1949

Background: Climate change is projected to increase the frequency and duration of extreme heat days in New York City (NYC), increasing heat risks among vulnerable populations. A Heat Vulnerability Index (HVI) previously developed in NYC based on epidemiological analysis, facilitated the City’s heat mitigation initiatives (i.e. planting street trees in high heat-vulnerable neighborhoods). The initiative also allowed an assessment of the role of land-use and vegetation on air temperature variations within these neighborhoods. Methods:Nearly 500 temperature sensors were installed on street trees and light poles in 16 medium to high HVI neighborhoods, with approximately 35 sensors within each neighborhood of size up to 1 km², during the summer of 2018. The average nighttime air temperatures (3 to 5 am) at these locations were modeled as a function of buffer-based (along street blocks) tree canopy, grass/shrubs, impervious surfaces, and buildings, allowing for non-linear relationships in a land-use regression model, adjusting for inter-neighborhood variations as a smooth function of XY coordinatesResults:With all predictors, the model R-squared was 71%. Street block level grass/shrub density was negatively associated with nighttime air temperature, with a ~0.8 degrees °C reduction within its range (0-25% cover). Street block level tree-canopy was also negatively associated with nighttime temperature, though it was strongly modified by street orientation: a ~0.4 degrees °C reduction for east-west streets over its range 0-60% cover, but null for north-south streets, likely influenced by both sunlight duration and wind patterns. Street block level impervious surface was positively associated with nighttime temperature, with ~0.2 degrees °C increase over its range of 5 to 50% coverage. Conclusions: In this high density, hyper-local temperature data measured in heat vulnerable neighborhoods, vegetative covers were associated with reductions in nighttime air temperatures. Parameters obtained from this study will be incorporated into modeling and projections for future heat mitigation planning.