Detroit Multipollutant

Pilot Project

Panel discussion 4: Technical Efforts to Support NAAQS and Air Toxics Programs

March 31, 2008

Karen Wesson

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Detroit Multipollutant Pilot Project:

Background Part of the technical component of the Air Quality

Management Plan (AQMP) Pilot Project to inform pilot project about the technical tools/methods/databases available and demonstrate their application by using Detroit as a testbed.

Address increasing need to provide multipollutant (MP) & multi-resolution air quality information for regulatory/policy development. Determine what source & pollutants to focus on to “maximize

benefits” of control programs & polices.

Improve information to public & stakeholders on multipollutant air quality issues and associated risks to health & environment

Provide framework to others (e.g. state & local agencies) on how to apply technical tools for MP assessments.

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Testing Multipollutant & Multi-Resolution:

Technical Challenges

Multipollutant: Release, control, and chemical formation of pollutants are interrelated NRC report: recommended that “the US transition from a pollutant-by-

pollutant approach to air quality management to a multipollutant, risk-based approach”….

Multi-resolution: Address regional and local-scale impacts of regulations and policies PM2.5 SIPS (e.g. AERMOD - Birmingham, Detroit, Atlanta, Cleveland;

CALPUFF – Allegheny Co, PA; CAMx – St. Louis, IL)

This project provides a challenge for all analytical components: Emissions Inventory: include CAPS & HAPS and support regional and

local scale modeling

Control Information: multi-pollutant for implementation into control strategies and sensitivity analyses

AQ modeling: account for primary & secondary aspects of criteria and toxic pollutants and assess regional and local concentrations and source contribution

Exposure/risk/benefits assessment: provide information on benefit of pollutant reductions at regional and local scales for criteria and toxic pollutants

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Analytical Multipollutant Framework

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View technical work and challenges as

falling into three main categories:

Conceptual Model Development Use 2002 analyses and ambient data to understand technical

and policy implications for multipollutant control strategy development

2002: Model & Tool Implementation and Evaluation Multipollutant framework implementation

Model/Tool Performance Evaluation: CMAQ, AERMOD & Hybrid Approach

Risk & Benefits Assessment Analyses

2020: Implementation of future year and control strategy cases Future year projections

Control strategy selections

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Conceptual

Model

Development

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Developing Conceptual Model

Utilizing MDEQ Reports (e.g. DATI Report, Annual Air Quality Reports, etc.), ambient data, Detroit Pilot Project data, and other data analysis studies determine: What are the important point, mobile, and area source

contributors?

Are emissions dominated by a few source types or more widely distributed throughout the source population?

What are possible sources are co-control?

How does the atmosphere respond to reductions in certain pollutants? When are there dis-benefits?

What controls have the greatest effect on reducing key pollutants?

Use information to develop a Conceptual Model indicating technical and policy implications of the current understanding of air quality

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Develop Conceptual Model specific to

Detroit MP problems VOC-limited regime → suggests focus on VOC controls

for ozone reductions

Important sources of PM2.5 in Detroit: metal processing, commercial cooking, residential wood burning, cement manufacturing → suggests implementing controls on these sectors

Many problem sources are emitting PM2.5 and toxics of concern (e.g. steel mills, cement manufacturing, woodstoves) → suggests potential co-control opportunity

High PM soil (primary) component at Dearborn and Allen Park → suggests focus on controlling local sources

Large mobile source component contribution suggested by receptor modeling → suggests implementing potential controls (could have co-benefits for O3, PM, & toxics (e.g. benzene, formaldehyde))

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2002: Model & Tool

Implementation

and

Evaluation

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2002: Implementing Multipollutant

& Multi-resolution Models & Tools

Emissions Inventory & Modeling 2002 NEI with Integrated CAPS & HAPS

EI improvements

Air Quality Modeling CMAQ v4.6.1

CAMx v4.5

AERMOD

Hybrid approach (2 equations)

Risk & Benefits Assessment BenMAP (O3, PM2.5 & Benzene)

HEM (Toxics)

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2002 NEI: Emissions Improvements

2002 NEI: Integrated HAPs & CAPs

Local-scale EI improvements

Steel Mill Study Data

LADCO Nonroad Study

Solvent Study

Emissions Modeling Improvements

1 km spacial surrogates and other improved land use based

inventory data

Link-based mobile emissions

Criteria & toxic emissions produced using CONCEPT and input

data from SEMCOG network (Generates gridded, hourly, link-

level emissions by vehicle class using highly resolved temporal

profiles for traffic volume and VMT mix)

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Urban-Scale Application – Detroit Network

Source: Alison Pollack of ENVIRON International Corporation

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Air Quality Modeling Photochemical Models

CMAQ v4.6.1 & CAMx 4.5 – “One-atmosphere” models include criteria pollutants and ~ 40 toxics

Modeled at 12 km for Midwest-centered domain

Modeled at fine-scale 4 km & 1km domains

AERMOD Dispersion Model Receptor domain centered on Detroit urban area: 36 x 48 km with

receptors placed every 1 km

Emissions domain extends 36+ km around receptor domain

Hybrid Approach Method Generates local gradients incorporating the advantages of both

CMAQ & AERMOD into one combined model output (via post-processing)

Allows preservation of the granular nature of AERMOD while properly treating chemistry/transport offered by CMAQ.

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4km CMAQ &

CAMx Domain

36x45

1km CMAQ &

CAMx Domain

72x108

AERMOD

Receptor

Domain

36x48

Detroit Domains

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Air Quality Modeling: Hybrid Approach

Method

AERMOD+CMAQCMAQAERMOD

CMAQ

AERMOD

Combined

AERMODAVG

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Benefits and Risk Assessment

The Modeled Attainment Test Software (MATS) tool will be used to provide input data to both BenMAP & HEM Creates a fusion of the ambient and modeled data across

domain

Treats ambient data as “truth” and allows modeled data to provide gradient

BenMAP (Benefits) Will be applied for O3 (12km), PM2.5 (12&1km), and benzene

(1km)

Fine-scale population data included in BenMAP

Local health data input

HEM (Risk) Will be applied for the 11 toxics (12 & 1km)

Includes ability to take gridded modeled input and interpolate to census track

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2002: Model/Tool Evaluation

Model Evaluation (w/ & w/o link-based): Using the AMET tool CMAQ & CAMx

AERMOD

Hybrid method (2 methods)

Risk & Benefits Assessment 12km vs 4km vs 1 km resolution

link vs no-link

Benzene: HEM vs BenMAP

Possible evaluation of HEM, HAPEM, SHEDS (in conjunction with DEARS)

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2020: Implementation of

future year

and

control strategy

cases

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Control Strategy: Sensitivity Analysis Control Database

Use control data available in AirControlNet and special studies.

“Multipollutanize” the control data with help from EPA source-specific engineers for controls in Detroit

Control Strategy 2020 with national rules

Control Strategy 1: “Status Quo”

Use controls for Detroit from illustrative NAAQS 2015 PM2.5 15/35 control scenario as presented in the recent PM2.5 RIA

Use list of controls consistent with those provided in Detroit O3 SIP Strategy Plan

Control Strategy 2: “Multipollutant Based”

Develop a multiple pollutant control strategy based on available “multipollutanized” PM2.5 & O3 control measures and knowledge of AQ issues in the Detroit area

This strategy should achieve PM2.5, O3, and air toxic reductions.

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Exposure/Risk/Benefits

Plans BenMAP (Benefits) - Apply BenMAP for O3 (12km), PM2.5 (12

& 1km), and benzene (1km) using fine-scale population data & local health data

HEM (Risk) – apply for the 11 toxics (12 & 1km)

Considerations How to use risk/benefits results together to quantify “co-benefits”

and make decisions in multipollutant context?

Use this information from Control Strategy 1 for consideration of toxics and criteria pollutant “effects” (i.e., co-benefits and trade-offs) as part of multipollutant control strategy development (CS2)

Apply a tool, such as MIRA, to aid in decision making process?

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Lessons Learned Emissions data used can make a large difference at

local scales (e.g. stack locations, road links) to modeled concentrations and risk & benefits estimates but getting this data can be time consuming.

Running CMAQ/CAMx with 12km grid resolution may not allow local gradients of PM2.5 & toxics to be captured.

Running a dispersion model for a large area with many sources may not be cost effective. Applying a photochemical model at finer grids may be alternative solution.

Multipollutant control information can be hard to find and the emissions inventory may not support it.

And we are still learning ….

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Team Members Louise Camalier

Neal Fann

Tyler Fox

Marc Houyoux

Robin Langdon

Rich Mason

Mark Morris

Sharon Phillips

Tesh Rao

Madeleine Strum

Larry Sorrels

Lee Tooly

Elineth Torres

Darryl Weatherhead

For more info:

http://www.epa.gov/scram001/modelingapps_mp.htm