Sub-Grid Scale Modeling of Air Toxics Concentrations Near Roadways Prakash Karamchandani, Kristen Lohman & Christian Seigneur AER San Ramon, CA 6th Annual.

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Sub-Grid Scale Modeling of Air Toxics Concentrations Near Roadways Prakash Karamchandani, Kristen Lohman & Christian Seigneur AER San Ramon, CA 6th Annual CMAS Conference October 1–3, 2007 Chapel Hill, NC

Background Population exposure to hazardous air pollutants (HAPs) is an important health concern Exposure levels near roadways are factors of 10 larger than in the background–models need to capture spatial variability in exposure levels Many of the species of interest are chemically reactive–e.g., formaldehyde, 1,3-butadiene, acetaldehyde–models need to treat the chemistry of these species Traditional modeling approaches are inadequate to provide both chemistry treatment and fine spatial resolution

Near-Roadway Modeling Air toxics emitted from mobile sources: –diesel particles –benzene –butadiene –formaldehyde –ultrafine particles –etc.

Three Major Approaches Parameterization of sub-grid variability Hybrid modeling (near-field model + grid-based model) Plume-in-grid modeling (this work)

Improving Spatial Resolution Parameterization of Spatial Variability Touma et al., J. Air Waste Manage. Assoc., 56, (2006) Ching et al., Atmos. Environ., 40, (2006) PDFs: sub-grid variability Formaldehyde PDF

Improving Spatial Resolution Hybrid Modeling Plume and background are simulated separately, then added Chemical reactions cannot be taken into account; only appropriate for chemically “inert” pollutants Formaldehyde concentrations  g/m 3  Touma et al., J. Air Waste Manage. Assoc., 56, (2006) Isakov & Venkatram, J. Air Waste Manage. Assoc., 56, (2006)

Improving Spatial Resolution Plume-in-Grid Modeling Combines 3-D grid-based modeling approach with a local scale modeling approach within a single model Provides capability of both capturing near-source variability and treating chemical transformations of reactive species Roadway emissions are treated as discrete sources and simulated with the embedded puff model Concentrations can be calculated at discrete receptor locations by combining the incremental puff concentrations from the puff model with the grid-cell average background concentration from the host grid model

Plume-in-Grid (PiG) Model Uses CMAQ as the host model and SCICHEM as the embedded puff model Based on previously developed PiG model for ozone and PM (CMAQ-APT, available from CMAS) Prototype version for this proof-of-concept study: –simulates near-source CO and benzene concentrations from roadway emissions –chemistry is switched off –roadway emissions are treated as a series of area sources along the roadway with initial size equal to the roadway width

SCICHEM Three-dimensional puff-based model Second-order closure approach for plume dispersion Puff splitting and merging Treatment of plume overlaps Optional treatment of building downwash Optional treatment of turbulent chemistry PM, gas-phase and aqueous-phase chemistry treatments consistent with host model

Model Application Busy interstate highway in New York City (I278) July 11-15, 1999 period of NARSTO/Northeast Program Grid model domain

Roadway Emissions Selected section of I278 passing through all five boroughs of New York City (~ 50 km) Section divided into small segments of 30 m length, with each segment representing an area source. Number of sources: ~1700 Emissions for each segment based on –County emissions for highway traffic (from SMOKE) –Traffic count information from the National Highway Planning Network (NHPN) for counties and I278 I278 emissions removed from 3-D CMAQ emissions file to avoid double counting of emissions

Receptor Locations Located along busiest stretch of roadway in Queens and Manhattan (Triborough Bridge) Located where roadway exhibited significant curvature, to increase the likelihood of capturing the maximum spatial variability in exposure levels Placed along transects perpendicular to the roadway at 10, 20, 30, 40, 50, 100, 200, 300, 400 and 500 m from the center of the roadway in both directions Source for map: Google

Results for Transect 1 (near intersection of I278 with Queens Blvd) Source for map: Google

Results for Transect 8 (Intersection of I278 with Grand Central Parkway) Source for map: Google

Results for Transect 15 (Triborough Bridge near Wards Island Park) Source for map: Google

Results for Transect 29 (I278-I87 Interchange; Bruckner Expressway) Source for map: Google

Observations in Los Angeles Near I-405 and I-710 Zhu et al., J. Air Waste Manage. Assoc., 52, (2002) –Measurements in vicinity of Interstate 405 –May to July 2001 –CO, Black Carbon (BC), and ultrafine particles –At 30, 60, 90, 150 and 300 m downwind and at 300 m upwind from freeway Zhu et al., Atmos. Environ., 36, (2002) –Measurements in vicinity of Interstate 710 –August to October 2001 –CO, Black Carbon (BC), and ultrafine particles –At 17, 20, 30, 90, 150 and 300 m downwind and at 200 m upwind from freeway

Qualitative Comparison with L.A. Observations LA Measurements NYC Model Predictions

Summary and Future Work Feasible to adapt available full-chemistry models to conduct sub-grid scale modeling of HAPs Model captures observed sub-grid scale variability in concentrations near roadways Future work should address: –Incorporate treatment of traffic-induced turbulence –Activate chemistry for reactive species –Improve computational efficiency of model –Application of model to region where data are available to evaluate the model (e.g., Los Angeles & North Carolina)