• Latest Version, 2024 Assessment
• Ambient noise, 2018 assessment

Continuous anthropogenic sound

Continuous anthropogenic sound from shipping became more widespread between 2018 and 2022, with a 23% increase in the area of UK waters exceeding 120 dB re 1 µPa. Interventions to reverse this trend are likely to be needed if the UK is to attain Good Environmental Status for this indicator. 

Background

Before the advent of human civilisations, the soundscape of the ocean consisted entirely of sound generated by marine species, together with other natural sounds such as wind, rain, and lightning (Duarte and others, 2021). Since sound can travel much further than light in the ocean, many marine organisms evolved to use sound as a vital sensory signal, including marine mammals, fishes, sea turtles, and many invertebrate species. In the 19th century, the growth of motorised shipping led to a spread of anthropogenic sound in the ocean which has now become almost ubiquitous, with negative effects documented on marine species ranging from zooplankton to blue whales (Williams and others, 2015; Duarte and others, 2021). 

In response to the threat of ecosystem-scale impacts from underwater anthropogenic sound (more commonly termed ‘noise’ or ‘noise pollution’), the UK Marine Strategy aims to ensure that levels of underwater noise ‘do not have adverse effects on marine ecosystems and animals at the population level’. The underwater noise descriptor of the UKMS includes an indicator for impulsive noise (e.g. noise from seismic airguns, explosions, or pile driving) and another indicator for continuous noise (the subject of this assessment), generated primarily by shipping, although activities such as drilling and dredging also contribute. 

At present, there are no quantitative criteria for achieving Good Environmental Status (GES) under the Descriptor for underwater noise and so this assessment focuses on quantifying the prevalence of continuous anthropogenic sound in UK waters since 2018, in accordance with the indicator definition. 

Figure 1. Continuous underwater sound is primarily generated by shipping. Image credit: Chris Pagan 

Assessment method

Under the UK Marine Strategy, Good Environmental Status for the continuous noise indicator is defined according to the “spatial distribution, temporal extent and levels of anthropogenic continuous low-frequency sound” (European Commission, 2017).  Since the spatial distribution of noise is required, noise mapping must be undertaken in order to assess the indicator (Merchant and others, 2022). Although field monitoring of continuous sound in support of the Descriptor has been ongoing since 2018, such monitoring only provides data at point locations in the UK EEZ. To produce noise maps of continuous sound, it is necessary to couple this field monitoring at specific locations with spatial models of continuous sound levels. Such models are derived from data on sound sources (e.g. ship movements, wind speed) and the propagation of underwater sound in the environment (which depends on bathymetry, seabed composition, and water column properties). 

Modelling approach 

The overall ship noise mapping approach was developed by Cefas under various Defra-funded projects and has been published in the peer-reviewed scientific literature (Farcas et al., 2020). The approach combines information on vessel movements from AIS ship-tracking data with acoustic models which estimate the noise levels emitted by ships and the way that this noise propagates through the marine environment at low frequencies. In addition to shipping noise, wind-generated noise is a significant noise source at low-frequencies (Wenz, 1962). To produce maps of underwater noise which can be validated with field measurements, the shipping and wind components are modelled separately and then combined. This methodology is similar to previously published work in the field (Aulanier and others, 2017; Cominelli and others, 2018; Erbe and others ,2012; Joy and others, 2019; Sertlek and others, 2019), although the Cefas study was the first to validate the model predictions at multiple monitoring sites (Farcas and others, 2020). 

 

Source modelling of ships and wind 

 

Source models describe the sound emitted at source. To produce noise maps, source models are combined with propagation models which describe how this sound subsequently dissipates in the marine environment. Source levels of wind-generated noise were modelled based on Reeder and others (2011) using wind speed data sourced from the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim/ERA-5 global atmospheric reanalysis (ECMWF, 2021). 

To estimate ship source levels, several models are available. Most models characterise noise from individual vessels according to ship speed and length (Breeding Jr and others, 1996; MacGillivray and de Jong, 2021; Ross, 1976), while others calculate the average source level of the entire fleet (Wales and Heitmeyer, 2002). The most up-to-date and recently validated model was developed as part of the Joint Monitoring Programme for Ambient Noise in the North Sea (JOMOPANS) project, known as the JOMOPANS-ECHO (hereafter J-E) model. This model adapted and updated from the previously used RANDI 3.1 naval ambient noise model (Breeding and others, 1996) using validation comparisons against ship source level measurements from the Vancouver Fraser Port Authority-led Enhancing Cetacean Habitat and Observation (ECHO) Program (Jansen and de Jong, 2017). The J-E model (MacGillivray and de Jong, 2021) retains the power-law dependence on vessel speed and length of the RANDI 3.1 model, but incorporates class-specific reference speeds and new reference spectrum coefficients, according the Automatic Identification System (AIS) ship type ID (Table 1). Thus, the J-E model calculates the ship source level spectrum as a function of frequency, speed, length, and AIS ship type. 

Table 1. The classification of vessels in JOMPANS-ECHO source level mode, according to the AIS ship type ID. For each vessel class, the reference speed and reference (mean) length used by the model are shown. 

Vessel Class	AIS ship type ID	Reference speed	Reference length
Fishing	30	6.4	32
Tug	31, 32, 52	3.7	28
Naval	35	11.1	79
Recreational	36, 37	10.6	45
Government/Research	51, 53, 55	8.0	58
Cruise	60-69 (length > 100 m)	17.1	268
Passenger	60-69 (length < 100 m)	9.7	52
Bulker	70, 75-79 (speed < 16 kn)	13.9	211
Containership	71-74 (all speeds)  70, 75-79 (speed > 16 kn)	18.0	294
Vehicle Carrier	n/a	15.8	194
Tanker	80-89	12.4	186
Dredger	33	9.5	81
Other	All other type ID	7.4	128

A comparison of the ship source level spectra for all thirteen classes of vessels distinguished by the J-E model is shown in Figure 2.  

Figure 2. Comparison of source level versus frequency of the JOMOPANS-ECHO model, for the thirteen classes of vessel distinguished by the model, in 1/3-octave bands. For each vessel class, the reference speed and mean length were used. 

As mentioned above, the J-E model incorporates power-law dependences of the source levels on the vessel length and speed. As an illustration, the dependency on vessel length is shown in Figure 3(a) for the case of “Bulk” class vessels using the class reference speed and four example vessel lengths. The dependency on vessel speed is shown in Figure 3(b) for the case of “Fishing” class vessels using the class reference (mean) length and four example of vessel speeds. 

Figure 3. Source level versus frequency of the JOMOPANS-ECHO model, for: (a) the Bulker class of vessels and four example vessel lengths; (b) the Fishing class of vessels and four example vessel speeds.  

Figure 4. Example AIS ship-tracking data, showing April 2021. Units are number of AIS transmissions per km2, interpolated to 10-minute time resolution, expressed as a power of 10 (i.e. range of colour bar is 10-2 to 103 AIS transmissions per km2). 

Vessel positions were derived from satellite Automatic Identification System (sAIS) data (Figure 4) for the North East Atlantic area (48N - 62N latitude and 16W – 9E) for 2018-2022, acquired from a commercial provider (exactEarth). The dataset contained positional data transmitted at short but irregular intervals (~5-30 minutes). These data were interpolated to 10-minute resolution, yielding 52,560 vessel position frames for each year.  

 

Propagation modelling 

 

Sound propagation was modelled using the energy-flux method (Weston, 1971), a computationally efficient range-dependent model which depends on bathymetry, sound speed, seabed reflectivity and acoustic frequency. Use of more complex models (e.g. parabolic equation) was investigated, but found to be computationally prohibitive due to the large number of source-to-receiver calculations required to produce the maps. Agreement between the chosen model and the depth-averaged predictions of a parabolic equation method (knowna as RAM; Collins, 1993) was found to be good, although the predictions from both models can be strongly dependent on the parameterisation of the seabed and thus require empirical optimisation of the seabed acoustic properties (Farcas et al., 2016). Bathymetry data was extracted from EMODNET with 7.5” resolution, temperature and salinity data from the Copernicus Atlantic European North West Shelf Ocean Physics Analysis and Forecast product (0.016° x 0.016°, 33 depth levels, daily mean values) (Copernicus, 2019). Seabed acoustic properties were derived from the Hamilton model (Hamilton, 1987) using EMODNET seabed sediment data.  

To improve computational efficiency, model domains can be gridded at varying spatial resolutions to reflect spatial differences in model uncertainty (Trigg et al., 2018). The shipping noise model used spatial grids at two resolutions: a lower resolution grid with latitude-longitude spacing of 3’ x 5’ (approximately 5 x 5 km) for coverage of the entire domain, as well as a high-resolution grid of 0.75’ x 1.25’ (approximately 1.3 x 1.3 km) for selective coverage of smaller areas near the coast and in areas of high shipping density, since this significantly improved accuracy at relatively low computational cost. 

To further improve computational efficiency, the bathymetry-dependent component of propagation loss was pre-computed and stored for each spatial node of the computational grid, up to a range of 100 km. The actual values of the propagation loss also depend on the water column properties, which are both time- and frequency-dependent. These were calculated subsequently when the shipping sources were integrated into the model (see below). 

 

Integration of propagation and source modelling components 

 

Each vessel positional frame was combined with the ship source model and applied to the propagation loss matrix for the corresponding month’s water column properties, yielding an instantaneous map of shipping noise. The wind noise layer computed from wind speed data was then either added to the ship noise layer to produce a prediction of the total noise field or subtracted from the total noise field to produce a prediction of the excess level of the ship noise above wind. These frames were computed at 10-minute intervals (yielding 52,560 frames per year) for each one-third octave frequency band centred in the interval 63 Hz – 4 kHz, and then analysed statistically to determine the median for each month and for the year overall. 

 

Validation 

 

A detailed validation of UK noise maps produced using the J-E ship source model was reported previously as part of a Defra-funded project (Cefas, 2022). The mean average error was calculated by comparing the model predictions with measured noise levels at three measurement stations in the North Sea and Celtic Sea, as shown in Table 2. The highlighted cells indicate the value of the frequency exponent which was used at each one-third octave centre frequency. 

Table 2. Mean average error (MAE) for J-E source model implementation across the Dowsing, Warp, and Puffin Island monitoring sites for a range of exponents for the frequency dependence of sound attenuation at frequencies below 1 kHz. Lowest MAE for each frequency is highlighted in Blue.  

Frequency exponent	63 Hz	125 Hz	250 Hz	500 Hz	1 kHz
1.0	26.9	21.2	7.0	5.5	7.2
1.3	26.4	14.7	5.1	6.4	7.2
1.4	24.8	11.6	5.3	6.7	7.2
1.5	21.8	8.6	5.9	7.0	7.2
1.6	17.6	6.6	6.6	7.3	7.2
1.7	12.5	6.0	7.3	7.6	7.2
1.8	8.4	6.5	8.1	7.9	7.2
1.9	7.3	7.6	8.9	8.2	7.2
2.0	8.3	8.9	9.7	8.6	7.2

Results

The noise maps for 2018-2022 show that continuous anthropogenic sound is primarily concentrated in the major shipping lane of the English Channel, with relatively high levels also present in the Celtic Seas to the south of the North Channel (which separates Northern Ireland and Scotland), and on the coast of northeast England and around Aberdeen (Figure 5). Inter-year differences are not readily apparent in these maps but can be seen by subtracting the five-year average noise map from the noise map for each year (Figure 6). Noise levels in 2018 were markedly lower than the 2018-2022 average in most areas, and markedly higher than average in 2022, demonstrating an overall increase in noise levels for most areas of the UK EEZ (Figure 7). 

 

Figure 5. Annual median modelled broadband sound pressure level (63 Hz – 4 kHz), 2018-2022. UK EEZ outlined, including division between Greater North Sea and Celtic Seas assessment areas. Units are dB re 1 µPa.  

Figure 6. Deviation from five-year average of the annual median modelled broadband sound pressure level (63 Hz – 4 kHz), 2018-2022. UK EEZ outlined, including division between Greater North Sea and Celtic Seas assessment areas. Units are decibels (dB). 

To quantify the change in noise levels in a way that is relevant to the UK Marine Strategy assessment areas, the percentage area which exceeded a certain noise level was calculated (Table 3). A continuous anthropogenic sound level of 120 dB re 1 µPa was chosen as an approximate benchmark above which marine life may be affected, in accordance with longstanding practice in the United States in relation to marine mammal behavioural disturbance (NOAA, 2023). Between 2018 and 2022, the percentage area of the UK EEZ exceeding 120 dB re 1 µPa rose from 13.7% to 16.9% (an increase in area of 23%; Table 3). However, there was a marked difference in the magnitude of this increase between the two UKMS assessment areas. In the Greater North Sea, the area exceeding 120 dB re 1 µPa rose from 18.2% to 19.5%, an increase of 7%, while in the Celtic Seas the increase was much greater, at 39% (from 10.9% area to 15.2%; Table 3). 

Table 3. Percentage area of UK EEZ and UKMS assessment regions exceeding 110, 120, and 130 dB re 1 uPa, annual average 2018-2022. 

Year	UK EEZ			UK Greater North Sea			UK Celtic Seas
	110 dB	120 dB	130 dB	110 dB	120 dB	130 dB	110 dB	120 dB	130 dB
2018	43.6	13.7	2.0	57.4	18.2	3.6	34.9	10.9	1.1
2019	48.2	15.7	2.3	62.5	19.6	3.8	39.3	13.3	1.4
2020	46.5	14.7	2.0	61.6	18.7	3.5	37.2	12.2	1.2
2021	50.1	16.1	2.3	67.0	19.8	3.6	39.8	13.8	1.5
2022	51.1	16.9	2.6	69.2	19.5	4.1	40.1	15.2	1.6

As suggested by the dip in the rising trend of the annual 120 dB exceedance plots (Figure 7), 2020 had lower noise levels than 2019, which was expected due to the reduction in shipping activity related to COVID-19 restrictions (March et al., 2021). This effect was more evident at quarterly scale (Figure 8), where the monotonic increase in area affected evident in the Q1 data was interrupted by lower noise levels in Q2-Q4 for 2020, coinciding with the introduction of COVID-related lockdowns toward the end of Q1 in 2020. 

Figure 7. Percentage area of UK EEZ exceeding a range of broadband noise levels (100-140 dB re 1 µPa), annual average from 2018 to 2022. 

Figure 8. Percentage area of UK EEZ exceeding 120 dB re 1 µPa, quarterly average from 2018 to 2022. 

Further information

In addition to the total continuous sound level, which is generally dominated by shipping noise, another metric was also considered, known as ship noise excess level. This metric is the difference between the total continuous sound level and an estimate of the background sound level due to wind. The ship noise excess level thereby indicates the magnitude of the increase in noise caused by shipping, compared to naturally occurring noise. There is currently debate over whether this metric may be more relevant than the total continuous sound level for assessing the effect of shipping noise on marine life. Compared to the total continuous sound level (Figure 9), the ship noise excess level showed strong seasonal periodicity (Figure 10), with a peak in summer and trough in winter, caused by higher wind noise in winter reducing the excess level. This feature obscured the underlying trend in absolute shipping noise levels. There is also less confidence in this metric since, unlike the total continuous sound level, it cannot be directly validated against field measurements but instead depends on a modelled estimate of wind noise which cannot be directly measured (since ship noise is generally also present in measurements made in UK waters). For these reasons, it was concluded that the total continuous sound level was a more appropriate and reliable metric by which to assess the indicator.

Conclusions

Acoustic modelling indicates that continuous noise pollution became more prevalent in UK waters during the assessment period, 2018 to 2022, with the area of the UK EEZ exceeding 120 dB re 1 µPa increasing by 23%. A greater proportion of the Greater North Sea was affected by such noise levels (19.5% in 2022), compared to the Celtic Seas (15.2% in 2022). However, the increase in the prevalence of such noise levels across the assessment period was greater in the Celtic Seas, with a 39% increase between 2018 and 2022, compared to an 7% increase for the Greater North Sea. 

Although the UK has yet to set threshold values for GES in relation to this indicator, the increasing trend in the indicator reduces the likelihood that GES is being attained or will be attained in future without intervention. This also runs counter to commitments made by UK Government under the OSPAR Convention, which has committed to reduce underwater noise to levels that do not affect the marine environment by 2030 (OSPAR, 2021). Action to reduce underwater noise from shipping is being taken at the IMO, and area-specific measures such as ship speed restrictions or rerouting of shipping lanes are available to UK policymakers. 

Knowledge gaps

The major knowledge gap for the assessment of GES for continuous anthropogenic sound is the relationship between levels of continuous anthropogenic sound and effects at the population scale. Although for some marine mammal species, models estimating this relationship exist, such predictions are highly uncertain and for most species the necessary data are not available. For this reason, a precautionary approach to setting threshold values for GES will be necessary, given the uncertain magnitude of impact on marine fauna populations. 

Further information

In addition to the abovementioned uncertainties regarding the degree of population-level effects from continuous noise pollution, further knowledge gaps relate to uncertainties in the acoustic modelling. Each of the acoustic model components is subject to its own uncertainties: ship source level, propagation loss (especially the effect of the seabed), and wind noise model (this is only significant for the ship noise excess calculations). 

The ship source model used the JOMOPANS-ECHO model (MacGillivray and de Jong, 2021) that represents the state-of-the-art in ship source estimation according to vessel class and speed. Nevertheless, it is derived from data gathered on the west coast of Canada, and so there may be differences in the noise outputs of different vessel classes based on differences in the fleet operating in UK waters. The variation of noise output with speed is also based on a simple power law scaling for all vessels, which may be overly simplistic in many cases. Testing of the performance of the JOMOPANS-ECHO model via comparison with calibrated ship source measurements in UK waters would allow better quantification of the extent of these uncertainties. 

Modelling sound propagation in shallow waters has always been challenging due to the strong influence of the seabed composition and the poor availability of seabed composition data to depths relevant for acoustic modelling. Even relatively simple propagation environments (e.g. sandy seabed) are challenging to model a priori, and in practice where high accuracy modelling is required, it is necessary to make acoustic measurements of sound propagation to reliably estimate the seabed acoustic properties (a process known as geoacoustic inversion). There are therefore significant uncertainties in the sound propagation model, although the optimization of this model via measurements has reduced the errors significantly (Cefas, 2022). 

The validation of the model using field measurements remains limited in terms of spatial coverage, with only three sites in English and Welsh waters used to validate the model, all of which are relatively near the coast. Extending this validation to cover a wider range of UK waters, particularly in Scotland and in offshore waters, would improve confidence in the model predictions. 

Reducing these sources of uncertainty will improve the accuracy of the indicator assessment. However, it is unlikely to affect the overall conclusion of an increasing prevalence of continuous noise pollution from shipping over the course of the assessment period.  

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Authors

Nathan Merchant¹, Adrian Farcas¹, Rosalyn Seddon¹ 

 

¹Centre for the Environment, Fisheries and Aquaculture 

Assessment metadata

Assessment Type	UK Marine Strategy
	Descriptor 11. Introduction of energy, including underwater noise
	Continuous low frequency sound (ambient noise)
Point of contact email	marinestrategy@defra.gov.uk
Metadata date	Wednesday, January 1, 2025
Title	Ambient Noise (continuous low frequency sound)
Resource abstract
Linkage
Conditions applying to access and use	© Crown copyright, licenced under the Open Government Licence (OGL).
Assessment Lineage
Dataset metadata
Dataset DOI	Farcas, Merchant, and Seddon. (2025). UK Marine Strategy Descriptor 11 ship noise assessment data for 2018 to 2022. Cefas, UK. V1. doi: https://doi.org/10.14466/CefasDataHub.172

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