Is this project an undergraduate, graduate, or faculty project?
Faculty
group
What campus are you from?
Daytona Beach
Authors' Class Standing
senior
Lead Presenter's Name
Andres Munevar
Faculty Mentor Name
Marwa El-Sayed
Abstract
In the past two decades, images have surfaced depicting severe smog and air pollution conditions blanketing urban environments. While shocking, these images shine light on the increasing level of pollution in the atmosphere. One pollutant of particular concern is Particulate Matter (PM), which is defined as any solid and/or liquid particles suspended or dispersed in the atmosphere. PM comes in three major size classifications: PM10, PM2.5, and PM1, where the number refers to the aerodynamic diameter of the particles, in microns. In an effort to advance research and curve the effects of PM in the atmosphere, low-cost PM sensors (LCPMS) have flooded the market in recent years. LCPMS use the light scattering properties of atmospheric particles, including Rayleigh and Mie scattering, or gravitational methods to measure particle concentrations. This novel sensor technology is relatively low-cost, with prices varying from $30-500 per sensor. The inexpensive nature of LCPMS makes PM research and data collection more attainable than ever before for individual and academic use. The lightweight and compact nature of most LCPMS allows them to become a prime candidate for use on unmanned aircraft (UA). Due to their ability to reach higher altitudes and travel long distances, UA have the potential to advance PM research past the realms of ground-level data analysis and give a better understanding of PM concentrations and composition at higher altitudes. Unfortunately, many of the new LCPMS on the market have flaws in their computation and general use; including but not limited to: build quality, mis-calibration, and erroneous readings in non-standard settings. Future research should examine the effectiveness and viability of using LCPMS on UA to collect data at varying altitudes. Hence, the aim of this study is to review the current state of LCPMS, with a focus on those that were used on UA, while noting discrepancies and flaws in the market offerings of LCPMS at the present moment. Ultimately, the better characterization of LCPMS on UA will enhance their use and allow for remedies to air pollution-stricken areas.
Did this research project receive funding support from the Office of Undergraduate Research.
No
Low-cost Particulate Matter Sensors and Their Future Use with Unmanned Vehicles
In the past two decades, images have surfaced depicting severe smog and air pollution conditions blanketing urban environments. While shocking, these images shine light on the increasing level of pollution in the atmosphere. One pollutant of particular concern is Particulate Matter (PM), which is defined as any solid and/or liquid particles suspended or dispersed in the atmosphere. PM comes in three major size classifications: PM10, PM2.5, and PM1, where the number refers to the aerodynamic diameter of the particles, in microns. In an effort to advance research and curve the effects of PM in the atmosphere, low-cost PM sensors (LCPMS) have flooded the market in recent years. LCPMS use the light scattering properties of atmospheric particles, including Rayleigh and Mie scattering, or gravitational methods to measure particle concentrations. This novel sensor technology is relatively low-cost, with prices varying from $30-500 per sensor. The inexpensive nature of LCPMS makes PM research and data collection more attainable than ever before for individual and academic use. The lightweight and compact nature of most LCPMS allows them to become a prime candidate for use on unmanned aircraft (UA). Due to their ability to reach higher altitudes and travel long distances, UA have the potential to advance PM research past the realms of ground-level data analysis and give a better understanding of PM concentrations and composition at higher altitudes. Unfortunately, many of the new LCPMS on the market have flaws in their computation and general use; including but not limited to: build quality, mis-calibration, and erroneous readings in non-standard settings. Future research should examine the effectiveness and viability of using LCPMS on UA to collect data at varying altitudes. Hence, the aim of this study is to review the current state of LCPMS, with a focus on those that were used on UA, while noting discrepancies and flaws in the market offerings of LCPMS at the present moment. Ultimately, the better characterization of LCPMS on UA will enhance their use and allow for remedies to air pollution-stricken areas.