A Scientist with Sensors and Spare Time:

Backyard Comparisons of Particulate Matter Sensors Tim S. Dye, Sonoma Technology, Inc., Petaluma, CA

Objective Data Flow & Handling

Preliminary Results

Evaluate different types of light-scattering particulate matter (PM) sensors during ambient, outdoor conditions.

Ambient Experiments

1. PDR-1500 vs. Dylos (1-, 15-, and 60-minute averages)

Collected 1-minute data (averaged)

Thermo PDR-1500 (PM2.5 in µg/m3)

Dylos Dc1100 (particle count)

Shinyei PPD42NS (particle count)

Acquired PM2.5 hourly data from Bay Area Air Quality

Management District (BAAQMD)

Transmitted to online database (Cosm) to synch time

Used the Data Management System (DMS) to

Store data

Perform quality control

Create 15- and 60-minute averages

Create data plots

2. PDR-1500 vs. Shinyei (1-minute averages)

3. Smoke Box Tests

Case Studies

Very good correlation with 1-minute data. Inconsistent response at low concentrations (<100 µg/m3).

Wood Smoke Episode

Local influences of smoke

PDR and Dylos

instruments affected by

humidity

North Wind Clean Out

Decent agreement

among PM instruments

North winds increased

mixing

Conclusions

Dylos

Good agreement with PDR-1500

R2 > 0.91

Responsive to rapid changes in

PM2.5

Tracked wood smoke events

Shinyei

Inconsistent response at low

concentrations (less than

100 µg/m3)

Responds at higher

concentrations (200+ µg/m3)

Dylos:

Shows a good response

over a range of

concentrations.

Shinyei:

Inconsistent response at

lower concentrations

(<100 µg/m3); appears

to respond at higher

concentrations.

What would you do differently?

How could we create a larger field deployment of these

sensors?

Tell us what you think

707.665.9900 | sonomatech.com

Poster presented by Tim S. Dye (tim@sonomatech.com) at the

Next Generation Air Monitoring Workshop—Air Sensors 2013:

Data Quality and Applications; March 19-20, 2013, Research

Triangle Park, NC (STI-5602).

PDR

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