Purpose -The purpose of this paper is to investigate the effect of fatigue life reduction of 2024 Al alloy for aerospace components due to the corrosive (exfoliation) environment. Both standard fatigue tests on prior corroded samples and fatigue tests conducted with the samples in corrosive solution are developed to define some guidelines for the inclusion of such effect in design and to improve aircraft life management. Design/methodology/approach -The effect of corrosion is taken into consideration, introducing specific concentration factors into the life estimation relationship. Differences between fatigue in corroded specimens and fatigue in presence of corrosive environment are emphasized. No crack propagation is considered. Two alternative procedures are considered in the analysis: "a-procedure" based on maximum stress calculated on un-corroded sample section; "b-procedure" based on stress calculated on final residual section, including corrosion. Findings -Related concentration factors are derived and compared by the experimental results with the aid of an original proposed a "power law". Typical power law (square kt) has been derived to cope with the coupling effect of fatigue and corrosive environment. Research limitations/implications -The original approach developed in the paper is based on few samples. For this reason, the conclusions are addressed as tendency behaviour. Practical implications -The combined effect of fatigue load acting in presence of corrosive environment reveals an important reduction in fatigue life that cannot be determined by means of classical fatigue tests performed on prior corroded samples. Social implications -Specific design updating procedure can be determined to cope with ageing of structures during service improving structural integrity. Originality/value -The derivation indicates a substantial equivalence of the considered two procedures both in the case of prior corroded samples and in combined situation. This tendency is consistent with the available data results. Original analytical relations are introduced to manage such kind of combined effect revealing consistency of data also if few samples were tested.