Uncertainty in operating parameters such as temperature undermines the reliability of using kinetic models in performance projections for plants operated under ambient non-isothermal conditions. This study develops a theoretical framework, which uses process kinetics, uncertainty quantification to define robust operating limits known as self-optimizing attainable regions, where by instead of defining a very large operating limit, which will be achieved some of the times for some of the reactor configurations, we define a self-optimizing limit, which will be achieved all the times for all possible reactor configurations (despite variations in temperature). Using a temperature range of 20 – 60∘C, , the results indicate that decreasing temperature uncertainty, increasing process temperature or using a multistage digester structure increases the self-optimizing operating limits: 1.53×10−4, 4.95×10−4 and 6.32×10−4(g/L)2 obtained for temperatures of 20.00, 31.60 and 52.40∘C respectively. The findings highly important in defining performance targets especially when there is uncertainty in environmental conditions.