Scope: Distributed Sensing of Aerosol Particle Counts Using Small Unmanned Aircraft Systems

Exposure to small aerosols that may enter the respiratory systems, and particularly those that may reach the alveolar region increase risks for both acute and chronic respiratory diseases such as asthma and bronchitis. They are also associated with long-term chronic irritation and inflammation, which can potentially lead to cancer. If the source of aerosols can be accurately determined, interventions, regulations, and policies can be implemented to reduce exposures and prevent disease. Sparse ground-based measurements of aerosol particles may not be adequate for distinguishing sources. The combination of ground-based measuring techniques with distributed aerial measurements may lead to much greater characterization of both the source and concentrations of exposures. Our long-term goal is to develop the ability to quantify the spatiotemporal distribution in local air quality to better understand the impacts of airborne contaminants on disease rates in agricultural communities. Aerosol particle counters deployed on small unmanned aircraft systems (UAS) will enable distributed sensing over the short time scales needed to map the spatial variability in local air quality. This in turn will help differentiate particle sources associated with agricultural activities (e.g., field equipment, grain handling, animal facilities) from external sources (e.g., roadways). Recent advances in UAS and miniature particle counters make this vision feasible. However, research is needed to understand how UAS deployment affects the accuracy of aerosol particle count measurements and how the distribution of aerosol particles sensed in the lower atmospheric boundary layer correspond to conditions at the surface where humans are exposed. We hypothesize that the spatial distribution of aerosol particle counts is heterogenous at local scale based on geography and proximity to aerosol sources. The rationale for completing this work is that better understanding of the spatiotemporal distribution of outdoor air quality may elucidate observed differences in health outcomes for farmers and their surrounding communities. The preliminary results obtained from our field experiment will be used as part of an investigator-initiated R01 application to NIOSH. This pilot project will accomplish the following specific aims in support of the development, validation, and demonstration of UAS-based aerosol particle measurements. Aim 1: Integrate aerosol particle counters into fixed-wing and multi-rotor UAS platforms. Existing remotely piloted aircraft (Loong 2160, Foxtech; Matrice 600 Pro, DJI) will be modified to carry existing small, lightweight handheld aerosol particle counters. Integration will require synchronization of data streams and designing physical mounts that minimize changes to flight characteristics. Aim 2: Validate airborne aerosol measurements against ground measurements. Instrumented UAS platforms will be tested at Wildcat Agricultural and Atmospheric Research Pavilion (WAARP) at the UK North Farm in Lexington, KY. Airborne and ground aerosol particle measurements will be analyzed along with meteorological conditions from a 10 m weather tower to determine the appropriate sampling rate and physical separation distance to collect highly correlated measurements as a function of environmental conditions. Aim 3: Quantify the spatial variability in aerosol particle counts across the UK North Farm & C. Oran Little Research Center. Two farms operated by UK will be used as test sites for collecting distributed aerosol particle measurements. Both farms include crop and animal production, grain storage, and are adjacent to major roadways. Measurements will be classified by specific land use to determine if known aerosol particle sources can be readily identified using our distributed measurement technique. The expected outcomes from this work are: 1) two different types of UAS platforms instrumented to collect aerosol particle measurements; 2) a novel dataset of ground and aerial aerosol measurements coupled with local meteorological measurements; and 3) a practical demonstration of the systems towards quantifying the spatiotemporal variability in aerosol particles.