Climate change and the impact on energy insecurity in the residential sector: A place-based analysis into the consumption and energy insecurity heterogeneities within Arizona

Climate change can widen the energy usage and health disparities between vulnerable  populations and their counterparts. Extreme heat continues to lead to the most deaths among  climate hazards annually. With each additional ton of CO2 emitted into the atmosphere, the  severity and frequency of extreme heat events will rise. Vulnerable populations are among  those most severely impacted by increasing heat waves and global warming due to financial  constraints that may hinder them from adopting climate adaptation technologies (e.g., air  conditioning systems). Thus, there is a need to identify how energy usage patterns of vulnerable  groups (e.g., low-income households) may be affected by rising temperatures and the degree to  which different interventions can mitigate financial strain and heat risk. This research aims to  answer the following questions: 1) how rising temperatures might affect household energy use,  given behavior patterns, technology adoption, and household structural characteristics, 2) the  energy equity implications of rising temperatures on behavioral patterns, technology adoption,  and household structural characteristics, 3) what is the degree of effectiveness of various  climate adaptation interventions given energy usage patterns of households to reduce energy  insecurity and greenhouse gas emissions?

I first use a five-point Ordinary Least Square (OLS) regression with fixed effects to derive and  model household temperature response functions within the Arizona area. I use smart-metered  household data to empirically relate temperature to daily electricity use, developing individual  functions for each household. These response functions are then used to develop a group-level  model (using a second-stage regression) relating AC efficiency, other cooling infrastructure,  housing infrastructure, and the number of days households are cooling their homes to connect temperature sensitivity to efficiency. Next, I use the model I developed to explore the climate impacts and simulate consumption changes, the impacts of AC efficiency improvements,  various cooling infrastructure scenarios, and the energy equity implications.  

Finally, I conduct a geospatial analysis to understand how the household response function  simulations would vary across census-tracts. I investigate the potential of climate adaptation  interventions to reduce electricity consumption and energy insecurity within the Salt River  Project utility service area’s tracts. I expand on the OLS regressions I developed to consider  weatherization. Additionally, I include external models to simulate urban cooling from tree cover  and NREL’s System Advisory Model to simulate rooftop solar with battery. One of the key  contributions of this work is to support the inclusion of a household’s lived experience to inform  and guide actions that cities and utilities can take to reduce insecurity and how to integrate such  metrics in guiding documentation for assessing and measuring climate risks (e.g., extreme heat)  in climate action plans. This work created a framework that cities can use to extend their climate  action plans, including quantitative metrics of climate impacts on inequality.