1. A parameter value estimator for a process primarily performed to control emission of a particular non-particulate pollutant into the air, the process having multiple process parameters (MPPs) including a parameter representing an amount of the particular non-particulate pollutant emitted, comprising: one of a neural network process model and a non-neural network process model representing a relationship between one of the MPPs, other than the parameter representing the amount of the emitted particular non-particulate pollutant, and one or more of the other MPPs; and a processor configured with the logic to estimate a value of the one MPP based on a value of each of the one or more other MPPs and the one model; wherein the one MPP is either (i) a pH level of matter applied in the process to absorb the particular nonparticulate pollutant and thereby control its emission into the air, (ii) a purity of a by-product produced in performing the process, (iii) an amount of oxygen dissolved in matter applied in the process to absorb the particular non-particulate pollutant and thereby control its emission into the air, (iv) an amount of ammonia applied in the process to absorb the particular non-particulate pollutant that is emitted into the air with the particular non-particulate pollutant that is not absorbed, or (v) an amount of applied ammonia in exhausted reduced NO x flue gas, the particular non-particulate pollutant being NO x , and the one or more other MPPs include an amount of the applied ammonia.