Ship traffic noise distribution in the Polish Baltic ...€¦ · Ship traffic noise distribution in...

Ship traffic noise distribution in the Polish Baltic

waters – results of BIAS EU project

Jarosław Tęgowski1, Thomas Folegot2, Radomił Koza1, Karolina Trzcińska1,

Iwona Pawliczka1, Jakub Zdroik1, Krzysztof Skóra1

1 Institute of Oceanography, University of Gdansk, al. Marszałka Piłsudskiego 46

81-378 Gdynia, Poland2 QUIET-OCEANS, 65 Place Nicolas Copernic, 29280 Plouzané, France

10th EAA INTERNATIONAL SYMPOSIUM ON HYDROACOUSTICSXXXIII Symposium on Hydroacoustics, May 17-20, 2016, Jastrzębia Góra, Poland

10th EAA International Symposium on Hydroacoustics, Jastrzebia Gora, May 17-20, 2016

Since World War II, the average level of the ambient noise increased by 12-15 dB (Bjørnø, 1998)

Bjørnø, L., 1998, Man-made contributions to ambient noise in the seas. Alippi, A. and Cannelli, G. B. Proceedings of the Fourth European Conference on Underwater Acoustics, Rome 2, 543-548.


The hearing ranges of different kinds of fish and mammals together with

the overlap in frequency with different sources of human-generated noise

from Slabbekoorn et al. (2010)

Baltic Sea Information on the Acoustic Soundscape - BIAS

• EU-Life+ project (2012-2016)

• Goals:

Implementation of MSFD Descriptor 11 in the Baltic Sea region

Establishing a baseline for continuous sound by measurements and

soundscape modeling

Establishing of a joint management, for e.g. handling of data and registry –

standards

Developing tools for handling of Descriptor 11.2.


MSFD - Marine Strategy Framework Directive


What the EC (LIFE +) is expected from the BIAS project?What will be the main result of the project?

BIAS - brochure


EQUIPMENT

WildLife Acoustics SM2M24 kHz – sampling frequency16 bits – resolution216=65536Dynamics: 20log10(216)=96 dB

POSITIONS OF 38 ACOUSTIC DATA LOGGERS DEPLOYEDIN THE BALTIC SEA

Swedish Defence Research Agency (FOI)

Finnish Environment Institute (SYKE)

Tallinn University of Technology (TUT)

Foundation of the Development ofUniversity of Gdansk (FRUG)

Institute for Technical and Applied Physics (ITAP)

German Maritime and Hydrographic Agency (BSH)

University of Southern Denmark (SDU)

Aarhus University (A)


377 000 km2

1 601 km max length

459 m max depth

40+ monitoring stations

12 months of continuous

measurement

2 monitoring categories (A & B)


• Category A Monitoring - to establish

information on the ambient noise in

a location and to ground truth noise

prediction, < 5 km?

• Category B Monitoring- to reduce

uncertainty on source levels to be used

as the input for modelling, close to shipping

lane



• Recording minimum one channel

• Gain 0/20 dB

• Hydrophone bandwidth min 10 Hz - 12 kHz

• Sampling rate: min 24 kHz

• Duty cycle: min 17 min per hour


Puck Bay

Gulf of Gdansk

2

1

b)a) Map of the areas where buoys were deployed

1) Gulf of Gdańsk (71m)

2) Puck Bay (30m)

3) Łeba (16.4m)

4) Darłowo – Ustka (40m)

5) Świnoujście (12 m)

b) Number of ship routes at Puck Bay and Gulf of

Gdansk

POSITINS OF 5 ACOUSTIC DATA LOGGERS DEPLOYEDIN THE POLISH PART OF THE BIAS PROJECT

a)

OUR BOAT „ZELINT”


Hel Marine Station of the UG Institute of Oceanography

DEPLOYMENT



RIG ON THE BOTTOM



RECOVERY



RESULT OF THE TRAWL-NET STRIKE ON THE RIGS

The reasons of data gaps:

Station 1 – one of the SD cards was found thrown out of the socket, possible reason – trawl net strike

Station 2 – battery failure

StationLast deployment

dateDays since 1st of January till last

deploymentDays of recording Rec/Total

1 05-10-2014 278 239 0,86

2 21-11-2014 325 319 0,98

3 15-10-2014 288 288 1

4 17-10-2014 290 290 1

5 13-10-2014 286 286 1

ACOUSTIC DATA TIME COVERAGE

QUALITY OF MEASUREMENTS


𝑀𝑆𝑃 = 𝑝𝑟𝑚𝑠2 =

1

𝑇න

0

𝑇

𝑝 𝑡 2𝑑𝑡

𝑝𝑟𝑒𝑓 = 1 µPa

• MSP – Mean Square Pressure

• RMS – Root Mean Square

• SPL – Sound Pressure Level

• SEL – Sound Exposure Level

• PSL – Peak Sound Level

• SNR – Signal to Noise Ratio

• PSD – Power Spectra Density

• PDF – Probability Density Function

𝑆𝑃𝐿 = 10𝑙𝑜𝑔10𝑝𝑟𝑚𝑠2

𝑝𝑟𝑒𝑓2 [dB 𝑟𝑒 1µPa]

METRICS USED IN SOUND LEVEL ASSESSMENT

SPL is the mean square pressure (MSP) relative to reference pressure pref



EXAMPLE OF SPL63Hz AND SPL125Hz VARIATION AT B1

WIND AND HEAVY SHIPPING TRAFFIC

1/3 octave bands

SPL63,125 independed

on wind speed

Depth 71m-80 m

AIS and VMS data


SPL2000,total depended

on wind speed

EXAMPLE OF SPL2000Hz AND SPL10Hz-10kHz VARIATION AT B1

WIND AND HEAVY SHIPPING TRAFFIC

AIS and VMS data

Depth 71m-80 m

MONTHLY AVERAGED NOISE SPECTRUM LEVEL, STATION B1, JANUARY – DECEMBER 2014



AVERAGED NOISE SPECTRUM LEVEL, STATION B1, JANUARY 2014


MONTHLY AVERAGED NOISE SPECTRUM LEVEL, STATION B5, JANUARY – DECEMBER 2014


AVERAGED NOISE SPECTRUM LEVEL, STATION B3, MARCH 2014


CUMULATIVE CURVES OF SPL FOR 63 Hz, 125 Hz AND 10 Hz – 10 kHz - 2014 YEAR

1

23

4

5

1

23

4

5

1

23

4

5

ships

ships

ships


SOUND PRESSURE LEVEL, 1/3 OCTAVE 125 Hz, FEB. – NOV. 2014POLISH ECONOMICAL ZONE, DEPTH = 10 m


SOUND PRESSURE LEVEL, 1/3 OCTAVE 63 Hz, JANUARY 2014BALTIC SEA

Percentile 05%Layer 1Depth 10 m


HOW TO CLASSIFY DIFFERENT SOURCES OF UNDERWATER AMBIENT NOISE?

PARAMETRICAL ANALYSIS

Example of 12 hours and 25 min continuous underwater ambient noise

registration by recorder number 1 at 11th of June 2014.

ships


Example of 12 hours and 25 min continuous underwater ambient noise

registration by recorder number 1 at 11th of June 2014

63Hz and 125Hz


1Alog1log~

10

max

10

S

SAS

The normalized power spectrum of ambient noise is defined as:

where A=105 – const., S() - power spectral density function and its maximum

value Smax(). The classification parameters were defined as the relationships

between parts of spectral density functions:

where m=2, 4, 8, 16 and fNy is the Nyquist frequency.

Ny

1

fm

1

0f

)(~1

dffSS

Dqm

PARAMETRICAL ANALYSIS OF AMBIENT NOISESPECTRAL AND WAVELET PARAMETERS OF AMBIENT NOISE

Ny

1

m

fm

1

0f

f

~1dfS

SS


The spectral moments of the r-th order: ωdωSωm r

r

0

spectral skewness:

40

2

2402

mm

mmm 1-

2

1

202

m

mm

23

2

3

m~

m~

spectral widths:

max

min

d,2

3,

b

b

Coifj bbaCE

SPECTRAL AND WAVELET PARAMETERS OF AMBIENT NOISE

7-channel dyadic decomposition (scale a = 2j, j=1,..,7)

3th-order Coiflet wavelet

where C(a,b) is the wavelet transformation coefficient, bmin and bmax are

boundary values of scale b (time)


NOISE SOURCES CLASSIFICATION ALGORITHM

Input vector of 23 spectraland wavelet parameters

computed for each 1 second segment of signal

Reduction of inputdata quantity

Principal ComponentAnalysis

3 uncorrelatedPrincipal Components

Segmentation algorithm Unsupervised Kohonen’s

neural networkor

Fuzzy c-meanscluster analysis

Decision about thenumber of clusters

Calinski-Harabaszstatistical criterion

or (and)Subtractive Cluster

Analysis

Clu

ste

rs


PRINCIPAL COMPONENTS

Ship noise


Clu

ste

rs

Samples x 108

Results of fuzzy logic clusterization algorithm

bottom picture – indication of ships


CONCLUSIONS

We have knowledge about levels and sources of underwater

ambient noise in the Baltic Sea.

Goals of project were accomplished successfully.

BIAS standards.

THANK YOU FOR YOUR ATTENTION


Ship traffic noise distribution in the Polish Baltic ...€¦ · Ship traffic noise distribution in...

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