 Ggy-1

    30%

    26%

    Upper bounds derived, as + 95%CI, within factor of 2.5.Larger range from more uncertain emission factors.

  • Level I: In-field monitoring

    Level II: Regional design & testing lab

    Confirm effectiveness of installed interventionsProvide rapid feedback to entrepreneurs

    Motivation: Quantify local benefits

    Provide independent evaluation of stove designsDetermine best practices for local conditions

    Motivation: Evaluate program success & potential for change

    Level III: University LaboratoryCompare costly with less-expensive measurements

    Understand nature and causes of emissionsMotivation: Scientific understanding

    AHDESA, HondurasTrees Water & People, USA

    Aprovecho, USA

    Uncertainty containment: emission factorsUncertainty containment: emission factorsCourtesy Tami Bond, University of Illinois, USA.