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This article presents empirically derived conversion rules between the environmental noise exposure metrics Leq24h, LDay, LEvening, LNight, Ldn, and Lden for the noise sources road, rail and air traffic. It caters to researchers that need to estimate the value of one (unknown) noise metric from the value of another (known) metric, e.g. in the scope of epidemiological meta-analyses or systematic reviews, when results from different studies are pooled and need to be related to one common exposure metric. Conversion terms are derived using two empirical methods a) based on analyzing the diurnal variation of traffic, and b) by analyzing differences between calculated noise exposure metrics. For a) we collected and analyzed diurnal traffic share data from European and US airports as well as data on the diurnal variation of traffic from roads in several European countries and from railway lines in Switzerland which were derived from counting stations and official records. For b) we calculated differences between noise metrics in over 50'000 stratified randomly sampled dwellings in Switzerland. As a result of this exercise, conversion terms, including uncertainty estimates, are systematically tabulated for all variants of the target metrics. Guidance as to the practical applicability of the proposed conversions in different contexts is provided, and limitations of their use are discussed. [ABSTRACT FROM AUTHOR]

Aims: The present study aimed to disentangle the risk of the three major transportation noise sources-road, railway, and aircraft traffic-and the air pollutants NO2 and PM2.5 on myocardial infarction (MI) mortality in Switzerland based on high quality/fine resolution exposure modelling., Methods and Results: We modelled long-term exposure to outdoor road traffic, railway, and aircraft noise levels, as well as NO2 and PM2.5 concentration for each address of the 4.40 million adults (>30 years) in the Swiss National Cohort (SNC). We investigated the association between transportation noise/air pollution exposure and death due to MI during the follow-up period 2000-08, by adjusting noise [Lden(Road), Lden(Railway), and Lden(Air)] estimates for NO2 and/or PM2.5 and vice versa by multipollutant Cox regression models considering potential confounders. Adjusting noise risk estimates of MI for NO2 and/or PM2.5 did not change the hazard ratios (HRs) per 10 dB increase in road traffic (without air pollution: 1.032, 95% CI: 1.014-1.051, adjusted for NO2 and PM2.5: 1.034, 95% CI: 1.014-1.055), railway traffic (1.020, 95% CI: 1.007-1.033 vs. 1.020, 95% CI: 1.007-1.033), and aircraft traffic noise (1.025, 95% CI: 1.006-1.045 vs. 1.025, 95% CI: 1.005-1.046). Conversely, noise adjusted HRs for air pollutants were lower than corresponding estimates without noise adjustment. Hazard ratio per 10 μg/m³ increase with and without noise adjustment were 1.024 (1.005-1.043) vs. 0.990 (0.965-1.016) for NO2 and 1.054 (1.013-1.093) vs. 1.019 (0.971-1.071) for PM2.5., Conclusion: Our study suggests that transportation noise is associated with MI mortality, independent from air pollution. Air pollution studies not adequately adjusting for transportation noise exposure may overestimate the cardiovascular disease burden of air pollution., (Published on behalf of the European Society of Cardiology. All rights reserved. © The Author(s) 2018. For permissions, please email: journals.permissions@oup.com.)