Environmental noise, which is caused by traffic, industrial and recreational activities, is known to be a nuisance for roughly 20 % of the European population. Transport systems are especially a matter of concern. These systems generate both noise and air pollution: in particular nitrogen oxide (NOx) or hydrocarbons (HC).
In the framework of the ENNAH project (ended in 2011), a number of recommendations have been stated in order to develop new strategies in Europe with regard to both noise and health.
As far as transportation was concerned, disentangling the effects of noise from air pollution represented a huge issue. In order to carry out epidemiological studies, it was necessary to assess the exposure to road traffic and related air pollution in great detail. Using modelling tools and sensing technologies can allow researchers to improve outcomes of this type of studies. These two potential technical frameworks (i.e. simulation techniques and new types of sensors) have been determined as enablers for identifying the effect of combined exposure.
First, it has been shown that a great variability of noise happens over a given period of time. This variability is due to the effects of acceleration or deceleration of road traffic or to effects of low frequency noises for instance. As these phenomena were not addressed in the majority of health studies at the time of the project launch (2009), correlations between noise and health outcomes have been poorly highlighted. In order to overcome this barrier, relevant simulation tools needed to be implemented.
These dynamic simulation models would be able to bring information about the spectral content (i.e. by making use of information about the deceleration, stops and acceleration of heavy vehicles providing low frequency noise) and the temporal structure of the noise level (i.e. by considering various types of indicators such as the number of noise events, percentile sound levels or traffic signal scale). In addition, microscopic traffic simulation models would consider the exact location and behaviour of individual vehicles. Microsimulation would also be capable of providing relevant information concerning additional noise indicators in health studies (e.g. loudness, tonality, number of events, etc.).
Second, it has been admitted that measurement errors affect the association of noise effect and health and trying to reduce these errors represents an important aspect of the assessment. Thus, the use of measurement techniques would still be considered as relevant, given that (i) modelled noise levels could differ from reality, (ii) individual noise exposure could not be extracted from modelled noise maps or (iii) advances in technology were lowering costs of measurements. Novel measurement techniques should therefore be implemented to reduce these inaccuracies.
In this context, Micro-Electro-Mechanical-Systems (MEMS) devices appeared to be a particularly interesting technology. These multi-parameter miniaturised and wireless sensing devices are well suited for air pollution monitoring. It has been shown in previous studies that 90% of calculated day values equalled measurements within 5 dB and even within 3 dB (with a more expensive technique). Modern measurements techniques would also facilitate the assessment of personal noise dose in health studies. Individual monitoring could therefore be opposed or associated to group exposure. However, a number of uncertainties (e.g. quick movements of the bearer or presence of wind) were still affecting personal dosimeters and these devices should be further developed.
Source: ENNAH - WP 3 Noise exposure assessment report.