Abstract
Purpose
Increases in residential insulation can reduce energy consumption and corresponding life cycle emissions, but with increased manufacturing and transportation of insulation and the associated impacts. In this study, we conducted life cycle analyses of residential insulation and estimated payback periods for carbon dioxide (CO2), nitrogen oxides (NOx), and sulfur dioxide (SO2) emissions, using modeling techniques that account for regional variability in climate, fuel utilization, and marginal power plant emissions.
Methods
We simulated the increased production of insulation and energy savings if all single-family homes in the USA increased insulation levels to the 2012 International Energy Conservation Code, using an energy simulation model (EnergyPlus) applied to a representative set of home templates. We estimated hourly marginal changes in electricity production and emissions using the Avoided Emissions and Generation Tool (AVERT), and we estimated emissions related to direct residential combustion. We determined changes in upstream emissions for both insulation and energy using openLCA and ecoinvent. Payback periods were estimated by pollutant and region. In sensitivity analyses, we considered the importance of marginal versus average power plant emissions, transportation emissions, emission factors for fiberglass insulation, and sensitivity of emission factors to the magnitude of electricity reduction.
Results and discussion
Combining the life cycle emissions associated with both increased insulation manufacturing and decreased energy consumption, the payback period for increased residential insulation is 1.9 years for CO2 (regional range 1.4–2.9), 2.5 years for NOx (regional range 1.8–3.9), and 2.7 years for SO2 (regional range 1.9–4.8). For insulation, transportation emissions are limited in comparison with manufacturing emissions. Emission benefits displayed strong regional patterns consistent with relative demands for heating versus cooling and the dominant fuels used. Payback periods were generally longer using average instead of marginal emissions and were insensitive to the magnitude of electricity savings, which reflects the structure of the intermediate complexity electricity dispatch model.
Conclusions
The life cycle benefits of increased residential insulation greatly exceed the adverse impacts related to increased production across all regions, given insulation lifetimes of multiple decades. The strong regionality in benefits and the influence of a marginal modeling approach reinforce the importance of site-specific attributes and time-dynamic modeling within LCA.
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Acknowledgements
This research was supported by the North American Insulation Manufacturers Association (NAIMA). NAIMA suggested the research topic and was provided the opportunity to give comments on the manuscript, but the authors had full editorial control of the content and the findings should not be attributed to NAIMA or its member companies. The authors thank Yann Tambouret for his contribution to the energy simulation modeling.
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Levy, J.I., Woo, M.K., Duintjer Tebbens, R. et al. Emission payback periods for increased residential insulation using marginal electricity modeling: a life cycle approach. Int J Life Cycle Assess 23, 1723–1734 (2018). https://doi.org/10.1007/s11367-017-1412-x
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DOI: https://doi.org/10.1007/s11367-017-1412-x