Abstract
Side reactions are undesirable in most industrial processes, as they decrease process yield and selectivity. For this reason, mononitrobenzene’s manufacturers set nitrophenols minimization as a critical goal, along with the MNB production targets. The mechanism of these side reactions in benzene nitration is still under debate and, so far, none of the alternatives has achieved general consensus in the scientific community. As an alternative, industrial data may provide valuable information on the contribution of inlet process variables and operating conditions upon the formation of nitrophenolic compounds in the adiabatic nitration process. In this work, Partial Least Squares regression was applied to data collected from a mononitrobenzene industrial production plant. This methodology allowed concluding that nitration temperature and mixed acid volumetric flow rate as the most influential variables in nitrophenols formation. The models developed enable proper estimates of DNP and TNP concentrations in the industrial process, although their explanation power is lower than those previously obtained by Quadros et al. (2005), in a pilot plant, and by Portugal et al. (2009) in their extended models.
