MATERIALS and GEOENVIRONMENT MATERIALI in GEOOKOLJE RMZ – M&G, Vol. 67, No. 4 pp. 161–219 (2020) ISSN 1408-7073 Ljubljana, December 2020 RMZ – Materials and Geoenvironment RMZ – Materiali in geookolje ISSN 1408-7073 Old title/Star naslov Mining and Metallurgy Quarterly/Rudarsko-metalurški zbornik ISSN 0035-9645, 1952–1997 Copyright © 2020 RMZ – Materials and Geoenvironment Published by/Izdajatelj Faculty of Natural Sciences and Engineering, University of Ljubljana/ Naravoslovnotehniška fakulteta, Univerza v Ljubljani Associated Publisher/Soizdajatelj Institute for Mining, Geotechnology and Environment, Ljubljana/ Inštitut za rudarstvo, geotehnologijo in okolje Velenje Coal Mine/Premogovnik Velenje Slovenian Chamber of Engineers/Inženirska zbornica Slovenije Editor-in-Chief/Glavni urednik Boštjan Markoli Assistant Editor/Pomocnik urednika Jože Žarn Editorial Board/Uredniški odbor Cosovic, Vlasta , University of Zagreb, Croatia Delijic, Kemal, University of Montenegro, Montenegro Dobnikar, Meta, Ministry of Education Science and Sport, Slovenia Falkus, Jan, AGH University of Science and Technology, Poland Gojic, Mirko, University of Zagreb, Croatia John Lowe, David, British Geological Survey, United Kingdom Jovicic, Vojkan, University of Ljubljana, Slovenia/IRGO Consulting d.o.o., Slovenia Kecojevic, Vladislav, West Virginia University, USA Kortnik, Jože, University of Ljubljana, Slovenia Kosec, Borut, University of Ljubljana, Slovenia Kugler, Goran, University of Ljubljana, Slovenia Lajlar, Bojan, Velenje Coal Mine, Slovenia Malbašic, Vladimir, University of Banja Luka, Bosnia and Herzegovina Mamuzic, Ilija, University of Zagreb, Croatia Moser, Peter, University of Leoben, Austria Mrvar, Primož, University of Ljubljana, Slovenia Palkowski, Heinz, Clausthal University of Technology, Germany Peila, Daniele, Polytechnic University of Turin, Italy Pelizza, Sebastiano, Polytechnic University of Turin, Italy Ratej, Jože, IRGO Consulting d.o.o., Slovenia Ristovic, Ivica, University of Belgrade, Serbia Šaric, Kristina, University of Belgrade, Serbia Šmuc, Andrej, University of Ljubljana, Slovenia Tercelj, Milan, University of Ljubljana, Slovenia Vulic, Milivoj, University of Ljubljana, Slovenia Zupancic, Nina, University of Ljubljana, Slovenia Zupanic, Franc, University of Maribor, Slovenia Editorial Office/Uredništvo Technical editors/Tehnicna urednika Blaž Janc and Jože Žarn Secretary/Tajnica Nives Vukic Editorial Address/Naslov uredništva RMZ – Materials and Geoenvironment Aškerceva cesta 12, p. p. 312 1001 Ljubljana, Slovenija Tel.: +386 (0)1 470 46 10 Fax.: +386 (0)1 470 45 60 E-mail: bostjan.markoli@ntf.uni-lj.si joze.zarn@ntf.uni-lj.si Published/Izhajanje 4 issues per year/4 številke letno Partly funded by Ministry of Education, Science and Sport of Republic of Slovenia./Pri financiranju revije sodeluje Ministrstvo za izobraževanje, znanost in šport Republike Slovenije. Articles published in Journal “RMZ M&G” are indexed in international secondary periodicals and databases:/Clanki, objavljeni v periodicni publikaciji „RMZ M&G“, so indeksirani v mednarodnih sekundarnih virih: CA SEARCH® – Chemical Abstracts®, METADEX®, GeoRef. The authors themselves are liable for the contents of the papers./ Za mnenja in podatke v posameznih sestavkih so odgovorni avtorji. Annual subscription for individuals in Slovenia: 20 EUR, for institutions: 30 EUR. Annual subscription for the rest of the world: 30 EUR, for institutions: 50 EUR/Letna narocnina za posameznike v Sloveniji: 20 EUR, za inštitucije: 30 EUR. Letna narocnina za tujino: 30 EUR, inštitucije: 50 EUR Transaction account/Tekoci racun Nova Ljubljanska banka, d. d., Ljubljana: UJP 01100-6030708186 VAT identification number/Davcna številka 24405388 Online Journal/Elektronska revija https://content.sciendo.com/view/journals/rmzmag/rmzmag-overview. xml?result=4&rskey=iClOT4# Table of Contents Kazalo Dolocevanje znacilnosti obmocja za inženirske namene z uporabo geofizikalnih in geotehnicnih metod Original scientific papersIzvirni znanstveni clanki Underwater noise in the Slovenian Sea 161 Podvodni hrup v slovenskem morju A. Popit Monitoring after the conclusion of mining works Laboratorijske preiskave abrazivnosti kamnin in zemljin na podrocju geotehnologije in rudarstva 177 T. Hribar, T. Pecolar, G. Vižintin Estimation of Depth to Bouguer Anomaly Sources Using Euler Deconvolution Techniques Ocena globine do virov Bouguerjeve anomalije z uporabo Eulerjevih dekonvolucijskih tehnik 185 G. O. Layade, H. Edunjobi, V. Makinde, B. Bada Site characterization for engineering purposes using geophysical and geotechnical techniques 197 A. A. Alabi Geochemical Fingerprinting pf Oil-Impacted Soil and Water Samples In Some Selected Areas in the Niger Delta Geokemicni kazalniki z nafto nasicenih vzorcev zemljin in vode na nekaterih izbranih podrocjih delte reke Niger A. V. Adeniyi, M. E. Nton, F. O. Adebanjo Original Scientific Article Received: March 08, 2021 Accepted: March 09, 2021 DOI: 10.2478/rmzmag-2020-0018 Underwater noise in the Slovenian Sea Podvodni hrup v slovenskem morju Andreja Popit* Institute for Water of the Republic of Slovenia, Ljubljana, Slovenia *andreja.popit@izvrs.si Abstract Continuous underwater noise has been monitored in the Slovenian sea near the lighthouse foundation at DebeliRticsinceFebruary2015,accordingtotheEU Marine Strategy Framework Directive (MSFD). An­thropogenic noise sources (e.g. seawater densities, dredging activitiesand cleaning of the seafloor) and meteorological noise sources (e.g. wind speed and pre­cipitation) were analysed in relation to the measured underwater noise levels using several graphical and statisticalmethods.Theresultsofthisstudyshowed that average equivalent continuous underwaternoiselevels were, by 11 dB (Leq,63 Hz) and 5 dB (Leq,125 Hz), high­er in the intervals when dredging activities took place than in the intervals when these activities were absent. Variation in underwater noise levels was partly related tothevariationoftheshipdensities,whichcouldbe explained by the relatively small acoustic propagation in the shallow seawater. Precipitation level did not in-dicateany significantassociationwiththevariations in continuous underwater noise levels,though some larger deviations in the wind speed were found to be associatedwiththelargerfluctuationsincontinuous underwater noise levels. Keywords: underwater noise, shallow sea, measuring equipment, natural and anthropogenic sound sources Introduction The background or ambient noise in the seas and oceansiscomposedofnatural(i.e.meteorolog­ical (wind speed, surface waves,precipitation), geological (tectonic processes) and biological)and anthropogenic (i.e. marine traffic) noisesources. It varies with the location and frequencyof underwater sound. In regions with high Povzetek V slovenskem morju izvajamo kontinuirne meritve podvodnega hrupa ob svetilniku pri Debelem rticu od februarja 2015. Meritve potekajo v skladu z Okvirno direktivo o morski strategiji. Za analizo antropogenih virov hrupa (gostota ladij, poglabljanje in cišcenje morskega dna) in meteoroloških virov hrupa (hitrost vetra in padavine) v povezavi z izmerjenimi ravnmi podvodnega hrupa smo uporabili graficne in statisticne metode. Rezultati te študije so pokazali, da so bile povprecne ekvivalentne ravni kontinuirnega podvodnega hrupa za 11 dB (Leq, 63 Hz) in 5 dB (Leq,125 Hz) višje v casu, ko so potekale dejavnosti poglabljanja, kot v casu, ko so teh dejavnosti ni bilo. Nihanja ravni podvodnega hrupa so bila v manjši meri povezana z nihanji gostote ladij, kar lahko razložimo z relativno majhno akusticno propagacijo v plitvem morju. Padavine niso bile veliko povezane z nihanji ravni podvodnega hrupa, medtem ko so bila nekatera vecja nihanja hitrosti vetra povezana z vecjimi nihanji ravni kontinuirnega podvodnega hrupa. Kljucne besede: podvodni hrup, plitvo morje, merilna oprema, naravni in antropogeni viri zvoka shippingdensities, the frequency band between 10Hzand200Hzisprimarilyassociatedwithshipping activity, constituting the largest anthro­pogenic contribution to the underwater ambientsound [1–11]. Most of the noise power radiated into thewater by surface ships comes from propellercavitation [1, 4, 12]. Propellernoise is generatedthrough several cavitation noise mechanisms: tip vortex cavitation, different types of bladecavitation, hub vortex cavitation, pressure puls­esduetowakeinhomogeneityatthepropellerplane, pressure pulses generated by the rotatingpropellerbladesandsingingduetoresonancebetweenbladenaturalfrequenciesandtrailingedge vortices. Some vesselsemit strongstruc­turalnoiseradiationarisingfromtheirhydrau­lic systems,gears,compressorsor othernoisy machinery [4]. An increase in the low-frequency ocean ambient noise levels was observed between 1963 and 2001 on the continental slope ofPoint Sur, California [7, 8, 13], between 1964and 2004, westwards of the San NicolasIsland, California [14] and between 1978and 1986 in the Northeast Pacific Ocean [15].Thiswasrelatedtotheshippingvesseltraf­fic. The numberof commercialvessels in the world’s oceans approximately doubled andthe gross tonnage quadrupled between 1965and 2003, with a corresponding increase in horsepower of the vessels. Increases in com-mercialshippingarebelievedtoaccountfor the observed increase in the low-frequency ambient noise [14]. More recently, between 2006 and 2016, observationsmade in the Northeast Pacific, Equatorial Pacific and in the South AtlanticOcean show a slightly decreasing trend in low-frequency ambient noise levels [16, 17]. This trend may be attributed to the fact thatworld vesselsize and gross tonnage have in­creased considerably over the recent years, while the number of vessels has decreased [18–21]. Wind-generated sea-surface agitation gov­erns much of the ambient noise in the fre­quency band between 200 Hz and 100,000 Hz.Wind-generated noise is largely the conse­quence of bubbles created in the processof wave-breaking. At lower frequencies(<500 Hz), the oscillation of bubble cloudsthemselves areconsidered to be the source of the sound [22, 23] while,at higher frequen­cies (>500 Hz), the excitation of resonant os­cillations by individual bubbles generates thesound [7, 24, 25]. At veryhigh frequencies, ~100,000 Hz, ther­mal noise generated by the random motion of water molecules begins to dominate. The thermal noise spectral density at 100,000Hz is 20–25dB re 1mPa2/Hz [7]. Rain can produce a peak in the ambientsound pressure spectral density (around60dB re 1mPa2/Hz) in the vicinity of 15kHz,corresponding to rain rates ranging from2 mm/h to 5 mm/h, measured at differentwind speeds [7, 26]. Underwater ambient noise is generatednot only by the combination of environmen­tal sea state and anthropogenic contributions (e.g. shipping), but also by significantamounts of biological noise from fish, inver­tebrates and whales. Biological noise maygenerate major background noise in some areas. Marine mammals, such as whales anddolphins, rely on sound to communicate witheach other, locate their prey and find their wayover long distances. All these activities, criti­cal to their survival, are being interfered withby the increasing levels of noise from ships[1, 4, 27–33]. The European Commission’sMarine Strategy Framework Directive (MSFD)2008/56/EC[34] and International MaritimeOrganization( IMO) guidelines for the reduc­tion of underwater noise from commercial shipping [35] have addressed underwaternoise pollution from shipping, as well as the promotion of the use of the appropriate miti­ gation measures.The EC MSFD 2008/56/EC [34] guidelines require the Member States to prepare a Marine Management Plan. These requirements were incorporated in Slovenian law by passing the Water Act [36] and by the Decree on the detailed content of the Marine management plan [37]. According to this legislation, Slovenia started to monitor continuous underwater noise near the lighthouse foundation at Debeli Rtic since February 2015. The aim of our study was to analyse con­tinuous underwater noise measurements from 2015 until 2018. The measured ambient low-frequency noise levels were most probably due to anthropogenic activities such as marine traf­fic, dredging activities and cleaning of the sea­floor, as well as to meteorological factors such as precipitation and wind. These levels were analysed through the proposed methodology and results of this study were discussed in this article. RMZ – M&G | 2020 | Vol. 67 | pp. 161–175 A. Popit Materials and methods Underwater noise measuring station and measured quantities A permanent underwater noise measurement station was established on the concrete foun­dation of a masonry lighthouse 300 m off the coast at Debeli Rtic, Slovenia in February 2015(Figure 1a). The coordinates of the lighthouseare Lat.: 45°35' 28.2" N, Lon.: 13°41' 59.1" E. The associated measuring equipment wascomposed of a spherical omnidirectional hydro­phone (Type 8105, Bruel &Kjaer ) installed at a depth of 4m (Figure 1b) (sea depth at thatlocation was 5 m). The hydrophone is con­nected to a sound analyser of Type 2250 Bruel&Kjaer, which includes a sound level meter andan octave-based frequency analyser, operat­ing in the frequency band of 6.3–20kHz. The hydrophone with a cable was installed througha metal pipe 1 m away from the lighthousefoundation to a depth of approx. 1m above theseabed, as shown in Figure 1b [38]. A soundanalyser was closed inside the lighthouse in awaterproof casing, according to the standardNational Electrical Manufacturers Association (NEMA) IP65 protocols, and maintaining resist­ance to water jets was ensured. The measuringsystem was connected to the batteries that werecharged by a solar panel [38, 39]. The mathematical definition of the meas­ured equivalent continuous sound level (Eq. 1)(also called time-average sound level), Leq, is 20times the logarithm to base 10 of the ratio of theroot mean square sound pressure (prms) duringa time interval to the reference sound pressure(p0, which is 1mPa) [40]: .p .2 .p . rms rms Lt =10 log =20 log (1) eq ()10 ˆ10 ˆ .p 0 ..p 0 . Root mean square of the sound pressure level (prms) (Eq. 2) in Pascals (Pa) [41] can be represented as: 1 ˆ2 1 prms =.-)˜2 pt ()2 dt (2) .1  tt .(2 1  where, Prms or the mean square sound pres­sure is the time integral of squared soundpressure over a specified time interval dividedby the duration of the time interval; and t1 and t2 are the start and stop times of the time in­terval over which the mean is evaluated. The RMS sound pressure is calculated by first squaring the values of sound pressure, averaging overthe specified time interval and then taking the square root. Figure 1: Location of the permanent underwater noise measurement station near Debeli Rtic in the Slovenian Sea (A) and a sketch of the lighthouse at Debeli Rtic on which the measuring equipment is installed showing the hydrophone at a depth of 4 m (sea depth at the location is 5 m) (B) [38]. Frequency analysis software enables deriva­tions ofthe equivalent continuous sound levels in 1/3-octave band with centre frequencies be­tween 6.3Hz and 20kHz, in the resolution of 10s. Daily arithmetic mean values were calcu­lated and recorded on a hard disc of 1 Terabyte (TB). The memory capacity of the disc enables recordings for 75days. Measured data were transferred, displayed and analysed using BZ-5503 Measurement Partner Suite [40] software. This software can be usedfor data archival, datapreview and data export, for post-process and export to other formats, online data display and remote access and operation, as well as for maintenance of the sound level meter software. With BZ-5503 Measurement Partner Suite,daily equivalent continuous sound levels (Leq val­ues) in the 1/3-octave band with centre frequen­cies between 6.3Hz and 20kHz were analysed. Methodology used for processing continuously measured data The first step in data processing was, in our case, done by the sound analyser of Type 2250 (Bruel & Kjaer ), which calculates equivalent continuous sound levels in 1/3-octave bands. Then we proceeded with the second step in data processing, to calculate the annual average of the continuous sound level. For monitoring and assessing anthropo­genic continuous low-frequency sound in wa­ter (D11C2) we used annual average of the squared sound pressure in 1/3-octave bands, one centred at 63Hz and the other at 125Hz, both expressed as a level in decibels in units of dB re 1mPa, according to the requirements of the Commission Decision EU/2017/848 [42]. The unit of measurement used for the criteria D11C2 is the annual average of the continuous sound level per unit area; proportion (percent­age) of extent in square kilometres of the as­sessment area. For this purpose we used the arithmetic mean (AM) in time T [43] (Eq. 3), which shows compatibility with Leq metric: 1 .() ()(3) AMT ()=NTpT n =1 NT n () RMZ – M&G | 2020 | Vol. 67 | pp. 161–175 where N(T) is the number of snapshots of duration T in 1year (Eq. 4) (assuming that the data are continuous, and contain no gaps for an entire year): () 1year NT =(4) T where pn(T) is the mean square sound pres­sure at the n-th snapshot of duration T. The arithmetic mean is expressed assound pressure level (SPL) (Eq. 5) in dB re mPa [43]: AM T () LT =log (5) ()10 AM 10 2 p ref where pref = 1mPa. Annual averages of the continuous sound level and standard deviation (STDEV) for 1/3-octave bands with centre frequencies of 63Hz and 125Hz were calculated using daily averages, which were calculated using the sound analyser. The results of the underwater noise meas­urements from the measuring station at DebeliRtic were analysed and reviewed using theBZ-5503 Measurement Partner Suite Software [39]. The equivalent unweighted continu­ous noise levels within 1/3-octave frequencybands with centre frequencies of 63Hz Leq,63Hz and 125 Hz Leq,125 Hz (in dB), according to the MSFD 2008/56/EC [34], were exported intoan excel spreadsheet for further analyses.The underwater noise data were available at half-hour intervals for the following peri­ods: from 13 February 2015 to 5 May 2015;26 September 2015 to 31 December 2015; 18August 2016 to 1 November 2016; 6 July 2017to 27 August 2017; and 18 August 2018 to 31December 2018. Average hourly values of equivalent con­tinuous underwater noise levels in 1/3-octave bands with centre frequencies of 63 Hz and 125 Hz for each measuring period were pre­pared and presented on diagrams. Asymmetry (A) (Eq. 6) was used totest the normality of the distribution ofunderwater noise levels. Asymmetry was A. Popit used to indicate the direction of data asymmetry [44]: A = (6) where m2 and m3 are the second and third moments around the average. The j-th moment is calculatedby the Eq. (7), represented below [44]: n .( xi -x _) j i =1 (7) m = j n When A is 0, the data set is symmetric to itsmean and the data are distributed symmetri­cally or normally (Gaussian distribution).At A < 0 the data are asymmetric to the left and at A > 0 the data are asymmetric to the right. If A < -1 or A > 1 the distribution is very asymmetric. If A is between -1and -0.5 or between 0.5 and 1, the distribution is moderately asymmet­ric. If A falls between -0.5 and 0 or between 0 and 0.5, the distribution is approximately symmetric. The statistics were calculated in Excel (Microsoft). Methodology for the analysis of anthropogenicsources (ship densities, dredging and cleaningactivities) of the underwater noise in thecanals of the Port of Koper Marine traffic in the sea is monitored with the Automatic Information System (AIS). Obtained AIS dataconcerning locations of the ships were analysed in the North Adriatic Sea for 2015, 2016, 2017 and 2018 to prepare hourly data on the ship densities in four different areas around the underwater noise measuring station at the lighthouse at Debeli Rtic, Slovenia. These four areas were namely within a radii of 2nautical miles (NM) and 5NM from the measuring sta­tion, in the Gulf of Trieste and the Gulf of Venice. Data on ship densities were prepared for each period during which underwater noise levels were recorded. Average hourly ship densities in all four ar­eas around the measuring station, for each Underwater noise in the Slovenian Sea period in which underwaternoise levels were recorded, were presented graphically in com­bination with the average hourly continuous underwater noise levels in 1/3-octave bands with centre frequencies of 63Hz and 125Hz. Asymmetry (A) was used to test the normality of the distribution of ship densities. Dredging activities were carried from7 September 2015 to 26 October 2015 from7:00–21:00 h, while cleaning activities of theseafloor in the canals of the Port of Koperwere carried out from 18 August 2016 to 31August 2016, and from 22 September2016 to29 September 2016 from 8:00–16:00h (Table1). Dredging was carried out in the sea with adredger and a trailed harrow for levelling theseabed, while the cleaning work was carried outfrom the mainland with the help of the Link-BeltLS-108B excavator crane. On the diagram concerning ship density in the four areas around the measuring station in combination with the average hourly con­tinuous underwater noise levels in 1/3-octave bands with centre frequencies of 63 Hz and 125 Hz, were drawn red arrows indicating dredging and cleaning activities. Average equivalent continuous underwater noise levels during dredging and cleaning activ­ities were analysed. Separately, average equiv­alent continuous levels of underwater noise were analysed at the time when there were no anthropogenic activities (Table 1). These analy­ses were performed to check whether the aver­age values (AVE) of equivalent continuous un­derwater noiselevels, in 1/3-octave bands with centre frequencies of 63Hz and 125Hz at the time ofdredging and cleaning activities, were higher than at the time when these activities were not being executed. Methodology for the analysis of meteorologicalsources of the underwater noise In this section, wind speed and precipitation were analysed as meteorological sources of underwater noise. Half-hourly data on wind speeds (m/s) from the Piran buoy (Lon.: 13.5454°, Lat.: 45.5481°, altitude: 0 m) and half-hourly data on precipitation (mm) from the meteorological station in the Port of Koper (Lon.: 13.7448°, Lat.: 45.5645°, Altitude: 2m), in the periods in which underwater noise Table 1: Periods with and without the anthropogenic activity Type of anthropogenic Periods with the activity anthropogenic activity 26.09.2015–26.10.2015 Dredging (7:00–21:00h) 18.08.2016–31.08.2016 & Cleaning of the seafloor 22.09.2016–29.09.2016 (8:00–16:00h) Periods without any anthropogenic activity 26.09.2015–26.10.2015 (22:00–6:00h) 18.08.2016–31.08.2016 & 22.09.2016–29.09.2016 (17:00–7:00h) levels were recorded, were obtained from the Environmental Agency of the Republic of Slovenia (ARSO). Average hourly wind speeds and precipi­tation levels in the individual periods werecalculated and presented graphically in com­bination with average hourly continuous un­derwater noise levels in 1/3-octave bandswith central frequencies of 63Hz and 125Hz.Furthermore, asymmetry (A) was used to testthe normality of the distribution of the aver­age hourly wind speeds and average hourlyprecipitation data. Results The average continuous underwater noise lev­els in the 1/3-octave bands with centre fre­quencies of 63Hz (Leq,63Hz) and 125Hz (Leq,63Hz) in dB re 1 mPa, average ship densities in the four areas around the measuring station (rL,2NM, rL,5NM, rL, Trieste. and rL, Venice), average wind speeds (vv) in m/s and average precipitation (hp) in mm in each measurement period are presented in Table 2. The average Leq,63Hz and Leq,125Hz levels meas­ured in the Slovenian Sea during the period 2015–2018 (Table 2) were 82.8–101.1 dB re 1mPa and 83.9–98.1dB re 1mPa, respectively. The ship densities were 2–252. The average wind speed was 1.8–4.6m/s and the average precipitation was 0.02–0.07mm. The Leq,125 Hz data were distributed close to the normal (Gaussian) distribution in all meas­uring periods (they were slightly asymmetric to the right or left), as the value of A was close to 0 (Table 3). The Leq,63 Hz data were distrib­uted moderately asymmetrically to the right RMZ – M&G | 2020 | Vol. 67 | pp. 161–175 (A = 0.5–1.1), except for the period from 18 August 2016 to 1 November 2016, when they were distributed approximately symmetrically (A = -0.4) (Table 3). The rL,2NM datawere distributed moderately asymmetrically to the right in all measuring pe­riods and the rL,5NM data and rL, Trieste were dis­tributed very asymmetrically to the left in the first two periods, very asymmetrically to the right in the third and fifth periods and approxi­mately symmetrical in the fourth period. The rL, Venice data were moderately asymmetrically distributed to the left in the first two periods, and moderately asymmetrically to the right to approximately symmetrically in the other peri­ods (Table 3). The vv data were distributed very asym­metrically to the right in all measuring periods, except in the period from 18 August 2016 to 1 November 2016, in which they were distribut­ed moderately asymmetrically to the right. The hp data were distributed very asymmetrically to the right in all measuring periods (Table 3). The relationship of the measured ambient low-frequency noise levels with the anthropo­genic activities (ship densities, dredging and cleaning activities) is shown in the diagrams (Figures 2–6) of the average hourly ship den­sities in the four areas around the underwater noise measuring station (rL,2NM, rL,5NM, rL, Trieste. and rL, Venice) in combination with the average hourly continuous underwater noise levels in 1/3-octave bands with centre frequencies of 63Hz and 125Hz. Blue curve presents Leq,63Hz, black curve presents Leq,125Hz, violet curve pre­sents ship density 2 NM from the measuring station, yellow curve presents ship density 5NM from the measuring station, green curve presents ship density in the Gulf of Trieste and A. Popit Table 2: The results of AVE and STDEV calculations of L, L, r, r, r, r dredging, cleaning activity, eq,63 Hz eq,125 Hz L,2 NM L,5 NM L, Trieste L, Venice, vv and hp in different measuring periods Average of From From From From From AVE and 13.02.2015 to 26.09.2015 to 18.08.2016 to 06.07.2017 to 18.08.2018 to STDEV 05.05.2015 31.12.2015 01.11.2016 27.08.2017 31.12.2018 AVE & STDEV of L eq,63Hz AVE & STDEV of L eq,125Hz 83.0±15.1 89.0±13.1 82.8±10.8 83.9±2.5 101.1±6.9 97.5±6.8 86.7±7.7 85.2±3.3 88.6±5.7 98.1±3.9 AVE & STDEV of rL,2NM 2±2 3±2 5±3 5±3 5±3 AVE & STDEV of rL,5NM 24±9 37±7 45±6 52±6 52±8 AVE & STDEV of rL, Trieste 35±13 50±10 58±8 71±9 70±11 AVE & STDEV of rL, Venice 117±52 186±51 252±53 246±48 247±56 AVE & STDEV of v v 4.6±3.3 4.5±3.8 4.6±2.7 1.8±1.2 2.0±1.6 AVE & STDEV of h p 0.02±0.13 0.04±0.35 0.07±0.61 0.02±0.31 0.05±0.32 AVE, average value; NM, nautical miles; STDEV, standard deviation. Table 3: The results of asymmetry (A) calculations of L, L dredging, cleaning activity, eq,63 Hz eq,125 Hz , rL,2 NM , rL,5 NM , rL, Trieste , rL, Venice, vv and hp in different measuring periods Asymmetry From From From From From 13.02.2015 to 26.09.2015 to 18.08.2016 to 06.07.2017 to 18.08.2018 to 05.05.2015 31.12.2015 01.11.2016 07.08.2017 31.12.2018 A of L eq,63Hz 1.0 0.5 -0.4 1.1 0.6 A of L eq,125Hz 0.2 0.1 0.0 0.1 -0.1 A of rL,2NM 0.8 0.7 0.6 0.6 1.0 A of rL,5NM -1.7 -3.0 1.1 0.4 2.0 A of rL, Trieste -1.6 -2.8 1.1 0.2 1.4 A of rL, Venice -0.7 -0.6 0.6 0.8 0.5 A of v v 1.1 1.2 0.8 1.1 2.4 A of h 20.5 16.2 14.8 22.4 10.9 p NM, nautical miles. brown curve presents ship density in the Gulf of Venice (Figures 2–6). Many gaps in the ship densities in 2015 (evident in Figures 2 and 3) and one major gap (evident in October 2018 in Figure 6) were due to the reason that AIS System did not operate during these periods. The red arrow on the diagram of aver­age hourly ship densities (Figure 3) indicates dredging activities, which took place from 26 September 2015 to 26 October 2015. The red arrows on the diagram of average hourly ship densities (Figure 4) show cleaning activi­ties at the seafloor in the canals of the Port of 168 140 Leq,125Hz (dB) 450 Leq,63Hz (dB) 120 Shipdensities 2 NMfrom the measuring station 400 Ship densities 5 NMfrom the measuring station Ship densities inthe GulfofTrieste 350 100 300 0 :10 5102.90.62 0 :30 5102.90.82 30.09.2015 05:00 2.10.2015 07:00 4.10.2015 09:00 6.10.2015 11:00 8.10.2015 13:00 10.10.2015 15:00 12.10.2015 17:00 14.10.2015 19:00 16.10.2015 21:00 18.10.2015 23:00 21.10.2015 01:00 23.10.2015 03:00 25.10.2015 05:00 27.10.2015 07:00 29.10.2015 09:00 31.10.2015 11:00 2.11.2015 13:00 4.11.2015 15:00 6.11.2015 17:00 8.11.2015 19:00 10.11.2015 21:00 12.11.2015 23:00 15.11.2015 01:00 17.11.2015 03:00 19.11.2015 05:00 21.11.2015 07:00 23.11.2015 09:00 25.11.2015 11:00 27.11.2015 13:00 29.11.2015 15:00 1.12.2015 17:00 3.12.2015 19:00 5.12.2015 21:00 7.12.2015 23:00 10.12.2015 01:00 12.12.2015 03:00 14.12.2015 05:00 16.12.2015 07:00 18.12.2015 09:00 20.12.2015 11:00 22.12.2015 13:00 24.12.2015 15:00 26.12.2015 17:00 28.12.2015 19:00 30.12.2015 21:00 0 :10 5102.20.31 0 :91 5102.20.41 16.02.2015 13:00 18.02.2015 07:00 20.02.2015 01:00 21.02.2015 19:00 23.02.2015 13:00 25.02.2015 07:00 27.02.2015 01:00 28.02.2015 19:00 2.03.2015 13:00 4.03.2015 07:00 6.03.2015 01:00 7.03.2015 19:00 9.03.2015 13:00 11.03.2015 07:00 13.03.2015 01:00 14.03.2015 19:00 16.03.2015 13:00 18.03.2015 07:00 20.03.2015 01:00 21.03.2015 19:00 23.03.2015 13:00 25.03.2015 07:00 27.03.2015 01:00 28.03.2015 19:00 30.03.2015 13:00 1.04.2015 07:00 3.04.2015 01:00 4.04.2015 19:00 6.04.2015 13:00 8.04.2015 07:00 10.04.2015 01:00 11.04.2015 19:00 13.04.2015 13:00 15.04.2015 07:00 17.04.2015 01:00 18.04.2015 19:00 20.04.2015 13:00 22.04.2015 07:00 24.04.2015 01:00 25.04.2015 19:00 27.04.2015 13:00 29.04.2015 07:00 1.05.2015 01:00 2.05.2015 19:00 4.05.2015 13:00 Leq(dB) .L Date and time Figure 2: Diagram of the average hourly ship densities in the areas of 2 NM and 5 NM from the measuring station in the Gulf of Trieste and the Gulf of Venice in combination with the average hourly continuous underwater noise levels in 1/3-octave bands with centre frequencies of 63 Hz and 125 Hz (Leq) in the period from 12 February 2015 to 5 May 2015. NM, nautical miles. 140 Leq,125Hz (dB) 450 Leq,63Hz (dB) 400 120 Ship densities 2 NM from the measuring station Date and time Figure 3: Diagram of the average hourly ship densities in the areas of 2 NM and 5 NM from the measuring station in the Gulf of Trieste and the Gulf of Venice in combination with the average hourly continuous underwater noise levels in 1/3-octave bands with centre frequencies of 63 Hz and 125 Hz (Leq) during the period from 26 September 2015 to 31 December 2015. The red arrow indicates the period from 26 September 2015 to 26 October 2015, when dredging activities were done in the Port of Koper. NM, 80 60 40 20 0 250 200 150 100 50 0 nautical miles. Koper during the following periods: 18–31 August 2016 and 22–29 September 2016. The results presented on these diagrams (Figures 2–6) are interpretedand discussed in the subsection Discussion. The average equivalent continuous under­water noise levels in 1/3-octave bands with centre frequencies of 63Hz and 125Hz were higher in the intervals by ˜ 11dB (Leq,63Hz) and 5 dB (Leq,125 Hz) when dredging activities took place than in the intervals when these activities were absent (Table 4). In addition, the average equivalent continuous underwater noise levels, RMZ – M&G | 2020 | Vol. 67 | pp. 161–175 were for 7dB (Leq,63Hz) and 7dB (Leq,125Hz), lower in the intervals, when cleaning activities took place than in the intervals when these activities were absent (Table 4). The relationship of the measured ambient low-frequency noise levels with the meteorologi­cal factors is depicted in the diagrams (Figures7–11) of the average hourly wind speeds and average hourly precipitation in each measuringperiod, in combination with the average hourlycontinuous underwater noise levels in 1/3-oc­tave bands with centre frequencies of 63Hz and125Hz. Blue curve presents Leq,63Hz, black curve A. Popit presents Leq,125 Hz, brown curve presents windspeed and green columns on the x-axis presentprecipitation. The results presented in these dia­grams (Figures 7–11) are discussed in the sub­section Discussion. Discussion In this section, the relationship between the pressures in the Slovenian Sea that arise from anthropogenic activities (shipdensities, dredg­ing activities and cleaning ofthe seafloor) and the equivalent continuous levels of underwater Underwater noise in the Slovenian Sea Leq(dB) 60 0 :10 7102 .70.6 0 :40 7102.70.7 8.07.2017 07:00 9.07.2017 10:00 10.07.2017 13:00 11.07.2017 16:00 12.07.2017 19:00 13.07.2017 22:00 15.07.2017 01:00 16.07.2017 04:00 17.07.2017 07:00 18.07.2017 10:00 19.07.2017 13:00 20.07.2017 16:00 21.07.2017 19:00 22.07.2017 22:00 24.07.2017 17:00 25.07.2017 20:00 26.07.2017 23:00 28.07.2017 02:00 29.07.2017 05:0030.07.2017 08:0031.07.2017 11:00 1.08.2017 14:00 2.08.2017 17:00 3.08.2017 20:00 4.08.2017 23:00 6.08.2017 02:00 7.08.2017 05:00 8.08.2017 08:00 9.08.2017 11:00 10.08.2017 14:00 11.08.2017 17:00 12.08.2017 20:00 13.08.2017 23:00 15.08.2017 02:00 16.08.2017 05:00 17.08.2017 08:00 18.08.2017 11:00 19.08.2017 14:00 20.08.2017 17:00 21.08.2017 20:00 22.08.2017 23:00 24.08.2017 02:00 25.08.2017 05:00 26.08.2017 08:00 27.08.2017 11:00 Date and time Figure 4. Diagram of the average hourly ship densities in the areas of 2 NM and 5 NM from the measuring station in the Gulf of Trieste and the Gulf of Venice in combination with the average hourly continuous underwater noise levels in 1/3-octave bands with centre frequencies of 63 Hz and 125 Hz (Leq) during the period from 18 August 2016 to 1 November 2016. The red arrows indicate the periods 18–31 August 2016 and 22–29 September 2016, during which cleaning of the channels in the Port of Koper was performed. NM, nautical miles. 120 500 450 100 400 350 80 Ship densities 5 NM from the measuring station Leq(dB) 0 :10 6102.80.81 0 :61 6102.80.91 21.08.2016 07:00 22.08.2016 22:00 24.08.2016 13:00 26.08.2016 04:00 27.08.2016 19:00 29.08.2016 10:00 31.08.2016 01:00 1.09.2016 16:00 3.09.2016 07:00 4.09.2016 22:00 6.09.2016 13:00 8.09.2016 04:00 9.09.2016 19:00 11.09.2016 10:00 13.09.2016 01:00 14.09.2016 16:00 16.09.2016 07:00 17.09.2016 22:00 19.09.2016 13:00 21.09.2016 04:00 22.09.2016 19:00 24.09.2016 10:00 26.09.2016 01:00 27.09.2016 16:00 29.09.2016 07:00 30.09.2016 22:00 2.10.2016 13:00 4.10.2016 04:00 5.10.2016 19:00 7.10.2016 10:00 9.10.2016 01:00 10.10.2016 16:00 12.10.2016 07:00 13.10.2016 22:00 15.10.2016 13:00 17.10.2016 04:00 18.10.2016 19:00 20.10.2016 10:00 22.10.2016 01:00 23.10.2016 16:00 25.10.2016 07:00 26.10.2016 22:00 28.10.2016 13:00 30.10.2016 04:00 31.10.2016 19:00 noise in 1/3-octave bands with centre frequen­cies of 63Hz (Leq,63Hz) and 125Hz (Leq,125Hz) (dB) is discussed. Furthermore, the relationship between the continuous underwater noise lev­els and the meteorological parameters (wind speed (m/s) and precipitation (mm)) is also commented upon. The average continuous underwater noiselevels (Leq,63 Hz and Leq,125 Hz) measured in the Slovenian Sea (Table 2) were similar to those reported in the literature, which were foundto be associated with the shipping noise[1–21]. Large variations of the Leq,63 Hz levels were highly related to variations of the Leq,125Hz 150 Leq,125Hz (dB) Leq,63Hz (dB) 600 Ship densities 2 NM from the measuring station 500 120 Ship densities 5 NM from the measuring station 40 Date and time Figure 5. Diagram of the average hourly ship densities in the areas of 2 NM and 5 NM from the measuring station in the Gulf of Trieste and the Gulf of Venice in combination with the average hourly continuous underwater noise levels in 1/3-octave bands with centre frequencies of 63 Hz and 125 Hz (Leq) during the period from 6 July 2017 to 27 August 2017. NM, nautical miles. .L.L 400 300 250 200 150 100 170 Leq,125Hz (dB) 650 140 Leq,63Hz (dB) Ship densities 2 NM from the measuring station 550 120 Ship densities 5 NM from the measuring station Ship densitiesinthe GulfofTrieste 450 100 Leq(dB) .L 0 :10 8102.80.810 :32 8102.80.02 23.08.2018 21:0026.08.2018 19:0029.08.2018 17:001.09.2018 15:004.09.2018 13:007.09.2018 11:0010.09.2018 09:0013.09.2018 07:0016.09.2018 05:0019.09.2018 03:0022.09.2018 01:0024.09.2018 23:0027.09.2018 21:0030.09.2018 19:003.10.2018 17:006.10.2018 15:009.10.2018 13:0012.10.2018 11:0015.10.2018 09:0018.10.2018 07:0021.10.2018 05:0024.10.2018 03:0027.10.2018 15:0030.10.2018 13:002.11.2018 11:005.11.2018 09:008.11.2018 07:0011.11.2018 05:0014.11.2018 03:0017.11.2018 01:0019.11.2018 23:0022.11.2018 21:0025.11.2018 19:0028.11.2018 17:001.12.2018 15:004.12.2018 13:007.12.2018 11:0010.12.2018 09:0013.12.2018 07:0016.12.2018 05:0019.12.2018 03:0022.12.2018 01:0024.12.2018 23:0027.12.2018 21:0030.12.2018 19:00 Date and time Figure 6: Diagram of the average hourly ship densities in the areas of 2 NM and 5 NM from the measuring station in the Gulf of Trieste and the Gulf of Venice in combination with the average hourly continuous underwater noise levels in 1/3-octave bands with centre frequencies of 63 Hz and 125 Hz (Leq) in the period from 18 August 2018 to 31 December 2018. NM, nautical miles. Table 4: The results of AVE and STDEV calculations of L and L in the periods with and without the anthropogenic eq,63 Hzeq,125 Hz, activity Type of the AVE & STDEV of L during the AVE & STDEV of L during the eq,63 Hzeq,63 Hz anthropogenic period of anthropogenic activity period without anthropogenic activity activity Dredging 26.9.2015–26.10.2015 (7:00–21:00h) 26.9.2015–26.10.2015 (22:00–6:00hr) Leq,63Hz =89.4±16.9dB re 1 µPa Leq,63Hz =79.5±13.5dB re 1µPa Leq,125Hz =88.6±10.1dB re 1µPa Leq,125Hz =83.3±7.2dB re 1µPa 27.10.2015–31.12.2015 (00:00–24:00 hr) Leq,63Hz =78.5±12.9dB re 1µPa Leq,125Hz =83.5±7.0dB re 1µPa Cleaning of the 18.8.2016–31.8.2016 (8:00–16:00)18.8.2016–31.8.2016 (17:00–7:00)seafloor 22.9.2016–29.9.2016 (8:00–16:00) 22.9.2016–29.9.2016 (17:00–7:00) L = 94.3± 12.3dB re 1mPa 30.9.2016–1.11.2016 (00:00–24:00 hr) eq,63Hz L = 90.6± 8.6dB re 1mPa L = 101.4± 14.7dB re 1mPa eq,125Hz eq,63Hz L = 97.7± 12.5dB re 1mPa eq,125Hz 80 60 40 20 0 350 250 150 50 -50 AVE, average value; STDEV, standard deviation. levels (Figures 2–6). Average hourly continuousunderwater noise levels (Leq,63 Hz and Leq,125 Hz) presented in Figures 2–6 show that the levels of Leq,63Hz were, for most of the measured days,lower than Leq,125Hz, which is in accordance withthe data presented in Table 2. This can be ex­plained by the fact that the propagation of un­derwater noise in the shallow seawater at 63Hz is lower than that at 125Hz. The results of this study showed that averageequivalent continuous underwater noise levelswere higher in the intervals by 11 dB (Leq,63 Hz)and 5 dB (Leq,125 Hz) when dredging activities took place, than in the intervals when these ac­tivities were absent. Furthermore, the averageequivalent continuous underwater noise levels were found to be lower in the intervals when cleaning activities took place, than when suchactivities were absent (Table 4). This finding in­dicated that cleaning activities were not relatedto the underwater noise levels. This might beexplained by the fact that cleaning of the sea­floor was performed with an excavator from themainland. The lowest average ship densities weremeasured within the areas of the radii of RMZ – M&G | 2020 | Vol. 67 | pp. 161–175 A. Popit from 26 September 2015 to 31 December 2015. 2 NM and 5 NM from the measuring station, while higher ship densities were observed inthe Gulf of Trieste; the maximum ship densi­ties were observed in the Gulf of Venice, asexpected (Table 2). The most likely reason un­derlying the fact that variation in underwaternoise levels was partly related to the varia­tion of the ship densities (Figures 2–6), couldbe the relatively small acoustic propagation inthe shallow sea [45, 46]. Acoustic propagation in shallow water environments was reported to be complex because of interference due toseafloorand sea surface sound reflections and sound transmission losses [47, 48]. Shallowwater channels do not allow propagation of low-frequency signals due to the wave-guideeffect; this implies that there would be a lowercut-off frequency below which sound waveswould not propagate, since the sound propa­gates into the sea bed [49, 50]. This phenom­enon leads to the less significant contributionof shipping to underwater noise. Figures 7–11 demonstrate that precipita­tion is not greatly associated with the fluctu­ations in continuous underwater noise lev­els, while some largerdeviations in the windspeed are associated with the largerfluctua­tions in continuous underwater noise levels. This could be explained by the fact that windblowing over the sea generates waves that, Leq(dB) Leq(dB) 100 0 :10 5102.90.620 :10 5102.20.31 0 :30 5102.90.820 :91 5102.20.41 30.09.2015 05:0016.02.2015 13:002.10.2015 07:0018.02.2015 07:004.10.2015 09:0020.02.2015 01:006.10.2015 11:0021.02.2015 19:008.10.2015 13:0023.02.2015 13:0010.10 .2015 15:0025.02.2015 07:0012.10 .2015 17:0027.02.2015 01:0014.10 .2015 19:0028.02.2015 19:0016.10 .2015 21:002.03.2015 13:0018.10 .2015 23:004.03.2015 07:0021.10 .2015 01:006.03.2015 01:0023.10 .2015 03:007.03.2015 19:0025.10 .2015 05:009.03.2015 13:0027.10 .2015 07:0011.03.2015 07:0029.10 .2015 09:0013.03.2015 01:0031.10 .2015 11:0014.03.2015 19:002.11.2015 13:0016.03.2015 13:004.11.2015 15:0018.03.2015 07:006.11.2015 17:0020.03.2015 01:008.11.2015 19:0021.03.2015 19:0010.11 .2015 21:0023.03.2015 13:0012.11 .2015 23:0025.03.2015 07:0015.11 .2015 01:0027.03.2015 01:0017.11 .2015 03:0028.03.2015 19:0019.11 .2015 05:0030.03.2015 13:0021.11 .2015 07:001.04.2015 07:0023.11.2015 09:003.04.2015 01:0025.11.2015 11:004.04.2015 19:0027.11.2015 13:006.04.2015 13:0029.11.2015 15:008.04.2015 07:001.12.2015 17:0010.04.2015 01:003.12.2015 19:0011.04.2015 19:005.12.2015 21:0013.04.2015 13:007.12.2015 23:0015.04.2015 07:0010.12.2015 01:0017.04.2015 01:0012.12.2015 03:0018.04.2015 19:0014.12.2015 05:0020.04.2015 13:0016.12.2015 07:0022.04.2015 07:0018.12.2015 09:0024.04.2015 01:0020.12.2015 11:0025.04.2015 19:0022.12.2015 13:0027.04.2015 13:0024.12.2015 15:0029.04.2015 07:0026.12.2015 17:001.05.2015 01:0028.12 .2015 19:002.05.2015 19:0030.12 .2015 21:00 4.05.2015 13:00 Date and time Figure 7: Diagram of the average hourly wind speeds (vv) and average hourly precipitation (hp) in combination with the average hourly continuous underwater noise levels in 1/3-octave bands with centre frequencies of 63 Hz and 125 Hz (Leq) during the period from 12 February 2015 to 5 May 2015. 120 30 Date and time Figure 8: Diagram of the average hourly wind speeds (vv) and average hourly precipitation (hp) in combination with the average hourly continuous underwater noise levels in 1/3-octave bands with centre frequencies of 63 Hz and 125 Hz (Leq) in the period Underwater noise in the Slovenian Sea 100 171 30 25 vv (m/s) and hp(mm) vv (m/s) and hp(mm) 25 120 100 120 Leq(dB) Leq(dB) Leq(dB) 0 :10 6102.80.81 Date and time Figure 11: Diagram of the average hourly wind speeds (vv) and average hourly precipitation (hp) in combination with the average hourly continuous underwater noise levels in 1/3-octave bands with centre frequencies of 63 Hz and 125 Hz (Leq) in the period from 18 August 2018 to 31 December 2018. RMZ – M&G | 2020 | Vol. 67 | pp. 161–175 A. Popit 25 Date and time Figure 10: Diagram of the average hourly wind speeds (vv) and average hourly precipitation (hp) in combination with the average hourly continuous underwater noise levels in 1/3-octave bands with centre frequencies of 63 Hz and 125 Hz (Leq) in the period from 6 July 2017 to 27 August 2017. 140 30 Date and time Figure 9: Diagram of the average hourly wind speeds (vv) and average hourly precipitation (hp) in combination with the average hourly continuous underwater noise levels in 1/3-octave bands with centre frequencies of 63 Hz and 125 Hz (Leq) in the period from 18 August 2016 to 1 November 2016. 120 20 18 16 14 25 140 30 20.08.2018 23:00 0 :61 6102.80.91 23.08.2018 21:008.07.2017 07:0021.08.2016 07:0026.08.2018 19:009.07.2017 10:0022.08.2016 22:0029.08.2018 17:0010.07.2017 13:001.09.2018 15:0011.07.2017 16:004.09.2018 13:0012.07.2017 19:007.09.2018 11:0013.07.2017 22:0010.09.2018 09:0015.07.2017 01:0013.09.2018 07:0016.07.2017 04:001.09.2016 16:0016.09.2018 05:0017.07.2017 07:003.09.2016 07:0019.09.2018 03:0018.07.2017 10:004.09.2016 22:0022.09.2018 01:0019.07.2017 13:006.09.2016 13:0024.09.2018 23:0020.07.2017 16:008.09.2016 04:0027.09.2018 21:0021.07.2017 19:009.09.2016 19:0030.09.2018 19:0022.07.2017 22:0011.09.2016 10:003.10.2018 17:0024.07.2017 17:0013.09.2016 01:006.10.2018 15:0025.07.2017 20:0014.09.2016 16:009.10.2018 13:0026.07.2017 23:0016.09.2016 07:0012.10.2018 11:0028.07.2017 02:0017.09.2016 22:0015.10.2018 09:0029.07.2017 05:0019.09.2016 13:0018.10.2018 07:0030.07.2017 08:0021.09.2016 04:0021.10.2018 05:0031.07.2017 11:0022.09.2016 19:0024.10.2018 03:001.08.2017 14:0024.09.2016 10:0027.10.2018 15:002.08.2017 17:0030.10.2018 13:003.08.2017 20:002.11.2018 11:004.08.2017 23:005.11.2018 09:006.08.2017 02:008.11.2018 07:007.08.2017 05:0011.11.2018 05:008.08.2017 08:004.10.2016 04:0014.11.2018 03:009.08.2017 11:005.10.2016 19:0017.11.2018 01:0010.08.2017 14:007.10.2016 10:0019.11.2018 23:0011.08.2017 17:009.10.2016 01:0022.11.2018 21:0012.08.2017 20:0010.10.2016 16:0013.08.2017 23:0012.10.2016 07:00 25.11.2018 19:00 28.11.2018 17:0015.08.2017 02:0013.10.2016 22:0016.08.2017 05:0015.10.2016 13:00 1.12.2018 15:0017.08.2017 08:0017.10.2016 04:00 4.12.2018 13:0018.08.2017 11:0018.10.2016 19:00 7.12.2018 11:0019.08.2017 14:0020.10.2016 10:00 10.12.2018 09:0020.08.2017 17:0022.10.2016 01:00 13.12.2018 07:0021.08.2017 20:0023.10.2016 16:00 16.12.2018 05:0022.08.2017 23:0025.10.2016 07:00 19.12.2018 03:0024.08.2017 02:0026.10.2016 22:00 22.12.2018 01:0025.08.2017 05:00 24.12.2018 23:0026.08.2017 08:00 27.12.2018 21:0027.08.2017 11:00 30.12.2018 19:00 vv (m/s) and hp(mm) vv (m/s) and hp(mm) vv (m/s) and hp(mm) when they are large enough, break and pro­duce underwater sound. This phenomenonis well described in several previous studies[7, 9, 22–25]. Conclusion The results of our study have indicated that the underwater noise levels in the Slovenian Sea are related to dredging activity in the Portof Koper and are partly related to variationsof the ship densities. Some larger deviationsin the wind speed were found to be associ­ated with the larger fluctuations in continuousunderwater noise levels, while precipitationwas not related to the underwater noise. Use of larger data sets is suggested to ensure thatit becomes possible to furtherstudy and evalu­ate underwater noise levels in relation to man- made or natural sound sources. Acknowledgements The current study was funded by the Ministry for the Environment and Spatial Planning, Slovenia. The AIS data from the year 2015 were obtained by the BALMAS project partnership. The AIS data from 2016 to 2018 were obtained by the Slovenian Maritime Administration in the frame of the Ministry for Infrastructure. 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Original scientific paper Received: Mar 24, 2021 Accepted: Mar 24, 2021 DOI: 10.2478/rmzmag-2020-0020 Monitoring after the conclusion of mining works Monitoring po opustitvi rudarskih del Tomaž Hribar1,*, Tomaž Pecolar1, Goran Vižintin2 1 Institute for Mining, Geotechnology and Environment, Slovenceva 93, 1000 Ljubljana, Slovenija 2 University of Ljubljana, Faculty of Natural Sciences and Engineering, Aškerceva 12, 1000 Ljubljana, Slovenija *tomaz.hribar@irgo.si Abstract After mining works are completed and the mine is per­manently closed, the holder of the mining rights must carry out monitoring in accordance with the applicable legislation and for the purpose of controlling the ex­traction area. This includes monitoring of the changes that have occurred during the process of mining, both on the surface and below it. This article presents an ex­ample of a monitoring program after the mining works are completed. The extraction of raw mineral materi­al in an underground mine results in various impacts on the surface and underground space. The areas or segments of monitoring are divided into two parts in this article: The underground part includes monitoring of the geomechanical, climatic, and hydrogeological changes, while monitoring on the surface requires spe­cial attention to be paid to the stability conditions of the surface above old mine works and hydrogeological conditions in the area above the extraction or impact area. A practical example of the monitoring program that needs to be made when a mine closes is given in the article. The program covers areas, presents the ways and methods of measurement, as well as report­ing of the measurements. The analysis procedure of already existing measurements, which need to be ana­lyzed and included in the preparation of the monitoring program, is also presented. Key words: monitoring, stability, extraction area, mea­surement method Povzetek Po opustitvi rudarskih del in trajnem zaprtju rudnika mora nosilec rudarske pravice skladno z veljavno za­konodajo in z namenom nadzorovanja pridobivalnega prostora izvajati monitoring. Monitoring obsega spre­mljavo sprememb, ki so nastale ob izvajanju rudarskih del, tako na površini kot pod njo. V clanku so predstavljena izhodišca za izdelavo pro-grama monitoringa po opustitvi rudarskih del. Prido­bivanje mineralne surovine v podzemnem rudniku ima za posledico razlicne vplive na površino in podzemni prostor. Podrocja oziroma segmenti monitoringa so v nalogi razdeljeni v dva dela. Jamski del spremljave ob-sega spremljavo geomehanskih, klimatskih in hidro­geoloških sprememb. Podobno je potrebno predvideti spremljavo dogajanj na površini, kjer je posebna pozor­ nost posvecena stabilnostnim razmeram površine nad jamskimi deli in hidrogeološkim razmeram v obmocju pridobivalnega prostora oziroma vplivnem obmocju. Podan je prakticen prikaz programa monitoringa, ki ga je potrebno izdelati ob zaprtju rudnika. V programu so zajeta podrocja, predstavljeni nacini in metode meritev, kakor tudi porocanje o le teh. Prav tako je predstavljen postopek analize že obstojecih meritev, ki jih je potreb-no analizirati in vkljuciti v izdelavo programa monito­ringa. Kljucne besede: monitoring, stabilnost, pridobivalni prostor, metoda meritev Introduction In the field of mining, during its operation and gradual closure, it is necessary to prepare technical mining documentation in the form of projects and programs to monitor the effects of mining on the underground and surface ar­eas for different periods [1]. With regard to the type of mining and the method of closing the mine, further impact monitoring is required. For this, it is necessary to develop a program on which further monitoring and measurements will be based [1].Due to montangeological conditions, it is not yet possible to leave underground areas com­pletely unattended during the mine closure phase. Based on previous experience, it is indi­cated by both geomechanical and hydrological developments in the areas of operation of in­dividual mines that the impact trend does not slow down with the closure of the mine, and hence further monitoring is needed. The effects of mining are manifested on the surface in the form of deformations, hydrological phenome­na, and stability effects on structures or terrain configuration [1, 2].Generally, mines already have an established system for monitoring their impacts at the ex­traction area, in the form of a concession deed and a contract. This system needs to be ana­lyzed, updated, and give detailed further proce­dures for monitoring. In this way, we can deter­mine which areas are suitable for further use in other fields and which areas need continued protection.A network of observations must be established in the wider area of the mine throughout the mining process as well as during its gradual closure. This covers the areas both below and above the surface of the entire extraction area, but they are divided by individual excavation fields or caves. Impact measurements are car­ried out on individual segments, such as visual observations, deformation measurements, and hydrological and geomechanical conditions [1–3].The measurement results of individual areas and segments need to be combined, compre­hensively analyzed, and the basis for further categorization of the impact area given. Mea­surements and observations of both the under­ground and surface areas, which contain data on the movements, inflows, flows, and levels of groundwater and surface water, as well as changes in the geomechanical characteristics of the area, must be collected and analyzed. The results of the analyses must be presented in the monitoring program in such a way that it is possible to categorize the impacts, which are divided into individual categories.Based on the measurement results analysis, it is necessary to determine the critical or limit Figure 1: Depiction of the RTH extraction area and areas of underground work [1]. RMZ – M&G | 2020 | Vol. 67 | pp. 177–184 Hribar T., Pecolar, T. and Vižintin G. values of the individual observation parame­ters for movements, flows or water levels, and the geomechanical characteristics of the mate­rials for each category [2].A practical example of preparing a monitoring program for the RTH coal mine is shown in the article. The monitoring program includes monitoring the impacts of mining both in the underground and on the surface area of the RTH extraction area. The underground part comprises four caves, while the surface area covers the entire extraction area through two municipalities. The area we address in this article is both an erosion and an impact area.The preparation of the monitoring program considers all applicable legislation, rules, stan­dards, and existing technical documentation, as well as geological and geotechnical data obtained from previous measurements in this area. Monitoring system The monitoring activities prescribed by the pro­gram must be carried out on the underground part and on the surface by individual segments and later defined into categories based on the analysis of the results. The segments are as fol­lows [1–3]:Visual inspections on the underground and surface areas; - Underground climate control; - Geotechnical measurements of underground structures and of the surface area; - Hydrological measurements in the mine and on the surface; - Surface movement measurements. The measurement methods and equipment are defined in the monitoring program for individ­ual observations and segments of measure­ments. Consequently, and with regard to the nature of the observed area, the specificity of an individual measurement and observation, and the accuracy and frequency of an individu­al measurement are determined. The monitoring program defines the interpre­tation of the results of individual areas and segments. Furthermore, it defines how the measurement results are placed in the impact categorization.Visual inspections must be carried out in the open sections of individual caves and on the en­tire surface of the extraction area, as prescribed in the monitoring program. Attention should be paid to the permanent structures in the cave, such as transport routes and paths intended for drainage. Surveys of the surface area are carried out with patrols, which can be a prob­lem, as some areas are more difficult to access. During patrols of the underground parts, cli­mate measurements are performed by record­ing possible gases, the temperature, and wind direction and strength.Geotechnical measurements in the under­ground and surface areas are carried out in accordance with the program and include the following [1]: - Deformation measurements of underground areas (extensometers, dynamometers, and measuring anchors); - Surface stability measurements (inclinome­ters); - Hydrogeological measurements in the mine (measurements of flows, inflows, and out­flows of water); - Hydrogeological measurements on the sur­face (piezometers, flows and water levels, physical and chemical properties of water); - Surface movement measurements (classical terrestrial methods, GNSS, UAVs). Figure 2 shows the surface deformations due to underground works, which must be monitored in accordance with the monitoring program by using inclination measurements and geodetic methods. When surveying surface movements, classi­cal geodetic and GNSS equipment are used, by which the measurement methods and pro­cedures are known. In recent times, there has been potential in using unmanned aerial vehi­cles, which make visual and measurement ob­servations much easier. However, they cannot be used for creating images of the entire RTH extraction space, as a large part of the area is inhabited, and at the same time there would be too much data captured, which would be difficult to process. This method is suitable for hard-to-reach areas, where an individual sur-face could be inspected visually and measured in a relatively short time. Table 1: The scope of unmanned aerial vehicle uses in mining [4]. Surface mines Underground mines Closed mines - Mine operation - Geotechnical characterization - Land subsidence monitoring - 3D mapping - Rock size distribution - Recultivation - Bank stability - Monitoring and measurement of gases - Surface mapping - Mine safety - Mine rescuing - Detecting gas pockets - Structure monitoring - Acid leakage monitoring - Facility management Alternative observation method Observations of surface changes both under­ground and on the surface can be carried out with relatively simple newer methods of moni­toring and observations using unmanned aeri­al vehicles. Recently, this method has become a more established one and for which we can determine relative as well as absolute changes with the help of surface model analyses. The problem that arises when using aerial record­ings is in the large amount of data, accuracy, and relatively demanding equipment. Further­more, these methods may be limited due to legislation that restricts the use of unmanned aerial vehicles in urban areas. RMZ – M&G | 2020 | Vol. 67 | pp. 177–184 Recordings of the state of the area in different periods can be captured with advanced aerial photography technology using unmanned ae­rial vehicles, which capture point clouds and photo-document the state of the surface. The results of aerial photography are presented in various visualization forms such as point clouds, 3D area models (digital surface mod­el) and DOF (digital ortho photo). We combine all this in AutoCAD Civil 3D, where we get a high-quality base for calculating masses. Table 1 gives the areas where unmanned aerial vehi­cles are used in mining and Figure 3 shows ex­amples of some unmanned aerial vehicles.Due to its content and method of processing, observations with the help of unmanned aeri­al vehicles interfere with the field of GIS (Geo­graphic Information System) or computer-aid­ed spatial information systems, which provide a modern management, organizational, and business basis for capturing, storing, searching, processing, analyzing, displaying, and dissemi­nating spatial data. The emphasis is on various analyses of spatial data [5].Aerial photography with unmanned aerial ve­hicles means a noncontact photogrammetric capture of spatial data. The results of the over­flight are aerial photographs of the area taken with a digital camera attached to the vehicle. Due to image matching, individual photos must overlap by at least 65%. Using image matching and photogrammetric methods, we can orient the bunch of images along both the horizontal and height axes. Thus, we obtain volume data in a relative coordinate system, which is orient­ed into the national coordinate system with the help of classical or GNSS technologies [4]. Hribar T., Pecolar, T. and Vižintin G. Figure 3: Unmanned aerial vehicles suitable for surface use: (A) Teklite, (B) GoSurv, (C) Swamp Fox, (D) Quadcopter, (E) Phantom 2 Vision+, and (F) Aeryon Scout [4]. Field data, measured with an unmanned aeri­al vehicle within different periods, is imported into AutoCAD CIVIL 3D as a cloud of points. Surface modeling is performed using the geo-static surface adjustment method.The basic idea is in the detailed recognition of some characteristics of the general course of the surface, which is to be determined from the data. These findings are used to estimate and determine values on missing or undefined parts of the surface. In the kriging method, the most important criterion is the smoothness of the surface, which we try to ensure by using statistical methods. Kriging is not a method that can be used automatically and without un­derstanding the given area, as it requires the user to be present and actively participate in certain decisions [6].As a result of modeling individual captured images, surface models of different periods (DMRs) are obtained [7]. We attach these im­ages on the same points on the edges, which enables us to compare the volumes between different time measurements. AutoCAD CIVIL 3D allows us to compare different surface mod­els as a composite grid of points in the base model (existing state) and comparative models (derived state) [8]. The volume of the mathe­matical formation of the surface difference is defined by the exact height differences of any point of the model. Both the capturing method and the DMR modeling method must be defined in advance by the monitoring program and are conditioned by the terrain configuration itself [9]. Monitoring area categorization The monitoring area categorization parame­ters are based on the results and interpreta­tion of the impact measurements of individual segments and areas [10]. The combined data of individual segments and areas are comprehen­sively analyzed, and the impact area categori­zation basis is provided [11].The impact categories are as follow: - Category I: The observation parameters are above the permitted values and cause insta­bility of the terrain, so that further intensive monitoring and ongoing remediation of the area is required. - Category II: The observation parameters are within the limit values and still affect the la-bility of the terrain, so further monitoring and, if necessary, remediation of the area is required. - Category III: The observation parameters are below the limit values and no further ob­servations are required. Figure 4. DMR display made with different interpolation algorithms. (A) Isohypse of a hypothetical area. (B) DMR constructed by vertical scanning algorithms. (C) DMR constructed by maximum slope algorithms. (D) DMR produced by the weighted average algorithm [5]. -Category IV: The observation parameters show that the area is suitable for further use for other purposes as well. A summary of the limits of the individual cate­gories for movements and inclinations is given in Table 2. The interpretation of measurements must be carried out based on the periodic measurement reports of individual segments, performed by a professionally trained team, which also leads and coordinates the measurements [12].The purpose of the measurements is to follow the time development of deformations on the surface, in the surface layers in critical areas, as well as in the entire extraction area. It is neces­sary to unambiguously determine the stability situation in populated areas, both within the security pillars and beyond.The basic criterion for determining additional measurements is the time development of the measured parameters of all measurements. Since the measurements are carried out on dif­ferent geological surfaces, it is impossible to give a general criterion of the permitted move­ment of the terrain in length units where it is necessary to act with mining or construction works. RMZ – M&G | 2020 | Vol. 67 | pp. 177–184 Hribar T., Pecolar, T. and Vižintin G. Table 2: Impact categorization [1]. Category [Limit] Segment I II III IV Movement measurements Above 50 mm, also new measurement sites Up to 50 mm and deformation trend Up to 20 mm and deformation trend Below 20 mm Inclinometer measurements Above 50 mm, also new measurement sites Up to 50 mm and deformation trend Up to 20 mm and deformation trend Below 10 mm Conclusion To monitor the impacts of mining in the wid­er area of the mine, it is necessary to prepare technical mining documentation in the form of a monitoring program during its operation and during the implementation of its gradual closure. A network of observations must be established in the wider area of the mine throughout the mining process and the gradual closure of the mine. This covers the area both below the sur­face and on the surface of the entire extraction area, by individual excavation fields or caves. Impact measurements are carried out by indi­vidual segments, such as visual observations, deformation measurements, and hydrological and geomechanical conditions.Based on the analysis of the measurement re­sults, critical or limit values of individual obser­vation parameters for movements, flows or wa­ter levels, and geomechanical characteristics of Monitoring after the conclusion of mining works materials are determined for each category and are as follows: Category I: The observation parameters are above the permitted values and cause instabili­ty of the terrain, so that further intensive mon­itoring and ongoing remediation of the area is required.Category II: The observation parameters are within the limit values and still affect the labil­ity of the terrain, so further monitoring and, if necessary, remediation of the area is required.Category III: The observation parameters are below the limit values and no further observa­tions are required.Category IV: The observation parameters show that the area is suitable for further use for other purposes as well.The article shows a practical example of pre­paring a monitoring program for the RTH coal mine. 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(2013): Instrumental monitoring of the subsidence due to groundwater withdrawal in the city of Murcia (Spain). Environmental Earth Sciences, 70(5), pp. 1957–1963. [11] Tomás, R., Cano, M., García-Barba, J., Vicente, F., Her­rera, G., Lopez-Sanchez, J.M., Mallorquí, J.J. (2013): Monitoring an earthfill dam using differential SAR interferometry: La Pedrera dam, Alicante, Spain. Engineering Geology, 157, pp. 21–32. [12] Herrera, G., Álvarez-Fernández, M.I., Tomás, R., González-Nicieza, C., Lez-Sánchez, J.M., Álva­rez-Vigil, A.E. (2012): Forensic analysis of buildings affected by mining subsidence based on Differential Interferometry (Part III). Engineering Failure Analy­sis, 24, pp. 67–76. RMZ – M&G | 2020 | Vol. 67 | pp. 177–184 Hribar T., Pecolar, T. and Vižintin G. Original scientific article Received: Jan 18, 2021 Accepted: Jan 25, 2021 Estimation of Depth to Bouguer Anomaly DOI: 10.2478/rmzmag-2020-0016 Sources Using Euler Deconvolution Techniques Ocena globine do virov Bouguerjeve anomalije z uporabo Eulerjevih dekonvolucijskih tehnik Gideon Oluyinka Layade1,*, Hazeez Edunjobi1, Victor Makinde1, Babatunde Bada2 1Department of Physics, Federal University of Agriculture, Abeokuta 2Department of Environmental Management & Toxicology, Federal University of Agriculture, Abeokuta *Layadeoluyinka018@gmail.com Abstract The geophysical measurement of variations in gravitational field of the Earth for a particular location is carried out through a gravity survey method. These variations termed anomalies can help investigate the subsurface of interest. An investigation was carried out using the airborne satellite-based (EGM08) gravity dataset to reveal the geological information inherent in a location. Qualitative analysis of the gravity dataset by filtering techniques of two-dimensional fast Fourier transform (FFT2D) shows that the area is made up of basement and sedimentary Formations. Further enhancements on the residual anomaly after separation show the sedimentary intrusion into the study area and zones of possible rock minerals of high and low density contrasts. Quantitative interpretations of the study area by 3-D Euler deconvolution depth estimation technique described the depth and locations of gravity bodies that yielded the gravity field. The result of the depth to basement approach was found to be in the depth range of 930 m to 2,686 m (for Structural Index, SI = 0). The research location is a probable area for economic mineral deposits and hydrocarbon exploration. Povzetek Izvedene so bile geofizikalne meritve sprememb zemeljskega gravitacijskega polja na dolocenih lokacijah. Spremembe gravitacijskega polja, imenovane anomalije, so lahko v pomoc pri raziskovanju dolocenega podzemnega obmocja. Vraziskavi so bili za obravnavano obmocje uporabljeni podatki gravitacijskega zemeljskega modela (EGM08). Kvalitativna analiza gravitacijskih podatkov s filtracijskimi tehnikami dvo­dimenzionalne hitre Fourierjeve transformacije (FFT2D) prikazuje, da obmocje sestavljajo kamnine podlage in sedimentne formacije. Nadaljnje analize prikazujejo sedimentne intruzije v obravnavano obmocje in obmocja potencialnih kamninskih mineralov z visokim in nizkim kontrastom gostote. Kvantitativna interpretacija obravnavanega obmocja s tehniko 3D Eulerjeve dekonvolucije razkriva globino in lokacijo gravitacijskih teles, ki vplivajo na spremembo gravitacijskega polja. Rezultat analize je globina do kamninske podlage, ki se nahaja v obmocju od 930 m do 2,686 m (za strukturni indeks SI = 0). Raziskovana lokacija je potencialno obmocje za ekonomicno pridobivanje mineralnih surovin in raziskovanje ogljikovodikov. Key words: gravitational field, intrusion, Kljucne besede: gravitacijsko polje, intruzija, enhancements, anomalous sources, density contrasts izboljšave, viri anomalij, kontrast gostote Introduction The inherent physical properties of sub­surface media such as sediments, rocks, voids, water, contacts among others are examined through geophysical survey [1]. Among these geophysical surveys is the gravity method which is primarily concerned with measuring gravitational field as part of potential field measurement [2–3]. It tries to determine the nature of the subsurface by relating the measured gravitational fields to density contrasts. Gravity survey can be carried out on the ground and can also be airborne but the airborne survey helps to cover areas that cannot be easily accessible, e.g. on waters [4]. Previous works in the locality have used magnetic method and rock petrography to investigate the study area. A number of techniques can be employed to yield the near surface spread of parameters describing the variations which include the 3-D analytic signal technique [5], Werner deconvolution, [6], 3-D Euler deconvolution, [7] and Multiple Source Werner deconvolution [8].Qualitatively, the gravity data is interpreted in order to describe and explain some important features which the results of the survey exposed with respect to possible geological formations and structures yielding the anomalies [9].While the quantitative interpretations involve numerical estimation of the depths and dimensions of anomalous sources. The research is thus, to estimate depths to gravity sources in the area of Abeokuta and environ using Bouguer gravity data. Hence, the application of 3-D Euler deconvolution technique for Where: F = force of attraction between two separate bodies G = constant of gravitation (G = 6.67 x 10-11 Nm2/kg2) M = mass of the earth m = mass of the second body R = separating distanceAlso, the second law of motion can be expressed as: .. (2) .= .. Thus: .(..) .= .. = .. (3) Where: F = the applied force of attraction dp = momentum change dt = time difference Equations (1) and (3) give: . = ...2 (4) Equation (4) is the gravitational field of the Earth on any mass. Description and Geologic Setting of the study area. computing the burial depths of anomalies.In 1867, Sir Isaac Newton proposed two laws upon which the gravity method is based: the law of universal gravitation that describes the force of attraction between two separate bodies of known masses [10–11] and the law of motion, which relates the applied force to the rate of change of momentum of a body.Mathematically: . = ... (1) .2 RMZ – M&G | 2020 | Vol. 67 | pp. 185–195 The location of the study area is represented .30) o–7. .00o(7 by Figure 1 within latitude .30) E spanning o–3. .00oN and longitude (3 3,025 km2 area. Basement complex (Abeokuta formation) and sedimentary (Ewekoro formation) respectively are the predominant geological nature of the area [12]. While the older granites which are magmatic in nature are of Precambarian age to early Palaeozoic [13]. Gneiss-migmatite complex comprising of gneisses, calcsilicate, quartzite, amphibolites and biotite-hornblende schist is the most Layade, G.O., Edunjobi, H.O., Makinde, V., Bada, B.S. 3O00'00" 3O06'00" 3O12'00" 3O18'00" 3O24'00" 3O30'00" Idere ... ... ... . ... .. ... . . ... ... Igbo-Ora . .. . ... .. .. .. ... ... Eruwa ... ... ... ... Idi-Emi ... .. ... Olorunsogo ... Opeji . .. . ... Imala ... ... ... Aiyetoro . Alabata ... ... Ishola .. ASHUWON ... HILL ... . ... Osiele . . .. ... ABEOKUTA Ibara-Orile Onibode ... . .. Jiga ... Kobape Iboro Ishaga Sawonjo Mashayi Lemode . Oba . 3O00'00" 3O06'00" 3O12'00" 3O18'00" 3O24'00" 3O30'00" 0 6.0 12.0 km LEGEND Alluvium, littoral&lagoonal GGm Muscovite&muscovite-Su Undifferenciated gneiss Geological boundary deposits tourmaline-granite gneiss complex mainly schist W Ewekoro Formation GGb Biotite-granite gneiss bS Biotite garnet schist& Faultlines biotite garnet gneiss A Abeokuta Formation Biotite & biotite-aS Amphibole schist/amphibolite Mylonites OGd hornblende granodiorite P Pegmatite or quartz vein OGf Fine-medium grained biotite& Su Quartzite&quartz schist Rivers biotite-muscovite granite pH Pyroxene-diorite OGh Coarse porphyritic hornblende Mag Augen gneiss Settlement granite and syenite OPg Porphyroblastic gneiss OGb Coarse porphyritic biotite& M Migmatite State boundary biotite-muscovite granite Figure 1: Geological Map of the Study Area. widely spread rock formation in the area anomaly map (Figure 2) after being reprojected according to Rahaman [14]. from the Universal Transverse Mercator of Zone 32 Northing (UTM 32N) to that of UTM 31N. A two-dimensional fast Fourier transform Methodology (FFT2D) filter named Magmap, which is an extension of Oasis Montaj (version 8.4) was The acquired gravity dataset of the study area applied on the Bouguer anomaly map to through Bureau Gravimetrique Internationale produce the Radially Average Power Spectrum (BGI) was processed to produce the Bouguer (RAPS), presented as Figure 4. The spectrum Figure 2: Bouguer Gravity Field of Abeokuta. aided the visualisation of the three demarcation of deep, intermediate and shallow anomalous gravity sources. Each of the segment is a representative of the gravity responses at given depths. Depth is proportional to the slope of the line segment [15–16]. This research requires a Regional-Residual separation technique to enhance shallower signals. A High-pass filter was employed to obtain the residual anomaly map (Figure 5). Subsequently, residual anomaly map was produced from the Bouguer gravity field [1, 17] by setting the cut-off wavenumber at 0.02 cycles/km to process the intermediate and shallow sources as the residual anomaly. The resulting residual anomaly was thereafter processed to produce the derivative of the field along the X-direction (Figure 6) and the Analytic signal map, the Analytic signal map (Figure 7) was observed to be a bit noisy and hence, upward continued at 1 km in order to sharpen the edges of anomalous sources and geological boundaries. These were also achieved through a two-dimensional fast Fourier transform (FFT2D), to accentuate structures linked with near surface causes [18]. The standard 3D Euler-deconvolution method is based on homogeneity equations that relate the gradients’ components of the potential field to the source location. The structural index (SI), . having values ranging from 0–2 for gravity sources [19]. These sources are described by different theoretical geometries with corresponding SI as follows; Sphere - (. =2), Vertical line end (pipe) - (. =1), Horizontal line (cylinder)- (. =1), Thin bed fault - (. =1), and Thin sheetedge - (. =0)respectively [20]. The 3D Standard Euler equation for potential field according to [20–21] is defined as: .T .T .T x +y .T +z .T + .T=x0 +y0 + .x .y .z .x .y .T (5) z0 .z + .b The coordinates of the measuring point are x, y, and z; b is a base level; the coordinates of the source location are x0, y0, and z0; while T is the total potential field respectively. RMZ – M&G | 2020 | Vol. 67 | pp. 185–195 Layade, G.O., Edunjobi, H.O., Makinde, V., Bada, B.S. Figure 3: Bouguer Anomaly Map showing some geological features. Figure 4: Radially Averaged Power Spectrum of the Gravity Field. Figure 5: Residual Anomaly Field (Bouguer Gravity Field High-Pass filtered at 50 km). Figure 6: First Horizontal Derivative along X-Direction. RMZ – M&G | 2020 | Vol. 67 | pp. 185–195 Layade, G.O., Edunjobi, H.O., Makinde, V., Bada, B.S. Figure 7: Upward Continued Analytic Signal Map. In computing the standard Euler deconvolution solutions, the recommendations from the findings of [20] were adopted by using the different structural indices of 0, 1 and 2 were tried in solving the solutions but only SI equals 1 gave a geologically meaningful solution, which reveals that the area is possibly characterized by structures like faults, contacts and thin sheet edge (dike), [22]. A square window size of 3000 by 3000 m containing number of grid cells in the gridded dataset was used in order to accommodate the depth of sources, as investigated by previous researches in the study area. Results and Discussions Qualitative Treatment The digitized data set of the area produced the Bouguer gravity map in Figure 2 and the radially average power spectrum in Figure 3. The anomaly was filtered to describe features associated with intermediate and shorter wavelengths. While Figure 5 shows the residual map for the separated Bouguer anomaly grid. Subsequently, the derivative maps of the field were generated from the high-pass filtered gravity filed, one of which is the derivative along X – direction presented as Figure 6 and the Analytic signal map that Figure 7 represents.In Figure 2, a gravity value ranging from 10.40 mGal to 26.40 mGal is observed on the Bouguer anomaly field. The anomaly map reveals high gravimetric values, towards northeastern zone of the area, which conforms to the lithological differences in the subsurface. On the other hand, within the southern, southwestern and northwestern regions, the variations in the lithology of the intra-basement of the area recorded low gravimetric values. Furthermore, the dominance of high gravity values around the Northeastern portion is a representative of possible undifferentiated gneiss complex which is mainly schist around ‘Eruwa’ (when compared with the Geological map of the study area). The portion marked ‘A-D’ on Figure 3 are alluvial and lagoonal deposits at the Oba area and the ‘demarcated’ marked region which is the transition zone that divides the Figure 8: Euler Solution Map of Abeokuta, for the Structural Index SI = 0. Figure 9: Euler Solution Map superimpose on the Residual Anomaly Map. RMZ – M&G | 2020 | Vol. 67 | pp. 185–195 Layade, G.O., Edunjobi, H.O., Makinde, V., Bada, B.S. study location into two distinctive geological Formations of Basement and Sedimentary Formations. The residual anomaly map in Figure 5 (Gravity field filtered at 50 km) has intermediate and short wavelengths with values ranging from -7.3 mGal to 6.4 mGal. In the southern and northern zones, gravity values are high but varies in Northwestern and Southeastern regions. In parts of the study area, there are sedimentary intrusions into the northern zones with low gravity values, other low-density areas suggest possible sedimentation (like Araromi and Abeokuta Formations).High pass–filtered residual anomaly grid gave rise to the derivative grids contained in Figures 6 and 7 to enhance the visualization and localization of the anomalous sources. The anomalies of the first horizontal derivative along the X-direction are aligned along N-S trend laterally, the anomalies or structures that trend in the same direction are from the same tectonic event, as posited by [23], while the regional effects of the total field have been attenuated. The range of anomaly for the Analytic Signal in Figure 7 is 0.002 mGal to 0.02 mGal with high gravity responses spatially distributed all over the area. Depth Estimation and Structural Evaluation The Figure 8 shows the Euler map with SI equals 0 having maximum range of 2,350 m to 2,686 m and average of 2,518 m (deep sources); and a minimum range of 930 m to 1,260 m with an average minimum depth of 1,095 m (shallow sources).The depth to basement of gravity anomalous sources evaluated in this research is a true representation of the sedimentary thickness, the works of [24] and [25] in and around the study area are all in agreement with the results of this research. The depth range obtained can slightly hold prospect for hydrocarbon accumulation as posited by [26] that the minimum sedimentary thickness required for hydrocarbon exploration is 2,300 m.Figure 10 represents the lineament map of inferred structures on the Euler depth solution map. The elongation of continuous plotted solutions confirms the presence of geological structures like faults, dike and/or sill in the area of investigation. Conclusion The qualitative interpretation of the area by the filtering techniques reveal the distinct features of basement and sedimentary Formations of the area. Alluvial deposits zone, sedimentary intrusions into the area and regions of possible high and low-density rock minerals have been mapped. Conclusively, the depths to basement of gravity sources in the area show prospects for hydrocarbon exploration and holds high potential for economic minerals exploration. References [1] Reynolds, M.J. (1997): Introduction to applied and environmental geophysics. John Wiley and Sons: New York, USA, 796 p. [2] Mickus, K., Hinojosa, J. (2002): The complete gravity gradient tensor derived from vertical gravity data: A Fourier Transform technique. Journal of Applied Geophysics, 46, 159–174. [3] Nicolas, O.M. (2009): The Gravity Method. Exploration for Geothermal Resources, pp. 1–9. [4] Telford, W.M., Geldart, L.P., Sheriff, R.E. (1990): Applied geophysics (2nd edition), Cambridge University Press: Cambridge, 770 p. [5] Roest, W.R., Verhoef, J., Pilkington, M. (1992): Magnetic interpretation using 3-D analytic signal. Geophysics, 57, 116–125. [6] Hartman, R.R., Tesky, D.J., Friedberg, J.L. (1971): A system for rapid digital aeromagnetic interpretation. Geophysics, 36, pp. 891–918. [7] Reid, A.B., Allsop, J.M., Granser, H., Millett, A.J., Somerton, I.W. (1990): Magnetic interpretation in three dimensions using Euler deconvolution. Geophysics, 55, pp. 80–99. [8] Hansen, R.O., Simmonds, M. (1993): Multiple-source Werner deconvolution. Geophysics, 58, pp. 1792– 1800. [9] Revees, C. (2005): Aeromagnetic Surveys; Principles, Practice and Interpretation. GEOSOFT, 155 p. [10] Telford, W.M., Geldart, L.P., Sheriff, R.E., Keys, D.A. (1976): Applied Geophysics. Cambridge University Press, 860p. [11] Rivas, J. (2009): Gravity and Magnetic Methods. Short course on Surface Exploration for Geothermal Resources. United Nations University, LaGeo: Elsavador, pp. 1–13. [12] Obaje, N.G. (2009): Geology and mineral resources of Nigeria. Lecture Note in Earth Science Series, 120. [13] Jones, H.A., Hockey, R.O. (1964): The Geology of Parts of Southwestern Nigeria. Bulletin of Geological Survey of Nigeria, 31, pp. 101–102. [14] Rahaman, M.A. (1976): Review of the basement geology of south western Nigeria in Geology of Nigeria. Elizabethan publishing company: Lagos, pp. 41–58. [15] Naidu, P.S. (1968): Spectrum of Potential Field due to randomly distributed sources. Geophysics, 33, pp. 337–345. [16] Spector, A., Grant, F.E. (1970): Statistical models for interpreting aeromagnetic data. Geophysics, 35, pp. 293–302. [17] Layade, G.O., Adebo, B.A., Olurin, O.T., Ganiyu, O.M. (2015): Separation of Regional-Residual Anomaly Using Least Square Polynomial Fitting Method. Journal of the Nigerian Association of Mathematical Physics, 30, pp. 69–180. [18] Hesham, S.Z., Hesham, T.O. (2016): Application of High-Pass Filtering Techniques on Gravity and Magnetic Data of the Eastern Qattara Depression Area, Western Desert, Egypt. National Research Institute of Astronomy and Geophysics, 5, pp. 106–123. [19] Thompson, D.T. (1982): A new technique for making computer-assisted depth estimates from magnetic data. Geophysics, 47(1), pp. 31–37. [20] Reid, A.B., Allsop, J.M., Thurston, J.B. (2014): The structural index in gravity and magnetic Interpretation: Errors, uses and abuses. Geophysics, 79(4), pp. 61–66. [21] Adegoke, J.A., Layade, G.O. (2019): Comparative depth estimation of iron-ore deposit using the Data-Coordinate Interpolation Technique for airborne and ground magnetic survey variation. African Journal of Science, Technology, Innovation and Development (AJSTID). 11(5), pp. 663–669, DOI:10.1080/2042133 8.2019.1572702. RMZ – M&G | 2020 | Vol. 67 | pp. 185–195 Layade, G.O., Edunjobi, H.O., Makinde, V., Bada, B.S. [22] Reid, A.B., Ebbing, J., Webb, S.J. (2014): Avoidable Euler Errors – the use and abuse of Euler deconvolution applied to Potential fields. European Association of Geoscientists & Engineers, Geophysical Prospecting, 62(5). [23] Omosanya, K.O., Akinbodewa, A.E., Mosuro, G.O. (2012): Integrated Mapping of Lineaments in Ago-Iwoye SE, SW Nigeria, Intl. J. Sci. Technol., 1(2), pp. 68–79. [24] Olowofela, J.A., Akinyemi, O.D., Badmus, B.S., Awoyemi, M.O., Olurin, O.T., Ganiyu, S.A. (2013): Depth estimation and source location of Magnetic anomalies from a Basement Complex Formation, using Local Wavenumber Method (LWM). IOSR Journal of Applied Physics, 4(2), pp. 33–38. [25] Olurin, O.T., Olowofela, J.A., Akinyemi, O.D., Badmus, B.S., Idowu, O.A., Ganiyu, S.A. (2015): Enhancement and Basement Depth Estimation from Airborne Magnetic Data. African Review of Physics, 10(38), pp. 303–313. [26] Wright, J.B., Hastings, D., Jones, W.B., Williams, H.R. (1985): Geology and Mineral resources of West Africa. George Allen and Unwin: London, 187 p. Original Scientific Article Received: February 19, 2021 Accepted: March 08, 2021 DOI: 10.2478/rmzmag-2020-0019 Site characterization for engineering purposes using geophysical and geotechnical techniques Dolocevanje znacilnosti obmocja za inženirske namene z uporabo geofizikalnih in geotehnicnih metod Aderemi A. Alabi* Department of Physics, Federal University of Agriculture, Abeokuta, Ogun State, Nigeria *derylab@yahoo.com Abstract Geophysical and geotechnical techniques were applied to determine the suitability of the sub­surface structure of Akole community area, Abeo­kuta, Nigeria, for the construction of engineering structures (CES). Four vertical electrical sound­ings (VES) were carried out, and 10 samples from different points at 1 m depth were analysed to determine soil moisture content, specific grav­ity (SG), Atterberg limits and California bearing ratio (CBR). The geoelectric sections revealed a maximum of five layers with the typical sounding curves of AKH and HKH types. Sieve analysis and tests for compaction limit, Atterberg limits, SG, op­timum moisture content and maximum dry density for compaction limit revealed that samples SP2, SP3, SP4, SP6, SP7, SP8, SP9 and SP10 are of low plasticity with SG values that fall within the per­missible range, while SP1 and SP5 are of medium plasticity and their SG values fall below the range of standard specifications. CBR analysis showed that SP1 and SP5 have low load-bearing capacities. VES 1 and 2, linked with SP1 and SP5, are consid­ered unstable and unsuitable to support the CES with shallow foundations; however, excavation of weak layers up to a depth of 5 m and reinforce­ment will enable the support. Key words: electrical resistivity, engineering structure, grain size, Atterberg limits, compaction test Povzetek Dolocitev primernosti tal za gradnjo inženirskih objektov na obmocju skupnosti Akole v Nigeriji je bila izvedena s pomocjo uporabe geofizikalnih in geotehnicnih metod. Izvedene so bile štiri navpicne sondažne geo-elektricne meritve. Za dolocitev vlažnosti, specificne teže, konsistencnih mej in kalifornijskega indeksa nosilnosti (CBR) je bilo preiskanih deset vzorcev tal iz razlicnih lokacij globine 1 m. Geo-elektricni prerezi so pokazali maksimalno petrazlicnihplastistipicnimisondažnimikrivuljami tipa AKH in MKH. Na vzorcih tal z oznakami SP2, SP3, SP4, SP6, SP7, SP8, SP9 in SP10 so bile opravljene sejalnaanaliza,dolocitevmejezgošcevanja,dolocitev konsistencnih mej, specificna teža, optimalna vlažnost in maksimalna suha gostota za mejo zgošcevanja. Vzorci imajo nizko stopnjo plasticnosti in specificno težo, ki spada v dovoljeno obmocje. Vzorca tal z oznakami SP1 in SP5 imata srednjo stopnjo plasticnosti in spadata pod obmocje standardnih zahtev. Preiskava s testom CBR je pokazala, da imata vzorca tal SP1 in SP5 nizko nosilnost na obtežbo. Preiskavi VES 1 in 2 sta prav tako pokazali, da sta vzorca SP1 in SP5 nestabilna ter neprimerna za temeljenje pri gradnji inženirskihobjektovsplitvimtemeljenjem,cepravbi z odstranitvijo plasti globine do 5 m in armiranjem dosegli primerno nosilnost za temeljenje. Kljucne besede: elektricna upornost,inženirski objekti, velikost zrn, Atterbergerjeve meje, zgošcevalni preiskus Introduction the years due to failure to carry out neces­ sary investigations before the structures are Developing nations have suffered from recur-erected [1–3]. Recently, the statistics of fail-ring collapse of engineering structures over ures of building and engineering structures throughout the nation has increased geomet­rically [4]. Factors responsible for failure of engineering structures are often attributed to substandard usage of building materials, old age of buildings, improper foundation design, non-compliance to specifications, inadequate supervision and nature of the sub-surface con­ditions of the ground on which the building is sited [5, 6]. The aftermath of structural failure of buildings is always huge, including loss of lives and valuable properties, as well as loss of financial investment. Since the earth provides support for ev­ery engineering structure, it is important toconduct preconstruction investigation of thesub-surface of any proposed site. This is toascertain the strength and the competence ofthe subsoil earth materials, as well as to carryout the timed post-construction monitoringof such structure to ensure its integrity [4, 7,].Geophysical methods (particularly, the elec­trical resistivity technique) have been widelyused for an extensive variety of engineeringand environmental problems because of theirreliability, efficiency and cost-effectiveness[4, 8]. The electrical resistivity technique hasalso proved to be a reliable tool for obtainingdetailed information about the sub-surface structure, particularly for detecting irregular­ities in and the complexity of the geologicalsub-surface [9]. Geotechnical study is another investigative approach that can provide excellent insight into the engineering properties of sub-surface soil materials [5]. The geotechnical test uses the principle of soil and rock mechanics to in­vestigate the sub-surface condition and to de­termine the relevant physical properties of the materials. Information, such as soil type, load-bearing capacity of materials, zone of weakness, resistance to penetration, compress­ibility and shrinkage limit, among others, is of­ten necessary before designing a very good and strong foundation for a proposed engineering structure [10]. Site characterization for building construc­tion purposes at the Federal University ofAgriculture, Abeokuta, Nigeria, was conduct­ed using geophysical and geotechnical meth­ods [11]. The area considered in the study was found to be suitable for both shallow and deep foundations. However, there weresome exceptions at a few points, whereinreinforcement was required to support shal­low and deep foundations. Subsoil evaluationof the pre-foundation at the proposed site at the Polytechnic of Ibadan was conducted [12] using geophysical and geotechnical tech­niques. The study revealed that the clay con­tent of the soil is low; the subsoil of the studyarea was therefore rated to be competent asfoundation material to support the proposed structure. Adequate understanding of soil properties is of paramount importance in the study of foundation integrity because it provides in­formation on the material properties of the soils, including ability to support the load of­ten exerted by the structure erected. The ob­jective of this study is to use geophysical and geotechnical techniques to investigate the nature and engineering properties of the sub­surface, its strength and capability (or oth­erwise) to bear the load of the engineering structure to be erected in Akole Community, Oke-Ata, Abeokuta, Southwestern Nigeria. Materials and methods Geomorphology and geology of the study area The study area is located at Akole Communityin Oke-Ata, Abeokuta North, Ogun State,Southwestern Nigeria, which lies betweenlatitudes 7°8'16.9" N and 7°8'24" N and lon­gitudes 3°17'9.2" E and 3°17'13.4" E. The ground in the study area lies at an eleva­tion between 62 m and 78 m above sea level (Figure 1). The climate is warm and tropical due to the rain-bearing ocean wind of the south-western monsoon and the northwest wind that arises from the Sahara desert. The rainy season of the study area starts around April and ends in October, with rainfall of nearly 1,238 mm per annum, while the dry season starts in November and ends in March. The area is located in a hummocky terrain with a well-pronounced undulating topography and prominent hills, RMZ – M&G | 2020 | Vol. 67 | pp. 197–207 A. A. Alabi. Figure 1: Topographical map of the study area showing profile base image. characterized by a moderate slope varying in altitude. The study area falls within the Precambrian Basement rocks of Southwestern Nigeria, with six major lithologic units, namely quartzite, banded-gneiss, biotite-schist, quartz-biotite schist and pegmatite [13]. Fieldwork procedure for geophysical survey The method used for the geophysical survey was the vertical electrical sounding (VES) using the Schlumberger electrode array. The Schlumberger array focusses on the ver­tical variation of sub-surface layers. The Schlumberger configuration of an electrode is quite sensitive to vertical sub-surface resistiv­ity below the centre of the array and it is less sensitive to horizontal changes in the sub-sur­face [14]. Data from a total of four VESs were acquired in the study area, and each of the potential differences and currents measured at each point were recorded. The apparent resistivity (. a) was computed from measure­ments of voltage (.V) and current (i) using Equation 1. . 22 . p( s - a ) / 4 .=. .. V (1) a ai where . a is the apparent resistivity obtained, s is the distance between the potential elec­trodes, a is the distance between the current electrodes, .V is the potential difference mea­sured and i is the current measured. Using WinResist software, the apparent re­sistivity values obtained were plotted against the electrode spacing to acquire the VES curves. Geotechnical method (laboratory tests for geotechnical survey) The soil moisture content (SMC), which is the water between the pores of the soil, was determined using the gravimetric method expressed by Equation 2 [15]. .. ( mass of Containermoistsoil + ) .. .- ( mass of Containerdrysoil . + ) (2) SMC = .. ( mass of Containerdrysiol + ) . . .- ( mass of Container ) . The Atterberg limit test verifies the liquid (LL) and plastic (PL) limits of a fine-grained soil. The LL refers to the moisture content at which the soil begins to behave as a liquid ma­terial and begins to flow, while the PL is defined as the moisture content at which soil begins to behave as a plastic material. The LL and PL were determined using the Casagrande method, as described in American Society for Testing and Materials (ASTM) Standard D4318. The dif­ference between the LL and the PL gives the plasticity index (PI). The compaction limit test describes the relationship between the mois­ture content and the dry density of a soil for a specified compactive effort (amount of energy that is applied to the soil). The compaction properties were determined using standard methods (ASTM D698 and ASTM D1557), the standard and modified efforts of 6,000 kN-m/m3 and 27,000 kN-m/m3, respectively, were cho­sen for the determination of the moisture–den­sity relationship. The California bearing ratio (CBR) expresses the ratio of force per unit area required to penetrate a soil mass with stand­ard circular piston at the rate of 1.25 mm/min to that required for the corresponding pen­etration of a standard material [16]. The CBR was determined following the procedure of ASTM D1883. The specific gravity (SG) of the soil was de­termined using a water pycnometer-based standard test (ASTM D854-00) expressed by Equation 3. ( ww - ) 21 , SG = ... ... (3) . ww ) - ( ww . ( -- ) 21 4 where w1 = empty weight of pycnometer, w2 = weight of pycnometer + oven-dried soil, w3 = weight of pycnometer + oven-dried soil + water, and w4 = weight of pycnometer + water. RMZ – M&G | 2020 | Vol. 67 | pp. 197–207 The grain size analysis estimates the per­centage of sand that was passed or retained by an individual sieve. A soil sample of 500 g was sieved to appropriate sieve sizes of 475, 236, 118, 600, 300, 150, 75 µm and weighed. The percentages of particles passing and par­ticles retained, as well as the quantity passing, were calculated using Equations 4, 5 and 6, respectively. , P = Mr * 100 (4) Tm R = 100 - P , (5) Q = T - M , (6) Pm r where Tm = total mass of the soils, R = percent­age retained, P = percentage passing, Mr = mass retained and QP = quantity passing. Data processing and interpretation Characteristics of the VES layers VES 1 The geoelectric curve for VES 1 (Figure 2) depicts five different sub-surface layers, which are as follows: topsoil, with resistivity value of 180O·m, thickness of 0.913m and depth of 0.913 m; sandy clay, with resistivity value of 145 O·m, thickness of 1.24 m and depth of 2.15 m; laterite, with resistivity value of 332 O·m, thickness of 1.56 m and depth of 3.71 m; saturated sandy clay, with resistiv­ ity value of 107O·m, thickness of 4.47m and depth of 8.18 m; weathered basement, with resistivity value of 3,385O·m and an inestima­ble thickness. Due to shrinkage and swelling of clayey soils, excavation must be done until an adequate-load-bearing layer is reached for shallow foundation construction within the VES Profile 1 region. VES 2 The geoelectric curve for VES 2 (Figure 3) depicts four different sub-surface layers, which include the following: topsoil, with resistivity value of 248 O·m, thickness of 0.867 m and depth of 0.867 m; sandy clay, with resistiv­ ity value of 190O·m, thickness of 4.03m and A. A. Alabi. Figure 2: Graph of apparent resistivity against electrode spacing for VES Profile 1. Notes: Blue line represents the phase values on the cross sections; the red line represents true resistivity; the black line in the graph represents apparent resistivity. Figure 3: Graph of apparent resistivity against electrode spacing for VES Profile 2. Notes: Blue line represents the phase values on the cross sections; the red line represents true resistivity; the black line in the graph represents apparent resistivity. depth of 4.9 m; saturated sandy clay, with resis­ tivity value of 175O·m, thickness of 11.9m and depth of 16.8 m; weathered basement, with resistivity value of 240 O·m and an immea­surable thickness. The compactness of the soil increases as the depth below the earth’s sub-surface increases; hence, it is strongly advised to increase the depth of the founda­tions constructed in VES Profile 2 to a depth not less than 3.1 m. VES 3 Four different sub-surface layers were delin­eated for VES 3: the topsoil, with resistivity value of 267 O·m, thickness of 0.573 m and depth of 0.573 m; sandy clay, with resistivity value of 167 O·m, thickness of 0.833 m and depth of 1.41 m; indurated sandy clay, with resistivity value of 671O·m, thickness of 9.92m and depth of 11.3 m; weathered basement, with resistivity value of 4,041O·m and an inestima­ble thickness (Figure 4). The soil constituents in the topsoil are fairly suitable for use in shal­low foundations, while further reinforcement is essential for deep foundations. VES 4 Four major sub-surface geoelectric layers were delineated from the interpretation results ofVES 4; these include the following: the topsoil, with resistivity value of 290 O·m, thickness of 0.564 m and depth of 0.564 m; sandy clay, with resistivity value of 167O·m, thickness of 0.752 m and depth of 1.32 m; indurated sandy clay, with resistivity value of 623O·m, thickness of 7.81 m and depth of 9.13 m; weathered base­ ment, with resistivity value of 4,355 O·m and an infinite thickness (Figure 5). The particles ofsoil constituting the topsoil are suitable for usein shallow foundations, and additional strength­ening is necessary for deep foundations. The VES profiles delineated a maximum of five geoelectric sub-surface layers. These are the top soil, sandy clay, laterite, saturated and indurated sandy clay, and basement rock with shallow sub-surface. The top soil – with resis­tivity values varying from 180O·m to 290O·m and thickness ranging from 0.56 m to 0.91 m – is composed of clayey sand and sand. The top­soil particles are relatively suitable for use in shallow foundations. The second layer is com­posed of sandy clay and clayey sand, with resis­tivity values ranging from 107O·m to 332O·m and thickness values between 0.76 m and 11.9 m. Saturated and indurated sandy clays have resistivity values varying from 240O·m to671O·m and thickness varying between 7.81m and 9.92 m, and the weathered/fresh basement has resistivity values rangingfrom 240O·m to4,355O·m, with the depth to bedrock generally Figure 4: Graph of apparent resistivity against electrode spacing for VES Profile 3. Notes: Blue line represents the phase values on the cross sections; the red line represents true resistivity; the black line in the graph represents apparent resistivity. RMZ – M&G | 2020 | Vol. 67 | pp. 197–207 A. A. Alabi. Figure 5: Graph of apparent resistivity against electrode spacing for VES Profile 4. Notes: Blue line represents the phase values on the cross sections; the red line represents true resistivity; the black line in the graph represents apparent resistivity. Table 1. Summary of the results of the VESs for the study area VES Location No. of layers Resistivity (Om) Thickness (m) Depth (m) Inferred lithology Curve type 1 Latitude 7°08' 17.2" Longitude 3° 17' 13.2" 1 2 3 4 5 180 145 332 107 3,385 0.91 1.24 1.56 4.47 – 0.91 2.15 3.71 8.18 – TopsoilSandy clayLaterite Saturated sandy clayFresh basement AKH 2 Latitude 7° 08' 17.0" Longitude 3° 17' 12.9" 1 2 3 4 248 190 175 240 0.86 4.03 11.9 – 0.86 4.90 16.8 – TopsoilClayey sandSaturated sandy clayWeathered basement HKH 3 Latitude 7° 08' 17.2" Longitude 3° 17' 10.0" 1 2 3 4 267 167 671 4,041 0.57 0.83 9.92 – 0.57 1.41 11.3 – TopsoilSandy clayIndurated sandy clayFresh basement AKH 4 Latitude 7° 08'24.0" Longitude 3° 17' 10.3" 1 2 3 4 290 167 623 4,355 0.56 0.75 7.81 – 0.56 1.32 9.13 – TopsoilSandy clayIndurated sandy clayFresh basement AKH VES, vertical electrical sounding. being <20 m. The best layer that acts as hard rock terrain is the A-type. The A-combination types are characterized by high load-bearing capacity [17]. In the study area, A-combination types (AKH-3 and HKH-1) constitute 75% (Table 1) of the VES survey points, which sug­gest capacity for load bearing. The geoelectric sections and representa­tive horizontal electrical profiling curves of the study area revealed that the lithology of the area is made up of topsoil, sandy clay, laterite (covering a few portions), saturated/Indurated sandy clay and weathered/fresh basement rock (Figure 6). Figure 6: Profiles of the geoelectric sections of the VES stations. Table 2. Results of analyses of the Atterberg limits, SG, moisture content and compaction limit Sample points SP1 SP2 SP3 SP4 SP5 SP6 SP7 SP8 SP9 SP10 LL 38.50 28.00 18.75 17.65 37.56 25.85 18.67 17.34 15.28 14.39 PL 23.97 18.25 13.5 14.09 24.21 17.96 13.81 12.37 12.63 11.98 PI 14.53 9.75 5.25 3.56 13.35 7.89 4.86 4.97 2.65 2.41 1st SG 2.35 2.55 2.64 2.38 2.40 2.67 2.58 2.71 2.57 2.75 2nd SG 2.45 2.57 2.80 2.80 2.45 2.67 2.55 2.38 2.71 2.50 Average SG 2.40 2.56 2.72 2.59 2.43 2.67 2.57 2.69 2.64 2.63 OMC (%) 38.67 14.90 15.20 16.52 47.56 13.94 16.24 11.87 12.57 10.21 MDD (kg/m3) 1,445 2,506 2,100 1,720 1,250 2,850 1,790 3,011 2,910 3,500 Moisture content 23.97 17.25 13.50 14.09 24.21 16.03 13.81 12.34 12.63 11.98 LL, liquid limit; PL, plastic limit; PI, plasticity index; SG, specific gravity; OMC, optimum moisture content; MDD, maximum dry density; SP, sampling point. Geotechnical results and discussion Interpretation of Atterberg limit test The PI of the soil samples (Table 2) revealed that soil samples SP2, SP3, SP4, SP6, SP7, SP8, SP9 and SP10 fall between PIs of 1% and 10%, which implies low plasticity, consisting of sand or silt with traces of clay, while soil samples SP1 and SP5 have PIs between 10% and 20%, depicting medium plasticity and composed of clayey loam soil. All the soil samples SP1–SP10 fall within the limits of the specifications, except SP1 and SP5, for whichthe LL and the PI exceeded the stipulated values of 35% and 12%, respectively, contrary to the Federal Ministry of Works and Housing (FMW&H) specification requirement in Clauses 6201and 6252. The PI of soil samples SP1 and SP5 is above the stan­dard limit and, therefore, they are considered to be highly plastic, which may pose a threat to the structure and consequently lead to struc­tural failure. Results of the SG test Table 2 shows the SG values obtained for the dif­ferent soil samples. All the samples fall between the ranges of specification, varying from 2.5 to RMZ – M&G | 2020 | Vol. 67 | pp. 197–207 A. A. Alabi. 2.75, excluding samples SP1 and SP5, which fall below the limit recommended by FMW&H [18]. In a previous paper [19], it was noted that the SG of soil grains is a key attribute in the assess­ment of aggregate parameters for construction purposes. The higher the SG of the soil towards the upper limit of the soil standard, the better is the soil for construction purposes. Soil moisture content All the samples (Table 2) have moderate moisture content, except for samples SP1 and SP5, which have very high moisture content. Samples SP1 and SP5 are considered to be poor for engineering purpose because of their high content of moisture, and this implies that they have high ability to retain water without releasing it. Results of the compaction limit test The results for the compaction limit test for each sample shown in Table 2 illustrates that the MDD for the soil samples ranges from 1,250 kg/m3 to 3,500 kg/m3, and the OMC ranges from 10.21% to 47.56%. All the samples, except SP1 Table 3. Results of the CBR test for the soil samples Sampling point Location SP1 Latitude 7° 08' 15.8" Longitude 3° 17' 13.3" SP2 Latitude 7° 08' 17.2" Longitude 3° 17' 13.2" SP3 Latitude 7° 08' 18.8" Longitude 3° 17' 13.3" SP4 Latitude 7° 08' 20.5" Longitude 3° 17' 13.4" SP5 Latitude 7° 08' 17.0" Longitude 3° 17' 13.0" SP6 Latitude 7° 08' 16.9" Longitude 3° 17' 11.3" SP7 Latitude 7° 08' 17.2" Longitude 3° 17' 10.0" SP8 Latitude 7° 08' 18.8" Longitude 3° 17' 10.0" SP9 Latitude 7° 08' 20.5" Longitude 3° 17' 10.0" SP10 Latitude 7° 08' 24.0" Longitude 3° 17' 10.3" and SP5, fall within the specifications of the FMW&H (1997), which recommends the MDD to be >1,680 kg/m3 and the OMC to be <18%. The density of the soil mass affects the strength of the soil, which implies that SP1 and SP5 have lower values compared to the standard values. The strength of a soil increases as its dry den­sity increases; the potential for the soil to take on water at later times is decreased by higher densities. Results of the CBR test The overall CBR values for the soaked (CBR_s) and unsoaked (CBR_u) samples, as shown in Table 3, fall within the specified limits for all the soil samples analysed, except for SP1 and SP5. The FMW&H specification states that the minimum strength of the material should not be <80% for CBR (for unsoaked samples), while the minimum strength of the material should not be <10% after at least 48 h of soaking (for soaked samples). The CBR_s values ranged from 3.05% to 29.76%, while CBR_u ranged from 60.25% to 98.95%. The values for CBR_u and CBR_s are 60.25% and 5.62% for SP1 and CBR_u (%) CBR_s (%) 60.25 5.62 89.34 14.00 91.00 18.00 97.00 21.00 70.45 3.95 84.37 12.89 90.56 20.86 97.96 27.95 98.95 29.76 98.00 28.00 Notes: CBR, California bearing ratio; CBR_s, CBR of soaked sample; CBR_u, CBR of unsoaked sample; SP, sampling point. Table 4. Summary of the results of sieve analysis Sample Sieve number 4 8 16 30 50 100 200 PAN Diameter (µm) 475 236 118 600 300 150 75 SP1 % Retained 14.43 12.70 12.99 13.99 9.05 13.08 11.26 12.50 % Passing 85.57 72.87 59.88 45.89 36.84 23.76 12.50 0 SP2 % Retained 9.35 9.83 12.49 12.88 13.5 14.56 15.51 11.88 % Passing 90.65 80.82 68.33 55.45 41.95 27.39 11.88 0 SP3 % Retained 9.72 10.06 12.27 12.43 12.79 14.62 15.60 12.51 % Passing 90.28 80.22 67.95 55.52 42.73 28.11 12.51 0 SP4 % Retained 9.73 13.37 12.39 12.48 13.67 12.81 13.05 12.5 % Passing 90.27 76.9 64.51 52.03 38.36 25.55 12.50 0 SP5 % Retained 10.04 10.23 12.35 12.53 12.67 14.63 15.04 12.51 % Passing 89.96 79.73 67.38 54.85 42.18 27.55 12.51 0 SP6 % Retained 9.91 10.29 12.01 12.51 12.98 14.6 15.19 12.51 % Passing 90.09 79.80 67.79 55.28 42.3 27.7 12.51 0 SP7 % Retained 9.93 10.43 12.56 12.7 13.32 15.56 13.00 12.50 % Passing 90.07 79.64 67.08 54.38 41.06 25.5 12.5 0 SP8 % Retained 10.21 10.31 12.03 12.54 13;00 14.63 14.96 12.32 % Passing 89.79 79.48 67.45 54.91 41.91 27.28 12.32 0 SP9 % Retained 9.84 10.37 12.41 12.24 13.02 14.56 15.03 12.53 % Passing 90.16 79.79 67.38 55.14 42.12 27.56 12.53 0 SP10 % Retained 9.95 10.25 12.25 12.47 12.90 14.50 15.18 12.50 % Passing 90.05 79.80 67.55 55.08 42.18 27.68 12.50 0 Note: SP, sampling point. 70.45% and 3.95% for SP5, respectively. This implies that the soil is clayey lateritic type of soil, which does not support heavy structures. In addition, moisture influx would be highly detrimental to the structures constructed at those locations. Results of sieve analysis All the soil samples SP1–SP10 (Table 4) fall within the limit of specifications for sieve anal­ysis since the percentage by weight of 15.18% passing the No. 200 sieve does not exceed the stipulated value of 35%, as required by the FMWH (1997) in Clause 6201. Conclusion A series of geophysical and geotechnical investigations have been carried out to give proper insight into the nature of sub-surface dispositions and their delineation to ensure building foundation integrity in the study area. The inferred lithology from the VES results revealed a maximum of five geoelectric lay­ers. The geotechnical method, which involved Atterberg limit tests, shows that all the soil samples have low PI and are composed of sand or silt with traces of clay, except samples SP1 and SP5 (soil samples extracted from VES 1 and VES 2), which have medium PI and are composed of clay soil. Soil samples SP1 and SP5 exceeded the stipulated value limit and there­fore pose a threat of structural failure. All the soil samples, except SP1 and SP5, had average SG values within the range of standard speci­fications. The laboratory result for the CBR for soil samples SP1 and SP5 indicated that the soil is clayey lateritic, which is highly detrimental to structures due to influx of moisture. The sieve analysis result showed that the entire set of soil samples has a size range within the RMZ – M&G | 2020 | Vol. 67 | pp. 197–207 A. A. Alabi. limit of specifications and does not exceed the standard value. The result for compaction limit revealed that all the soil samples are within the specified standard, except SP1 and SP5. It is vital to note that shallow foundations for any engineering structure are considered unsuit­able at the weak zones because of the presence of incompetent materials, which tend to pose a threat to the development of future civil engi­neering structures in any given area. References [1] Amadi, A.N., Eze, C.J., Igwe, C.O., Okunlola, I.A., Okoye, N.O. (2012): Architects and geologists view on the causes of building failures in Nigeria. Modern Applied Science, 6(6), pp. 31, DOI:10.5539/mas.v6n6p31. [2] Ayininuola, G.M., Olalusi, O.O. (2004): Assessment of building failures in Nigeria: Lagos and Ibadan Case Study. African Journal of Science and Technology, 5(1), pp. 73–78, DOI:10.4314/ajst.v5i1.15321. [3] Dimuna, K.O. (2010): Incessant incidents of building collapse in Nigeria. A challenge to stakeholders. Global Journal of Researches in Engineering, 10(4), pp. 75–84. [4] Oyedele, K.F., Okoh, C. (2011): Subsoil investigation using integrated methods at Lagos, Nigeria. Journal of Geology and Mining Research, 3(7), pp. 169–179. [5] Olayanju, G.M., Mogaji, K.A., Lim, H.S., Ojo, T.S. (2017): Foundation integrity assessment using integrated geophysical and geotechnical techniques: Case study in crystalline basement complex, Southwestern Nigeria. Journal of Geophysics and Engineering, 14(3), pp. 675–690, DOI:10.1088/1742-2140/aa64f7. [6] Oluwafemi, O., Ogunribido, T.H. (2014): Integrated geophysical and geotechnical assessment of the per­ manent site of Adekunle Ajasin University, Akungba- Akoko, Southwestern, Nigeria. Pelagia research library, 5(2), pp. 199–209. [7] Oladele, S., Oyedele, K.F., Dinyo, M.O. (2015): Pre-construction geoelectrical and geotechnical assessment of an engineering site at Alapere/Agboyi, Lagos, Nigeria. Ife Journal of Science, 17(3), pp. 543–552. [8] Falae, P.O. (2014): Application of electrical resistiv­ ity in buildings foundation investigation in Ibese Southwestern Nigeria. Asia Pacific Journal of Energy and Environment, 1(2), pp. 95–107, DOI:10.15590/ apjee/2014/v1i2/53748. [9] Soupois, P.M., Georgakopoulos, P., Papadopoulos, N., Saltos, V., Andreadakis, A., Vallianatos, F., Sanis, A., Markris, J.P. (2007): Use of engineering geophysics to investigate a site for a building foundation. Journal of Geophysics and Engineering, 4(1), pp. 94–103, DOI:10.1088/1742-2132/4/1/011. [10] Farinde, M.A., Oni, S.O. (2015): Geophysical and geotechnical characterization of newly constructed Abadina-Ajibode road, University of Ibadan, Ibadan. Journal of Multidisciplinary Engineering Science and Technology (JMEST), 2(1), pp. 363–378. [11] Alabi, A.A., Adewale, A.O., Coker, J.O., Ogunkoya, O.A. (2017): Site characterization for construction pur­poses at FUNAAB using geophysical and geotechnical methods. RMZ–Materials and Geoenvironment, 64, pp. 1–14, DOI:10.2478/rmzmag-2018-0007. [12]Adejumo, S.A., Oyerinde, A.O., Aleem, M.O. (2015): Integrated geophysical and geotechnical subsoil evaluation for pre-foundation study of proposed site of vocational skill and entrepreneurship center at The Polytechnic, Ibadan, SW, Nigeria. International Journal of Scientific and Engineering Research, 6(6), pp. 2229–5518. [13] Akinse, A.G., Gbadebo, A.M. (2016): Geologic map­ping of Abeokuta metropolis, southwestern Nigeria. International Journal of Scientific and Engineering Research, 7(8), pp. 2229–2518. [14] Loke, M.H. (1999): Electrical imaging surveys for environmental and engineering studies; a practical guide to 2-D and 3-D surveys. Self-Published Note Book, pp. 15–57. [15] Black, C.A. (1965): Methods of Soil Analysis. Part 1, American Society of Agronomy, No 9. [16] Roy, T.K., Chattapadhyay, B.C., Roy, S.K. (2010): California bearing ratio evaluation and estimation: a study of comparison. Indian Geotechnical Conference, IGC-2010, IIT, Mumbai, pp. 19–22. [17]Mookiah, M., Thiagarajan, S., Madhavi, G. (2015): Surface geo-electrical Sounding for the deter­mination of aquifer characteristics in part of the Palar Sub-Basin, Tamilnadu, India. International Conference on Science Technology Engineering and Management [ICON-STEM’15], 8. [18] Federal Ministry of Works and Housing (FMW&H). (1997): General specification for roads and bridges. Vol II, Federal Highway Department, FMWH, Lagos, Nigeria, 168 p. [19] Gidigasu, M.D. (1976): Laterite soil engineering (Pedogenesis and Engineering Principles). Elsevier Scientific Publishing Company: Amsterdam, 554 p. Original Scientific Article Received: February 17, 2021 Accepted: February 19, 2021 DOI: 10.2478/rmzmag-2020-0017 Geochemical Fingerprinting pf Oil-Impacted Soil and Water Samples In Some Selected Areas in the Niger Delta Geokemicni kazalniki z nafto nasicenih vzorcev zemljin in vode na nekaterih izbranih podrocjih delte reke Niger Adeola V. Adeniyi*, Matthew E. Nton, Falode O. Adebanjo Department of Geology, University of Ibadan, Ibadan, Nigeria *Corresponding author: E-mail: adeolaadeniyi93@gmail.com Abstract With over 50 years of oil exploration and exploitation in the Niger Delta, there has been an increasing rate of environmental degradation due to hydrocarbon pollution. This study is aimed at tracing the sources of the oil spills and the distribution of pollutants in selected communities in the Niger Delta using geo­chemical techniques. A total of sixteen samples made up of ten crude oil-impacted soil samples taken at a depth of 30 cm and six water samples (two from boreholes, two from burrow pits and two from sur­face water – one from a river and the other from rain harvest as control) were collected. The identification and quantification of aliphatic hydrocarbons (AHs) and polycyclic aromatic hydrocarbons (PAHs) in the samples were performed with an Agilent 7890B gas chromatography flame ionisation detector (GC­FID). The AHs including pristane and phytane, to­gether with seventeen priority PAHs, were identified. The values of AHs and PAHs in the water samples ranged from 0.13 mg/l to 5.78 mg/l and 0.09 mg/l to 1.109 mg/l, respectively, while that for the soil sam­ples ranged from 22.52 mg/kg to 929.44 mg/kg and 10.544 mg/kg to 16.879 mg/kg, respectively. Key words: PAH, aliphatic hydrocarbon, fingerprinting Introduction The Niger Delta is one of the major hydrocar­bon provinces of the world, with an estimated reserve of about 23 billion barrels of oil and 183 trillion cubic feet of natural gas with ongoing exploration in the province for over 50 years Povzetek Z vec kot petdesetimi leti raziskovanja in pridobivanja nafte na obmocju delte reke Niger narašca stopnja degradacije okolja zaradi onesnaževanja z ogljikovodiki. Namen raziskave je slediti virom razlitij nafte in porazdelitev onesnaževal v izbranih skupnostih v delti reke Niger z uporabo geokemicnih pristopov. Skupno je bilo odvzetih 16 vzorcev, od tega 10 vzorcev z nafto nasicenih zemljin iz globine 30 cm ter 6 vzorcev vode, od tega dva iz vrtin, dva iz jame ter dva iz površinske vode (en vzorec iz reke in en iz deževnice). Z detektorjem plamenskega ioniziranja s plinskim kromatografom Agilent 7890B (GC-FID) je bila izvedena identifikacija in kvantifikacija alifatskih ogljikovodikov (AH) in policiklicnih aromatskih ogljikovodikov (PAH). Identificirani so bili AH z vkljucujocim pristanom (pristane) in fitanom (phytane) skupaj s 17 PAH. Vrednosti AH in PAH v vzorcih vode se gibajo med 0.13 mg/l do 5.78 mg/l in 0.09 mg/l do 1.109 mg/l. Vrednosti AH in PAH v vzorcih zemljine se gibajo med 22.52 mg/kg do 929.44 mg/kg in 10.544 mg/kg do 16.879 mg/kg. Kljucne besede: PAH, alifatski ogljikovodik, kazalniki [1]. Much of the oil industries located within this region have contributed immensely to the growth and development of the nation. However, oil exploration activities haverendered the Niger Delta region one of themost severely degraded ecosystems in theworld [2]. Crude oil spills are common in the region with an estimated total of over 7,000oil spill accidents reported over 50 years [3].Studies have shown that the quantity of oilspilt over this period amounts to 9–13 mil­ lion barrels, which is equivalent to 50 Exxon Valdez spills [4]. These spills occur through equipment fail­ure, operational mishap, haulage, oil bunkering and/or vandalisation of pipelines leading to the destruction of aquatic and terrestrial flora and fauna of the Niger Delta region [5]. Geochemical or Oil fingerprinting is one ofthe ways of assessing and evaluating petroleumpollution. It involves the analysis of the releasedoil with gas chromatography (GC) and measure­ment of the hydrocarbon compound contents[6]. From the qualitative method (visual com­parison of chromatograms) as well as quan­titative determination of polycyclic aromatichydrocarbons (PAHs) diagnostic ratio, n-alkane distribution and statistical analysis of data ob­tained are used for source identification and in­terpretation of chemical data from oil spills. Anassessment and evaluation of hydrocarbon pol­lution are therefore essential to curb the grow­ing rate of environmental degradation in the region as well as its social, economic and healthimpacts. This assessment includes; determina­tion of sources, characterisation, distribution,and fate of organic pollutants such asPAHs andaliphatic hydrocarbons (AHs) in the Niger Delta.The objective is to evaluate the AH and PAHswhich are said to be source-specific. Location and geology of the study area The study area lies within the Niger Delta region between latitudes 5°37'00"E–5°47'00"E and longitudes 5°53'00"N–6°02'30"N (Figure 1) and cuts across Sapele and Ethiope West Local government, Delta State, Nigeria. Stratigraphically, the Niger Delta consists of three formations, notably; Akata Formation, which is the oldest unit and constitutes under compacted shales, turbidites and silts. This is overlain by the paralic Agbada Formation, made up of alternating sequences of sand­stone and shale which contains most of the hydrocarbon reservoirs in the basin while the youngest unit is the Benin Formation, which is made up of continental sands [7]. The area is Figure 1: Geological map of the Niger Delta region showing the study area (modified after Geological Map of Niger Delta [8]). RMZ – M&G | 2020 | Vol. 67 | pp. 209–219 Adeniyi et al. characterised by an even topography. It is situ­ated in the tropics and experiences a fluctuat­ing climate characterised by rainy and dry sea­sons. The area is drained by minor rivers which are tributaries of the major River Ethiope with a dendritic pattern. Materials and methods Sampling and sample preparation The field study involved the collection of soil andwater samples from selected points as shown inFigure 2. A total of sixteen samples made up of tencrude oil-impacted soils taken at a depth of 30 cmand six water samples (two from boreholes, twofrom burrow pits plus and two from surfacewater – one from a river and the other from rain harvest as control) were collected. The water andsoil samples were collected in clean, well-labelledglass jars and aluminium foils, respectively, andtaken to the laboratory for analyses. Due to the relatively high volatility and instability of AHsand PAHs, the soils were not prepared using con­ventional soil preparation techniques such asgrinding and sieving. However, the soil sampleswere dried by mixing the samples with 5 g ofanhydrous sodium sulfate. Analytical methods Organic pollutants were separated from thesoil and water samples using an ultrasonicextraction and a separatory funnel, respec­tively. The extracts were fractionated into theAH and PAH fractions by eluting with n-hex­ane and dichloromethane, respectively. The identification and quantification of AHs andPAHs were performed with an Agilent 7890Bgas chromatography flame ionisation detector(GC-FID). The gas chromatographic columnhas a detection limit of 0.01 ppm. Separationoccurs as the constituents of the vapour par­tition between the gas and liquid phases andoven temperature was programmed from 60°C Figure 2: Map of study area showing the sample points (insert: map of Nigeria showing the Niger Delta region). to 180°C. Identification of analytes was doneby comparing the retention time of an individ­ual compound to that of a reference standard. Results and discussion Concentration of AH and PAH The results of the AH and PAHs in this study are shown in Table 1. The concentrations of the AHs and PAHs found in the studied samples are low when compared with values from other areas in the Niger Delta (Table 2). However, in this study, the concentrations are higher than the regulatory limits given by the United Nations Environment Programme (UNEP) [9]. Occurrence, distribution and sources of PAHs The distribution of seventeen priority PAHs in the water and soil samples in the study area is presented in Table 3. The main PAH pol­lutants in the studied areas were found to be Chrysene, Acenaphthene, Methylnaphthalene, Naphthalene, Anthracene, Benzo(g,h,i)perylene, Fluorene, Indeno(1,2,3-cd)perylene and Phenanthrene. It is important to note that the sum of the PAHs in the contaminated soil samples is 10.54–16.89 times higher than the standard level (1 mg/kg) of heavy [10]. The level of PAH pollution in the control sample (Sw-1) is very low as compared with those from the other samples studied. The spatial distribution of PAHs in this study is shown in Figure 3 and indicates a predominance of three-ring PAHs which suggests recent depo­sition according to Jiao et al. [11]. The abun­dance of three-ring PAHs in the study area is in agreement with studies of some oil-pol­luted sites in the Niger Delta [12]. The four-ring PAHs are also abundant and they indi­cate the persistence of high molecular weight (HMW) PAHs in the environment. According to Li et al. [13], petrogenic sources are those PAHs derived from petroleum spills while pyrogenic sources are generated by incomplete combus­tion of fossil fuel such as coal, crude oil and natural gas plus biomass. Diagnostic ratios such as Phenanthrene/Anthracene, Fluorene/Pyrene, Benz(a)pyrene/Chrysene, Naphthalene/Acenaphthene, Anthracene/(Phenanthrene + Anthracene), Fluoranthene/(Fluoranthene + Table 1: Results of concentration of the AHs and PAHs present in the soil and water samples Sample name Sample medium AHs PAHs Css_1 Soil 37.59 mg/kg 16.88 mg/kg Css_2 Soil 25.70 mg/kg 11.66 mg/kg Css_3 Soil 34.43 mg/kg 14.72 mg/kg Css_4 Soil 22.52 mg/kg 14.77 mg/kg Css_5 Soil 929.44 mg/kg 14.54 mg/kg Css_6 Soil 79.55 mg/kg 15.91 mg/kg Css_7 Soil 36.85 mg/kg 13.11 mg/kg Css_8 Soil 34.86 mg/kg 10.54 mg/kg Css_9 Soil 44.73 mg/kg 12.15 mg/kg Css_10 Soil 41.93 mg/kg 15.81 mg/kg Cbw_1 Water 0.22 mg/l 0.09 mg/l Cbw_2 Water 0.13 mg/l 0.29 mg/l Pw_1 Water 5.78 mg/l 0.86 mg/l Pw_2 Water 5.14 mg/l 1.11 mg/l Sw_1 Water (control) 0.61 mg/l 0.17 mg/l Sw_2 Water 2.08 mg/l 0.86 mg/l AH, aliphatic hydrocarbon; PAHs, polycyclic aromatic hydrocarbons. RMZ – M&G | 2020 | Vol. 67 | pp. 209–219 Adeniyi et al. Table 2: Comparison of AH and PAH present in the studied samples with those found in some other areas in the Niger Delta and some regulatory standards Sample medium Reference AHs (mg/l) PAHs (mg/l) Contaminated soil Borehole Present study Olawoyin et al. [14] Adedosu et al. [12] Udoetok and Osuji Leo [24] United Nations Environment Programme (UNEP) [9] Department of Petroleum Resources (DPR) [15] United States Environmental Protection Agency (USEPA) [10] Present study 22.52–929.44 7,878.8–76,510.9 575.96–1,202.47 77.64–3,946.58 10 No limit No limit 0.13–0.22 10.54–16.88 31.4–132.0 7.40–78.30 8.16–3,756.81 No limit 1.00 1.00 0.09–0.29 Olawoyin et al. [14] Ibezue et al. [29] WHO No limit 0.03–0.422 0.0002 119.90–450.58 0.002–0.007 0.0002 Department of Petroleum Resources (DPR) [15] No limit 0.1 Surface water Present study 0.61–2.08 0.17–0.86 Inyang et al. [30] 2.5–183.0 No limit European Union Environmental Protection Agency (EUEPA) [25] 0.3 No limit Department of Petroleum Resources (DPR) [15] No limit 0.0001 WHO No limit 0.05 Contaminated Present study 5.14–5.78 0.86–1.11 water Inyang et al. [30] 2.5–183.0 No limit European Union Environmental Protection Agency (EUEPA) [25] 0.3 No limit WHO No limit 0.05 AH, aliphatic hydrocarbon; PAH, polycyclic aromatic hydrocarbon. Pyrene), Benzo(a)anthracene/(Benzo(q)anthracene+ Chrysene), Indeno(1,2,3-cd)perylene/(Indeno(1,2,3-cd)perylene + Benzo(g,h,i)perylene) and low molecular weight (LMW) hydrocar-bon/HMW hydrocarbon have been utilised in deducing the source of pollution [18, 20, 23, 26, 28]. From the source diagnostic indices as pre­sented in Table 4, most PAHs in the study area are from petrogenic sources with a minor con­tribution from pyrogenic sources. Normal alkanes and isoprenoids distribution and sources Although some components of the PAHs andAHs in the study area have been degraded, themajority of the other components still persist in the environment which may affect groundwater,rivers and soils. This may be injurious to bothhuman and animal health. Some sources of the PAH and AH studied are pyrolytic, i.e. from com-bustion/bush fire occasioned by explosion of oiltankers, oil installations, leakages from oil pipesand pipelines explosion during oil bunkering orpipeline vandalism. All these have bearing onagriculture, water supply settlement and thebiodiversity within the study area. Cancer risk assessment PAHs are known to be injurious to health. Theeight PAHs typically considered as possible car­cinogens are Benzo(a)anthracene, Chrysene,Benzo(b)fluoranthene, Benzo(k)fluoranthene, RMZ – M&G | 2020 | Vol. 67 | pp. 209–219 Adeniyi et al. Table 3: Occurrence and spatial distribution of PAHs in the soil and water samples PAHs Water samples (mg/l) Soil samples (mg/kg) Cbw_1 Cbw_2 Pw_1 Pw_2 Sw_1 Sw_2 Css_1 Css_2 Css_3 Css_4 Css_5 Css_6 Css_7 Css_8 Css_9 Css_10 Nap BDL 0.04 0.098 0.043 BDL 0.046 0.814 0.819 0.809 0.758 1.228 1.004 0.913 0.807 0.746 0.788 Mnap BDL BDL 0.066 0.176 BDL 0.064 1.814 1.007 1.356 1.106 3.249 1.548 1.264 1.093 1.235 1.350 Acep BDL BDL 0.056 0.037 BDL 0.066 3.352 1.148 1.666 0.683 1.459 2.311 1.672 1.340 1.740 1.830 Ace BDL 0.07 0.081 0.087 BDL 0.073 1.404 1.437 1.420 1.558 3.020 1.536 1.401 1.410 1.376 1.433 Fl BDL BDL 0.036 0.173 BDL 0.042 0.768 BDL 0.697 1.216 1.085 0.959 0.706 0.697 0.769 0.771 Phe BDL 0.06 0.061 0.048 BDL 0.057 0.985 1.041 1.032 1.027 0.174 1.509 0.961 0.803 0.801 0.958 Ant BDL 0.01 0.010 0.133 0.166 0.017 0.364 0.274 0.375 0.744 0.111 1.632 0.336 0.222 0.233 0.265 Flu BDL 0.05 0.046 0.040 BDL 0.057 0.924 0.906 1.156 0.841 0.088 0.301 1.027 0.759 0.747 0.927 Pyr BDL BDL BDL BDL BDL BDL BDL BDL BDL BDL 0.146 0.250 BDL BDL BDL BDL BaA BDL BDL 0.133 0.050 BDL 0.015 0.299 BDL 0.313 0.707 0.259 0.134 0.292 0.124 0.104 0.269 Chr 0.02 0.05 0.205 0.137 BDL 0.033 1.217 0.296 0.758 1.265 0.108 0.483 0.620 0.241 0.491 0.082 BbF 0.02 0.01 0.010 0.042 BDL 0.105 1.592 0.728 0.506 2.668 0.085 0.447 0.501 0.108 1.149 0.066 BkF 0.02 0.01 0.018 0.010 BDL 0.018 0.860 0.320 0.199 0.434 0.269 0.169 0.393 0.157 0.242 0.248 BaP 0.02 BDL BDL 0.025 BDL 0.015 0.252 0.215 0.883 0.228 0.091 0.366 0.167 0.413 0.203 0.283 DahA BDL BDL 0.026 0.012 BDL 0.014 0.202 0.211 0.290 0.194 0.065 0.151 0.359 0.516 0.263 0.295 InP 0.01 BDL BDL 0.038 BDL 0.114 0.912 1.895 0.407 0.665 0.562 0.396 0.598 0.659 0.182 3.374 BghiP BDL BDL BDL 0.060 BDL 0.126 1.119 1.362 2.852 0.673 2.545 2.722 1.899 1.193 1.869 2.870 Total 0.09 0.3 0.856 1.109 0.166 0.863 16.879 11.657 14.720 14.768 14.543 15.917 13.108 10.544 12.151 15.807 Mean 0.005 0.02 0.050 0.065 0.010 0.051 0.993 0.688 0.866 0.869 0.855 0.936 0.771 0.620 0.715 0.930 Ace, Acenaphthene; Acep, Acenaphthylene; Ant, Anthracene; BaA, Benzo(a)anthracene; BaP, Benzo(a)pyrene; BbF Benzo(b)fluoranthene; BDL, Below Detection Limit; BghiP, Benzo (g, h, i) perylene; BkF, Benzo(k)fluoranthene; Chr, Chrysene; DahA, Dibenzo (a, h) anthrace; Fl, Fluorene; Flu, Fluoranthene; InP, Indeno (1, 2, 3-cd) perylene; Mnap, 2-Methylnaphthalene; Nap, Naphthalene; Phe, Phenanthrene; Pyr, Pyrene. Benzo(a)pyrene, Dibenzo(a,h)anthracene,been identified as being highly carcinogenic. Indeno(1,2,3-cd)pyrene and Benzo(g,h,i)The World Health Organization (1993) revealed perylene. In particular, Benzo(a)pyrene has that Benzo(a)pyrene concentration of 0.7 mg/lcorresponds to an excess lifetime cancer risk of10–5. The BaP-equivalent (BaPE) is used as a way to access carcinogenic risk due to the con­tamination by PAHs. The BaPE not only includesthe risk due to BaP but also calculates all of the carcinogenic PAHs, where each of the PAH isweighed according to its carcinogenicity in rela­tion to the carcinogenicity of BaP, which is mea­sured by 1. This index can be calculated withthis equation [17]; BaPE= BaP + (BaA*0.06) + (BkF*0.07) + (BbF*0.07) + (DahA*0.06) + (InP*0.08). BaPE ranged from 0mg/l to 0.042mg/land 0.22 mg/kg to 1.16 mg/kg in the water andsoil samples, respectively. The highest value of BaPE in the samples is in Css_3, hence indicating PAH diagnostic ratio .LMW/.HMW Fl(Fl + Pyr) Value range <1 >1 <0.5 >0.5 Source PyrogenicPetrogenic Petroleum Emissions Diesel Emissions Reference Zhang et al. [26] Ravindra et al. [20] Value ranges from studied samples 0–2.45 0–0.4 Inferred source Petrogenic/pyrogenic Petroleum emissions Ant(Phe + Ant) Flu(Flu + Pyr) <0.1 >0.1 <0.4 0.4–0.5 >0.5 PetrogenicPyrogenic PetrogenicFossil fuel Combustion Grass, wood, coal combustion Pies et al. [18] De La Torre-Roche et al. [27] 0–0.21 0–0.4 Petrogenic/pyrogenic Petrogenic/mixed source of fossil fuel and combustion BaA/(BaA + Chr) 0.2–0.35 >0.35 Coal combustion Vehicular emission Aky and Çabuk [23] 0–0.31 Coal combustion/petrogenic <0.2 >0.35 Petrogenic Combustion Yunker et al. [28] InP/(InP + BghiP) <0.2 0.2–0.5 Petrogenic Petroleum Combustion Yunker et al. [28] 0–0.23 Petrogenic/petroleumcombustion >0.5 Grass, Wood, Coal Combustion SLMW/SHMW, the sum of low molecular weight hydrocarbon/the sum of high molecular weight hydrocarbon. RMZ – M&G | 2020 | Vol. 67 | pp. 209–219 Adeniyi et al. Table 5: The concentrations of AHs in the soil and water samples AHs Water samples (mg/l) Soil samples (mg/kg) Cbw_1 Cbw_2 Pw_1 Pw_2 Sw_1 Sw_2 Css_1 Css_2 Css_3 Css_4 Css_5 Css_6 Css_7 Css_8 Css_9 Css_10 C8 BDL BDL BDL 0.11 BDL 0.51 12.76 1.13 0.59 0.30 2.38 BDL 1.32 1.44 1.77 9.42 C9 BDL BDL 0.02 0.01 BDL BDL BDL BDL BDL BDL BDL BDL BDL BDL BDL BDL C10 BDL BDL 0.81 0.17 BDL 0.01 BDL BDL BDL BDL 0.94 BDL BDL BDL 0.29 0.59 C11 BDL BDL 0.08 0.04 BDL 0.04 1.63 BDL BDL BDL 11.06 BDL BDL BDL BDL 0.53 C12 BDL BDL 0.18 0.11 BDL BDL BDL BDL BDL BDL 6.35 BDL BDL 0.06 BDL 0.04 C13 BDL BDL 0.23 0.18 BDL 0.14 2.43 0.36 0.46 BDL 11.24 BDL BDL 0.18 1.28 3.06 C14 BDL 0.02 0.33 0.23 0.03 0.01 0.53 0.77 0.66 0.42 47.91 0.09 BDL 0.17 0.57 0.56 C15 BDL BDL 0.31 0.23 BDL BDL BDL BDL BDL 0.06 48.04 0.88 0.13 0.29 BDL BDL C16 BDL 0.04 0.33 0.25 0.02 0.01 0.85 0.19 0.12 0.69 29.37 3.90 0.31 0.39 0.95 0.89 C17 BDL BDL 0.31 0.25 BDL BDL BDL BDL BDL BDL 9.39 6.82 BDL BDL BDL BDL C18 BDL 0.03 0.28 0.23 0.01 0.04 0.45 0.10 0.73 0.60 17.20 7.94 0.13 BDL 0.93 0.64 C19 BDL 0.01 0.21 0.20 0.02 BDL BDL 0.27 0.22 0.13 16.14 7.08 BDL 0.19 0.14 BDL C20 BDL 0.02 0.22 0.28 0.03 0.05 0.39 1.18 0.65 0.78 24.05 7.78 1.24 1.36 1.65 0.74 C21 BDL BDL 0.20 0.19 BDL BDL BDL BDL BDL 0.12 15.49 6.19 0.04 BDL BDL BDL C22 BDL BDL 0.26 0.22 0.02 0.02 1.37 0.57 0.28 BDL 15.23 5.27 1.49 1.71 0.45 0.17 C23 0.01 BDL 0.26 0.17 BDL BDL 0.13 BDL BDL 0.24 11.69 4.35 BDL 0.42 BDL BDL C24 0.01 0.02 0.36 0.23 0.03 BDL BDL BDL 0.60 1.62 19.32 4.16 0.38 0.34 BDL 0.05 C25 0.02 BDL 0.30 0.17 BDL BDL 0.40 BDL BDL 0.19 13.90 3.17 BDL BDL BDL BDL C26 0.02 BDL 0.12 0.16 BDL 0.04 0.73 0.66 1.01 0.74 12.47 2.75 1.40 1.14 1.15 0.96 C27 0.02 BDL 0.14 0.14 BDL BDL 0.59 BDL BDL 0.31 10.58 2.44 BDL 0.19 BDL BDL C28 0.01 BDL 0.11 0.12 BDL 0.03 0.86 0.30 0.71 0.54 18.87 1.93 0.96 1.18 0.80 0.68 C29 BDL BDL 0.08 0.10 BDL BDL 0.24 BDL BDL BDL 30.88 1.19 BDL BDL BDL BDL C30 BDL BDL 0.08 0.05 BDL BDL BDL BDL BDL BDL 29.12 0.29 BDL BDL BDL BDL C31 BDL BDL 0.08 0.08 BDL BDL 1.06 BDL BDL BDL 15.14 1.11 0.63 0.32 BDL BDL (Continued) Table 5: Continued AHs Water samples (mg/l) Soil samples (mg/kg) Cbw_1 Cbw_2 Pw_1 Pw_2 Sw_1 Sw_2 Css_1 Css_2 Css_3 Css_4 Css_5 Css_6 Css_7 Css_8 Css_9 Css_10 C32 BDL BDL BDL BDL BDL 0.11 BDL 2.47 4.62 0.72 4.53 BDL BDL 0.44 5.40 3.79 C33 BDL BDL BDL 0.31 BDL 0.40 5.05 8.38 12.62 2.20 13.12 BDL 3.23 4.24 13.73 10.84 C34 BDL BDL BDL BDL BDL BDL BDL BDL BDL BDL 15.04 3.88 3.66 BDL BDL BDL C35 BDL BDL BDL BDL 0.07 BDL BDL BDL 11.16 BDL 6.12 BDL BDL BDL BDL BDL C36 0.13 BDL BDL 0.75 0.03 0.02 8.12 7.66 BDL 6.97 11.78 BDL 9.81 7.43 12.83 11.78 C37 BDL BDL 0.15 BDL 0.26 0.65 BDL BDL BDL BDL 5.90 BDL 9.99 11.26 BDL BDL C38 BDL BDL BDL BDL BDL BDL BDL BDL BDL BDL 2.27 BDL BDL BDL BDL BDL C39 BDL BDL BDL BDL BDL BDL BDL BDL BDL BDL BDL BDL BDL BDL BDL BDL C40 BDL BDL BDL BDL BDL BDL BDL BDL BDL BDL BDL BDL BDL BDL BDL BDL PRISTANE BDL BDL 0.27 0.16 BDL BDL BDL BDL BDL 5.32 392.91 6.70 BDL BDL BDL BDL PHYTANE BDL BDL 0.04 0.02 0.08 BDL BDL 1.67 BDL 0.56 61.00 1.64 2.12 2.10 BDL BDL Pr/nC17 0 0 0.900.630 0 0 0 0 041.840.98 0 0 0 0 Total 0.22 0.13 5.78 5.14 0.61 2.08 37.59 25.69 34.43 22.52 929.44 79.55 36.85 34.86 44.73 41.94 AH, aliphatic hydrocarbon. Table 6: The AH diagnostic ratios (after Sojinu et al. [22]) Sample CPI OEP Cbw_1 0.29 1.81 Cbw_2 0.06 0 Pw_1 0.76 0.82 Pw_2 0.71 0.79 Sw_1 2.14 0 Sw_2 1.47 0 Css_1 0.44 0.21 Css_2 0.60 0 Css_3 2.46 0 Css_4 0.24 0.27 Css_5 0.85 0.72 Css_6 0.87 0.94 Css_7 0.68 0.006 Css_8 1.09 0.31 Css_9 0.57 0 Css_10 0.48 0 Mean 0.86 0.37 AH, aliphatic hydrocarbon. that PAHs at this sample point have high car­cinogenic effects. Conclusion The prevalence of petrogenic-derived PAHs wasconfirmed in the studied samples. AHs in bothmedia originated from both petrogenic and bio-genic. The AHs are products from both terres­trial and marine inputs. The pollution level of the study area is high as compared with USEPA, DPR and WHO standards which poses healthhazards. However, the values are lower com­pared with other areas in the Niger Delta. 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