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Evaluating Regional Pulmonary Deposition using Patient-Specific 3D Printed Lung Models

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Development, Evaluation, and Application of a Primary Aerosol Model.

I T Wang¹, T Chico², Y H Huang²

¹a Environmental Modeling & Analysis , Thousand Oaks , California , USA.

Journal of the Air & Waste Management Association (1995)

|October 28, 2017

Summary

The Segmented-Plume Primary Aerosol Model (SPPAM) accurately simulates air pollution dispersion, especially for roadway sources. It shows high organic fractions in PM2.5, influenced by traffic proximity and meteorology.

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Area of Science:

Atmospheric Science
Environmental Modeling
Air Quality Assessment

Background:

The Industrial Source Complex Short-Term (ISCST) model is widely used but has limitations in simulating plume dispersion under light winds and handling numerous line sources.
The Segmented-Plume Primary Aerosol Model (SPPAM) was developed to address these limitations and improve algorithms for plume transport, dispersion, and particle dry deposition.

Purpose of the Study:

To generalize the ISCST model for light wind conditions and numerous roadway sources.
To develop improved algorithms for plume transport velocity, line/area source dispersion, and particle dry deposition.
To evaluate the performance of the SPPAM using experimental data and apply it to a real-world case study.

Main Methods:

The SPPAM was developed with enhanced algorithms for plume transport, dispersion from line/area sources, and dry deposition.
Model performance was evaluated using the 1983 PNL dual tracer experimental data.
The SPPAM was applied to analyze primary PM2.5 impacts in the Rubidoux area, considering various emission sources like road dust and vehicular exhaust.

Main Results:

SPPAM predictions showed good agreement with experimental observations for plume advection-dispersion and particulate matter (PM) depletion by dry deposition.
In Rubidoux, predicted primary PM2.5 to PM10 concentration ratios ranged from 0.39-0.46.
Estimated organic fractions of primary PM2.5 impacts were 34-41%, primarily attributed to nearby heavily traveled roadways.

Conclusions:

The SPPAM is a capable tool for simulating air pollution dispersion, particularly from roadway sources, and accurately predicts PM depletion by dry deposition.
The model highlights the significant contribution of traffic-related emissions to PM2.5 concentrations, especially the high organic fraction.
Receptor location relative to roadways, traffic volume/composition, and meteorological conditions are key factors influencing air quality predictions.