Simulating Energy Use, Indoor Temperatures, and Utility Cost Impacts Amidst a Warming Climate in a Multi-family Housing Model

Abstract

Rising ambient temperatures due to climate change will impact both indoor temperatures and heating and cooling utility costs. In traditionally colder climates, there are potential tradeoffs in how to meet the reduced heating and increased cooling demands, and issues related to lack of air conditioning (AC) access in older homes and among lower-income populations to prevent extreme heat exposure. We modeled a typical multi-family home in Boston (MA) in the building simulation program EnergyPlus to assess indoor temperature and energy consumption in current (2020) and projected future (2050) weather conditions. Selected households were those without AC (no AC), those who ran AC sometimes (some AC), and those with sufficient resources to run AC always (full AC). We considered stylized cooling subsidy policies that allowed households to move between groups, both independently and in conjunction with energy efficiency retrofits. Results showed that future weather conditions without policy changes yielded an increase in indoor summer temperatures of 2.1 °C (no AC), increased cooling demand (range: 34–50%), but led to a decrease in net yearly total utility costs per apartment (range: − $21 to − $38). Policies that allowed households to move to greater AC utilization yielded average indoor summer temperature decreases (− 3.5 °C to − 6.2 °C) and net yearly total utility increases (range: + $2 to + $94) per apartment unit, with greater savings for retrofitted homes primarily due to large decreases in heating use. Our model results reinforce the importance of coordinated public policies addressing climate change that have an equity lens for both health and climate goals.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11524-023-00790-3.

Introduction

Substantial increases in global temperatures are expected in the coming decades [1], leading to increasing demand for adaptation strategies, such as air conditioning (AC). In traditionally cooler climates like the Northeastern US, there will be increased demand for AC in places that have not had as much need before and where access may be limited [2]. Despite 80–90% of Americans having at least some AC access [3], those without it are more likely to be lower-income individuals, belong to systemically marginalized groups, and be unable to afford to run their AC [4]. Lower-income households in the USA spend a large portion of their monthly budget on utility bills and have greater energy burdens than their higher income counterparts [5]. For those lacking access to AC or the ability to pay for utility bills, there will be increasing challenges maintaining comfortable indoor temperatures during hot weather.

While strategies for adaptation to a warming climate are important, mitigation measures at the city and state level are also critical. Like many states, Massachusetts (MA) has established greenhouse gas (GHG) reduction targets, aiming for an 80% reduction from a 1990 baseline by 2050 [6]. Residential building retrofits will be essential to climate mitigation efforts given their contribution to GHG emissions (27% statewide in MA) and relatively slow housing stock turnover. With a warming climate, heating energy demand is anticipated to decrease due to both higher winter ambient temperatures and retrofits that tighten the building envelope, which would be balanced against increased cooling demand for AC [7]. This tradeoff between heating and cooling will depend on factors such as the extent of utility subsidies and building structural characteristics. The net implications of various policies for disinvested and resource-constrained communities are unclear.

Models that can estimate the impact of building upgrades on heating and cooling demands while simultaneously considering indoor environmental conditions are integral to evaluate future adaptation and mitigation policies. While energy modeling and simulation studies have shown anticipated increases in AC prevalence and net energy savings for cities in historically colder climates [8], they have not specifically considered the challenges for lower-income households with constraints on cooling access and affordability, leading to increases in utility bills to achieve thermal comfort [9]. Monitoring studies have found high indoor temperatures in lower-income and affordable housing units during hot weather [10], highlighting the importance of understanding the impacts of rising ambient temperatures on populations without AC access.

To provide insight about some of these complex tradeoffs in a warming climate, we evaluated indoor temperatures and energy costs in a modeled multi-family home typical of affordable housing in Boston, MA, USA, building on our previous work modeling indoor air quality and energy use [11–13]. We evaluated the implications of cooling subsidies and residential energy efficiency retrofits for households with adequate to no cooling and considered the implications for future policy.

Methods

Overview

Our models evaluated two stylized policy interventions in multi-family residences in Boston, MA, USA, in present-day and future warmer weather: (1) subsidies for AC and (2) energy efficiency housing retrofits (Fig. 1). Leveraging our previous building simulation work [11, 12], we compared energy used for heating and cooling, summertime indoor temperatures, and total annual utility costs for heating and cooling.

Fig. 1.

Conceptual diagram of framework with modeling scenario factors and main outcomes: energy consumption, utility cost, and summer indoor temperatures, and meteorology and policy affect some outcomes directly and others indirectly through residential AC utilization

Location and Building Simulation Modeling

We modeled a four-story mid-rise multi-family home that is typical of affordable, older housing stock (i.e., pre-1980 construction, several floors, greater than 20 units) in Boston, MA. This building type is the target of energy efficiency housing retrofits in decarbonization initiatives that the state is undertaking as part of Massachusetts 2050 Roadmap [14]. Although based in Massachusetts, this is a typical building type found in many urban areas, and it is likely that similar decarbonization initiatives will be implemented across the country and throughout the world in the coming years.

We leveraged a previously developed co-simulation model [15] where CONTAM, a multi-zone air and contaminant transport analysis program (National Institute of Standards and Technology, Gaithersburg, MD), and EnergyPlus, a whole building energy simulation program (Department of Energy, Washington, DC), are coupled to continuously track multiple indoor environmental and energy use parameters. In our analysis, we used this modeling framework to continuously track indoor temperatures and energy consumption, similar to previous work [11–13]. Further building model information is available in Supplemental Fig. 1 and Supplemental Table I.

Current and Future Weather

We created a year of weather data for current (2020) and future (2050) conditions to use in our simulations. Current weather data were constructed using hourly meteorological and solar radiation data from the National Solar Radiation Database (NSRDB) (National Renewable Energy Laboratory, Golden, CO) from 1998 to 2020 for Boston, MA, USA [16]. Ten weather files were developed with a bootstrap algorithm to randomly select a month of data for a given year to make new weather files. This method preserved the correlation in the meteorological parameters in each month (similar to other weather file compilation [17]) allowed us to expand beyond the single modeled year of weather data as in other approaches [12, 17], and created variation rather than a single point estimate for each outcome.

For the 2050 weather, we modified current weather data to represent a set of future years based on large-scale climate models that are downscaled to a smaller region, a process known as “morphing,” or the Belcher methodology [18]. We applied the weather morphing tool to each of the ten current weather files for the year 2050, which morphed all meteorological variables (full model information available in Supplemental Table II). For ease of presentation, we describe these meteorological changes as “future weather.”

Ambient temperatures in both 2020 and 2050 were averaged across all ten simulation run scenarios in the yearly, summertime, and wintertime seasons. We calculated cooling degree days and heating degree days in both 2020 and 2050 as defined by the U.S. Energy Information Administration (EIA) and compared these values to existing data and predicted future meteorological data for Boston, MA [19, 20].

Cooling

We conducted comparisons for three household types based on ability to cool, operationalized by owning or operating AC. The first group includes households that cannot afford to run AC or do not have AC at all. The second group comprises households that run AC some of the time, which may be due to several factors, including preference for a relatively warmer indoor temperature or cost-related constraints. The third group includes households that run AC to maintain their home at a comfortable temperature, without any financial constraints. We refer to these groups as “no AC,” “some AC,” and “full AC” in this analysis, recognizing that these activity levels represent a combination of the ability to own as well as afford to operate AC (Table 1).

Table 1.

Model scenarios by air conditioning (AC) utilization group, weather year, and retrofit status

Model run	AC group and thermostat setpoint	Weather year	Energy efficiency retrofit status
a	Full AC1 (23.9 °C)	2020	No
b	Full AC (23.9 °C)	2050	No
c	Full AC (23.9 °C)	2050	Yes
d	Some AC2 (26.7 °C)	2020	No
e	Some AC (26.7 °C)	2050	No
f	Some AC (26.7 °C)	2050	Yes
g	No AC3 (no setpoint)	2020	No
h	No AC (no setpoint)	2050	No
i	No AC (no setpoint)	2050	Yes

¹Full AC: Operationalized with a thermostat setting of 23.9 °C, following the minimum ASHRAE recommended temperature and the MA 2050 Building Decarbonization Report as the recommended cooling setpoint [14]

²Some AC: Operationalized with a thermostat setting of 26.7 °C, the maximum recommended indoor temperature according ASHRAE [25]

³No AC: Operationalized without temperature control/setpoint for air conditioning

Model Scenarios

An overview of all model scenarios is provided in Table 1. We evaluated the impacts along four different axes of interest: weather from 2020 to 2050 without changing AC utilization, achieving cooler indoor temperatures with changes in AC utilization, energy efficiency retrofits, and the combination of cooler temperatures with energy efficiency retrofits.

In models to assess the impact of future weather conditions compared to current weather conditions, we evaluated households that maintained their same AC utilization patterns and absorbed increased cooling costs or higher temperature exposures in the absence of AC (Table 2, first section).

Table 2.

Model scenario comparisons with calculation steps

Description	Outputs calculated from Table 1 model scenarios1
Impact of weather changes between 2020 and 2050
Maintaining full AC in 2050 vs. full AC in 2020	µ(Run b) − µ(Run a)2
Maintaining some AC in 2050 vs. some AC in 2020	µ(Run e) − µ(Run d)
Remaining without AC in 2050 vs. 2020	µ(Run h) − µ(Run g)
Impact of cooler indoor temperatures in 2050—gaining access to AC
Full AC vs. no AC	µ(Run b) − µ(Run h)
Some AC vs. no AC	µ(Run e) − µ(Run h)
Full AC vs. some AC	µ(Run b) − µ(Run e)
Impacts of energy efficiency retrofits in 2050
Remaining at full AC	µ(Run c) − µ(Run b)
Remaining at some AC	µ(Run f) − µ(Run e)
Remaining at no AC	µ(Run i) − µ(Run h)
Gaining access to full AC vs. some AC	µ(Run c) − µ(Run e)
Remaining without AC access vs. non-retrofitted building in 2020	µ(Run i) − µ(Run g)
Combined impacts of cooler indoor temperatures and retrofits in 2050
Maintaining full AC with retrofit vs. no AC or retrofit	µ(Run c) − µ(Run g)
Maintaining some AC with retrofit vs. no AC or retrofit	µ(Run c) − µ(Run f)

¹Calculations include differences between mean summertime indoor temperatures, energy (natural gas for heating and electricity for cooling), and net total utility costs for both heating and cooling

²Averages across all model simulation scenarios were taken with the designation µ = mean

Subsidies for AC and energy efficiency housing retrofits were the two stylized policies modeled under current and future weather conditions. Subsidies for AC were operationalized by shifting households to a higher level of AC use, effectively improving the ability to cool the household (Table 2, second section).

Energy efficiency housing retrofits were modeled by changing specific building envelope parameters impacting energy consumption, based on the state of MA’s proposed goals, and current non-retrofitted building characteristics were based on the IECC standards for existing pre-1980 buildings to represent older housing in Boston, MA [21] (Supplemental Table I). We assumed that these buildings have not received any energy retrofits to date and were heated using natural gas. Electrification of the heating system was out of scope for this analysis, and, given the known pace of switching sources [22], we anticipated many buildings to still require a gas-based fuel source.

For the energy efficiency retrofitted homes, we considered remaining in the same AC group, gaining access to more cooling, and remaining without AC (Table 2, third section). This final scenario aims to capture a lower-income subset of the population that may live in a retrofitted building but still be cost-constrained in paying for utilities.

The combination of cooling subsidies and retrofits was modeled by shifting households to higher levels of AC use, plus receiving a home energy efficiency retrofit through changes in building parameters as described above (Table 2, fourth section).

Data Analysis

Model outputs included one year of hourly energy consumption (electricity for cooling and natural gas for heating), hourly utility cost to residents, and hourly indoor summer temperatures in each apartment. Energy consumption totals were continuously tracked in EnergyPlus and were aggregated (mean and standard deviation) for the cooling (June, July, and August) and heating (November, December, January, February, and March) seasons, respectively. We calculated the total electricity used for cooling in thousand kWh and total natural gas used for heating in million BTU. Utility costs in 2020 were calculated from the EIA in Massachusetts at 23.32 cents/kWh electricity for residences and $17.42 per thousand cubic feet natural gas for residences [23]. To estimate 2050 costs, we utilized the EIA Annual Energy Outlook 2022 data to estimate percent changes in residential utility costs for electricity and natural gas, respectively [24].

Summertime indoor temperature means and standard deviations were calculated for each apartment in the months of June, July, and August and averaged across all 32 apartments and by AC group status. To compare current and future scenarios, we calculated the absolute differences between two scenarios based on weather conditions year (current and future), home status (non-retrofitted or retrofitted), and AC utilization group (“no AC,” “some AC,” or “full AC”) as shown in Tables 1 and 2. All results are presented as means and standard deviations based on the outputs from each of the ten simulation runs during each weather file timeframe (2020 or 2050). Percent differences were calculated using the method of new value subtracted from the original value and divided by the original value × 100%.

Results

Our models quantified the impacts of future weather on energy consumption, net utility cost, and summertime indoor temperatures across weather, policy, and AC utilization scenarios. There was a 34% increase in electricity use for cooling for the “full AC” group and a 50% increase for the “some AC” group in 2050 compared to 2020, with a 35% decrease in natural gas for heating. Summertime average indoor temperature across 32 apartments increased by 2.1 °C between 2020 and 2050 for the no AC group (30.1 to 32.2 °C), while air-conditioned units were able to adequately cool to modeled set points for the “some AC” and “full AC” groups. Our models also quantified the impacts of future weather on ambient temperatures and heating and cooling degree days (Supplemental Table III).

Impact of Weather Changes on Indoor Temperature, Energy Use, and Costs with no Changes in AC Utilization

Even though summertime cooling costs increased from 2020 to 2050 (Fig. 2a, points a to b and points d to e), total utility costs per year decreased, due to the reduction in wintertime heating demand and projected changes in electricity and natural gas costs in 2050 (Fig. 2b, points a to b, d to e, and g to h). Average total utility costs per year decreased for heating and cooling seasons per apartment unit for all AC utilization groups (Table 3, first section).

Fig. 2.

a Cooling costs (mean and SD) across AC utilization groups per apartment in 2020 and 2050 in US dollars and b yearly utility costs (mean and SD) for heating and cooling per apartment across AC utilization groups in 2020 and 2050 in US dollars, and point labels are given in Table 1

Table 3.

Impacts of changes in weather, AC utilization groups, and housing retrofits on indoor temperatures and total utility costs per apartment

ΔAC Group	ΔIndoor temperature (°C)	ΔTotal utility cost ($)	ΔTotal utility cost (%)1
Weather changes from 2020 to 2050
Full AC → Full ACb−a	0	− 26	− 11
Some AC → Some ACe−d	0	− 21	− 10
No AC → No ACh−g	+ 2.1	− 38	− 30
Achieving cooler indoor temperatures in 2050
No AC → Full ACb−h	− 6.1	+ 132	+ 150
No AC → Some ACe−h	− 3.5	+ 94	+ 107
Some AC → Full ACb−e	− 2.6	+ 38	+ 21
Energy efficiency housing retrofits in 2050
Full AC → Full ACc−b	0	− 56	− 25
Some AC → Some ACf−e	0	− 54	− 30
No AC → No ACi−h	+ 0.41	− 42	− 48
Some AC → Full ACc−e	− 2.7	− 18	− 10
No AC (2020) → No AC (2050)2,i−g	+ 2.5	− 80	− 63
Combined impacts of cooler indoor temperatures & housing retrofits from 2020 to 20503
No AC → Full AC4,b−g	− 6.1	+ 94	+ 75
No AC → Full AC w/ retrofitc−g	− 6.2	+ 38	+ 30
No AC → Some AC4,e−g	− 3.5	+ 56	+ 45
No AC → Some AC w/ retrofitf−g	− 3.5	+ 2	+ 1.6

^a−iLabels for model runs from Tables 1 and 2

¹Δ Total utility cost calculated as (original value-new value)/original value × 100%

²Comparison between the non-retrofitted home in 2020 and the retrofitted home in 2050 to represent residents who may not be able to afford or able to use AC even with a retrofit

³Comparisons are between a non-retrofitted home in 2020 and both a non-retrofitted home and a retrofitted home in 2050 as indicated by the change in AC group description

⁴Additional comparison shown for non-retrofitted homes to show side-by-side comparison for savings with retrofits

Energy Costs of Achieving Cooler Indoor Temperatures in 2050

We quantified utility costs for cooling for residents to achieve cooler indoor temperatures under 2050 conditions in the non-retrofitted building (Supplemental Table IV). Greater cooling demand increased annual costs but decreased indoor temperatures by 2.6 to 6.1 °C on average for the whole building during the summertime, with households able to maintain the more comfortable temperatures of 23.9 °C or 26.7 °C (Table 3, second section).

Energy Use Savings Due to Housing Retrofits in 2050

In model scenarios with energy efficiency retrofits, natural gas for heating use decreased by 48% for a retrofitted home in 2050 relative to a non-retrofitted home. There were also reductions in cooling electricity consumption of 75 kWh per apartment (“some AC” → “some AC”) and 63 kWh per apartment (“full AC” → “full AC”) compared to non-retrofitted homes in 2050, corresponding to decreases of 15% and 9.1%, respectively.

For the “no AC” group, average summertime indoor temperatures increased by 0.41 °C with a retrofit compared to a non-retrofitted home in 2050 weather (Table 3, second section), while the “full AC” and “some AC” households maintained the same indoor temperature as in the non-retrofitted home in 2050 with smaller standard deviations in indoor temperatures (Supplemental Table IV).

Additionally, compared to non-retrofitted homes in 2020, summertime indoor temperatures increased by 2.5 °C with energy retrofits in homes without AC in 2050, while total utility cost per year decreased (Table 3, third section), representing households that may still be cost-constrained even after experiencing a housing retrofit. Total net utility cost (heating + cooling) per year decreased relative to non-retrofitted buildings for all households with no change in AC utilization, and, for households moving from “some AC” (non-retrofitted) to “full AC” (retrofitted), net utility costs still decreased (Table 3, third section).

Combined Impacts of Cooler Indoor Temperatures and Retrofits in 2050

Compared to the non-retrofitted building in the baseline year 2020 with “no AC,” moving to either “some AC” or “full AC” in 2050 led to increases in net total utility costs for the non-retrofitted building but were much lower for the retrofitted building (Table 3, fourth section). Retrofits led to utility cost savings of $54 (“no AC” → “some AC”) and $56 (“no AC” → “full AC”) compared to homes that were not retrofitted. Increased access to air conditioning corresponded with decreases in summertime indoor temperature averages of 3.5 °C (“no AC” → “some AC”) and 6.2 °C (“no AC” → “full AC”) for non-retrofitted homes in 2020 compared to retrofitted homes in 2050.

Discussion

Our findings indicate that rising ambient temperatures will have a substantial influence on residential energy consumption patterns, utility costs, and indoor temperatures, with patterns varying by household type and impacted by multiple hypothetical policies. While heating demand decreased due to warmer temperatures year-round and net total utility costs decreased, cooling demand for electricity increased by 33–49% for groups with AC utilization in future weather compared to current weather. For those who could not afford or lacked access to AC, they would experience an increase of average indoor temperature of 2.1 °C compared to current weather conditions.

Candidate policy measures lead to some shifts in both costs and indoor temperatures, though often with tradeoffs between the two. For example, cooling subsidies allowed residents to move to cooler thermostat settings with expected increases in cooling demand and associated costs. Retrofits provide a way to reduce heating demand significantly and cooling demand slightly for the already cooler homes but lead to even greater indoor temperature increases in the “no AC” group. In the cases where cooling subsidies are sufficient to allow for AC utilization among those previously without it, net utility costs increased, though retrofits yielded substantial savings at the household level. Predicted increases in natural gas prices coupled with decreases in electricity prices led to more anticipated savings given the decreased heating and increased cooling demand for homes in 2050.

Exposure to high indoor temperatures contributes to adverse health effects for susceptible populations, such as the elderly who have more difficulty regulating their body temperature and for groups that remain vulnerable to heat from factors like old housing and individual variation in AC use [2]. Our model results reinforce that, in the absence of AC use, indoor temperatures would routinely exceed ASHRAE recommendations of 75–80.5 °F (24–27 °C) [25] and leave occupants vulnerable to ambient temperature increases. This is consistent with other studies, which found residential indoor temperature values of 34.8 °C (maximum) in Detroit, MI, in 2009 [10], and a heat index (combination of temperature and relative humidity) in the range of 25–30 °C across three public housing sites in Elizabeth, NJ, in 2017 [26]. Quantifying indoor exposure to high temperatures is essential for vulnerable populations, especially those in public and affordable housing, as shown in New York City where less than half of public housing units have AC, despite 90% of the entire city population with AC access [27].

While it has been shown that AC reduces the risk of heat-related mortality [2], residents do not always use this method to cool. Along with the economic drivers, residents have reported disliking the physical feel of AC, wanting to conserve energy, and fears of crime especially with window units [28]. Our study did not specify the reasons underlying the “no AC” group, but implicit in our model framework is the assumption that a subsidy would increase utilization, which may not be correct for all populations.

Regardless of the policy mechanism, strategies to provide in-place cooling for those who lack access and mobility to travel to cooling shelters should be pursued given the warming climate. Programs such as the Low Income Home Energy Assistance Program (LIHEAP) have been used successfully to subsidize heating [29], and our analyses reinforce that higher ambient temperatures will reduce heating demand in places like Massachusetts. LIHEAP may constitute a funding source for utility subsidy reallocation as cooling demand increases without sacrificing the assistance that many populations require for thermal comfort year-round [29]. Local community organization groups such as WEACT for Environmental Justice in New York City are advocating for amendments to state policies to expand LIHEAP to increase AC access and to reduce energy burdens for vulnerable populations [30]. In Chelsea, MA, recent funding for residents to provide utility assistance and a lottery for air conditioning units helped to meet short-term demand for cooling during the hot summer months, but does not address the long-term policies needed for equitable access to AC [31]. Cooling access disparities will continue to worsen under the effects of climate change, aging building stock, and increasing energy insecurity for lower-income households without intentional policy interventions to reach these populations.

Limitations and Opportunities for Future Work

Our analysis is highly stylized and models a single type of multi-family home with various assumptions around thermostat settings, building envelope and ventilation upgrades, and utility costs. As such, our findings cannot provide conclusive insights about the efficacy of specific subsidy models, how energy consumption patterns would change with different cost structures, or the cost-effectiveness of residential energy retrofits. Relatedly, energy and temperature simulation models are clearly uncertain especially given limitations in including dynamic population behavior. That said, we used well-validated models, and our findings are intended to illustrate analytical approaches that could be applied in specific settings in the future, and the simulation modeling platform allowed us to examine multiple hypothetical changes that could not be empirically observed.

Our future weather estimates were based on a single global climate model and scenario from an earlier IPCC report, which contributes uncertainty to our projections. However, our estimated cooling and heating degree days were comparable to those in an analysis that looked at cooling and heating degree days in the USA historically and at end-of-century future (2080–2099), [20], indicating that the trends in our analysis were reasonable.

In addition, this work focused primarily on the interplay between indoor temperature exposure, energy consumption, and utility costs for residents. However, energy efficiency retrofits may also influence the indoor environment as shown in studies where weatherization increased the contribution of indoor sources but reduced infiltration of ambient-sourced pollutants [32]. Some of the adverse effects can be addressed through ventilation improvements and using filters for particulates (i.e., PM_2.5). To illustrate the benefits of coordinated interventions, we ran simulations adding MERV-12 filters to the HVAC systems in our retrofitted house (full results not shown) and found average reductions of 70% (from 36 to 11 µg/m³) due to both the filters and increased ventilation within the home as part of the retrofit, reinforcing the importance of implementing retrofits with multiple endpoints in mind.

Finally, our modeling did not address novel technologies and additional cooling strategies that would be part of the decarbonization and climate mitigation strategies for homes; rather we showed that retrofits designed for heating-dominated climates tend to hold heat in. We primarily incorporated heating-focused strategies such as building envelope upgrades and improved insulation [14], which led to an increase in summertime temperature for the “no AC” group with warmer future temperatures. Effective strategies should incorporate multiple endpoints and consider the heating and cooling demands. Electric heat pumps provide multiple benefits including providing cooling access for residents while transitioning off fossil fuel-based energy sources. Additional ways to improve the cooling capabilities of buildings have been proposed, including outdoor shutters [33], air-based radiative cooling systems with a thermal storage wall [34], and tree shading and increased tree canopy [35].

Conclusion

We modeled a series of stylized multi-family residences with different populations based on household income and evaluated the impacts of future weather conditions driven by ambient temperatures, cooling subsidies to keep residents at a comfortable temperature, and energy efficiency upgrades. Our findings reinforced the importance of centering the residential experience by modeling varying degrees of AC utilization, which is often left out of energy and building modeling studies. We additionally demonstrated the tradeoffs between cooling and heating energy demand, which will depend substantially on future energy costs, and which reinforce the importance of cooling subsidies for lower-income populations. The dual implementation of subsidies and retrofits can provide thermal comfort to the most vulnerable residents in the USA as rising temperatures continue to drive cooling demand. With an equitable and holistic focus on multiple building endpoints, indoor environmental quality and human health can also be improved as well as creating more resilience to climate change in our building stock.

Supplementary Information

Below is the link to the electronic supplementary material.

Abbreviations

AC

Air conditioning

ASHRAE

American Society for Heating, Refrigeration, and Air-Conditioning Engineers

BTU

British thermal units

EIA

Energy Information Administration

GHG

Greenhouse gas

HVAC

Heating, ventilation, and air conditioning

IECC

International Energy Conservation Code

IPCC

Intergovernmental Panel on Climate Change

kWh

Kilowatt hours

LIHEAP

Low-Income Home Energy Assistance Program

MA

Massachusetts

MERV

Minimum efficiency reporting value

NREL

National Renewable Energy Laboratory

NSRDB

National Solar Radiation Database

PM_2.5

Particulate matter of aerodynamic diameter less than 2.5 microns

SD

Standard deviation

SRES

Special Report on Emissions Scenarios

Author Contribution

Conceptualization: C L. C, J A, M. P F, J I. L, C W. M; data curation: C L. C; formal analysis: C L. C; funding acquisition: M. P F; methodology: C L. C, C W. M, K V, J A, L C, J I. L, M. P F; resources: M. P F; software: C L. C, C W. M, L C; supervision: J A, L C, J I. L, M. P F; visualization: C L. C, C W. M; roles/writing—original draft: C L. C; writing—review and editing: C L. C, C W. M, K V, J A, L C, J I. L, M. P F.

Data Availability

Data used in model generation are included in this article. Full model results are available upon request. All aggregated results are included in this manuscript and supplemental data.