Exploration of low-carbon approximate probability design method for concrete structures

With the world increasing concerns about climate change and environmental protection, reducing carbon emissions has become a crucial issue for various industries. With industrial development and rapid urbanization leading to a surge in energy demand, Chinas building-related carbon emissions have escalated in recent years. By 2020, the carbon emissions from construction industry accounted for a significant 50.9% of the total emissions nationwide. Concrete structures account for more than 60% of the total building stock in China, calling for the adoption of low-carbon design methods in concrete structures. Drawing upon the safety design process, this paper introduces a practical low-carbon probabilistic design approach. This method aims to facilitate engineering decision-making that meets the carbon reduction targets quantitatively, thus fostering sustainable development within the construction industry. By exploring the randomness inherent in carbon emissions, a low-carbon limit state equation was developed. To assess the level of concrete structures to meet carbon reduction targets, the concept of low-carbon index was introduced. This paper also distinguished between permanent carbon and variable carbon based on their sources. The former includes carbon emission from structural materials at the materialization stage and the end-of-life stage, while the latter encompasses operational carbon and embodied carbon from decorative materials and maintenance materials. Within these boundaries, two distinct low-carbon design paradigms were clarified: One focusing on structural embodied carbon and the other addressing whole life carbon in buildings. Considering the uncertainty of carbon emissions, the partial factor was introduced to simplify the probabilistic design into approximate probability design criteria. The carbon limits of concrete structures were deduced by a case study. Using Monte Carlo simulations, Chinas future building stock was predicted based on probabilistic predictions of population, urbanization rate, and uncertainty quantification of per capita floor area. Furthermore, based on the total carbon limit of the construction industry, the uncertainty result of the annual average carbon limit per unit area was obtained, i.e., 49.7 kg CO(2)e m(-2) a(-1) in the year of 2025 as an example. Based on the yearly accumulation of the annual average limit values, take the newly built concrete structure in 2025 with a design life of 50 years as an example, the whole life carbon limit was 928.14 +/- 18.98 kg CO(2)e/m(2). Based on the hypothesis of normal distribution, the influence of the proportion of permanent carbon, variable carbon and building type on the partial factor was explored. Under a certain low-carbon failure probability target, the partial factors were directly related to the magnitude of the variability and proportion of permanent carbon and variable carbon. Within the error range of 10(-1), different building types of concrete structures were able to adopt unified partial factors. When the low-carbon failure probability target was set at 0.05, the permanent carbon and variable carbon partial factors could be set as 1.1 and 1.8, respectively. Three kinds of influence coefficients were introduced to modify the carbon emission partial factor design expression. To specify the building type influence coefficient, it is necessary to clarify the actual probability model of permanent carbon and variable carbon. It was suggested to establish emission inventory and utilize multi-source carbon emission factor regression to fit discrete data, thereby developing a random variable or random process model. Further, it was recommended to explore the change of carbon limits under different regulation scenarios and regional disparities based on the typical carbon neutrality scenarios and comprehensive consideration of the economic development and technical level of various regions.