Quality with Quantity: 

Improving the Nationwide Correction Model for Purple Air Sensors

Over the summer of 2022, I was a research intern for NASA's Student Airborne Science Activation (SaSa) program. They immersed us in a variety of atmospheric science topics and had us conduct a research project on our chosen subject. I was placed in the Planetary Boundary Layer group where I focused on the detection of particulate matter. Purple Air sensors piqued my interest due to its citizen science aspect and its affordability. But scientists are hesitant to use its data due to the sensor's bias and the lack of reliability in the installment of the sensors. 

Over the summer, I wanted to learn how the sensors detect the drop in PM 2.5 after a cold front. I chose to analyze particulate matter that are only 2.5 microns large due to its harmful effects on human health and mortality. Its microscopic size makes it hard to detect until health problems arise, such as irritation in the eyes, nose, throat or lungs. Citizens purchase air quality monitors to become more aware of the potential harm in their environment and I want to ensure that the data being reported is accurate and precise.

The cold front allows me to study the effects of temperature and humidity on the concentration of PM 2.5 . I compared Purple Air measurements with the Environmental Protection Agency's (EPA) Air Quality Monitoring Systems and plotted the humidity and temperature measurements along with it. A nationwide correction model was recently published (Barkjohn et. al 2021) for Purple Air. But even with the correction, I found that while Purple Air captures the large changes in PM 2.5 concentration, it continues to struggle in precisely quantifying it. I hypothesized that humidity and precipitation are causing the overestimation since the sensors are dependent on environmental factors. I proposed to continue my research during the school year by improving the correction model by creating a specific regional model and accounting for the differences in its environment and weather.

During the Fall 2022 semester, I worked on creating a regional correction model for Purple Air Sensors in the Chesapeake Bay Area. I am continued to compare the measurements of PM 2.5 from Purple Air Sensors (with the current nationwide correction model applied) and the Environmental Protection Agency's Air Quality Monitoring Systems throughout a one year time period. By plotting the data and creating a regression model, I was able to see the changes in PM 2.5 concentration throughout the season and analyze the strength of its correlation. I hope to adjust the current nationwide correction model's relative humidity factor to improve the accuracy of the sensor's measurements. The results were presented at the American Meteorological Society Conference in January 2023 and at University of Maryland Baltimore County's  (UMBC) Undergraduate Research and Creative Achievement Day (URCAD) in April 2023.

During Summer 2024, I interned for Pennsylvania State University's MMAQH Program (Mid-Atlantic Meteorology and Air Quality Health) as a joint partnership with UMBC's Atmospheric Science Department. There, I continued to research more about refining Purple Air's algorithm, specifically focusing on sensors in the Baltimore, MD area. The following poster was presented at the AMS national student conference 2025.

A final report of the research was required upon completion of the MMAQH program. In September 2024, I had the opportunity to publish my final report as a research paper in the UMBC Review Journal. My paper underwent thorough reviews and the feedback allowed me to reevaluate the initial research poster's results and create a publishable report. Throughout this process, I've become the point of contact for Purple Air sensors in my research group and trained graduate students in accessing the data.

These projects were my first glimpses into the research world and it has been an amazing, educational experience. I enjoyed the opportunity to learn more about another scientific discipline and it expanded my perspective about the importance of my mechanical engineering courses. 

Before, I began my internship, I knew very little about the earth sciences, especially with the atmospheric field. I felt anxious due to my lack of exposure and was unsure how I would manage in conducting a personal research project. This experience allowed me to explore my outside of my comfort zone. Over the course of my undergraduate career, with the help of my graduate mentors, I learned a lot about data analysis and became more confident in my research skills. 

This experience helped me realize how truly versatile mechanical engineering is because I continuously had to apply my knowledge from classes like Statistics, Thermodynamics and Physics to gain a better understanding of the planetary boundary layer. It also allowed me to get a glimpse into the design process and study how it affects the performance of a sensor. I enjoyed being around other student and professional researchers and getting to know them. Their passion and enthusiasm for their projects is infectious and it encourages me to continue learning more about the atmospheric science field.

This research experience helps me with my goal in contributing to the grand challenge of engineering the tools of scientific discovery. I am working directly with sensors, learning how its design affects its performance and data analysis and I am learning how to address the needs and concerns of scientists.

a. Effective Communication: During conferences, I organize my research and its results on a poster board. I have to create an elevator pitch that is clear and concise to garner the audience’s interest.

b. Disciplinary Communication: During group meetings, I present my research updates in PowerPoints and must clearly communicate how the graphs I present represent my findings. 

c. Creativity: My research experience is based in the atmospheric science field and I’ve learned to become creative in connecting it with social justice. Researching purple air sensors allows me to connect citizen science to lawmaking because the data can show correlations with social inequalities such as higher pollution concentration in areas causing higher rates of lung issues. Scientists can use this data to inform the local government to create restrictions on nearby sources of pollution such as factory emissions. 

d. Practice and Process of Inquiry: In order to be approved to continue my summer research, I had to propose my plan and what results I hoped to achieve. My goal throughout the semester was to improve Purple Air Sensor’s correction model by making it regional based. I had to check in with my graduate mentor about how I would conduct my analysis. 

e. Nature of Disciplinary Knowledge: I learned how to view my knowledge of engineering thermodynamics in an atmospheric science aspect such as understanding how the concentration of particles are affected by the sun due to the diurnal cycle. 

f. Understanding Ethical Conduct: I must take accountability for the honesty of my results by ensuring that the data being used has not been tampered with. My goal is to improve a correction model so that scientists can use these networks of sensors to support their research and that the data being processed is accurate. 

Demonstrate the ability to work independently and identify when input, guidance, and feedback are needed. 

My research has mostly been independent work. I would set hours during the week and treat it like a job to help me stay on track and to have access to my graduate mentor whenever I needed help, especially with coding. 

Accept constructive criticism and apply feedback effectively

I’m required to give updates on my research every week to my mentor and present it at least once during a group meeting. Constructive criticism from my graduate and faculty mentors and the program managers from my summer research program is very beneficial to improving my analysis and it helps me understand the subject better especially since it is outside of my major.