[Objective] This study aims to optimize the coupling conditions for CO₂ reinforcement of recycled coarse aggregate (RCA) by investigating the interactions of three key factors—CO₂ concentration, carbonation temperature, and relative humidity—using response surface methodology (RSM). The innovation lies in using a systematic RSM-based approach to model and optimize the carbonation process, overcoming the limitations of traditional methods by capturing complex inter-factor interactions. This provides a more efficient and reliable framework for enhancing RCA performance in sustainable construction applications. [Methods] A Box-Behnken design using Design-Expert software was applied, encompassing 17 sets of carbonation tests to evaluate the effects of CO₂ concentration (20%-60%), carbonation temperature (20-60℃), and relative humidity (35%-65%). RCA was derived from waste concrete blocks in Baotou, China, and characterized in accordance with GB/T 25177-2010, with particle sizes between 4.75 and 31.5 mm. The measured responses included crush value (indicator of mechanical strength), water absorption (indicator of porosity), and apparent density (indicator of compactness). Carbonation experiments were performed in a controlled environment, and the obtained data were utilized to develop quadratic regression models using RSM. Analysis of variance (ANOVA) was conducted to assess the significance, reliability, and interactions of the models, using evaluation criteria including F-statistic, p-value, coefficient of determination (R²), adjusted R², predicted R², coefficient of variation (C_V), and signal-to-noise ratio (Adeq Precision). Optimization was performed using the numerical module of Design-Expert to determine the optimal carbonation conditions, which were validated experimentally to confirm model accuracy. [Results] The interaction between carbonation temperature and relative humidity had the strongest effect (p>0.05 for BC interaction), followed by the CO₂ concentration-temperature (AB) and CO₂ concentration-relative humidity (AC) interactions. The CO₂ concentration-temperature (AB) interaction was the most significant, resulting in a parabolic response. Water absorption initially decreased with increasing CO₂ concentration and temperature, but increased under extreme conditions due to reduced CO₂ diffusion and calcium ion dissolution. The CO₂ concentration-relative humidity (AC) interaction was the most significant, making apparent density peak under moderate conditions (e.g., 42% CO₂ concentration and 44 ℃) and decline at extremes due to moisture-induced calcium loss or CO₂ saturation. The optimization process determined the optimal carbonation conditions as 38% CO₂ concentration, 41 ℃ carbonation temperature, and 49% relative humidity. Under these conditions, the predicted values were 14.3% for crush value, 3.80% for water absorption, and 2 700 kg/m³ for apparent density. Experimental validation produced measured values of 14.6% (crush value), 3.85% (water absorption), and 2 702 kg/m³ (apparent density), with relative errors of 2.1%, 1.3%, and 0.1%, respectively. All relative errors were below 5%, confirming model accuracy. Compared with untreated RCA, the optimized carbonation treatment reduced crush value by 18.0%, decreased water absorption by 20.5%, and increased apparent density by 0.9%, demonstrating practical effectiveness. Response surface diagrams and contour plots illustrated these interactions. For example, the temperature-relative humidity interaction for crush value showed a steep elliptical contour, while the CO₂ concentration-relative humidity interaction for apparent density presented a flat parabolic surface. These results highlighted the innovation of applying RSM to decipher complex multi-factor couplings, which previous studies did not fully address. [Conclusion] This study successfully develops and validates RSM-based regression models for optimizing the CO₂ reinforcement of RCA, with high reliability and precision confirmed by statistical indicators and experimental validation. The optimal conditions effectively improve RCA properties and provide a sustainable solution for waste concrete recycling and carbon emission reduction. The developed model offers a reliable reference for industrial applications, facilitating the adoption of CO₂ -modified RCA in concrete production. Future research can apply this approach to other aggregate types or larger-scale scenarios, further advancing a circular economy in the construction industry.