Residential energy efficiency interventions: A meta‐analysis of effectiveness studies

Background The residential sector releases around 17% of global greenhouse gas emissions and making residential buildings more energy efficient can help mitigate climate change. Engineering models are often used to predict the effects of residential energy efficiency interventions (REEI) on energy consumption, but empirical studies find that these models often over‐estimate the actual impact of REEI installation. Different empirical studies often estimate different impacts for the same REEI, possibly due to variations in implementation, climate and population. Funding for this systematic review was provided by the evaluation function at the European Investment Bank Group. Objectives The review aims to assess the effectiveness of installing REEIs on the following primary outcomes: energy consumption, energy affordability, CO2 emissions and air quality indices and pollution levels. Search Methods We searched CAB Abst, Econlit, Greenfile, Repec, Academic Search Complete, WB e‐lib, WoS (SCI and SSCI) and other 42 databases in November 2020. In addition, we searched for grey literature on websites, checked the reference lists of included studies and relevant reviews, used Google Scholar to identify studies citing included studies, and contacted the authors of studies for any ongoing and unpublished studies. We retrieved a total of 13,629 studies that we screened at title and abstract level, followed by full‐text screening and data extraction. Selection Criteria We included randomised control trials, and quasi‐experimental studies that evaluated the impact of installing REEIs anywhere in the world and with any comparison. Data Collection and Analysis Two independent reviewers screened studies for eligibility, extracted data and assessed risk of bias. When more than one included study examined the same installation of the same type of REEI for a similar outcome, we conducted a meta‐analysis. We also performed subgroup analyses. Main Results A total of 16 studies were eligible and included in the review: two studies evaluated the installation of efficient lighting, three studies the installation of attic/loft insulation, two studies the installation of efficient heat pumps, eight studies the installation of a bundle of energy efficiency measures (EEMs), and one study evaluated other EEMs. Two studies, neither appraised as having a low risk of bias, find that lighting interventions lead to a significant reduction in electricity energy consumption (Hedges' g = −0.29; 95% confidence interval [CI]: −0.48, −0.10). All the other interventions involved heating or cooling, and effects were synthesizised by warmer or colder climate and then across climates. Four studies examined the impact of attic/loft insulation on energy consumption, and two of these studies were appraised as having a low risk of bias. Three studies took place in colder climates with gas consumption as an outcome, and one study took place in a warmer climate, with the electricity consumption (air conditioning) as the outcome. The average impact across all climates was small (Hedges' g = 0.04; 95% CI: −0.09, 0.01) and statistically insignificant. However, two of the studies appear to have evaluated the effect of installing small amounts (less than 75 mm) of insulation. The other two studies, one of which was appraised as low risk of bias and the other involving air conditioning, found significant reductions in consumption. Two studies examined the impact of installing electric heat pumps. The average impact across studies was not statistically significant (Hedges' g = −0.11; 95% CI: −0.41, 0.20). However, there was substantial variation between the two studies. Replacing older pumps with more efficient versions significantly reduced electricity consumption in a colder climate (Hedges' g = −0.36; 95% CI, −0.57, −0.14) in a high risk of bias study. However, a low risk of bias study found a significant increase in electricity consumption from installing new heat pumps (Hedges' g = 0.09; 95% CI, 0.06, 0.12). Supplemental analyses in the latter study indicate that households also used the heat pumps for cooling and that the installed heat pumps most likely reduced overall energy consumption across all sources—that is, households used more electricity but less gas, wood and coal. Seven studies examined bundled REEIs where the households chose which EEMs to install (in five studies the installation occurred after an energy audit that recommended which EEMs to install). Overall, the studies estimated that installing an REEI bundle is associated with a significant reduction in energy consumption (Hedges' g = −0.36; 95% CI, −0.52, −0.19). In the two low risk of bias studies, conducted with mostly low‐income households, installed bundles reduced energy consumption by a statistically significant amount (Hedges' g = −0.16; 95% CI, −0.13, −0.18). Authors' Conclusions The 16 included studies indicate that installing REEIs can significantly reduce energy consumption. However, the same type of REEI installed in different studies caused different effects, indicating that effects are conditional on implementation and context. Exploring causes of this variation is usually not feasible because existing research often does not clearly report the features of installed interventions. Additional high quality impact evaluations should be commissioned in more diverse contexts (only one study was conducted in either Asia or Africa—both involved lighting interventions—and no studies were conducted in South America or Southern Europe).