Neighborhood scale heat mitigation strategies using Array of Things (AoT) data in Chicago

Extreme high temperatures in summers lead to an increased risk of heat-stress in vulnerable neighborhoods of cities. With intense socioeconomic, health and meteorological data collection in urban areas, there is a need to better understand the linkages between climate change and planned adaptation and mitigation efforts that impact urban metabolism at micro- (neighborhood) scales. This pilot study analyzes in situ meteorological observations in the City of Chicago using the newly installed, networked urban sensor project entitled the Array of Things (AoT) for the summertime period between June 1^st and July 10^th, 2018. During this time period, excessive heat warnings were issued for the city on June 16^th and on June 29^th. Point-source measurements of air temperature, humidity, and pressure measurements are gathered from AoT nodes and spatially interpolated on a uniform grid using kriging techniques. AoT data are statistically compared and quality controlled with other standard meteorological observations in Chicago. We also use the City of Chicago's dataset to obtain micro-scale social metrics, such as frequency of 311 calls and crime, along with electricity consumption to develop a framework for urban planners to reduce adverse heat impacts. Long-term extrapolations will be addressed, along with implications of implementation of green infrastructure to combat urban heating in Chicago's most vulnerable areas.