A mechanism–system diagnosis–optimization framework for quantifying carbon–pollutant synergies and trade-offs in iron ore sintering

Source-side coordinated control of carbon emissions and air pollutants is essential for the green transition of iron ore sintering, but remains challenging because carbon reduction, combustion efficiency, and pollutant mitigation are strongly coupled within the sintering bed. This study develops a Mechanism–System diagnosis–Optimization (M–S–O) framework that integrates a transient porous-bed reactor model, carbon–pollutant diagnosis, and feasible-domain Pareto screening, and applies it to validation and optimization analysis based on data from a 362 m2 industrial sintering machine. Sensitivity analysis shows that CO2 and CO are mainly governed by coke-related carbon supply, SO2 by sulfur input, and NOx by both fuel-N availability and residence-related transport conditions after the NO–CO reduction pathway is considered. Four-objective Pareto analysis reveals that deep CO2 reduction may intensify incomplete combustion: in the low-CO2 region of 120–140 kg/t, CO exceeds 20.0 kg/t and NOx exceeds 1.6 kg/t. A representative TEC scenario increases effective product mass by 10.3%, reduces specific fan work by 26.0%, and decreases SO2 and NOx by 24.4% and 11.7%, respectively. These results indicate that coordinated sintering control should shift from simple carbon-input restriction toward reactor-level optimization of heat utilization, residence time, and aerodynamic load.