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Research over the past decade has highlighted the climate impacts of natural gas leakage throughout the supply chain, from production to processing to transmission and distribution. Urban methane emissions from local distribution and end-users initially received less attention, yet they can be a significant emissions source in areas with aging infrastructure. This study provides the first empirical evidence on the impact of local gas leaks on nearby house prices. Using high-resolution geographical data in property transactions and a difference-in-differences method, we find that gas leaks significantly reduce nearby house prices by 2.61% ($11,700) on average in MA. Our estimation is robust to the different boundary definitions of the control group. More importantly, the estimated benefits of fixing gas leaks are larger than the average costs per repair reported by utilities in MA.

Methane leaks in natural gas systems are low-hanging fruit for near-term, locally driven climate policy. Recent work suggests this emissions source is larger than previously believed and that repairing a small number of high emitters can cost-effectively reduce system-wide leakage. How successful are these repairs on the ground? Here, we assess the effectiveness of repair policies in the Massachusetts distribution system. Our analysis leverages state-wide utility data, on-site empirical measurements, stakeholder interviews, and document and legal analysis. We use these mixed methods to investigate the rate of repair failure, where a gas utility identifies and fixes a leak, but on-site emissions are not eliminated. We find that repair failures are relatively common, yet they are repeatedly neglected in policy. By not accounting for repair failures, policy may overestimate the effectiveness of distribution system repairs in meeting local greenhouse gas reduction targets. These results also underscore the importance of data transparency for monitoring and verifying subnational climate policies.

Energy technologies emitting differing proportions of methane and carbon dioxide vary in their relative climate impacts over time, due to the different atmospheric lifetimes of the two gases. Standard technology comparisons using the global warming potential (GWP) emissions equivalency metric do not reveal these dynamic impacts, and may not provide the information needed to assess technologies and emissions mitigation opportunities in the context of broader climate policy goals. Here we formulate a portfolio optimization model that incorporates changes in technology impacts as a radiative forcing (RF) stabilization target is approached. An optimal portfolio, maximizing allowed energy consumption while meeting the RF target, is obtained by year-wise minimization of the marginal RF impact in an intended stabilization year. The optimal portfolio calls for using certain higher methane-emitting technologies prior to an optimal switching year, followed by methane-light technologies as the stabilization year approaches. The model is applied to transportation technology pairs and shows that, by accounting for the differing decay behavior of gases, optimal switching portfolios allow energy consumption gains of up to 50% compared to relying on the higher methane-emitting technology alone. The results allow for estimates of target timelines for mitigating methane emissions from energy technologies.