Chemical engineering framework for decarbonization and process improvement in an industrial formalin plant

This study presents a comprehensive process-level approach to mitigate carbon dioxide emissions in an existing industrial formaldehyde production plant (200 kt/year capacity) through silver-catalyzed methanol oxidation. A validated ChemCAD simulation model, parameterized using real industrial data from four silver catalyst operation cycles, integrates multi-objective optimization with comprehensive uncertainty analysis. Monte Carlo simulation (n = 100,000) and Root Sum Square methods confirm measurement system reliability with relative uncertainty below 0.4%, providing robust foundation for optimization strategies. Analysis of four catalyst cycles refines the literature-reported optimal catalyst temperature range of 923–953 K to a precise value of 899.1 K, achieving simultaneous minimization of CO2 emissions and maximization of formaldehyde selectivity through the Derringer-Suich desirability function method. Implementation of optimal operating conditions results in 3423 t/year CO₂ emission reduction while maintaining identical production capacity. Temperature sensitivity analysis reveals a robust 13 K operational window (890–903 K), demonstrating practical industrial applicability despite inherent process control limitations. The optimization methodology integrates Fishburn's additive utility theory with Simple Additive Weighting techniques, validated through multiple decision-making frameworks. Results demonstrate that prevention-based emission reduction strategies provide immediate return on investment with zero capital expenditure compared to end-of-pipe treatment solutions requiring substantial upfront investment, with the 24–54 K temperature reduction compared to literature values enabling significant energy efficiency improvements alongside emission reductions.