Carbon emissions assessment of cement mixing piles for soft loess improvement and carbon emission reduction using white mud-cement composite material

Abstract

During the highway construction in the soft loess region of Northwestern China, there are always tens of thousands of cement mixing piles were used. Which generates a large amount of carbon emissions, thereby affecting the environment. The Simplified Energy and Emissions Assessment Model (SEEAM) is used to quantify carbon emissions considering monitoring data of IoT (Internet-of-Things) system. To reduce the error of the carbon emissions of large samples, Monte Carlo simulation was used to quantify carbon emissions based on the small samples. The results showed that cement had a 47,530.78 t carbon missions contributing the 95.64 % of the total carbon emissions. To concurrently ensure strength and reduce carbon emissions, this study investigates the unconfined compressive strength variations in white mud-cement composite material solidified soft loess. It indicated that 10 % and 20 % white mud provided an alkaline environment and nucleation sites for cement hydration reactions, combining the filling voids. According to the observation results of TG and SEM, the content of 10 % white mud increased the quantity of early hydration product CSH in cement. Which maintained a high level of strength by comparing the cement solidified soft loess. In addition, when the white mud content is 50 %, the white mud-cement composite material reduced 576 % carbon emissions in the cement mixing pile engineering. This study can provide guidance for the selection of engineering construction design schemes, as low-carbon emission schemes are conducive to green and sustainable development of the environment.

Keywords

• Carbon emissions
• Embodied Energy
• Uncertainty analysis
• Monte Carlo simulation
• White mud-cement