Atmospheric Aerosol Studies Mentor: Daryl Albano University of - - PowerPoint PPT Presentation

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: CO2, SO2, 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 circuit 2. Programming the data acquisition software 3. Designing and Building the housing 4. Testing the assembled sensors 5. 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

• f 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 Sensor

Arduino Uno Ethernet Shield MicroSD 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

• peration

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 location 3. Power on sensor and begin collection timer 4. After collection timer is complete, power down the device 5. 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 presentation Mahalo Nui Loa!!!