Atmospheric Aerosol Studies

Mentor: Daryl Albano

University of Hawai`i at Hilo

Students: Macy Ahuna, Craden Astrande, Seneca Helfrich, Britney Ho, Dylan Hong, Devon Morimoto, Nagahiro Ohashi, and Tara Marie Takafuji

Waiākea High School

Project Overview

Particulate Matter Overview

● Particulate matter (PM) is commonly found in air

pollution○ Examples: CO

2, SO

2, etc.

● PM has been attributed to major health effects,

leading to the highest health problems

● Exposure to PM could exacerbate existing

cardiovascular diseases

● Due to PM, air pollution is estimated to kill 3.7 million

people/year worldwide

Source: D. M. Holstius, A. Pillarisetti, K. R. Smith and E. Seto, "Field calibrations of a low-cost aerosol sensor at a regulatory monitoring site in California," Atmospheric Measurement Techniques, vol. 7, pp. 1121-1131, 2014.

Project Goals

❖ Design and engineer atmospheric aerosol sensors

❖ Deploy sensors for aerosol measurement collection

❖ Analyze data for atmospheric studies

Table of Contents

Project Components

1. Designing the sensor circuit2. Programming the data

acquisition software3. Designing and Building the

housing4. Testing the assembled sensors5. Deploying the sensors● Accomplishments● Future Improvements

1. Designing The Sensor Circuit

Electrical Components

● Arduino Microcontroller○ Primary Controller

● Particulate Matter Sensor○ Collects particulate matter as small

as 2.5 micrometers

● Ethernet Shield○ Future implementation for Internet

of Things

○ Stores SD card

● LCD screen○ Displays data

● 5V Fan○ Draws air through the intake

● Real-Time Clock○ Keeps track of date and time

Hello, world!

Real Time Clock

5V Fan

PM SensorArduino UnoEthernet ShieldMicroSD card

LCD Display

2. Programming the Data Acquisition

● Arduino IDE used● Programming Language in C

Software Development

Tools

Program Flowchart

START

Is SD card initialized?

Is the LCD display

working?

Did the concentration value print?

Collect and store data

END

False

False

End operation

False

True

True

True

Continue Operation

3. Designing & Building the Housing

Initial Housing Designs

● Initially, a simple design was created○ A box with a housing for the

Arduino and the bread board

● Later, the design was changed to compensate for the volume of the fan

Revising and improving the

designs

● The housing was later changed to attach the battery on the outside. But then we decided to use Velcro

● Finally, the housing was extended to fit all the components within and the cover was designed to project the LCD screen

4. Testing the Assembled Sensors

Testing Airflow

● Proper airflow determines best data acquisition

● Placement of sensor, fan, electronics, intake placement were tested and considered.

● Goal: Determine suitable location and placement of electronics, intake, and exhaust fan

● Results: Negative airflow (exhaust air) brings smoother airflow into housing. Placement of sensor on bottom gives more exposure to data

Testing the Assembled Sensors

Controlled Data Measurements

● Sensors were tested in controlled environment by using known pollution sources

● Carbon Dioxide, Sulfur Dioxide, etc. were analyzed by sensors in controlled environment

● Data comparisons were made to real-world datasets, such as Hilo and Mauna Loa data

Testing the Assembled Sensors (cont.)

● Calibrating the sensors○ Low Pulse Occupancy (LPO) - Opacity

percentage of circulated air

○ Determining method to understand data

measurements

○ The formulas below were used to determine

concentration levels

ratio=LPO/(sampleTime*10.0)

concentration=1.1 × ratio^3-3.8 × ratio^2+520 × ratio+0.62

Measurement of sulfur dioxide

Measurement of carbon dioxide

Testing sensor accuracy

● Each dataset is an individual test with three devices running simultaneously

● Data was collected at Mauna Loa● Goal: Determine whether there is disparity between

three devices● Results: Each sensor reports similar results. Thus,

accuracy between each sensor and housing configuration is consistent with results

5. Deploying the sensors

Data Acquisition Procedure

1. Determine a location for best fit of air measurements

a. Clear intake and exhaust

2. Position the sensor in appropriate location3. Power on sensor and begin collection

timer4. After collection timer is complete, power

down the device5. Retrieve data from microSD card after

device has successfully powered down

Hilo Data Analysis

Data measured around late

afternoon, similar time to

traffic density decreasing

Results show that CO2

emissions decrease over time

into the evening

Thus, higher traffic density

correlates to higher CO2

emissions

Measurement of CO2

concentration in Hilo late afternoon

Mauna Loa Data Analysis

Mauna Loa is a great test site

for SO2

analysis

Thus, it is a great site for

testing

Datasets were measured at

noon on a clear day

Results show no significant

change in PM data. Might be

due to little activity, resulting

in lower measurements

Measurement of SO2

concentration on Mauna Loa around noon with clear weather

Accomplishments

Goals Accomplished

Designing and engineering PM

sensing devices

Programming and testing

software for data acquisition

Analyzing measured data from

Hilo and Mauna Loa

Future Improvements

Improving the PM sensing devices

Implementing the “Internet of Things” for the devices. The idea is to have the devices communicate and send data to a web server for remote viewing from a web browser. Also, improve file-handling, such as remote backups, etc.

Adding new sensors (temperature, humidity, etc.) for additional data analysis

Simplify the electronic configuration. Reduce wire-clutter

This concludes the presentationMahalo Nui Loa!!!