Future Aerosol Emissions From Industrial and Utility Boilers Soonkyu Jung 1 Tami. C. Bond 2, and David G. Streets 3 1,2 Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA 3 Decision and Information Sciences, Argonne National Laboratory, Argonne, Illinois, USA

Combustion Image from downloads.htmwww.saltwater.co.uk/ downloads.htm Aerosols are an important pollutant in urban areas. PM2.5 are considered to have significant adverse effect to human health and stringent regulations to reduce PM2.5 emission have been issued in many world regions.

Black Carbon and Climate Black carbon has been the second largest climate forcing after CO2. - Jacobson (2000) Combined with a reduction of black carbon emissions and plausible success in slowing CO2 emissions, this reduction of non-CO2 GHGs could lead to a decline in the rate of global warming, reducing the danger of dramatic climate change (Hansen et al, 2000)

Radiative Forcing (IPCC,2001)

Challenges Warm or cool? OC scatter light back to space thus acting to reduce the warming BC warms climate by absorbing sun lights Determining the ratio is a difficult task Where & How much of the BC/OC comes from? Different Combustion process / Control Historical & future emission Lack of historical data

Aerosol-Climate Study Overview Emission Inventory Emission Factor Fuel Consumption Regional Properties Climate Model

Aerosol Emissions from Combustion pathenvi/basics/bas1.html Aerosol from deferent fuel Combustion technology have totally different properties & amount By Using this idea, we develop aerosol emission inventory

Total Emissions Where, j species; k country ; l sector; m fuel type ; n fuel/technology combination; EmEmissions FCfuel consumption, kg/yr EFEmission Factor specific to fuel/technology combination (including the effects of control devices), g/kg XFraction of fuel of this sector consumed by a specific technology, where X =1 for each fuel and sector BOND ET AL., 2004

Determination of the total emission kg pm 1,000kg Sector : TransportFuel typeFuel ConsumptionEmission FactorFuel Fraction EFpm,g/kg Diesel normal Diesel Super emitter

Present Day Estimate of BC/OC - Bond et al. 2004

Which of these will change in the future? Fuel Change en.wikipedia.org Coal-fired, high BC Gas or electric, low BC We Use IPCC SRES Scenario for fuel estimation

Which of these will change in the future? Technology Change Google.com Old burner - high BC Modern Combustor, low BC We Develop Dynamic Simulation tool For future technology splits

Which of these will change in the future? Emission Control Technology Street, 2004 We Develop Dynamic Simulation tool For future technology splits Electrostatic precipitator, high collection efficiency Cyclone, low collection efficiency

Governing factors of technology change Diffusion Studies suggest Adoption rate of new technology is: -Positively related to the Benefits & Technology popularity -Negatively related to the Costs We use (based on historical trend simulation): Emission Standards of species ( Regulation ) Technology popularity (e.g. Installed Capacity) Technology limitation (Newer technology takes time to be used in Developing countries) Economic situation

Drivers : Regulation and Control Efficiency

Drivers : Government Regulation

Drivers : Capacity - Case of Cyclone Furnace Uncontrolled NO Concentrations for Types of combustion (Air Pollution Control Manual, 1992, p. 216)

Technology Choice Probabilities - Case of Cyclone Furnace

Drivers : - Boiler Population Trend

Estimate Boiler Age Distribution - From Fuel Consumption Data

Emission Standards Modeling - Particulate Matter over GDP per Capita

Drivers : Industry Sector Change Agriculture Dominant ---- Service Sector Dominant

Description of The Model

Schematic diagram for developing future emissions inventory model

Preliminary Result Total global coal-boiler capacity is estimated to increase (in all scenarios, Ranging from 394%-605% for the power sector) Use of coal boilers for power generation is expected to be high in many world regions, because the demand for electricity is expected to increase in all scenarios (from 340%-540%) and use of coal for electricity generation to remain high (20%-31%)

Preliminary Result (Cont.) The boiler capacity in South Asia is forecasted to take the largest of the 2050 values of 9%-20% under most scenarios except A2 scenario which expects USA as the largest share

Selected global combustion technology changes (a)

Questions? Thank you

Description of The Model - Simulate initial Distribution of Boilers Create Boiler inventory Combustor Type Control Equipment Type Boiler Age (Estimated from Fuel Consumption) Capacity Distribution

Description of The Model - Run the Model for a Step Year Examine Boiler Age and Retire Boilers Check New Regulation and Upgrade Control Equipment Calculate amount of capacity of boilers in this step year Determine the firing type and control device

Description of The Model - Determine Emissions Technology Splits from simulation will be interfaced with Emission Inventory program

17 World Regions in this model (From IMAGE Group 2002)

Boiler Capacity Distribution - Assume Follow S-Shape Curve

IPCC Scenarios A1, A2, B1, B2 Fuel, GDP U.S DOE Utility Survey U.S. EPA Industrial Boiler Inventory Bond et al 2004 Inventory IEA Historical Fuel Data Determine Distribution - Create 10 Capacity Groups Set unit number in each group Simulate Distribution Create Blank Cells Number of Units of Groups Initialize Unit properties (Sources) Capacity (Distribution module) Technology (Previous Inventory) Age (Age module) Determine model size of a country Determine Age Based on U.S Historical Trend + IEA Historical Fuel data Run the model to the Next 5Year ChK Boilers Age Retire Boilers New Regulations? Regulation Modeling Current Emission Standards Data GDP Future Capacity Modeling Future Fuel Choose New Control Device Need New Boilers? Choose New Boilers Target Year? Y Determine Technology Splits No, Next Step Emission Factor Modeling Modules GDP Splits probability model SPEW Future Emission Inventory Schematic methodology for the development of future emission inventory of boilers

SRES Scenarios

Emphasis on sustainability and equity Emphasis on material wealth Globalisation Regionalisation A1 Balanced A1 Fossil A1 Technology B1 B2 A2 What are the IPCC SRES scenarios

IPCC Scenarios Emphasis on sustainability and equity Globalisation Regionalisation / fragmentation Globalised, intensive Market-Forces Emphasis on material wealth Regional, extensive Mixed green bag Globalised, extensive Sustainable development Regional, intensive Clash of civilisations

Impacts Impacts of more intense rainfall on storm drains/sewers Changes in circulation and the implications for air pollution Coastal cities and tidal surge Implications of increased wind storm IPCC Working Group, 2002

Present Day Estimate of BC/OC - Bond et al. 2004

Previous Estimates of Aerosol Emissions From Fossil Fuel Combustion (Tg/Year)

Calculation j species BC( Black Carbon) or OC( Organic Carbon) k country Country level (in large country, State or Province level) l sector Residential, Industry, Power, Transport, Biomass Burning m fuel type Diesel, Hard Coal, Gasoline, Wood… n fuel/technology combination Fuel used by a specific technology

Total Emission(2-2) Sector Fuel Fuel/Technology combination

Emission Factors (EF) Emission Factors of BC and OC ( j = BC or OC ) EF BC =EF PM F 1.0 F BC F cont, Where EF PM the bulk particulate emission factor, g/kg F 1.0 fraction of emissions with diameters smaller than 1μm F BC fraction of fine particulate matter that is black carbon F cont the fraction of fine PM that penetrates the control device EF OC =EF PM F 1.0 F OC F cont, Where F OC fraction of fine particulate matter that is organic carbon

Fuel consumption of the future FC i,k,l,m = FC 1996,k,l,m × FCIM i,k,l,m / FCIM 1996,k,l,m where FC 1996,k,l,m IEA Energy Statistics data for the year 1996 FCIM fuel consumption in the IPCC IMAGE dataset.

Emission factors for the future EF i,j,l,m,n = EFPM i,j,l,m,n × fsub j,l,m,n ×fC j,l,m,n ×fcont i,l,m,n Where f sub = f 1.0 fC = fraction of the particulate matter that is carbon (F BC +F OC )

Evolution of Emission Factors fC j,l,m,n, fsub j,l,m,n and EFPM Constant over time for each combination of scenario/species/sector/fuel/technology fcont i,l,k,m,n Collection efficiency could be estimated from regulation, economics, technology innovation fcont = 1/{1+exp(-[log(αCn)+ βStd pm + γ])} where, α, β, γ coefficients Cn technology adoption parameter Std pm Emission Standards of particulate matter EF i,j,k,l,m,n = EFPM i,j,l,m,n × fsub j,l,m,n ×fC j,l,m,n ×fcont i,l,k,m,n

Radiative Forcing

Values of Particulate Matter Emission Characteristics for Stationary Combustion BOND ET AL., 2004

Emission Standards Modeling Short-term emission standards reflect present (and proposed) legislation longer term emission standards are assumed to improve due to technological enhancements Use GDP per Capita as a proxy for technological enhancements