Urban heat island (UHI) effects depend on several factors, including air quality, temperature changes, and land cover. We used a holistic approach to quantify the UHI factors affecting air quality by developing three index-models (i.e., an environmental risk impact index (ERII), a social vulnerability index (SVI), and a health impact index (HII)) via multiple linear regression analysis for the city of Camden, NJ. Landsat 8 images were used to create surface-temperature and proportional vegetation (Pv) gradient, which were sampled along with environmental, social, and health variables in the study area. The results conclude that Pv is a better regressor than normalized difference vegetation index (NDVI). The highest contributors in the models were Pv, water fraction, % imperviousness and digital elevation model (DEM) with the relative importance of 20.5%, 33.5%, 32.5%, 9% in ERII, 19.6%, 32.4%, 32%, 8% in SVI, and 20.1%, 32.6%, 31.8%, 8.9% in HII model, respectively. The neighborhoods at risk identified by the models are Lanning Square, Bergen Square, Central waterfront, Cooper grant, Gateway, Liberty Park, Whitman park and Parkside, which fall within the index range of 7.3–10 and mostly associate with >32 °C. The indices will provide guidance in identifying neighborhood-risks of UHI-air-pollution.