A carbon sink calculation model for concrete buildings considering time-variant environment

Abstract

This study proposes an innovative computational framework to enhance the accuracy of carbon sink estimation for concrete buildings under time-variant environments (TVE), in addressing the limitations of conventional models that assume constant exposure conditions by integrating long-term trends and seasonal variations in temperature, relative humidity (RH), and atmospheric CO₂ concentration. A coupled kinetic model was developed, incorporating cement hydration dynamics, heat transfer, moisture transport, and carbonation reactions. Unlike traditional models, this model accounts for pore structure evolution during the hydration and carbonation, the varied environmental conditions, and the interactions between moisture and CO₂ during carbonation. Fixed RH assumption overestimates the carbon sink because it neglects the inhibitory effects of low/high RH fluctuations observed in real environments. A case study was conducted for carbonation sink analysis on an office building in Hangzhou, China, over a 50-year service life. Key findings reveal that the carbon sink rate initially rises rapidly, peaks in the 10th year, and gradually declines due to pore-blocking effects and consumption of carbonatable materials. Seasonal fluctuations in carbonation rates were predominantly driven by RH variations, while TVE modeling showed a 2.15 % higher carbon sink compared to constant-environment assumptions. Fixed CO₂ conditions underestimated carbonation, whereas fixed RH overestimated it, with temperature playing a minor role. The framework demonstrated superior accuracy over traditional empirical models, reducing overestimation by 6.9 % through mechanistic modeling of physicochemical interactions. This study highlights the necessity of incorporating TVE into carbon accounting systems and provides a robust tool for optimizing concrete structures' carbon sink potential, supporting decarbonization strategies in the construction sector.