Tag Archives: noise pollution

sirens on emergency vehicles: “more harm than good”?

I knew it – all those sirens on ambulances and fire trucks tearing around town might not be improving outcomes. They are bad for our hearing (especially for the people working on the trucks) and might startle drivers into making mistakes or sudden unpredictable moves. Sure, the idea is that if you are having a heart attack or stroke the second count. But according to this article at least, the data just don’t support the idea that those sirens are getting the paramedics to you faster.

Americans love our sirens. When I lived in Singapore for a couple years, one thing I noticed was that police, fire trucks (which were often more like vans), and ambulances didn’t use sirens much. Now, Singapore tore down most of its historic buildings (which you could argue is sad), which means its buildings are mostly very modern standardized high rises. I think that is one reason they don’t need the big fire trucks. Their streets are wide and well maintained (this is not great for pedestrians or people on bicycles). They also do congestion pricing on a major scale so they just don’t have the traffic we have (I support this, but you could argue it is inequitable because the rich can afford to drive while everyone else takes public transportation. The public transportation is very good and reliable however.) Sirens aside, I found Singapore awful in terms of urban noise pollution and wore ear plugs much of the time I was there. The noise didn’t seem to bother most of the locals or people from nearby countries.

open source street noise model

Here’s an open-source code for modeling street noise propagation. It’s written in R and open source database and GIS tools.

This paper describes the development of a model for assessing TRAffic Noise EXposure (TRANEX) in an open-source geographic information system. Instead of using proprietary software we developed our own model for two main reasons: 1) so that the treatment of source geometry, traffic information (flows/speeds/spatially varying diurnal traffic profiles) and receptors matched as closely as possible to that of the air pollution modelling being undertaken in the TRAFFIC project, and 2) to optimize model performance for practical reasons of needing to implement a noise model with detailed source geometry, over a large geographical area, to produce noise estimates at up to several million address locations, with limited computing resources. To evaluate TRANEX, noise estimates were compared with noise measurements made in the British cities of Leicester and Norwich. High correlation was seen between modelled and measured LAeq,1hr (Norwich: r = 0.85, p = .000; Leicester: r = 0.95, p = .000) with average model errors of 3.1 dB. TRANEX was used to estimate noise exposures (LAeq,1hr, LAeq,16hr, Lnight) for the resident population of London (2003–2010). Results suggest that 1.03 million (12%) people are exposed to daytime road traffic noise levels ≥ 65 dB(A) and 1.63 million (19%) people are exposed to night-time road traffic noise levels ≥ 55 dB(A). Differences in noise levels between 2010 and 2003 were on average relatively small: 0.25 dB (standard deviation: 0.89) and 0.26 dB (standard deviation: 0.87) for LAeq,16hr and Lnight.