Prenatal urban traffic noise exposure impairs spatial learning and memory and reduces glucocorticoid receptor expression in the hippocampus of male rat offspring

IntroductionExposure to noise stress during early life may permanently affect the structure and function of the central nervous system. The aim of this study was to evaluate the effects of prenatal exposure to urban traffic noise on the spatial learning and memory of the rats' offspring and the expression of glucocorticoid receptors (GRs) in their hippocampi.MethodsThree g\roups of pregnant rats were exposed to recorded urban traffic noise for 1, 2 or 4 h/day during the last week of pregnancy. At the age of 45 days, their male offspring were introduced to the Morris water maze (MWM) for assessment of spatial learning and memory. The corticosterone levels were measured in the offspring's sera by radioimmunoassay, and the relative expression of glucocorticoid and mineralocorticoid receptors (MRs) in their hippocampi was evaluated via RT-PCR.ResultsFacing urban traffic noise for 2 and 4 h/day during the third trimester of pregnancy caused the offspring to spend more time and to travel a larger distance than the controls to find the target platform. Analogously, these two groups were inferior to their control counterparts in the probe test. Also, prenatal noise stress elevated the corticosterone concentration in the sera of the rats' offspring and dose-dependently decreased the relative expression of the mRNA of both GRs and MRs in their hippocampi.ConclusionsUrban traffic noise exposure during the last trimester of pregnancy impairs spatial learning and memory of rat offspring and reduces GRs and MRs gene expression in the hippocampus.

Near-surface site investigation by seismic interferometry using urban traffic noise in Singapore

We have evaluated a field test in the city of Singapore to assess the feasibility of the passive seismic survey for bedrock depth determination and to further investigate the optimal acquisition parameters. The ambient noise field, dominated by urban traffic noise, is recorded passively for the application of seismic interferometry. Spectral analysis indicates that the traffic-induced noise by local roads is concentrated between 3 and 25 Hz. We use multiple signal classification beamforming for wavefield direction of propagation analysis. We apply seismic interferometry to retrieve the surface-wave part of the Green’s functions, based on which surface-wave dispersion relations are extracted and further inverted for 1D S-wave velocity profiles. Subsequently, we compare the inversion results from seismic interferometry with borehole logs at multiple sites in Singapore and establish that the bedrock depths are well-determined using passive seismic methods within a maximum error of 3 m. By investigating the convergence of the crosscorrelograms, we ascertain that the best compromise of cost, efficiency, and accuracy for a passive site investigation in Singapore can be achieved in 15 min in the morning of a working day using an array as short as 30 m with six vertical geophones, although these parameters should be reinvestigated at other sites and other times. The success of this case study demonstrates that accurate near-surface site investigation can be achieved with faster acquisition, fewer receivers, and a smaller acquisition footprint compared with conventional methods, all of which improve the efficiency particularly in a highly developed urban environment.

Variability analysis of urban traffic noise measurands

The paper presents the analysis results of measurements recorded by road traffic and noise monitoring station. The station is located in a medium size town in Poland (Kielce) situated at the national road to Cracow. The traffic flow was measured over the period between January and December 2013 for twenty four hours a day. Statistical analysis methods were used to determine the variability and uncertainty of the results. The measurements from two vehicular lanes running towards the town and two lanes running towards Cracow were analyzed. The variability of the results was described using parameters such as the coefficient of variation and positional variation. The results of vehicle traffic measurements were used to simulate changes in the noise measurand variation within 1-hour intervals. The Nordic Prediction Method was used for this purpose. It was found that in most cases, the distribution of the tested variable was not normal. Box plots were used to assess whether outliers data occurred in the recorded results. The variability of noise and type A uncertainty was evaluated.