# Mapping Noise from Motorised Transport in the Context of Infrastructure Management
## 1 Introduction  
Studies indicate that approximately 40% of Europeans are exposed to daytime noise levels exceeding the World Health Organisation (WHO)'s recommended threshold of 55 dB [1, 2]. The European Environment Agency reports that road noise affects around 125 million people, making it a significant social and environmental issue [3, 4]. Noise is estimated to contribute to the loss of approximately 1.6 million disability-adjusted life years (DALYs) annually in Europe alone [5, 6]. The ongoing urbanisation and increasing demand for transport services, coupled with the rise in the number of motor vehicles, significantly impact the magnitude of the adverse effects of noise on both people and the environment [7]. According to the Polish Central Statistical Office, road transport accounts for over 80% of all freight transport in Poland [8], exacerbating the problem of noise emissions. Car transport is a primary contributor to urban noise pollution, responsible for approximately 80% of the overall noise levels in many cities [9, 10]. Numerous research papers have examined the relationship between traffic congestion and noise levels, highlighting the co-occurrence of public health issues as a result of increased noise exposure based on the models developed [3, 8, 11, 12]. The primary organ affected by excessive noise impact ishearing; however, indirect effects, such as heightened stress levels and diminished quality of life, associated with increased dB values have also been noted [13; 14]. The World Health Organisation (WHO) has established guidelines indicating that noise levels exceeding 55 dB can lead to significant annoyance and health disorders. In contrast, levels above 70 dB can result in permanent hearing loss and increased mortality from cardiovascular causes [15]. Studies also indicate that noise exposure can trigger physiological stress responses, manifesting as elevated blood pressure, heart disease, and other cardiovascular conditions [16; 17]. A meta-analysis by [PERSON] highlights that road noise is a risk factor for coronary heart disease and may also influence an increased risk of stroke [18]. Similarly, research has shown that people living near heavily trafficked roads experience more sleep disturbances and various health issues. Estimates suggest that the indirect impact of road noise contributes to approximately 2000 premature deaths per year in Japan alone [19]. The effect of noise on sleep disturbance is associated with a potential increased risk of cognitive impairment and mental health issues, for example, increasing the risk of ischemic heart disease (IHD) [16], attention deficit disorder (HA) [20], sleep disturbances (HSD) [21; 22], and depression [23; 24]. The relationship between noise exposure and annoyance is also significant: studies demonstrate that even at similar decibel levels, different types of noise (e.g., road vs. aeroplane) can induce varying degrees of annoyance and health impacts [25; 26]. This suggests that noise characteristics, including frequency and duration, are crucial in determining health effects [25]. Researchers indicate that prolonged exposure to high noise levels can lead to increased irritability, anxiety, and depression [13; 27]. In addition to direct health impacts, noise from motorised transport has broader implications for urban planning and community well-being. Metropolitan areas with high traffic noise often experience reduced physical activity among residents, as noise discomfort can discourage outdoor activities [28; 29]. This decline in physical activity can contribute to various health problems, including obesity and related chronic diseases [30; 31]. Furthermore, green spaces have been shown to mitigate some of the adverse effects of noise pollution by promoting physical activity and enhancing mental well-being [32]. The accumulation of noise pollution in urban areas can diminish the quality of life, disrupt local ecosystems [33; 34], and contribute to biodiversity loss [35; 36].