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

) 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.