Carbon footprint dataset of concrete based on field surveys at commercial mixing plants in Shandong, China.

Carbon dioxide (CO2) emissions from concrete have grown rapidly, ranking second after the power sector. Current emission factors often overlook regional heterogeneity. To bridge this knowledge gap, this study takes Shandong Province, a typical region in China, as a case study. Considering the difference in geography, history, culture, and economic development, Shandong is divided into five subregions: Eastern, Western, Southern, Northern, and Central Shandong. This study developed a fundamental carbon footprint dataset of concrete by collecting 993 mix proportions of strength grades (C25-C60) from field surveys over the past five years. Statistical analysis showed that raw material dosages followed normal distributions (Kolmogorov-Smirnovtest, p > 0.05), while transportation distances and electricity consumption followed lognormal distributions. Based on statistical characteristics, a Monte Carlo simulation with 10,000 iterations was conducted to establish a stochastic model for carbon emissions accounting. Model performance was validated against survey data, achieving a mean absolute percentage error (MAPE) of 1.89% and a coefficient of determination (R²) of 0.9904. Sensitivity analysis identified cement dosage as the key driver of emissions.