Emissions from energy production and other anthropogenic activities are altering the physical and chemical properties of the atmosphere and have been linked to weather modification, environmental degradation, human health problems, and changes in clouds and aerosols. Weather forecast models require better observational constraints on the vertical heating rate of the atmosphere in order to more accurately predict precipitation patterns, especially for severe events. Observations are particularly needed in the Arctic, where warming driven by light-absorbing aerosols is likely accelerating the ice melt. This SBIR project will develop a new, miniaturized aerosol water uptake (hygroscopicity) measurement system suitable for deployment on UASs in order to make observations 1) more often, 2) in more locations, 3) at reduced cost compared to conventional aircraft, and 4) in difficult to access regions such as the Arctic. The system avoids problems with current approaches that are too slow, large in size, and costly. Specifically, the project will support the development of: (1) a miniaturized aerosol water uptake spectrometer optimized for UAS deployment and (2) a portable field calibration system. Phase I of the project will involve coupled heat and mass transfer modelling of the device to minimize its size, weight and power consumption for deployment on the Tigershark and other similarly sized UASs. The humidification system will be miniaturized for the small size requirements of the UAS and a prototype tested with known particle sizes and chemical properties to assess performance. Commercial applications and other benefits include creating new, cost-effective tools to study aerosol radiative forcing, creation of data sets to validate weather prediction and cloud condensation nucleus models, measurements in health effects studies, flux measurements of aerosol species from ocean and land surfaces, studies of rapid aerosol evolution around clouds, and providing sensors for indoor air monitoring for green buildings, industry and households.
