Introduction
Environmental noise, and persistent high levels of transportation noise in particular, have been shown to have considerable effects on human health and well-being [1,2]. According to the WHO, one third of the EU citizens are annoyed by environmental noise and about 25% of the EU citizens experience sleep disturbances due to environmental noise [1]. According to the first round of noise mapping in agglomerations and on major roads, around 56 million people within agglomerations and 34 million people outside agglomerations across the EU are exposed to noise levels above Lden 55 dB [3], a limit level that has been suggested by the WHO to protect the majority of people from being seriously annoyed [4]. Railway noise seems to be a less serious problem than road traffic noise as only 6.3 million citizens in agglomerations and 5.4 million along major railways outside agglomerations in the EU are exposed to noise levels exceeding Lden of 55 dB, according to the first noise mapping [3]. Indeed, exposure to the same level of railway noise is likely to result in less annoyance in comparison to road traffic and aircraft noise, as documented by exposure-response functions based on a meta-analysis of empirical studies on noise annoyance [2,5], possibly with the exception of high-speed trains in Korea and Japan, which are reported to produce more noise annoyance at the same noise levels [6,7].
Despite this type of evidence, relatively little is known about how road and rail traffic noise affect overall life satisfaction. The purpose of this paper is to fill this gap by linking different concepts that have appeared in the empirical literature, proposing a unified model and submitting this model to an empirical test. Specifically, this paper aims to link noise exposure, noise sensitivity, noise annoyance, residential satisfaction and overall life satisfaction.
Noise Annoyance and Noise Sensitivity
Environmental noise is defined as unwanted sound caused by emissions from traffic and industrial and recreational infrastructures, which may cause annoyance and health damage. The noise originating from transport is a classic nuisance, or externality in economic terms. This is a spill-over effect of an activity which affects the welfare of others, without being compensated by the producer of the externality. One of the effects of noise exposure on the well-being of humans consists in noise annoyance defined as “a feeling of displeasure associated with any agent or condition, known or believed by an individual or group to adversely affect them” [8]. According to Miedema, noise annoyance is “a sensitive indicator of adverse noise effects and by itself means that noise affects people’s quality of life” [9]. Thus, noise annoyance appears to mediate some of the health effects of noise exposure [10].
Over the last 40 years, a substantial body of literature has provided evidence on the relationship between the levels of noise exposure and expected noise annoyance. In a seminal synthesis, Schultz [11] translated exposure-response relationships from several social surveys into common day-night average sound levels and proposed the average of those relationships as a means for predicting community annoyance from transportation noise. Miedema and Oudshoorn [5] later developed a more elaborated model for predicting three levels of noise annoyance for road, rail and aircraft noise for two alternative noise metrics: the day-night levels (mostly used in the USA) and the day-evening-night levels endorsed in the EU’s Environmental Noise Directive. In a recent study for the Danish Ministry of Science, Technology and Innovation, Pedersen et al. [12] developed logistic functions for exposure-response annoyance relationships with various covariates representing the effects and parameters of noise sources, locations, activities, perceived acoustic attributes and non-acoustic factors. These noise exposure functions, which describe the relationship between noise exposure and noise annoyance in probabilistic terms, typically consider noise exposure values between 45 dB and 75 dB in order to avoid uncertainty.
Noise annoyance is currently one of the most extensively studied metrics for assessment of environmental noise impacts on people. The ISO standard 15666:2003 provides a five-point scale of annoyance (not annoyed, slightly, moderately, very and extremely annoyed) for socio-acoustic and social surveys on noise effects.
Noise annoyance is influenced by many factors besides noise exposure, including person-related variables (age, stress level, duration of exposure to noise, noise sensitivity), house-related variables (floor number, number of windows oriented towards the noise source), and the characteristics of the noise source (traffic flow during the day and night) [13]. Noise sensitivity is probably the most important non-acoustic factor of noise annoyance [13–20], while socio-demographic factors usually play a minor role [21]. As a matter of fact, noise sensitivity seems to be related to an individual’s psychological characteristics, independent of noise exposure [21].
Life Satisfaction
Happiness, subjective well-being, and life satisfaction are some of the terms that appear interchangeably in the literature to denote the evaluation of one’s life as a whole [22,23] or specific aspects of life [24]. The concept of “overall” life satisfaction on which we focus in this paper originated in psychology and sociology, but has recently also made its way into economics, where it is used as a measure of “experienced utility” [25] and applied in a number of empirical studies that aim at monetary valuation of non-market goods [26].
Since “overall” life satisfaction is an evaluation of one’s life as a whole, it can essentially be influenced by any number of possible factors. Empirical studies show that many economic variables such as income, unemployment, and inflation are predictive of life satisfaction [22,27–29] as are factors that characterize one’s socio-demographic situation (age, gender, parenthood) and health status [30].
Recent research has shown that besides the socio-demographic and economic variables, ambient environmental quality, too, affects life satisfaction. It has been found that climatic conditions affect life satisfaction at the aggregated country level [31] and also at the individual level [32,33]. Similarly, air pollution has been found to affect life satisfaction at the aggregated country level [34–36], as well as the individual level [37,38]; one study known to us has also found an effect of perceived air pollution on life satisfaction [30]. It is important to note that factors of life satisfaction may interact in a way that either attenuates or amplifies the direct effects of those factors on life satisfaction. One example of such an interaction would be the difference in the level of life satisfaction between urban and rural areas, which is a function of the country’s economic development [39] and leads urban populations, especially in less developed countries, to express higher life satisfaction despite the serious problems that they are facing in their urban environments.
Only a few studies have examined the effect of traffic noise exposure on life satisfaction. Lercher and Kofler [40] have found a significant negative effect of traffic noise (from road and rail traffic) on overall life quality in alpine rural areas. Their finding suggests that the effect takes on a concave function and increases particularly at noise levels higher than 60 dB(A). A study by van Praag and Baarsma [41] has examined and found an effect of exposure to aircraft noise on individual life satisfaction. Another study has examined the effect of perceived adverse noise-related effects (perceived air pollution and perceived noise pollution regardless of their source) on life satisfaction [30], but has found this effect only for some of the model specifications, which may lead one to infer that the effect is not particularly strong.
Besides the studies into the effect of noise on overall life satisfaction, there are several empirical papers that focus on the effect of noise exposure and noise annoyance on satisfaction with some aspects of one’s life (as opposed to satisfaction with one’s life as a whole). Probably the most studied aspect of life satisfaction found to be related to noise is residential satisfaction or one’s satisfaction with the quality of life in a specific area. A study by Botteldooren et al. [42] has found an effect of road traffic noise exposure on residential quality. A study by Schreckenberg et al. [21] has examined the effects of exposure to aircraft noise and related noise annoyance on different aspects of quality of life (i.e., satisfaction with dwelling, residential area, infrastructure, quietness, and attractiveness of the residential area) and found that there was a significant negative effect of noise exposure on the attractiveness of the residential area and the total score of residential satisfaction, and also a significant effect of noise annoyance on satisfaction with dwelling. A study by Kroesen et al. [43] has found an effect of exposure to aircraft noise on residential satisfaction mediated by noise annoyance.
There is also additional evidence concerning the effect of traffic noise on different aspects of human well-being that comes from studies of health-related quality of life. For instance, a study by Shepherd et al. [44] has found the effect of aircraft noise, mediated by annoyance, on quality of life (measured as a multidimensional construct that included physical health, psychological well-being, social relationships and environmental factors). A study by Dratva et al. [45] has found an effect of road traffic noise on all aspects of health-related quality of life (physical functioning, physical role, bodily pain, vitality, social functioning, emotional role, and mental health) except general health. However, the (overall) life satisfaction used in this study is conceptually different from health-related quality of life [46] and effects of traffic noise on health-related quality of life therefore do not necessarily imply that (overall) life satisfaction shall be affected too.
As far as we are aware, the direction of the causation between overall life satisfaction and residential satisfaction has not been established by previous research. This is closely related to a more general debate in the life satisfaction literature between proponents of so-called “bottom-up theories” of subjective well-being, who argue that domain satisfactions affect overall life satisfaction, and proponents of “top-down theories”, who propose that the causation runs in the opposite direction [47]. Apparently, there is no general solution to the top-down vs. bottom-up debate because the direction of the causation is specific to each domain satisfaction and, in addition, can be bidirectional, spurious, or any combination of these [48], and can even be unstable across models and datasets [49].
Studies known to us assume that residential satisfaction affects life satisfaction in a bottom-up fashion (see, e.g., [50,51]). However, no empirical study has specifically examined the direction of the causation between residential satisfaction and life satisfaction and this question therefore remains open.
The cross-sectional evidence exploited in this study is not particularly suitable to testing alternative hypotheses about the direction of the causation. In fact, we can detect whether one or the other direction of the causation assumed in the model leads to a higher or lower misfit of the model but there is no way to compare the misfit of the two alternative models statistically because these are non-nested models.
Assuming bottom-up causation or top-down causation between life satisfaction and residential satisfaction can lead to different results and their interpretations regarding the effect of noise on life satisfaction. For this reason, and because we are unable to establish the direction of the causation between residential satisfaction and life satisfaction, we propose and empirically test models that specify either a bottom-up or a top-down relationship between the two variables.