Christian Yadao, originally from the Sinait Municipality in the Philippines, was raised in Kihei, Hawaii, Maui. He is currently pursuing an associate’s degree in Electronics and Computer Engineering at the University of Hawaii at Maui College. Christian’s immediate professional goal is to become an Electronic Technician for a company on Maui, and he plans to further his education by obtaining a bachelor’s degree in Electrical Engineering in the near future. Outside of his academic pursuits, Christian enjoys exercising, spending time with friends, and playing video games.
Home Island:Â O’ahu
High School:Â
Institution when accepted: University of Hawai’i at Maui
Project Site: Canada–France–Hawaii Telescope : CFHT, Waimea, Big Island HI
Mentor: Windell Jones
Project title:Â Commissioning an integrated SO2 and particle sensor for detection of VOG at the Mauna Kea summit.
Abstract:
The primary mirror is an integral component of the Canada-France-Hawaii Telescope (CFHT). Due to its location near two active volcanoes, Kilauea and Mauna Loa, high SO2 levels along with poor air quality can significantly reduce the mirror coating lifespan and image quality. During eruptions, CFHT staff have detected sulfur through handheld gas detectors and by smell. This project aims to develop a robust sulfur dioxide (SO2) and air particulate monitoring system to log data and alert CFHT staff when air quality is low. This will enable staff to cover the mirrors to prevent acidic particles from accumulating on the mirror’s surface and to monitor SO2 levels before, during, and after an eruption. To address this issue, we designed an enclosure in SolidWorks and manufactured it using 3D printing, providing proper housing and protection for the sensors and board. We verified the housing’s airflow by conducting comparative tests with the sensors placed both inside and outside the enclosure, ensuring that the readings were similar to confirm adequate airflow. Subsequently, we developed code in Python and C++ for data collection using a custom PCB equipped with an Arduino board, an SO2 sensor, and a particle sensor. The code was thoroughly reviewed to ensure valid data collection and proper sensor calibration, ensuring the system’s reliability in detecting VOG. The system will seamlessly integrate with existing CFHT environmental status systems, providing a comprehensive air quality monitoring solution. The expected outcome is a sensor system that allows further functionality of the existing particle sensors by adding SO2 detection capability.