The use of temporal factors for improved CO2 emissions accounting in buildings

Abstract

This paper is an investigation into the issues around how we calculate CO2 emissions in the built environment. At present, in Building Regulations and GHG Protocol calculations used for buildings and corporate CO2 emissions calculations, it is standard to use a single number for the CO2 emission factor of each source. This paper considers how energy demand, particularly electricity at different times of the day, season and even year can differ in terms of its CO2 emissions. This paper models three different building types (retail, office and home) using standard software to estimate a profile of energy demand. It then considers how CO2 emissions calculations differ between using the single standard emissions factor and using an hourly emissions factor based on real electrical grid generation over a year. The paper also examines the impact of considering lifetime emissions factors rather than one-year factors using UK government projections. The results show that there is a significant difference to the analysis of benefit in terms of CO2 emissions from different measures – both intra- and inter-year – due to the varying CO2 emissions intensity, even when they deliver the same amount of net energy saving. Other factors not considered in this paper, such as impact on peak generation and air quality, are likely to be important when considering whole-system impacts. In line with this, it is recommended that moves are made to incorporate intra- and inter-year emissions factor changes in methodologies for calculating CO2 emissions. (This is particularly important as demand side response and energy storage, although generally accepted as important in the decarbonisation of the energy system at present will show as an increase in CO2 emissions when using a single number.) Further work quantifying the impact on air quality and peak generation capacity should also be considered. Practical application: This paper aims to help practitioners to understand the performance gap between how systems need to be designed in order to meet regulations compared to how buildings perform in reality – both today and in the future. In particular, it considers the use of ‘real-time’ carbon factors in order to attain long-term CO2 reductions. This methodology enables decision makers to understand the impacts of different energy reduction technologies, considering each of their unique characteristics and usage profiles. If implemented, the result is a simple-to-use dataset which can be embedded into the software packages already available onto the market which mirrors the complexity of the electricity grid that is under-represented through the use of a static carbon figure.