The present investigation intends to add to the fundamental process design know-how for dry flue gas cleaning, especially with respect to process flexibility, in cases where variations in the type of fuel and thus in concentration of contaminants in the flue gas require optimization of operating conditions. In particular, temperature effects of the physical and chemical processes occurring simultaneously in the gas-particle dispersion and in the filter cake/filter medium are investigated in order to improve the predictive capabilities for identifying optimum operating conditions. Sodium bicarbonate (NaHCO(sub 3)) and calcium hydroxide (Ca(OH)(sub 2)) are known as efficient sorbents for neutralizing acid flue gas components such as HCl, HF, and SO(sub 2). According to their physical properties (e.g. porosity, pore size) and chemical behavior (e.g. thermal decomposition, reactivity for gas-solid reactions), optimum conditions for their application vary widely. The results presented concentrate on the development of quantitative data for filtration stability and overall removal efficiency as affected by operating temperature. Experiments were performed in a small pilot unit with a ceramic filter disk of the type Dia-Schumalith 10-20 (Fig. 1, described in more detail in Hemmer 2002 and Hemmer et al. 1999), using model flue gases containing SO(sub 2) and HCl, flyash from wood bark combustion, and NaHCO(sub 3) as well as Ca(OH)(sub 2) as sorbent material (particle size d(sub 50)/d(sub 84) : 35/192 (micro)m, and 3.5/16, respectively). The pilot unit consists of an entrained flow reactor (gas duct) representing the raw gas volume of a filter house and the filter disk with a filter cake, operating continuously, simulating filter cake build-up and cleaning of the filter medium by jet pulse. Temperatures varied from 200 to 600 C, sorbent stoichiometric ratios from zero to 2, inlet concentrations were on the order of 500 to 700 mg/m(sup 3), water vapor contents ranged from zero to 20 vol%. The experimental program with NaHCO(sub 3) is listed in Table 1. In addition, model calculations were carried out based on own and published experimental results that estimate residence time and temperature effects on removal efficiencies