status and changes to the us national emissions inventory (nei)

Status and Changes to the US National Emissions Inventory (NEI)

Thompson G. Pace, PE

U.S. EPA

Research Triangle Park, NC

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Overview of this Presentation Brief Perspective on The US’s PM Problems The US’s National Emissions Inventory

Current Practices Changes being considered / implemented

Specific source categories (and process-based model development) Wildland Fires Fugitive Dust Mobile Sources Ammonia

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PM 2.5 In Ambient Air - A Complex MixturePM 2.5 In Ambient Air - A Complex Mixture

Primary Particles(Directly Emitted)

Secondary Particles(From Precursor Gases)

Carbonaceous

OtherCrustal Ammonium

Nitrate

NOx

AmmoniumSulfate

SO2

SecondaryOrganics

VOC

Ammonia

Crustal

June 2000 / tgp

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PM2.5 Ambient Composition Carbonaceous SulfateSoilNitrate Not Chemically

Characterized

S. Coast(Avg 28 ug/m3)

Phoenix(13.3 ug/m3)

Knoxville(18.8 ug/m3)

Seattle(8.7 ug/m3)

Rochester(14.9 ug/m3)

San Joaquin Valley(Avg - 37 ug/m3)

New Haven(13.7 ug/m3)

Washington, DC(14.5 ug/m3)

Urban

Denver(Welby)

El Paso(22.5 ug/m3)

Birmingham(21.3 ug/m3)

Dallas(18.3 ug/m3)

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Total Carbon – Directly Emitted PM2.5(National Emissions ~ 2M TPY)

0% 5% 10% 15% 20% 25% 30% 35%

Transportable Fugitive Dust

Agricultural Burning

Ind. & Comm. Processes

Res. Heating & Open Burning

Ind. & Comm. Combustion

Mobile Sources

Wildland Fire

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SO2 – Precursor to Ammonium Sulfate Formation(National Emissions ~ 17.6 M TPY)

0% 10% 20% 30% 40% 50% 60% 70% 80%

Other

Mobile Sources

Industrial Processes

Other Fuel Comb.

Electric Utiilities

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NH3 – Precursor to Ammonium Sulfate & Nitrate(National Emissions ~ 4.8 M TPY)

0% 10% 20% 30% 40% 50% 60% 70% 80%

Other

Waste Disposal

Industrial Processes

Highway Vehicles

Fertilizer Application

Animal Husbandry

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Crustal Materials (Mainly Fugitive Dust) PM2.5 is usually < 1 ug/m3 annual average

Exception: Most of Southwest, California Main Sources:

Unpaved roads Agricultural tilling Construction Windblown dust Fly ash

Large emissions – low transportable fraction

PreliminaryNEI for

Base Year 20XX

States & Other

Stakeholders

Improved NEI for

Base Year 20XX

Local Activity Levels & Variables

Factorand Model

Improvements

Refining & Improving Inputs(Process Repeated Yearly - Emphasized every 3 Years)

Starting Point for NEI

Emissions Processor

Input to AQ Model

Emission Factors & Models

State / Local / Tribe Improvements

Databases for Source

Activity Levels

Defaults - Emissions

Related Variables

Existing Point

Source Data

Growth Factors for

Some Categories

NEI Development ~ Cooperative, Iterative

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Changes to NEI Preparation Process 12 month Schedule is being considered

(now 36 months) Improving the Technical Infrastructure

Develop Improved Tools Data Acquisition, Estimation & Distribution New technologies must be used

GIS Process Models Remote Sensing

PM2.5 Program Priorities Wildland Fires, Fugitive Dust, Mobile Sources & Ammonia

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Fuel Type and Loading

Fuel Consumption

Emissions Production

Dispersion / AQ Modeling / Monitoring

Fire Occurrence

Fire EmissionsProcess Modeling

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Tools to Support Fire Emissions Estimation

Fire Occurrence Databases Ground-based data systems Remote Sensing

Comparison of Ground Reported and Remote Sensed FiresAugust 1, 2001

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Potential Role(s) for Remote Sensing in Fire Emissions Estimation and Smoke Transport Fire Identification & Characterization

Time & date, location, size Fuel Characterization (Fuel Type & Loading)

Default maps (resolution, specificity) Natural alterations to “default” conditions Fuel treatments to reduce fire hazard Fuel moisture

Emissions Production Heat release & emissions Plume initial conditions

Transport & transformation Terrain Impacted populations

Ground-truthing Actual vs modeled plume path fixed networks & portable monitoring * Re

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Tools to Support Fire Emissions Estimation

Fire Occurrence Databases Ground-based data systems Remote Sensing

Fire Emissions Modeling AP-42 and past National Emissions Inventories

Methods simplistic, migrating to newer tools for 2002 (v2) Current: NFDRS, Consume, FOFEM, EPM New: Fire Emissions Production Simulator (FEPS) replaces EPM New: FCC national fuels mapping replacement for NFDRS

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Tools to Support Fire Emissions Estimation

Fire Occurrence Databases Ground-based data systems Remote Sensing

Fire Emissions Modeling AP-42 and past National Emissions Inventories

Methods simplistic, migrating to newer tools for 2002 (v2) Current: NFDRS, Consume, FOFEM, EPM New: Fire Emissions Production Simulator (FEPS) replaces EPM New: FCC national fuels mapping replacement for NFDRS

BlueSky system BlueSky-EM (emissions) RAINS Grid-model Linkage

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BlueSkyRAINS ~ Output Products

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Example Fire Trajectories for August 1, 2004

[BlueSkyRAINS (BSR) and Hazard Mapping System (HMS) Disagree]

Legend

BSR Fire

HMS Fire

Trajectories by

BSR Modeling (Every 3 Hr)

Trajectories by Remote Sensing (AM & PM)

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Fugitive Dust Technical Issues

Emissions very high (wrt) crustal matter in samples PM2.5 to PM10 Ratio Removal of dust near the source (< 100m)

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Fugitive Dust Technical Issues

Emissions very high (wrt) crustal matter in samples PM2.5 to PM10 Ratio Removal of dust near the source (< 100m)

Process-based Emissions Model (future) Soil / road surface silt content Soil moisture Rainfall Crop cover Ground cover Wind speed

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Other PM Priority Source Categories Mobile Sources

Mobile 6 & NONROAD (2004 version) NMIM, consolidated model w/ county database

Temperature, barometric pressure Fuel properties Vehicle Kilometers Traveled

Complete rework of models forthcoming Multi-scale mOtor Vehicle & equipment Emissions System

Ammonia Process-based model under development by RPO’s

Condensibles Including condensibles increased PM2.5 significantly

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In Summary NEI Development Schedule

We believe the US can shorten its NEI development schedule by factor of 2 or 3

Better utilization of emerging technologies GIS, Remote Sensing, Process-based emissions models

Priority categories for PM Wildland Fires Fugitive Dust Mobile Sources Ammonia Condensibles