Western Regional Technical Air Quality Studies:

support for Ozone Air Quality Planning in the West

Tom Moore

Air Quality Program Manager

Western Regional Air Partnership

WESTAR & University of Nevada - Ozone Transport Conference

Reno, NV

October, 11, 2012

EPA national Ozone Standard

• Measured at ground stations, highest 8-hour average each day

• 4th highest values each year are averaged over 3-year periods to

determine compliance (e.g., 2007-09, 2008-10)

• Current Ozone health standard level is 75 ppb

• EPA (again) (re)considering revised Ozone health standard in a

range of 60 to 70 ppb

• EPA also considering a secondary Ozone standard for

ecosystem protection

• Attainment and maintenance of Ozone standard(s) achieved

through state and federal emissions control programs/strategies

3-year Average 4th Highest 8-Hour Ozone value by County

2008-2010

AQS Federal Reference Method data from the monitoring site in each County with the highest Ozone values

3-year Average 4th Highest 8-Hour Ozone value for Rural/Class I Sites

2008-2010

AQS Federal Reference Method data from rural or Class I area monitoring sites

Western ozone precursors - key emissions sources

• Power plants decreasing markedly

• Mobile sources controlled and emission rates decreasing

markedly through federal rules and state testing programs

• Fire effects receiving intensive study

– Deterministic & Empirical Assessment of Smoke’s Contribution to

Ozone (DEASCO3)

– Others

• Biogenics (natural plant sources)

• Oil and gas

• All sources currently being studied in comprehensive regional

modeling analysis – 2008 base year

– West-wide Jumpstart Air Quality Modeling Study (WestJumpAQMS)

100,000

150,000

200,000

250,000

300,000

350,000

400,000

450,000

500,000

550,000

600,000

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

Western State Power Plant Emissions Trends

SO2 (tpy)

NOx (tpy)

Data from EPA Clean Air Markets Division

• Fire is essential in the West

• Historic land management,

climate have altered

(worsened) fire events

• Fire is an episodic contributor

to visibility-impairing

aerosols

• All types of fire (not just large

wildfires) are important

"Modeling indicates that, at certain times, increased visibility impairment

from fire is likely to exceed the potential visibility improvements

associated with other GCVTC recommendations“ (1996 GCVTC report)

0

2,000,000

4,000,000

6,000,000

8,000,000

10,000,000

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

Wildfire Acres Prescribed Fire Acres

U.S. Wildfire and Prescribed Fires Acres Burned - 1990 through 2011

Projected Change for selected Western States

in Anthropogenic NOx Emissions from 2002 to 2018

Projected Change for selected Western States

in Gaseous Volatile Organic Compound Emissions from 2002 to 2018

* -

Today - everything and the kitchen sink

• Biogenic Emissions Improvement

• Fire’s Effects on Elevated Regional Ozone

• Oil & Gas Emissions

• 3-State Air Quality Study

• Regional Photochemical Grid Modeling with

Ozone, PM2.5, and Visibility Source

Apportionment for the Western U.S.

Biogenic Emissions

• Biogenic emissions are VOCs from vegetation, CO and NO

from soils

– Biogenics frequently dominate VOC emissions

– Natural precursors to ozone and particulate matter

– Natural, but influenced by human activity, e.g., crops and forestry

• High temporal and spatial variability due to dependencies on

land cover and environmental factors

• Computer models are required

– EPA’s BEIS models developed since the 1980s

– NCAR’s MEGAN model developed since the 2000s

• Models continue to evolve with new science and better sources

of data, e.g., satellites, field studies

Improved 2008 Biogenic Emission Inventories across the West

• Improve biogenic data for AQ planning

by western States

o SIP modeling

o WestJump AQMS

• Targeted inventory evaluations and

improvements

o Use of satellite data

o Compare EPA’s model to other models

• New state-of-science biogenic emission

model an outcome

o MEGAN v2.10

• ENVIRON and NCAR team

• Project funded by WESTAR

• Completed March 2012

• Biogenics Improvement materials

WestJump AQMS Domains

Improvements in MEGAN v2.10

• Explicit canopy environment

– Light and temperature within tree canopies

• Updated emission algorithms

– Detailed VOC composition

– Light and temperature dependence

• Updated emissions factors

– Applied results from field studies in 6 Western states

• Improved soil NOx emissions

– Effects of fertilizer application and precipitation

• Temporal changes in biomass (LAI) every 8 days based

on 1 km MODIS satellite data

• 30 meter landcover data from Landsat

Result Highlights

MEGAN LAI for

July 17-25, 2008

m2/10m2 Change in average MEGAN LAI for

the first week in July in 2003-2005

compared to 2010-2011

LAI measures vegetation amount – satellites see seasonal

changes, dead vs. live leaves for input to emission inventories

Comparisons with Other Models

Average emissions for July 3-18,2008

SMOKE-BEIS MEGAN v2.04 MEGAN v2.10

Monoterpene

Isoprene

SMOKE-BEIS MEGAN v2.10

MEGAN v2.10

SMOKE-BEIS

Isoprene

4,212 kg/hr-km2 5,474 kg/hr-km2 4,735 kg/hr-km2

Photosynthetically Active Radiation (PAR)

VOC, CO, NO, etc.

Clouds

MEGAN Model

Method 1

Met Model

Predictions

PAR = 0.45 x SRAD

Where:

• SRAD is solar radiation

(w/m2) from WRF or MM5

based on predicted clouds

• 0.45 is fraction of SRAD

in 400-700 nm band

(simplifies reality)

• Convenient but subject to

model prediction biases

• Analysis of GOES

satellite imagery

• Satellite provides PAR

based on actual clouds

• Good agreement with

ground measurements

• Preferred method where

data are available (i.e.,

lower 48 states)

Method 2

Satellite

Observations

Solar Radiation (PAR)

Isoprene Comparisons for July 3-18, 2008

MEGAN v2.10 PAR from WRF

MEGAN v2.10 Satellite PAR

Difference WRF - Satellite

Domain Total = 4735 kg/hr km2 Difference = 1769 kg/hr km2

37% decrease

Domain Total = 6504 kg/hr km2

• Using more accurate satellite PAR data produced substantial

changes in biogenic emissions

• Real-world application of satellite data to air quality planning

– better than we can do from the ground using met models

Project Outcomes

• Improved 2008 biogenic emission inventories for the West

• Photochemical Grid Model-ready biogenic emissions for air quality analysis and planning: – Ready to use in state, EPA, and local, and other agencies’ air quality

modeling studies

– Applied in WestJumpAQMS regional project for transport assessment and source apportionment

• Solar radiation from satellite data provides more accurate emission estimates than default solar radiation from meteorological models

• Publicly available new MEGAN v2.10 – State of the science emissions tool, subject to ongoing peer review

– Readily updated with subsequent years’ landuse/landcover data for newer emissions

Considerations for AQ Modelers and Planners

• Evaluate sensitivity of ozone and PM to biogenic emission improvements

• Further improvements to biogenic emissions in urban areas would require field studies

• Biogenic emissions will respond to changes in climate

– Plant distributions change

– Emissions responses to temperature and drought

• Recovery of vegetation and biogenic emissions after major fires and insect outbreaks – Use typical vegetation density as basis for AQ planning?

– Do different species regrow?

Fire’s Effects on Elevated Regional Ozone

Deterministic & Empirical Assessment of Smoke’s

Contribution to Ozone (DEASCO3)

companion study to start late 2012:

Prescribed and Other Fire Emissions: Particulate Matter

Deterministic & Empirical Tagging & Assessment of Impacts on

Levels (PMDETAIL)

Funding for both from FLM Joint Fire Sciences Program

DEASCO3 project - purpose & goals

• Assess fire’s impact on elevated ozone episodes with

retrospective studies in the West and Southeastern U.S.,

using empirical and photochemical modeling analyses

• Studies of fire and ozone in 2002 through 2008

• Outcomes

• Support future collaborative FLM-state ozone air quality planning

• Develop “lessons learned”, basic analysis rules for fire-ozone episodes,

and online tools for FLM-state air quality planning

• Through the WRAP Fire Emissions Tracking System (FETS), prepare

and implement planning-grade fire emissions inventories in the FETS

suitable for SIP work by states and FLMs

• Publish data and analysis results in transparent and reproducible formats

Activity Data

Loading Moisture

Emissions

Model

distribute emissions

Chemical

Profiles

Loft emissions F

ET

S

DE

AS

CO

3

DEASCO3 Hypotheses

Technical

Ho1 – Smoke from fire contributes to background concentrations

of O3 in large areas of the U.S.

Ho2 – Fire/Smoke management can affect formation of O3.

Ho3 – Fire(s) cause/contribute to O3 exceedances.

Policy

Ho4 – Better quantitative information will help FLMs to assess the

use of smoke management techniques to address nonattainment

issues.

Ho5 – The Rank Order(s) in the Online Tool will help FLMs to be

more effective in the air quality planning processes.

Methods to Test Hypotheses

• Paired PGM results & empirical assessments

• Case Studies & Sensitivity modeling

• PGM, Obs data, & empirical assessments

• PGM

Ho1 - Fires Contribute to background

concentration

Ho3 - Fires cause/

contribute to O3

exceedance(s)

Ho5 - Rank Order(s) will help FLMs be effective in air

quality planning

Ho2 and Ho4 - SMPs : affect O3 formation

and use to address non-attainment

Data Sets for Assessment Work

EI

• 2002 (As-is)

• 2008 (refined)

• FINN (top down)

PGM

• 2002 (36 km)

• 2008 (12 km)

Case Studies

• Refined EI

• PGM (4km)

Source Apport

• OSAT

• PSAT

Obs

• AQS

• Castnet

Other

• Trajectories

• Satellite Detects

Grey lines depict

HYSPLIT back- and

forward-trajectories

from an ozone

monitor in southern

Oregon and the

Biscuit fire

MTBS fire

perimeters for fires

that started in July

2002 are shown in

grey

Ozone

concentrations listed

include the modeled

contribution from

fire (OSAT), total

modeled layer1

ozone, and observed

ozone at monitor

locations.

Prototype

Results

for Tool

WestJump AQMS

2008 NEIv2

(USFS collaboration)

Leveraging

DEASCO3

Improved AQ

Planning

PMDETAIL

Except. Event

applications

Why such a focus on the O&G industry sector? Recent modeling in Colorado Ozone NAA indicates O&G sector could

account for up to 50% of VOC and 10% of NOx inventories in NAA

Percentages could be even higher in other Rocky Mountain States

• Phase III: • Considers every major oil and gas production basin in the Rocky

Mountain states, including New Mexico, Utah, Colorado, Wyoming,

Montana and North Dakota

• Nearly all major oil and gas source categories and all major criteria

pollutants: NOx, VOC, CO, PM, SOx

• Provides updated, regionally consistent methodology which combines

state-permitted sources databases with direct industry survey for

some source categories

• Makes use of latest oil and gas production and well statistics from

commercially available IHS database

• Most detailed oil and gas emissions inventory to date

Phase III Oil & Gas Emission Inventory Effort

• Large Point Sources

(Gas plants, compressor stations)

• Drill Rigs

• Wellhead Compressor Engines

• CBM Pump Engines

• Heaters

• Pneumatic Devices

• Condensate and Oil Tanks

• Dehydrators

• Completion Venting

• Lateral compressor engines

• Workover Rigs

• Salt-Water Disposal Engines

• Artificial Lift Engines (Pumpjacks)

• Vapor Recovery Units (VRU’s)

• Miscellaneous or Exempt Engines

• Flaring

• Fugitive Emissions

• Well Blowdowns

• Truck Loading

• Amine Units (acid gas removal)

• Water Tanks

Phase I and II – Source Categories Phase III – Source Categories

Example - Geographic and Temporal Scope - WY

• Wyoming Basins being presented

here – Southwest Wyoming (Greater

Green River) Basin, Wind River

Basin, Powder River Basin

• For all basins the boundaries of the

basins have been aligned with county

boundaries

• All basins are analyzed for tribal and

non-tribal inventories (where

applicable)

• Baseline inventories developed for

2006 with midterm projections to

2012 or 2015 (2012 for Wind River

Basin) and 2009 updates developed

for Wyoming basins

Example - Geographic and Temporal Scope - WY

• NOx emissions – compressor engines, drill rigs, heaters, other engine types

Results – Example NOx Emissions

Breakdown By Source Category

Southwest Wyoming Basin Powder River Basin

Compressor engines

44%

Drill rigs27%

Heaters2%

Miscellaneous engines

20%

Artificial Lift2%

Other Categories

5%

Compressor Engines

54%

Drill rigs24%

Heaters12%

Dehydrator2%

Other Categories

6%

• VOC emissions – more complicated; tanks, pneumatics, fugitives, dehydration, compressor engines

Results – Example VOC Emissions

Breakdown By Source Category

Compressor Engines

2%Drill rigs

1%

Pneumatic devices

17%

Pneumatic pumps

6%

Fugitives24%

Dehydrator10%

Condensate tank 33%

Oil Tank2%

Venting -initial

completions1%

Venting -recompletions

0.5%

Other Categories

3%Compressor

engines27%

Drill rigs2%

Venting -initial

completions5%

Venting -recompletions

7%

Fugitives14%

Miscellaneous engines

3%

Artificial Lift2%

Dehydrator6%

Oil Well Truck Loading

6%

Pneumatic Devices

20%

Other Categories

8%

Southwest Wyoming Basin Powder River Basin

Results – Per-Well NOx Emissions

0.00

0.50

1.00

1.50

2.00

2.50

Wind River Basin Powder River Basin Southwest Wyoming Basin

Em

iss

ion

s (

ton

s/a

cti

ve w

ell)

Base Year (2006)

Mid Year (2009)

Future Year (2015*)

* Wind River Basin Estimates are for 2012

0

10

20

30

40

50

60

70

80

Wind River Basin Powder River Basin Southwest Wyoming Basin

Emis

sio

ns

(to

ns/

BC

F to

tal g

as p

rod

uct

ion

)Base Year (2006)

Mid Year (2009)

Future Year (2015*)

* Wind River Basin Estimates are for 2012

Results – Per-Unit-Gas-Production VOC Emissions

3-State Air Quality Study - Objectives

• EPA R8, NPS, USFS, BLM, States of UT, WY, CO

• Facilitate more complete and consistent air quality

analysis for NEPA and other air quality decisions

• Improve timeliness

• Reduce duplication of air quality analyses resulting in

lower costs

• Improve collaboration

Summary of future work planned

• Workplan through 2014 approved last week

• Activities to be completed by late 2012 – early 2013

– Final workplan through 2014 with completes warehouse

– Data integration--WestJumpAQMS 2008 base year and other datasets from cooperators

– Work underway • CIRA data warehouse development and roll-out

• Emissions modeling data improvement

– Technical Committee to develop data quality criteria for acceptance and approval of emissions data into warehouse

– Monitoring – ongoing

– Modeling-Emissions modeler work with Warehouse staff

• 2013 Expectations – Base Case Modeling and hopefully future case

– Secure outside funding for monitoring and warehouse O and M and modeling updates

Regional Photochemical Grid Modeling with

Ozone, PM2.5 and Visibility Source

Apportionment for the Western U.S.

WestJumpAQMS

• West-wide Jump-start Air Quality Modeling

Study (WestJumpAQMS) objectives:

– Initiate the next generation ozone and PM2.5 modeling

for the western U.S.

Develop modeling platform that can be used for transport,

NAAQS and NEPA analysis

– Further a concept initiated by NMED, EPA R6, BLM,

BP and WRAP

– Continue approach developed and work performed by

WRAP Regional Modeling Center (RMC)

Overview of WestJumpAQMS Modeling Approach

• 2008 calendar year

• WRF meteorological model

• 2008 NEIv2.0 emissions with augmentations

• SMOKE emissions model

– WRAP updated MEGAN v2.10 for biogenics

– MOVES for on-road mobile sources

• CAMx and CMAQ photochemical grid models

• Ozone and PM Source Apportionment modeling to

begin to analyze transport issues

36/12/4 km WRF/SMOKE Domains

• 36 km CONUS Domain

• 12 km WESTUS Domain

• 4 km Inter-Mountain West

Processing Domain

(IMWPD)

– WRF meteorological and

SMOKE emissions model

run for the entire 4 km

IMWPD

– Photochemical Grid Model

(PGM) applied to smaller 4

km domains for source

apportionment (window)

2008 SMOKE Emission Categories

• Continuous Emissions Monitor (CEM) Points

• Non-CEM Points (2008 NEIv2.0)

• Area and Non-Road (2008 NEIv2.0)

• MOVES for on-road mobile sources

• Oil and Gas WRAP Phase III projected to 2008

– Includes new Permian Basin (NM/TX)

• Fire Inventory from NCAR (FINN)

– Updated with DEASCO3 JSFP fire inventory

• WRAP Windblown Dust Model

• Lightning and Sea Salt

• MOZART boundary conditions

Model Performance Evaluation (MPE)

• Initial 36/12 km CAMx & CMAQ Runs

• Refined 36/12/4 km CAMx Runs

• Evaluation Databases:

– AQS: hourly gas-phase ozone, NO2, CO etc.

– FRM: 24-hour total PM2.5 mass

– CSN: 24-hour speciated PM2.5

– IMPROVE: 24-hour speciated PM2.5

– CASTNet: weekly speciated PM2.5 and hourly ozone

– NADP: weekly sulfate and nitrate wet deposition

– Ozonesonde: intermittent vertical ozone soundings

• FRM Network

FRM CSN

IMPROVE CASTNet

CAMx Source Apportionment Modeling

• APCA version of Ozone Source Apportionment

Technology (OSAT)

• Particulate Source Apportionment Technology

(PSAT)

– Sulfate (SO4)

– Nitrate (NO3) and Ammonium (NH4)

– Primary PM (EC, OA, OPM2.5)

• Use standard model output for SOAA vs. SOAB

• Two Rounds of Source Apportionment Modeling

Level 1 APCA Ozone Source Apportionment

• CAMx 36/12 km – Ozone Season

• Western State Source Regions

• 2 Source Categories

– Anthropogenic

– Natural

Initial Source Apportionment Modeling

• Level 1 APCA Ozone: State Regions by Anthro-Natural

– Described Previously

• Level 2 OSAT Ozone: One Source Region and Anthro-

Natural

– Examine VOC-limited vs. NOX-limited O3 Formation

• Level 3 PSAT PM: State Regions/Anthro-Natural

– Like Level 1 only for PM (SO4, NO3/NH4 & Primary)

• Preliminary Results and Detailed Source Apportionment

Modeling Plan

– 2nd round of additional apportionment with more source

categories and/or sub-state spatial regions possible

On-Line Source Apportionment Visualization Tool

• Source Apportionment

modeling produces lots of

information

• Extract key information at

sites and developed on-line

visualization tool

– AQS, IMPROVE, etc.

• Allow users to drill down

into Source Apportionment

results for sites and sources

of interest

• CENRAP Visualization Tool for

Regional Haze planning

– CAMx PSAT 36 km CONUS

– State-specific PM

– 2002 / 18 Visibility impacts at Class I

areas

– Example – Rocky Mountain National Park

Example non-WestJumpAQMS work - 2018 Worst 20%

Days at Rocky Mountain National Park

Source Categories by Species

Example non-WestJumpAQMS work - 2018 Worst 20%

Days at Rocky Mountain National Park

Species by Source Categories

Example non-WestJumpAQMS work - 2018 Worst 20%

Days at Rocky Mountain National Park

• Ranked Contributions by Source Region and Category

WestJumpAQMS Schedule

• 8-month delay getting

started waiting for 2008

NEIV2.0

• Products - WRAP webpage: – http://www.wrapair2.org/WestJump

AQMS.aspx

• Modeling Plan – 1/23/12

• WRF Evaluation Report – 2/29/12

• 13 Emissions Memos – Various Stages

– Emissions modeling complete early

October 2012

• Draft Modeling & Source

Apportionment Protocol – Review and comment October

– November 2012

• 2008 Base Case

Modeling – November - December 2012

• Preliminary Source

Apportionment Work – January - March 2013

• Final Report – March – May 2013

WestJumpAQMS - key next steps

• Need feedback from states, feds,

others on:

– Source Apportionment approach

and thoughts about representing

the results,

and

– Locations for extracting Source

Apportionment results, if results

beyond monitoring sites are

wanted

Air Quality Planning Summary

Clean Air Act

• §110 (a)(2) – requires each SIP to address interstate

transport of air pollutants when a NAAQS is revised

– Attainment and maintenance

– All NAAQS pollutants

– All areas of a State

• §110 (a)(2)(D)(i) – requires adequate provisions in each SIP

to prohibit air pollutant emissions from within a State from:

– Significantly contributing to nonattainment in any other State

– Interfering with maintenance of the NAAQS in any other State

– Interfering with measures required to prevent significant

deterioration of air quality or to protect visibility in any other State

Clean Air Act

• §110 (a)(2) – precise nature and content of an

“interstate transport” SIP not stipulated – EPA guidance

• Technical demonstration to support negative declaration

– Emissions and meteorology within the State

– Proximity to nearest nonattainment area in another State

– Modeling evaluation

– Consider expected attainment year

– Account for controls “on-the-way”

– Programs that prevent significant deterioration of air quality

in any other State

– Regional Haze SIP approval by EPA will be the program to

protect visibility in any other State

Air Quality planning requirements for EPA national Ozone Standard

• Cleanup (implementation) plans due from each state for the area(s)

in the state violating the Ozone standard

• All 50 states also complete a “good neighbor” plan to determine if

their emissions cause or contribute to Ozone problems in another

state

• More stringent Ozone standard(s) will require:

– Local solutions for sources in the violating (nonattainment) area,

– A regional component to address interstate transport,

– An analysis of the contribution from international sources that states are

unable to control, and

– An understanding of how much natural sources like wildfire are contributing

to high Ozone episodes.