More than 100 countries worldwide have pledged carbon neutrality by 2050 to reduce the negative environmental impacts of carbon emissions. To reach this goal, every part of the industry must prepare to transform and take precautions. Heat exchangers are one of the most common parts of industrial production. The industrial operation of heat exchangers still offers lots of opportunities to minimize their carbon footprints. This goal can be achieved by their optimized operation. This work investigates the operation of a laboratory plate heat exchanger controlled by a proportional-integral-derivative (PID) controller and by an optimization-based model predictive controller (MPC). The analysis is performed using both, the simulations, and the laboratory experiments. The carbon footprint and energy consumption of the heat exchanger are analysed and compared. The paper investigates whether the optimization-based approach subject to the constraints on manipulated variables and controlled variables, considering economic criteria, simultaneously, reduces the carbon footprint of a laboratory heat exchanger control.