Underwater noise pollution is a significant environmental issue that can have detrimental effects on marine ecosystems. One of the main sources of underwater noise pollution is ship traffic, which has been shown to negatively impact marine animals by masking communication signals, altering their behaviors, and even causing hearing loss. In the Red Sea, ships are the main contributor to underwater noise pollution, particularly in areas with high shipping traffic. This thesis aims to understand the spatial and temporal distribution of underwater ship noise in the Red Sea using an acoustic propagation model, namely the Range-dependent Acoustic Model (RAM). RAM takes into account anthropogenic and environmental inputs including water temperature, salinity, and bathymetry to predict sound propagation in the Red Sea. By running RAM with inputs of ship traffic data, maps of underwater ship noise in the Red Sea were generated. These maps are important tools for policymakers and marine resource managers to identify areas of high noise pollution, target mitigation efforts accordingly, and guide future research on the effects of underwater noise pollution on marine life in the Red Sea.

The distance of sound propagation in water is inversely proportional to the frequency; there for the low frequency noise generated by distance shipping contribute most to the low frequency components of the ocean ambient noise. In order to improve the performance of sonar application, understanding and predication shipping noise is important. In this study, noise data was collected by vertical line array (VLA), in South China Sea of Asian Seas International Acoustics Experiment (ASIEX) in 2001. Due to the limited access to the satellite imagery, and based on the assumption that fishing vessels in South China Sea has similar operational pattern and lighting in recent years, the night time satellite image data was acquired by Defense Meteorological Satellite Program DMSP - Operational Linescan System(DMSP-OLS) of 2005. Linear regression was analyzed between fishing light pixel distribution and low frequency noise level variation, fishing light was expressed in terms of total pixel number and total light intensity, and distance from fishing vessel to VLA was assumed by spherical and cylindrical spread. The results show high correlation between total light intensity and noise level, and cylindrical spreading is better assumption in shallow water on the continental shelf at low frequency. As a conclusion, this study successfully prove that by using the night satellite image, the low frequency fishing vessel noise can be predicted with reasonable accuracy.

Wave energy has the potential to contribute considerably to the UK's energy mix. The marine environment is already subjected to many anthropogenic pressures. There is a need to develop the industry as sustainably as possible. A key concern is the potential for underwater noise to affect marine life. A wave energy converter (WEC; BOLT Lifesaver, Fred Olsen Ltd.) was deployed at the Falmouth Bay marine renewable energy test site (FaBTest). The underwater sound levels were recorded at this site for a two week baseline period, a five-day installation period and intermittent operational and non-operational activity from March 2012 - November 2013. The recordings were also analysed for the Marine Strategy Framework Directive (MSFD) indicator third octave bands of 63-Hz and 125-Hz for shipping noise. The median and modal sound levels in Falmouth Bay were found to be loudest in the frequency range 100 Hz - 1 kHz and affected by local shipping activity. During installation activity, the sound levels were louder at all frequencies recorded as compared to similar periods with no installation activity, with a mean difference of 6.9 dB Hz-1 in the range 10 Hz to 48 kHz. Long term marine renewable energy construction projects may affect the MSFD indicator bands. There was little overall difference in the average sound levels for the operational and non-operational periods as the median PSD levels were louder by an average of 0.04 dB Hz-1 during the operational activity as compared to the non-operational activity. The results of this study indicate that the effect of a single WEC device on the overall sound levels in Falmouth Bay is relatively low considering the substantial presence of shipping in the area. However, in the immediate vicinity of the device (<200 m), the sound produced was found to be of significance to marine animals. It therefore requires considering in future deployments, particularly at a site with little anthropogenic activity.

Long-term omni-directional ambient noise was collected at several sites in the Gulf of Mexico during 2004 and 2005. The Naval Oceanographic Office deployed bottom moored Environmental Acoustic Recording System (EARS) buoys approximately 159 nautical miles south of Panama City, Florida, in water depths of 3200 meters. The hydrophone of each buoy was 265 meters above the bottom. The data duration ranged from 10-14 months. The buoys were located near a major shipping lane, with an estimated 1.5 to 4.5 ships per day passing nearby. The data were sampled at 2500 Hz and have a bandwidth of 10-1000 Hz. Data are processed in eight 1/3-octave frequency bands, centered from 25 to 950 Hz, and monthly values of the following statistical quantities are computed from the resulting eight time series of noise spectral level: mean, median, standard deviation, skewness, kurtosis and coherence time. Four hurricanes were recorded during the summer of 2004 and they have a major impact on all of the noise statistics. Noise levels at higher frequencies (400-950 Hz) peak during extremely windy months (summer hurricanes and winter storms). Standard deviation is least in the region 100-200 Hz but increases at higher frequencies, especially during periods of high wind variability (summer hurricanes). Skewness is positive from 25-400 Hz and negative from 630-950 Hz. Skewness and kurtosis are greatest near 100 Hz. Coherence time is low in shipping bands and high in weather bands, and it peaks during hurricanes. The noise coherence is also analyzed. The 14-month time series in each 1/3- octave band is highly correlated with other 1/3-octave band time series ranging from 2 octaves below to 2 octaves above the band's center frequency. Spatial coherence between hydrophones is also analyzed for hydrophone separations of 2.29, 2.56 and 4.84 km over a 10-month period. The noise field is highly coherent out to the maximum distance studied, 4.84 km. Additionally, fluctuations of each time series are analyzed to determine time scales of greatest variability. The 14-month data show clearly that variability occurs primarily over three time scales: 7-22 hours (shipping-related), 56-282 hours (2-12 days, weather-related) and over an 8-12 month period.

Species distribution maps can provide important information to focus conservation efforts and enable spatial management of human activities. Two sympatric marine predators, grey seals (Halichoerus grypus) and harbour seals (Phoca vitulina), have overlapping ranges but contrasting population dynamics around the UK; whilst grey seals have generally increased, harbour seals have shown significant regional declines. A robust analytical methodology was developed to produce maps of grey and harbour seal usage estimates with corresponding uncertainty, and scales of spatial partitioning between the species were found. Throughout their range, both grey and harbour seals spend the majority of their time within 50 km of the coast. The scalability of the analytical approach was enhanced and environmental information to enable spatial predictions was included. The resultant maps have been applied to inform consent and licensing of marine renewable developments of wind farms and tidal turbines. For harbour seals around Orkney, northern Scotland, distance from haul out, proportion of sand in seabed sediment, and annual mean power were important predictors of space-use. Utilising seal usage maps, a framework was produced to allow shipping noise, an important marine anthropogenic stressor, to be explicitly incorporated into spatial planning. Potentially sensitive areas were identified through quantifying risk of exposure of shipping traffic to marine species. Individual noise exposure was predicted with associated uncertainty in an area with varying rates of co-occurrence. Across the UK, spatial overlap was highest within 50 km of the coast, close to seal haul outs. Areas identified with high risk of exposure included 11 Special Areas of Conservation (from a possible 25). Risk to harbour seal populations was highest, affecting half of all SACs associated with the species. For 20 of 28 animals in the acoustic exposure study, 95% CI for M-weighted cumulative Sound Exposure Levels had upper bounds above levels known to induce Temporary Threshold Shift. Predictions of broadband received sound pressure levels were underestimated on average by 0.7 dB re 1μPa (± 3.3). An analytical methodology was derived to allow ecological maps to be quantitatively compared. The Structural Similarity (SSIM) index was enhanced to incorporate uncertainty from underlying spatial models, and a software algorithm was developed to correct for internal edge effects so that loss of spatial information from the map comparison was limited. The application of the approach was demonstrated using a case study of sperm whales (Physeter macrocephalus, Linneaus 1758) in the Mediterranean Sea to identify areas where local-scale differences in space-use between groups and singleton whales occurred. SSIM is applicable to a broad range of spatial ecological data, providing a novel tool for map comparison.