Adam N. Pasch1, Ashley R. Russell1, Leo Tidd2, Douglas S. Eisinger1, Daniel M. Alrick1, Hilary R. Hafner1, and Song Bai1

1Sonoma Technology, Inc., Petaluma, CA2The Louis Berger Group, Inc., Morristown, NJ

forNational Cooperative Highway Research Program

AASHTO Standing Committee on the EnvironmentNCHRP 25-25/Task 89

August 20, 2014

Establishing Representative Background Establishing Representative Background Concentrations for Quantitative Hot-Spot Analyses Concentrations for Quantitative Hot-Spot Analyses

for Particulate Matterfor Particulate Matter

STI-6051

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NCHRP Background PM StudyNCHRP Background PM Study• Overview

– Project motivation– Research purpose

• EPA guidance• NCHRP study (focus of this presentation)

– Ambient data use • Four-step method• Phoenix, AZ examples

– CTM use

• Future research needs

Project MotivationProject Motivation

• Background concentrations are required for PM hot-spot analysis

• Determination of representative background concentrations is critical (especially when the project increment is small)

• Current guidance is limited on how to assess representativeness

3Overview

Research PurposeResearch Purpose• NCHRP 25-25 Task 89

– Support PM hot-spot analyses– Develop step-by-step methods– Create illustrative examples and template

• Key technical issues– Selection of representative monitor(s)– Identification of exceptional or exceptional-

type events

4Overview

1. Estimate background PM concentrations using ambient data (three years)– Single representative monitor– Interpolation among representative

monitors

2. Calculate background PM concentrations using chemical transport modeling (CTM) outputs (not discussed in this talk)

Interagency consultation is required.

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EPA Guidance: Two MethodsEPA Guidance: Two Methods

EPA Guidance

• Exceptional events: unusual or naturally occurring events that affect air quality but are not reasonably controllable (NAAQS violation).– Require a detailed demonstration to be

submitted and approval by EPA to remove data

– Regulatory impact

• Exceptional-type events (no NAAQS violation or no demonstration packet submitted). Handled as research only at this time.

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EPA Guidance: Exceptional Events EPA Guidance: Exceptional Events (EEs)(EEs)

EPA Guidance

1. Select representative PM monitoring site(s).

2. Acquire and process PM concentration data.

3. Assess data quality and representativeness.

4. Calculate background PM concentrations, following EPA requirements.

Determine data impacted by an exceptional-type or air transport event and document and remove these data from consideration (research purposes only).

7NCHRP Study

Using Ambient Data: Major StepsUsing Ambient Data: Major Steps

Considerations include• Distance from project site• Wind patterns (upwind of project preferred)• Land use/density/mix of sources• Monitor height and elevation• Monitor type and purpose• Data availability and completeness• Interagency consultation

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Step 1: Select Representative Monitor Site Step 1: Select Representative Monitor Site

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Identify Candidate Monitors and DataIdentify Candidate Monitors and Data

Example: PM10 monitor sites and data acquisition from EPA AirData website.

Hypothetical Project

Location

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Assess Meteorology and Land UseAssess Meteorology and Land Use

Example above: wind rose created using the AirNow-Tech website.

Example below: Map of land use types based on USGS data.

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Sources include• AirData (replaces AirExplorer – linked to

AQS) – recommended by EPA guidance• AirNow-Tech (backfilled with AQS data)• AQS Data Mart• AQS Web Application• Local air quality agency

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Step 2: Acquire and Process PM DataStep 2: Acquire and Process PM Data

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Example of PM Data Acquisition MethodsExample of PM Data Acquisition Methods

Example below: data acquisition from the AirNow-Tech website.

Example above: data acquisition from the AirData website.

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• Identify and remove concurred EEs• Cautionary notes for AirData users

– AirData flags data as Exceptional, but not Exceptional and concurred

– Analysts need to manually identify and exclude concurred EEs within AirData

• Check data completeness (75% by quarter, over three years minimum)

• Identify exceptional-type events (research)

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Step 3: Assess Quality, RepresentativenessStep 3: Assess Quality, Representativeness

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Considerations• Temperature (was residential wood burning

likely?)• Visibility• Wind (i.e., wind speeds greater than 25 mph)• Smoke or haze reported (or smoke plumes

evident from satellite observations)• Transport (i.e., trajectories from a source

region)

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Screen Anomalous PM DataScreen Anomalous PM Data

Exceptional-type eventsAir transport events

Research only:

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Data obtained from AirNow backfilled with AQS data.

Phoenix PMPhoenix PM1010 Data: Exceptional Event Data: Exceptional Event

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Met. Data: Blowing Dust All QuadrantsMet. Data: Blowing Dust All Quadrants

BLDU ALQDS = Blowing Dust All Quadrants Haze

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Visibility Photos: August 3, 2011Visibility Photos: August 3, 2011

12:00 a.m. 3:00 a.m.

Source of images: Arizona Department of Environmental Quality (ADEQ)

http://www.azdeq.gov/environ/air/plan/download/eed_080311.pdf

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Step 4: Calculate Background PMStep 4: Calculate Background PM

• PM10 design value– 24-hr maximum over three years

• PM2.5 design value– Annual average: average for each quarter,

then average for each year over three years– 24-hr

• Tier 1 – simpler, more conservative design values

• Tier 2 – more complex

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• Using 2010–2012 data– Before = 341

µg/m3

• Removing PM10 data – All exceptional events

•144 µg/m3

– Exceptional-type events•129 µg/m3 (research)

(24-hr PM10 NAAQS = 150 µg/m3)

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Step 4: Calculate Background PMStep 4: Calculate Background PM

2010 to 2012 maximum daily PM10 concentrations for the Central Phoenix Monitor (based on data obtained from AirData).

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Future Research NeedsFuture Research Needs• EPA-approvable data exclusion

methods to handle exceptional-type events.

• Help to obtain CTM outputs for use in forecasting future background PM concentrations.

• Best practices and lessons learned from real-world PM hot-spot analyses.

• Processes to encourage SIP development to support background PM estimation.

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ConclusionsConclusions• Monitor site selection will be influenced by

many practical considerations; multiple sites may be needed for large, spatially complex projects.

• Project analysts should budget analyses to cover complex data processing such as exceptional event removal and multi-year data assessments.

• Exceptional-type events can substantially impact background concentrations.