# Noise Annoyance in Physical Sciences: Perspective 2015-2024
## 3 Results
These include attempts to determine whether noise annoyance contributes to reduced physical activity [70], elevated blood pressure [71; 72], sleep disturbances, and increased levels of irritation due to various noise sources [73; 74; 75]--such as school noise [76; 77] or wind turbine exposure [78]. Associations between noise exposure and diseases, including cardiovascular [64; 65; 79] and respiratory conditions [80], were also identified. Studiesfocusing on physiological responses as potential indicators of noise impact were considered particularly insightful [81]. Some studies addressed both psychological and physiological responses to noise simultaneously, such as those examining reactions to changing urban noise conditions [82; 83]. This type of research indicates the need for multiple scales to assess the noise correlation with psychological and physiological responses. Important are not only the type of sound and sound level, but also the time of exposure, or the gender of the recipient [83]. In addition to psychological and physiological studies, the literature review also revealed research on behavioral responses to noise. These included studies on work efficiency under distracting noise conditions [84], standards influencing drivers' intentions to reduce noise [85], public opposition to wind farm construction [86; 87], and human behavior in so-called quiet zones within cities [88]. In the context of urban planning, research explored the relationship between types of urban development and noise perception [89], as well as the relationship between vehicle speed and sound emission levels [90]. Other studies investigated the acoustic properties of residential buildings [91; 92; 93], including heating system designs and their susceptibility to sound transmission [94]. A further group of publications focused on vehicle design. These included studies on cars, such as active noise reduction systems [95], engine compartment insulation [96], and the detectability of low-emission (noise-wise) electric vehicles by pedestrians [97]. Aircraft noise reduction also formed a significant group, encompassing studies on aircraft structure optimization [98; 99; 100; 101; 102; 103; 104; 105; 106; 107] and noise levels in specific ship compartments [108]. These topics are closely tied to engineering research, along with studies on helicopter noise [109; 110; 111; 112], urban air transport [113; 114; 115; 116], and the impulsiveness of noise generated by road warning strips [117; 118]. Other works addressed noise emissions across various urban locations [119] and at airports [120]. Helicopter studies have investigated the importance of emission angles in determining noise sources [109], as well as the influence of wind [110]. This is an issue that should, according to the researchers, be reflected in plans over the development of air public transport, especially in the context of predicting noise from helicopter rotors [114]. Finally, several studies proposed noise modeling solutions, including active noise control [121], runway design [122; 123], noise-reducing urban environments [50], and simulations of sonic wave propagation [124; 125]. Table 1 presents the number of articles within the designated categories, segmented by the years of publication. To facilitate the systematization of the collected material, the publication years were grouped into two distinct periods: 2015-2019 and 2020-2024. Furthermore, the coefficient of dependence between individual categories was calculated using the chi-square (x\({}^{2}\)) test. The underlying assumption was that if the resulting \(p\)-value is significantly lower than the established significance level of 0.05, the null hypothesis, which posits no association between the category distribution and the time periods, could be rejected. This rejection would indicate statistically significant differences in how the analyzed categories are distributed across the 2015-2019 and 2020-2024 intervals.