Emission Inventory EMISSIONS INVENTORY DEVELOPMENT IN CALIFORNIA. Presentation Outline 9/30/2015

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EMISSIONS INVENTORY DEVELOPMENT IN CALIFORNIA San Joaquin Valley Public Advisory Workgroup September 3, 215 Gabe Ruiz Sylvia Vanderspek California Air Resources Board Presentation Outline Emission Inventory Overview Inventory Development Inventory Forecasting Spatial Allocation 2 Emission Inventory A comprehensive estimate of air pollutant emissions, by source, for a specific geographic area during a given time period 3 1

Uses for Emission Inventories Identify pollutants of concern and their sources Determine amount, distribution, trends Input to air quality modeling Identify and track control strategies Input to health risk assessment 4 How does the emission inventory fit into the planning process? Clean Air SIP Control Assessment Modeling & Transport Emission Inventory Air Quality Monitoring Types of Emissions Sources Stationary Sources Areawide Sources Mobile Sources (On-Road and Off-Road) Natural Sources 2

Pollutants Criteria Pollutants (related to SIPs) Reactive organic gases (ROG) Oxides of nitrogen (NO x ) Oxides of sulfur (SO x ) Particulate matter (PM 1 and PM 2.5 ) Ammonia (NH 3 ) Toxic Air Pollutants Hundreds of toxic compounds and metals 7 Stationary Sources Refineries Manufacturing Food processing Electric utilities Gas stations Dry cleaners Stationary engines Areawide Sources Consumer products Solvents Paved & unpaved road dust Farming operations Open burning 3

Mobile Sources Cars Trucks and Buses Aircraft Trains Ships Recreational vehicles Farm equipment Natural Sources Biogenics Geogenics Wildfires Windblown dust Types of Inventories Planning (annual and seasonal) Forecasted (future year projections) Gridded/Modeling 12 4

INVENTORY DEVELOPMENT PROCESS 13 Resources Continuous and iterative process Over 4 people at State level Additional staff in each of 35 air districts Millions in research dollars 14 Agency Responsibilities ARB coordinates with 35 local air pollution control/air quality management districts Districts have responsibility for all point sources ARB and districts share responsibility for areawide sources ARB is responsible for all mobile and natural sources 15 5

California Inventory at a Glance Over 8 emission categories Over 3,2 subcategories Over 23, unique stationary sources Historical facility data from 1979 to 213 Emission forecasts to 235 16 Estimating Emissions Process Rate (Activity) X Emission Factor = Emissions per Unit Number of Units X Emissions = Total per Unit Emissions Point Sources Facility operators report activity, emissions data, temporal data, and other facility information to local air district Various estimation methodologies available Continuous emission monitors Source testing Fuel consumption Published emission factors Material balance Engineering judgment 18 6

Areawide Sources ARB and/or local air districts develop estimation methodologies Data sources: County-level activity data from surveys, industry reports, census reports, other government agencies Emission factors from U.S. EPA (AP-42) or special studies 19 On-Road Mobile Sources ARB has developed motor vehicle emissions models since 197s. EMFAC214 is most recent on-road model Data sources: DMV vehicle registration data Emission factors by vehicle class, technology and model year Travel activity (vehicle-miles, or VMT) from local transportation planning agencies 2 Off-Road Mobile Sources ARB has developed category-specific models (trains, ocean-going vessels, commercial harborcraft, recreational boats, off-road equipment) Each model reflects the unique characteristics (equipment types, activity, emission factors, economics) of the source category 21 7

EMISSION INVENTORY FORECASTING 22 What is a Forecasted Emissions Inventory? Projection of a base year inventory that reflects expected growth or decline in emissions Uses growth surrogates based on forecasted trends such as fuel consumption, economic conditions, or population growth Reflects effects of existing emission controls and other emission reduction programs 23 Inventory Forecasts All emission forecasts are conducted by ARB Point and areawide sources are forecasted from base-year inventory using the California Emission Projections and Analysis Model (CEPAM) Mobile source emissions are forecasted by EMFAC and off-road models 24 8

Basic Forecasting Equation E FY = E BY x GF x CF where: E FY = Future year emissions E BY = Base year emissions GF = Growth Factor CF = Control Factor Growth Factors Derived from forecasted trends for economic or demographic surrogates that best correlate to the activity for a given source category Growth surrogate examples: Source Category Industrial Boilers Consumer Products Architectural Paint Growth Surrogate Fuel Consumption Human Population Housing Units Sources of Growth Surrogate Data Industry forecasts Local governments (population forecasts, VMT projections, etc.) State and federal government agencies (census data, fuel consumption, employment data, etc.) Econometric models (economic output and employment forecasts) 9

Control Factors Control factors account for emission reductions from adopted rules and regulations Derived from adopted ARB regulations, District rules, or other agencies regulations which result in emission reductions from a source category They can also reflect a technology change on a particular emission process Emissions Forecasting Example Consumer Products 23 tons/day VOC in 25 Growth Surrogate: State Human Population 35 3 25 2 15 1 5 VOC Emissions 2 25 21 215 22 225 23 235 5 45 4 35 3 25 2 15 1 5 Projected Population (Millions) 2 25 21 215 22 225 23 235 29 Emissions Forecasting: Grown-Only Emissions Growth Profile Year Growth Factor 25 1. 21 1.4 215 1.8 22 1.13 225 1.18 23 1.23 235 1.28 VOC tons/day 35 3 25 2 15 1 5 VOC Emissions Grown with Population 2 25 21 215 22 225 23 235 3 1

Emissions Forecasting: Grown and Controlled Emissions Control Profile Year Control Factor 25 1. 21.89 215.82 22.82 225.81 23.8 235.78 VOC Tons/day 35 3 25 2 15 1 5 Consumer Products VOC Emissions 2 25 21 215 22 225 23 235 Year Reductions from Controls 31 Impact of Growth Surrogate Selection: Glass Manufacturing NOx Projections NOx tons/day 1 9 8 7 6 5 4 3 2 1 Economic Output (Base year 22) 22 27 212 Emission Projections Actual Emissions NOx tons/day 1 9 8 7 6 5 4 3 2 1 Construction Activity (Base year 27) 22 27 212 Emission Projections Actual Emissions 32 Long-term Glass Manufacturing NOx Emissions Projections 1 9 8 7 Actual Emissions Old Projection Revised Projection NOx tons/day 6 5 4 3 2 1 22 27 212 217 222 227 33 11

On-Road Mobile Source Forecasting EMFAC214 uses actual vehicle fleet data to estimate emissions through 212 Incorporates new methodologies to forecast vehicle emissions through 25 Key forecasts are new vehicle sales and VMT projections 34 New Vehicle Sales Forecast 35 VMT Projections 36 12

Sample Off-Road Model Updates Locomotives Activity forecasts for individual train types Accounts for rail line changes in grade Growth rates are consistent with ARB s ocean-going vessel and truck growth projections Diesel Agricultural Equipment Reflects equipment used on California farms Activity data and growth rates developed by agricultural economists in cooperation with ag community 37 San Joaquin Valley NOx Emissions 25 2 Tons/Day 15 1 212 231 5 Point Area On-Road Mobile Off-Road Mobile 38 Dominant NOx Emission Sources (212) Other On- Road On-Road Off-Road Aircraft Passenger Vehicles Trains Marine Vessels Trucks and Buses Farm Equipment Off-Road Equipment Rec Vehicles 39 13

San Joaquin Valley VOC Emissions 25 2 Tons/Day 15 1 212 231 5 Point Area On-Road Mobile Off-Road Mobile 4 Dominant VOC Emission Sources Chemical Point Sources Misc. Residential Fuel Combustion Architectural Coatings Area Sources Managed Misc. Burning Printing Cleaning and Surface Coatings Petroleum Marketing Oil and Gas Production Composting Pesticides Consumer Products Farming Operations Coatings and Related Solvents Food and Agriculture 41 SPATIAL ALLOCATION 14

Emissions Gridding Planning inventory Modeling inventory 43 Modeling Inventory Development Planning Inventory Annual Estimates (tons/yr) County Totals Criteria Pollutants Modeling Inventory Hourly Gridded Speciated 44 Point Source Allocation Spatial - actual location of facility (latitude/longitude) Temporal - how emissions vary by: Month Day of week Hours per day Assigned for each individual process 45 15

Area Source Allocation Spatial - distributed by a surrogate that best represents location of emissions 46 Area Source Spatial Allocation Examples Polygon Point Line 47 Area Sources Temporal Allocation How emissions vary by: Month Day of week Hours per day Relative Amount 12 1 8 6 4 Residential Cooking Daily Profile 2 1 3 5 7 9 11 13 15 17 19 21 23 Hour of Day 48 16

On-Road Emissions Data Emission Rates Speeds Trip Starts Link Vehicle Miles Traveled Temperature Relative Humidity Vehicle Types Day of Week 49 Summary Emission inventories provide technical foundation for clean air plans Inventory development takes time and significant resources Development process is a continuous and iterative Cooperative effort between government agencies and industry 5 Thank You! 51 17