Abstract
In recent years, climate change has become one of the most widely discussed topics in the political and economic domains. Climate change, formerly referred to as global warming, refers to a rapidly changing climate as a result of increasingly high levels of greenhouse gases in the atmosphere. Many climate scientists point to an ever-increasing dependence on fossil fuels as the major culprit of this phenomenon. As such, my technical research focuses on detecting levels of Nitrogen Dioxide (NO2) in the atmosphere using a 3U CubeSat. We have chosen Nitrogen Dioxide as our target chemical because it is a well-known greenhouse gas with documented spectral properties. As such, by measuring the atmospheric concentration of this gas we can estimate the concentration of several other pollutants that are more difficult to measure across large areas. As each of these pollutants have a unique spectral signature, the satellite is fitted with a custom-made spectrograph that is capable of measuring NO2 columns with a spatial resolution of at least l km2. The satellite, which is scheduled to launch from the ISS in the spring of 2021, will operate in Low Earth Orbit and detect the concentration of NO2 over seven key cities. With this data we can improve the existing models of NO2 pollution while also attaining a better understanding of the atmospheric effects of emission-producing technologies. As there are several alternatives to fossil fuels, this data may be used to guide legislation to establish better regulations or incentivize large manufacturing firms to shift toward clean energy.
Though my STS research focuses specifically on the viability of UAVs in the agricultural and delivery industries, this topic draws several parallels with my capstone project. According to the EPA, the two industries in question contribute roughly one-fifth of the total U.S. emissions in addition to other forms of pollution. As UAVs are typically emission-free and have the technical capacity to replace several existing technologies used within these industries, their implementation could drastically reduce each industry’s carbon footprint. Additionally, this research shows that there are several financial benefits associated with substituting current technologies with UAVs. The major existing technologies explored in this research are crop dusting planes in the agricultural sphere and delivery trucks in an urban delivery setting. Through a cost-benefit analysis it becomes very clear that UAVs can provide a cheaper alternative to these technologies while decreasing the human input required for their operation. Furthermore, when comparing the energy input of UAVs with that of formative technologies, it is undeniable that they cause significantly less harm to the environment. Nevertheless, their adoption into these sectors has been very gradual due to several economic, cultural, and legal obstacles. The economic barriers stem from the fact that there is a large initial cost of replacing existing technology with UAVs. While this issue is not as prevalent in the delivery industry, which is dominated by large corporations, it does affect their adoption into the agriculture sphere which is mostly comprised of small, family owned farms with less access to capital. The cultural barriers that inhibit their adoption typically result from the military origins of UAV technology which typically saturates the public discourse about their use. The most prevalent obstacle, however, pertains to the legal restrictions that greatly limit the ability of UAVs to compete with existing technology. Since several FAA regulations inhibit commercial UAVs from exercising their full technical capacity, they cannot adequately compete with existing technology.
Notes
School of Engineering and Applied Science
Bachelor of Science in Aerospace Engineering
Technical Advisor: Chris Goyne
STS Advisor: Bryn Seabrook
Technical Team Members: Isabel Araujo, Genesis Brockett, Alex Brookes, Noah DeMatteo, Max Diamond, Sami Khatouri, William McNicholas, Matt Moore, Adelaide Pollard, William Schaefermeier, Huy Tran, Hannah Umansky
