Abstract: Methanol has emerged as one of the most promising carbon-neutral renewable fuels for internal combustion engines, offering a viable pathway to reduce greenhouse gas emissions and meet increasingly stringent emission standards. Developing advanced combustion strategies for compression-ignition engines has become imperative in alignment with global carbon neutrality initiatives. Methanol-diesel dual-fuel engines operating under reactivity-controlled compression ignition (RCCI) mode represent a groundbreaking solution, enabling ultra-low emissions without compromising thermal efficiency. To resolve the critical challenge of achieving emission-economy equilibrium in dual-fuel engines, a three-dimensional (3D) computational fluid dynamics (CFD) model of a methanol/diesel reactivity-controlled compression ignition (RCCI) engine was developed. The coupled effects of intake air temperature (IAT), intake pressure (IP), and methanol substitution ratio (MSR) on the combustion process and emission formation mechanisms were systematically investigated. A second-order regression model was developed using the Box-Behnken response surface methodology, with equivalent brake-specific fuel consumption (ESFC) and NOx, CO, and HC emissions as multi-objective functions for multi-parameter co-optimization. The results reveal that elevating IAT from 320 K to 360 K and increasing IP from 210 kPa to 230 kPa leads to increased peak cylinder pressure and indicated mean effective pressure (IMEP). Appropriate elevation of IAT and IP significantly reduces ESFC and HC emissions by enhancing combustion efficiency and mixture homogeneity. However, the increase in IAT leads to a simultaneous increase in NOx emissions and Soot concentration. Notably, the IAT exhibits a more pronounced regulatory effect on combustion phasing and heat release rate than the IP. Under constant intake pressure conditions, increasing MSR and IAT synergistically advance start of combustion and center of combustion, reducing ESFC while elevating peak cylinder pressure and IMEP. The simultaneous increase in IAT and MSR promotes a significant rise in NOx formation rate and emissions, while HC emissions gradually decline. Moreover, the synergistic control of MSR and IP effectively hinders Soot formation, revealing the coupled interaction mechanisms between operational parameters in emission control strategies. Dominant control over pollutant emissions is attributed to the coupled effects of IAT and MSR, whereas IP demonstrates a secondary influence. Nonlinear coupling interactions between MSR and intake parameters govern HC and NOx emission trends. Optimal NOx reduction is achieved via moderate IP combined with lower IAT. However, intermediate IAT coupled with elevated IP enhances Soot oxidation rates, decreasing Soot emissions. The second-order response surface models constructed via response surface methodology exhibit strong goodness-of-fit and predictive capability, with both R² and R²_adj values exceeding 0.98, while maintaining differences between R² and R²_pred below 0.2 across all models. In addition, under the optimal parameter set obtained through multi-objective optimization, the discrepancy between predicted values and simulation results remains below 4%. Response surface analysis reveals IAT and MSR as the dominant factors governing engine emissions, whereas IP exhibits relatively minor effects. Furthermore, the interactive effects between these parameters exhibit distinct nonlinear contributions to pollutant emissions. Under the optimal parameter combination of an intake temperature of 325.5 K, intake pressure of 230 kPa, and MSR of 34.5%, the ESFC reaches 204.04 g/(kW·h), with NOx, CO, and HC emissions reduced to 9.74, 8.58, and 10.98 g/(kW·h), respectively. Compared to the fuel-economy-optimal condition B9, this strategy achieves a 48.65% reduction in NOx emissions and a 10.95% decrease in CO emissions, while maintaining a marginal 3.09% increase in ESFC within constrained boundaries. These findings establish a theoretical foundation for multi-parameter synergistic optimization of control parameters in methanol/diesel RCCI engines to balance fuel economy and emission performance.