Geochemical dynamics and origin of natural radionuclides and heavy metals in current coastal sedimentary systems in the Republic of Congo

Geochemical dynamics and origin of natural radionuclides and heavy metals in current coastal sedimentary systems in the Republic of Congo | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Geochemical dynamics and origin of natural radionuclides and heavy metals in current coastal sedimentary systems in the Republic of Congo Freddy Cacharel KAYA, Hasna AIT BOUH, Jémina Consolé BOUNKOUTA, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8330803/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This study aims to characterize the geochemical distribution, levels, and origin of natural radionuclides ( 238 U, 226 Ra, 210 Pb, 232 Th, and 40 K) and heavy metals (Cd, Pb, Zn, Mn, Mg, and Cu) in recent sediment samples from the coast of the Republic of Congo, an environment subject to significant human pressure but still understudied. Surface samples were collected in river and lagoon estuaries, then analyzed by gamma spectrometry (GeHP) for radionuclides and by atomic absorption spectroscopy (AAS) for heavy metals. Additional analyses of organic matter (LOI), Pearson correlations, and ACP allowed us to determine the origin and geochemical dynamics of the elements. The results show activities that are mostly below the UNSCEAR thresholds, except for notable enrichments in 210 Pb at Mvassa and 232 Th at Loukonzi lagoons. The metals show significant contamination in Cd and Pb, associated with industrial, port, and petroleum activities. The spatial distribution is controlled by grain size, hydrodynamics, organic matter, and atmospheric inputs. These results highlight the coexistence of lithogenic and anthropogenic sources and emphasize the need for enhanced environmental monitoring in sensitive areas to anticipate the growing impacts of industrial pressures and climate change. Environmental Chemistry Geochemistry Natural radionuclide heavy metal coastal sediment geochemical dynamics localized enrichment lithogenic and anthropogenic sources Figures Figure 1 Figure 2 Highlights - Localized radionuclide enrichments (Pb and Th); - Significant contamination in heavy metals (Cd and Pb); - Multifactorial geochemical control; - Coexistence of both lithogenic and anthropogenic sources. 1. Introduction Primordial naturally occurring radioactive metals, also known as geogenic or telluric metals, such as 238 U, 235 U, 232 Th, and 40 K, as well as their decay products; stable heavy metals (Ag, As, Cd, Co, Cr, Cu, Hg, Ni, Pb, Se, Sn, V, Y, Zn, etc.) are present in low concentrations in the Earth's crust and soils, mainly in trace amounts since the formation of the Earth (IAEA, 2017; Callender, 2003 ; Alloway and Ayres, 1997). Their redistribution on the surface of continents occurs via three main natural phenomena: the weathering of outcropping rocks, the dissolution or leaching of rocks by groundwater, and volcanic eruptions (IAEA, 2017). Furthermore, anthropogenic industrial activities such as mining and oil extraction, energy production, agriculture, livestock farming, fishing, and maritime traffic are major sources of radionuclides and heavy metals in terrestrial environmental compartments (Cook et al., 2018 ; Chalghmi, 2015 ; IARC, 2012; Persson and Holm, 2011 ; IRSN, 2002, 2010; Carvalho, 2006 , 2011 ). These emissions, which, combined with the effects of climate change (marine acidification, anoxia, coastal erosion, sea level rise), weaken ecosystems and public health (IAEA, 2021 ; IARC, 2012; USEPA, 2002). Sediments, which are veritable environmental archives, make it possible to monitor the levels of radioactive and non-radioactive pollutants in aquatic systems, whose behavior, mobility and toxicity are strongly modulated by ion chemistry and various processes such as adsorption, co-precipitation, or fixation on colloids (Madadi et al., 2023 ; IAEA, 2017; Strady, 2010 ; Aranguren, 2008 ; Callender, 2003 ), that is to say, to a large extent, depend on their type of binding forms, in particular exchangeable forms, carbonates, iron and manganese oxides, sulfides and organic matter, as well as the residual fraction. Nevertheless, in the regional context, anthropogenic pressure is high in the Congo coastal sedimentary basin (oil, ports, industry, agriculture). However, studies on radioactive and metal contamination and the detailed geochemistry of marine-coastal sediments remain very limited. In this context, the objective of this study is to characterize the distribution and levels of natural radionuclides and heavy metals in recent sediments in the coastal systems of the Republic of Congo, with a view to elucidating their origin and the biogeochemical, hydrodynamic, and anthropogenic processes that determine their behavior, accumulation, and spatial distribution. This investigation responds to an essential need for reference data, which is currently almost non-existent for this region, and constitutes an important contribution to the understanding of the sedimentary and environmental dynamics of the Congolese coastline, as well as to a detailed geochemical interpretation. 2. Materials and methods 2.1. Description of the study area The present study was conducted along the Congolese coastline of the southern Atlantic Ocean. This coastline stretches from southwest Gabon to northeast Angola over a length of around 170 km (Callec et al., 2015 ; Godgenger et al., 2009 ). Details on the description of this study area and the sampling sites (Fig. 1 ) are described in our previous studies (Kaya et al., 2024a , b ). 2.2. Sampling protocol The sampling protocol used in this study is that proposed by the International Atomic Energy Agency (IAEA, 2003, 2024), described in our previous studies (Kaya et al., 2024a , b ), as well as the description of the samples. 2.3. Sample preparation, radionuclides and heavy metals measurement. The sample preparation protocol is based on the International Atomic Energy Agency process (IAEA, 2003, 2024), details of which are given in the work of Kaya et al. ( 2024a , b ). However, the measurement of natural radionuclide activities was carried out at the gamma spectrometry laboratory of the Centre National de l'Energie, des Sciences et des Techniques Nucléaires (CNESTEN) in Morocco, where an ORTEC high-purity germanium (GeHP) detector was used. Details of the performance, detector capacity, analysis procedure and energy lines for measuring the radionuclide activities of 238 U( 234 Th), 226 Ra( 214 Bi), 228 Ra( 228 Ac), 228 Th( 212 Bi), 210 Pb and 40 K are described in our previous work (Kaya et al., 2024a ). A reference material (IAEA-326 and IAEA-327) (IAEA, 2001) was used for quality control of the measurement procedure. Heavy metals were also analyzed in the CNESTEN-Morocco elemental analysis laboratories using the destructive single-element atomic absorption spectrometry (AAS) method with flame. The measuring device is a Thermo Scientific iCE 3500 SERIES. Heavy metal concentrations were determined using Thermo SOLAAR software. The analysis was performed in duplicate and the average was recorded. Further information on the description of the equipment, the measurement principle, the physical and chemical sample preparation procedure, and the reference material (Marine Sediment IAEA 433) used are detailed in our previous study (Kaya et al., 2024b ). 2.4. Organic matter content analysis The organic matter content was determined using the loss-on-ignition (LOI) method and expressed as the percentage weight loss after combustion (Heiri et al., 2001 ; IAEA, 2024) as the formula below: $$\:Loss\:on\:ignition=\frac{dry\:mass\:before\:combustion\:-\:dry\:mass\:after\:combustion}{dry\:mass\:before\:combustion}\:\times\:100$$ 1 The measurement protocol (IAEA, 2024) consists of weighing 3g of the sample in porcelain crucibles and calcining it in a Thermolyne Furnace series 30400 incinerator (calcimeter) at a temperature of 500°C for 6 hours. After 6 hours of calcination, the sample is cooled to 100°C and transferred to a desiccator where it is cooled to room temperature before being weighed again. 2.5 Origin of natural radionuclides and heavy metals in surface sediments: Application of Pearson’s statistical analyses and Principal Component analysis (PCA). The interrelationship and dependence between radionuclides, heavy metals, their relative weights, and parameters such as organic matter and particle size in different environmental matrices are often assessed using a multivariate statistical method. In this study, Pearson's correlation and principal component analysis (PCA) were applied to evaluate the relationship between radionuclides, heavy metals, and organic matter (OM) in order to deduce their origins in sediments. Pearson's correlation matrix is a statistical measure that provides correlation values to assess the degree of linear relationship between two variables. Values range from − 1 to + 1, with values closer to -1 or + 1 indicating a stronger correlation. A positive correlation indicates that the variables increase or decrease together, while a negative correlation indicates that one variable increases and the other decreases. Values close to zero indicate no correlation. Principal component analysis (PCA) is the most appropriate tool for finding relationships between variables and parameters (Jolly et al., 2023 ; De Bartolomeo et al., 2004 ), and is also used to interpret the different sources of pollutants or contaminants in various environmental matrices (Kaya et al., 2024b ; Karadeniz et al., 2024 ; Ustaoğlu et Yuksel, 2024; Yazman et al., 2024 ; Jolly et al., 2023 ). The covariance matrix was calculated to determine how the variables vary together. Next, the VARIMAX method was applied to improve interpretation by maximizing correlations between variables and components. Bartlett's sphericity test and the Kaiser-Meyer-Olkin (KMO) criteria were used for validation and examination of the association between radionuclides, heavy metals, and organic matter. Statistical analysis of the study was performed using SPSS Statistics 17.0 software. 3. Results and discussion The activities of natural radionuclides (expressed in Bq/kg), concentrations of trace metals (Cd, Cu, Pb, Zn, Mg, and Mn, in mg/kg), and organic matter content (% OM) measured in surface sediments in the study area as well as their spatial distribution are presented in Table 1, Figure 2. Table 1: Natural radionuclide activies (Bq/kg), trace metal concentrations (mg/kg) and OM (%) content in surface sediments of coastal zone of the Republic of Congo. Sites Ref 234 Th 226 Ra 210 Pb 228 Th 228 Ra 40 K Cd Pb Cu Mg Mn Zn O.M Tchilassi river LTCH 10,0 ± 3,1 5,1 ± 0,7 8,4 ± 3,9 4,8 ± 0,3 6,4 ± 0,9 40,8 ± 3,9 0,1 24,5 15,5 83,5 116,6 28,6 15,6 Loukonzi lagoon RLK02 29,3 ± 2,0 17,6 ± 1,0 38,4 ± 2,0 76,0 ± 3,9 80,5 ± 4,9 107,2 ± 6,8 0,05 26,0 34,4 311,9 171,9 51,9 14,8 RLK05 26,5 ± 1,9 14,1 ± 1,2 66, 3 ± 3,1 62,3 ± 3,4 87,5 ± 6,0 122,7 ± 9,6 0,32 18,7 32,8 1093,8 173,1 28,9 20,7 RLK07 28,9 ± 5,7 14,9 ± 1,6 34,5 ± 7,3 56,4 ± 3,0 66,7 ± 4,4 96,9 ± 8,0 0,04 33,1 31,1 352,4 157,8 68,5 15,4 Red river RR01 31,9 ± 4,7 15,2 ± 1,4 28,7 ± 6,0 29,2 ± 1,6 34,8 ± 2,5 46,4 ± 4,9 0,48 30,2 17,7 186,0 92,7 78,6 8,4 RR02 19,5 ± 1,5 13,9 ± 0,9 27,9 ± 2,9 20,9 ± 1,1 25,2 ± 2,0 34,5 ± 2,1 0,05 29,1 14,3 144,2 100,5 40,9 6,6 RR03 9,0 ± 1,4 9,0 ± 0,6 17,5 ± 2,2 10,0 ± 1,0 17,1 ± 1,6 26,8 ± 2,0 0,11 36,9 17,3 111,5 89,2 39,8 4,5 Songolo river RS01 33,7 ± 1,8 4,9 ± 0,5 9,6 ± 1,8 5,5 ± 0,4 9,3 ± 1,1 63,8 ± 4,0 0,07 19,0 10,8 217,0 77,1 49,6 6,0 RS05 12,9 ± 1,9 6,7 ± 0,6 35,1 ± 2,4 10,0 ± 0,5 11,8 ± 1,0 133,3 ± 7,7 0,03 34,1 15,8 1312,1 130,9 133,4 5,5 RS06 15,4 ± 1,0 7,1 ± 0,5 30,1 ± 1,7 12,0 ± 0,6 14,5 ± 1,1 71,5 ± 4,5 0,05 13,7 15,7 1129,7 110,1 97,7 11,2 Mvassa lagoon MV01 15,0 ± 3,3 7,9 ± 0,8 79,6 ± 6,4 7,2 ± 0,4 8,5 ± 1,0 93,6 ± 6,8 2,23 25,9 15,1 974,3 53,3 34,5 7,9 MV03 8,7 ± 1,2 6,2 ± 0,5 53,5 ± 2,4 5,3 ± 0,3 9,3 ± 1,0 38,3 ± 2,9 0,06 37,8 15,5 226,5 56,6 54,8 5,3 MV04 13,7 ± 2,7 5,4 ± 0,6 77,8 ± 6,0 5,1 ± 0,3 6,9 ± 1,0 62,9 ± 4,8 0,04 44,9 4,6 1004,8 51,4 62,4 7,7 Min 8,7 4,9 8,4 4,8 6,5 26,8 0,03 13,7 4,6 83,5 51,4 28,6 4,53 Max 33,7 17,6 79,6 76 87,5 133,3 2,2 44,9 34,4 1312,1 173,1 133,4 20,68 Mean 19,6 9,9 39 23,4 29,1 72,2 0,3 28,7 18,5 549,8 106,2 59,2 10,0 3.1 Geochemical inventory of natural radionuclides in surface sediments: concentration, distribution and origin. Uranium-238 series ( 238 U, 226 Ra, 210 Pb) 238 U activities vary between 8.7 ± 1.2 Bq/kg and 33.7 ± 1.8 Bq/kg, with an average of 19.6 ± 5.3 Bq/kg, below the UNSCEAR reference value (35 Bq/kg). The highest concentrations are observed in Loukonzi and Songolo, while the lowest occur in Tchilassi and Mvassa. The conservative behavior of 238 U in estuarine environments explains the low levels observed: the radionuclide remains mostly dissolved and its adsorption onto particles is limited. According to Jeambrun (2012), uranium preferentially binds to organic matter, carbonates, or phosphates; thus, the low organic matter content in Mvassa and Tchilassi directly influences the low fixation of 238 U. Its spatial variability reflects the effect of salinity, pH, mineralogy, and hydrological dynamics, which control the reduction of U(VI) to U(IV) and its precipitation (IAEA, 2023; IRSN, 2010). 226 Ra, determined from its descendants 212 Bi and 214 Pb (609 keV and 351 keV), exhibits very low activity levels (4.9 ± 0.5 – 17.6 ± 1.0 Bq/kg; average 9.9 ± 0.8 Bq/kg), all below the UNSCEAR threshold (35 Bq/kg). Radium is not very mobile and is strongly adsorbed by clays and organic matter. According to studies conducted by the International Atomic Energy Agency (IAEA, 2014) and the work of Cuvier (2015), the behavior of radium depends on competition with other ions (Ca 2+ , Ba 2+ , Mg 2+ ), salinity, and ionic strength. This explains the variations observed between sites. The higher mobility of radium compared to uranium therefore indicates a tendency for diffusion from sediments into water. 210 Pb shows high variability : 8.4 ± 3.9 Bq/kg and 79.6 ± 6.4 Bq/kg, with an average (39.0 ± 3.7 Bq/kg) above the UNSCEAR limit (35 Bq/kg). The highest levels are found in Mvassa (70.3 ± 4.9 Bq/kg) and Loukonzi (46.4 ± 4.1 Bq/kg), areas identified as potentially sensitive. 210 Pb is strongly influenced by atmospheric inputs via the decay of 222 Rn, explaining the excess 210 Pb enrichment ( 210 Pb ex ) (Laissaoui et al., 2018; IAEA, 2017; El Mamoney and Khater, 2004; Miralles, 2004). Its strong affinity for fine particles and organic matter explains the high values in lagoon environments with low hydrodynamics. The absence of a 210 Pb/ 226 Ra equilibrium (ratios 1.6 - 14.5) confirms an uncontrolled external contribution and geochemical conditions favoring its fixation (Kaya et al., 2024a). Thorium-232 series (²³²Th, ²²⁸Ra, ²²⁸Th) Concentrations of 232 Th( 228 Ra) vary between 6.5 ± 0.9 and 87.5 ± 6.0 Bq/kg, with an average of 29.1 ± 2.0 Bq/kg. An exceptional enrichment is observed in Loukonzi (78.2 ± 5.1 Bq/kg), above the UNSCEAR threshold (30 Bq/kg). It is known that 228 Ra is depleted in estuarine sediments, but that after radioactive decay of 232Th in the solid grains of the sediments, a fraction of the 228 Ra recoil atoms penetrate the aqueous interstitial space and eventually reach the overlying water column (El Mamoney and Khater, 2004). Thorium is a very immobile element, strongly associated with heavy minerals (ilmenite, zircon, rutile) and clays. This could explain its enrichment in the Loukonzi lagoon, which reflects the presence of variegated clays rich in heavy metals, a possible influence of black sands (titanium-bearing minerals), a probable contribution linked to the calcareous-sandstone point of Nkounda described by Callec et al. (2015), or even industrial effluents. However, geochemistry indicates a predominantly lithogenic origin, consistent with the low mobility of Th. On the other hand, 228 Th (56.4 ± 3.0 - 76.0 ± 3.8 Bq/kg) follows the distribution of 228 Ra, confirming mineralogical control and a common origin. Potassium-40 series (⁴⁰K) The activities of 40 K (26.8 ± 2.0 – 133.3 ± 7.7 Bq/kg) remain well below the UNSCEAR limit (400 Bq/kg). According to Love et al. (2003) and Court (2014), 40 K is an excellent marker for clays and silts. The low concentrations at Tchilassi and Red rivers could be explained by strong hydrodynamics, preventing the accumulation of fine particles. The contrasts between sites reflect mineralogical variations (clays vs. sands). Ultimately, areas rich in clay (Loukonzi lagoon, Red River) reveal enrichment in 238 U, 226 Ra, and thorium. These areas reflect low hydrodynamics, resulting in the accumulation of fine particles and enrichment in radionuclides. The sandy areas (Songolo, Tchilassi, and Mvassa) show lower activity, dominated by 40 K and isolated heavy minerals. These areas are characterized by high dispersion and low retention. The very high 210 Pb/ 226 Ra ratios indicate a dominant atmospheric contribution (Kaya et al., 2024a). On the other hand, those with 238 U/ 226 Ra > 1 reflect the loss of Ra through diffusion, reflecting the greater solubility of radium (El Mamoney and Khater, 2004). Ratios of 226 Ra/ 228 Ra < 1 refer to areas of sedimentary accumulation (Arriola-Velásquez et al., 2021), and those between 40 K/ 232 Th or 40 K/ 238 U indicate sandy mineralogy rich in heavy minerals (Satyanarayan Bramha et al., 2025). The coastal sedimentary environments of the Congo have mainly natural radionuclide levels, which are generally below UNSCEAR thresholds (UNSCEAR, 2000), with the exception of 210 Pb in Mvassa and 232 Th in Loukonzi. Spatial distribution is controlled by: mineralogy (clays, sands), hydro-sedimentary dynamics, physicochemical parameters (pH, salinity, OM), atmospheric inputs for 210 Pb, and some limited anthropogenic influences. These results suggest geochemical behavior consistent with the properties of each radionuclide and highlight the need for targeted environmental monitoring in sensitive areas (Mvassa, Loukonzi). 3.2 Geochemical inventory of heavy metals in surface sediments: concentration, distribution, behavior and origin. Heavy metals of geochemical interest (Mg, Mn) and environmental interest (Cd, Cu, Pb, Zn) were analyzed in surface sediments using atomic absorption spectrometry (AAS). This single-element technique did not allow for the quantification of a wider range of elements, but the results obtained (Table 1) provide a representative overview of metal contamination in the study area. The concentrations are in descending order: Mg > Mn > Zn > Pb > Cu > Cd. However, two elements, Cd and Pb, significantly exceed the local natural geochemical background levels: Cd: 0.4 mg/kg (geochemical background: 0.1 mg/kg) ; Pb: 28.8 mg/kg (geochemical background: 20.68 mg/kg) The highest levels were recorded: For Cd: Mvassa lagoon (2.22 mg/kg), Red River (0.5 mg/kg), Loukonzi lagoon (0.32 mg/kg). For Pb: Mvassa lagoon (44.9 mg/kg), Red River (36.9 mg/kg), Songolo River (34.1 mg/kg); Loukonzi lagoon (33.1 mg/kg), Tchilassi River (24.5 mg/kg). Zinc (Zn) levels are generally lower than the geochemical background, with the notable exception of the Songolo River, where the average is 93.6 mg/kg, compared to a geochemical background of 82.4 mg/kg (Kaya et al., 2024b). The enrichment of Cd and Pb relative to the geochemical background indicates a disruption of natural flows, typical of environments subject to industrial discharges. The most contaminated sites (Mvassa, Songolo, Rouge) are located in the direct area of influence of the Ndjeno oil terminal, the gas-fired power plant, petrochemical, metallurgical and fertilizer industries, the autonomous port and ship maintenance activities. These activities are known to emit Cd (refineries, hydrocarbon combustion, chemical industries) and Pb (metallurgy, fuels, batteries, atmospheric deposits). The simultaneous presence of stable Pb and 210 Pb, confirmed by other studies (Tamponnet 2009; Kaya et al., 2024), reinforces the hypothesis of atmospheric dispersion followed by deposition in sediments. The geochemical anomaly in Zn recorded in the Songolo River reflects enrichment influenced by both the lithology of the sediments and anthropogenic pressure (Kaya et al., 2024b), which can be explained by the presence of shipyards, ship scrap, and metal waste; landfills rich in plastics, rubber, and batteries, identified as major sources of Zn (Jimenez, 2016); a possible lithogenic contribution (alteration of Zn-bearing minerals). This overlap of natural and anthropogenic sources is consistent with the observations of Mohajane and Manjoro (2022), Chahouri et al. (2023) and Jolly et al. (2023). However, the low concentrations recorded in the Tchilassi and Red Rivers can be explained by a vigorous hydrodynamic regime; a grain size fraction dominated by sand; and a low retention capacity for fine particles, which are the main carriers of heavy metals (Kaya et al., 2024b). According to the Fondriest Environmental (2014), sands have low adsorption capacity, which limits the accumulation of metals in sediments. Finally, sediments from the Congolese coastline show significant enrichment in Cd and Pb; localized Zn contamination; a strong influence from industrial, port, oil, and metallurgical activities (Kaya et al., 2024b); and a geochemical impact that depends on grain size, hydrosedimentary dynamics, and proximity to anthropogenic sources. Thus, the overall geochemical footprint highlights a clear dominance of anthropogenic sources over natural inputs in several coastal areas. 3.3 Influence of organic matter on the geochemical distribution of heavy metals The organic matter (OM %) content measured in sediments varies between 4.5% and 20.7%, with an average of 10.3% (Table 1). The sites with the highest OM content are the Tchilassi River and Loukonzi Lagoon. Conversely, the Songolo River, Red River and Mvassa Lagoon have relatively low values. Organic matter plays a major role in the adsorption of heavy metals, the complexation of metal cations (Cu 2+ , Pb 2+ , Zn 2+ , Cd 2+ ), and the trapping of metals in fine, anoxic sediments. Thus, sites rich in organic matter are generally conducive to increased heavy metal accumulation. However, industrial sites (Songolo, Mvassa) show lower organic matter concentrations, which can be explained by regular dredging operations that reduce the organic fraction and intense microbial degradation of matter in distorse environments (Mejjad et al., 2018; Mirsa, 2012) and high hydrodynamics that export fine particles rich in organic matter. The variability of heavy metals therefore reflects the availability of organic matter, grain size (the finer the sediments, the more metals they retain), and proximity to sources of pollution. As a result, areas rich in organic matter act as geochemical traps, while areas poor in organic matter but close to industry (Songolo, Mvassa) may show anomalies linked to recent inputs, explained by the rapid circulation of particles and direct discharges. Furthermore, the distribution of heavy metals in coastal sediments is not random; it results from the interaction between anthropogenic inputs, organic matter content, hydrosedimentary dynamics, and local mineralogy. These factors determine each site's capacity to accumulate, transport, or release heavy metals into the coastal ecosystem. 3.4 Correlation between radionuclides, heavy metals, and organic matter in surface sediments along the Congolese South Atlantic coastline. The correlation between variables makes it possible to trace their common source. The interdependence between natural radionuclides and heavy metals, as well as organic matter in surface sediments, was assessed using statistical methods such as Pearson's correlation and principal component analysis (PCA). Pearson correlations Table 2 presents Pearson's correlation coefficients between radionuclides, heavy metals, and organic matter in surface sediments in the study area. These correlations allow us to explore the geochemical behavior of elements by identifying associations between variables that may share a common origin, mode of transport, or similar geochemical affinity. The following observations were made: Moderate correlations (ρ < 0.05): indicators of natural or mixed associations Moderate positive correlations were observed between several radionuclides and organic matter: 234 Th- 226 Ra (0.61), 234 Th- 228 Th (0.63), 234 Th- 228 Ra (0.62), 234 Th-OM (0.61), 226 Ra-Mn (0.65), 226 Ra-OM (0.59), 210 Pb-Mg (0.60), 40 K-Mn (0.60). These associations suggest similar mobility or geochemical behavior in the sedimentary environment. In particular, organic matter (OM) plays a key role in the trapping and complexation of radionuclides ( 234 Th, 226 Ra) and certain major geochemical elements (Mg, Mn, K). The link between Ra and Mn could reflect co-precipitation in oxyhydroxide phases, which is common in diagenetic environments. The 210 Pb-Mg correlation is typical of sorption on clay and organic phases, with Mg often present in silicates. Table 2: Pearson correlation of different variables in surface sediment samples. 234 Th 226 Ra 210 Pb 228 Th 228 Ra 40 K Cd Pb Cu Mg Mn Zn OM 234 Th 1 226 Ra 0.61 * 1 210 Pb -0.15 0.02 1 228 Th 0.63 * 0.88 ** 0.11 1 228 Ra 0.62 * 0.85 ** 0.13 0.99 ** 1 40 K 0.30 0.25 0.39 0.52 0.52 1 Cd -0.06 -0.04 0.52 -0.14 -0.14 0.17 1 Pb -0.39 -0.10 0.28 -0.21 -0.23 -0.24 -0.13 1 Cu 0.47 0.78 ** 0.02 0.93 ** 0.93 ** 0.53 -0.07 -0.29 1 Mg -0.17 -0.22 0.60 * -0.03 0.00 0.70 ** 0.25 -0.13 -0.05 1 Mn 0.43 0.65 * -0.20 0.83 ** 0.83 ** 0.60 * -0.34 -0.37 0.87 ** 0.08 1 Zn -0.03 -0.11 -0.10 -0.12 -0.17 0.37 -0.27 0.11 -0.14 0.48 0.09 1 OM 0.61 * 0.59 * -0.16 0.78 ** 0.79 ** 0.47 -0.24 -0.54 0.78 ** 0.07 0.84 ** 0.04 1 ** (the bilateral correlation is significant at the 0.01 level). * (the bilateral correlation is significant at the 0.05 level). Strong correlations (ρ < 0.01): signs of a common origin and coupled behaviors Very strong correlations were found between thorium and radium radionuclides and certain trace metals: 226 Ra- 228 Th (0.88), 226 Ra- 228 Ra (0.85), 226 Ra-Cu (0.78), 228 Th- 228 Ra (0.99), 228 Th-Cu (0.93), 228 Ra-Cu (0.93). These correlations indicate a probable common source for these elements, or at least an association in the same sedimentary compartment, dominated by organic matter and metal oxides. Copper (Cu), although non-radioactive, shares geochemical behavior similar to actinides and decay products due to its strong affinity for organic ligands and Fe and Mn oxyhydroxides. The Ra-Th-Cu system appears to be structured by mixed anthropogenic inputs (industrial or urban discharges) and natural geochemical processes. The central role of organic matter (OM) and Mn in elementary associations The strong correlations between 228 Th, 228 Ra, and Cu with Mn and OM reinforce the idea of coupled behavior in sediments: 228 Th-Mn (0.83), 228 Th-OM (0.78), 228 Ra-Mn (0.83), 228 Ra-OM (0.79), Cu-Mn (0.87), Cu-OM (0.78), Mn-OM (0.84). These data indicate that Mn and organic matter act as major geochemical vectors for the trapping of these elements. Mn, in the form of oxyhydroxides, is known to effectively adsorb radionuclides and trace metals before being remobilized under reducing conditions. OM, on the other hand, plays an essential role in the sorption, complexation, and stabilization of metals and radionuclides, particularly in biologically productive lagoon environments. Geochemical and environmental implications These cross-correlations between radionuclides ( 234 Th, 226 Ra, 228 Ra, 228 Th, 210 Pb), heavy metals of environmental interest (Cu, Pb, Cd) and geochemical elements (Mn, Mg, 40 K), as well as organic matter, reveal complex interactions governed by both natural and anthropogenic processes: correlations with Mn and OM reflect diagenetic and biogeochemical processes controlling the mobility of elements; strong Cu-Ra-Th associations reveal potential industrial contamination linked to metallurgical, port, or urban discharges ; The involvement of Mg, 40 K, and other major elements suggests an influence of the petrographic nature of the sediments and source rocks. These results corroborate the conclusions of previous studies conducted in similar coastal environments, notably in Agadir Bay (Chahouri et al., 2023) and Oualidia Lagoon (Mejjad et al., 2018) in Morocco, the South African Atlantic coast (Mohajane et Manjoro, 2022), and the estuarine areas of Bangladesh (Jolly et al., 2023), where similar distribution patterns are observed, highlighting the strong dependence of metal concentrations on local sedimentary conditions and anthropogenic pressures. Principal component analysis (PCA) Principal component analysis (PCA), supported by statistical validity tests (Kaiser-Meyer-Olkin index and Bartlett's sphericity test), was applied to the measured variables in order to identify latent structures and multivariate relationships in the data. The results are presented in Table 3. PCA, after Varimax rotation with Kaiser normalization, allowed the extraction of four (04) principal components, all characterized by eigenvalues greater than 1, together explaining 85.81% of the total observed variance. With the exception of 234 Th (extraction values < 0.6), all variables have a high representation quality, ranging from 72% to 99%, indicating their relevance in the structuring of the components. Component 1 accounts for 44.99% of the variance and highlights mixed geochemical signatures and accumulation linked to organic matter. It is the most influential component and includes the following elements: 226 Ra (0.89), 228 Th (0.99), 228 Ra (0.99), Cu (0.94), Mn (0.84), OM (0.74) and, to a lesser extent, 234 Th (0.62). This association highlights strongly coupled geochemical behaviors characteristic of a reducing system rich in organic matter and influenced by mixed inputs: Mn, an element sensitive to redox conditions, is a tracer of early diagenesis (IAEA, 2024; Mejjad et al., 2020), promoting the precipitation of oxyhydroxides capable of trapping numerous metal cations; Cu has a strong affinity for organic ligands and Fe/Mn oxyhydroxide phases, which explains its co-variation with OM and Mn. Its presence may also indicate anthropogenic inputs (industrial and urban waste) (Chahouri et al., 2023; Jolly et al., 2023; Mohajane et Manjoro, 2022) but also natural mobilization from sediments; Radionuclides 226 Ra, 228 Ra, and 228 Th, although present in low concentrations, show a very strong correlation, indicating a common lithogenic origin, probably linked to the mineralogy of source rocks and fine sediments. This component therefore reflects a synergy between natural processes (diagenesis, organo-metallic affinity, radioactive decay) and localized anthropogenic activities, linked to the sedimentary and biogeochemical dynamics of the area. Component 2 accounts for 18.62% of the variance and explains lithogenic inputs altered by industrial activities. It includes 40 K, Mg, and Zn, elements that represent predominantly lithogenic geochemical behaviors. 40 K and Mg are associated with silicate minerals (feldspars, micas, chlorites) (Arriola-Velásquez et al., 2021; Strady, 2010; Aranguren, 2008; Love et al., 2003) present in reworked or continental sediments. Zn, although also of natural origin, is often locally enriched by anthropogenic activities (Jolly et al., 2023), particularly by metal discharges, antifouling paints, and ferrous debris from old ships at the Songolo site (Kaya et al., 2024b). This component therefore illustrates hybrid geochemical behavior, where natural lithogenic inputs are modified or reinforced by localized anthropogenic activities, particularly in port and industrial areas. Component 3 accounts for 12.68% of the variance and is a marker of active industrial pollution dominated by a strong correlation between 210 Pb (0.82) and Cd (0.85). These two elements are recognized as environmental markers sensitive to anthropogenic pollution. Cd, a highly toxic element (IARC, 2012; USEPA, 2002), is a classic contaminant of coastal and estuarine environments, generally originating from industrial sources: energy production, refining, batteries, phosphate fertilizers, chemical discharges, etc. (IARC, 2012; Chalghmi, 2015; IRSN, 2004). 210 Pb, a natural isotope in the uranium decay chain, can also be found in excess in areas subject to human activity (Kaya et al., 2024a), particularly in industrialized areas or areas with high organic sedimentation (IAEA, 2017, 2024). This component reflects a clear signature of industrial contamination, particularly in areas of oil, chemical, or port activity, where these elements are mobilized, transported, and trapped in sediments (as in the case of the Mvassa lagoon). Component 4, which accounts for only 9.52% of the variance, highlights an exclusively anthropogenic origin of lead (Pb: 0.95), an element typically associated with industrial and urban pollution. According to the work of Moubakou Diahou (2024), Cook and al. (2018), and Cuvier (2015), Pb is released into the environment through atmospheric emissions (Ferreira-Batista et De Miguel, 2005), oil production, natural gas combustion, and construction and infrastructure debris. Its significant accumulation in the sediments of the Mvassa and Loukonzi lagoons can be linked to the proximity of the gas-fired power plant, the Njeno oil terminal located near the Mvassa lagoon, and the major construction zones of the Nkounda Special Economic Complex extending toward the Loukonzi lagoon. This component therefore reflects targeted and localized pollution, mainly resulting from recent industrial activities. Ultimately, the joint integration of ACP and Pearson correlation analysis made it possible to group the elements according to their geochemical affinities and probable sources, highlighting three main origins for the elements studied: natural origin, linked to sediment lithology ( 40 K, Mg, Ra, Th), this source controls the background distribution of radionuclides and major elements; anthropogenic origin, dominated by metals such as Cd, Pb, Cu, and 210 Pb, which is directly linked to industrial, energy, and urban activities in the region, affecting the quality of sediments and aquatic ecosystems; finally, a mixed origin, reflecting an interaction between natural and anthropogenic processes. This source is particularly visible in the first component, where lithogenic radionuclides interact with metal pollutants (Cu, Zn, Mn) and organic matter, highlighting the importance of redox conditions and sediment composition in controlling the distribution of contaminants. Table 3: Component matrices after VARIMAX rotation with Kaiser normalization and variable representation quality in surface samples Components 1 2 3 4 Extraction 234 Th 0.62 -0.09 -0.12 -0.28 0.55 226 Ra 0.89 -0.15 -0.02 0.13 0.82 210 Pb 0.08 0.36 0.82 0.36 0.93 228 Th 0.99 0.05 0.01 -0.01 0.99 228 Ra 0.99 0.05 0.04 -0.03 0.98 40 K 0.48 0.78 0.21 -0.15 0.90 Cd -0.14 -0.01 0.85 -0.17 0.77 Pb -0.19 -0.05 0.00 0.95 0.94 Cu 0.94 0.05 0.01 -0.12 0.90 Mg -0.08 0.90 0.35 -0.08 0.95 Mn 0.84 0.26 -0.29 -0.24 0.92 Zn -0.17 0.76 -0.47 0.16 0.85 OM 0.74 0.08 0.14 -0.39 0.72 Eigenvalue 5.85 2.42 1.65 1.24 % Total variance 44.99 18.62 12.68 9.52 These results highlight the value of combining robust statistical tools with in-depth geochemical and environmental analysis to assess sediment quality and detect sources of pollution in estuarine environments. They also provide scientific support for the implementation of environmental management measures and the monitoring of vulnerable ecosystems exposed to increasing anthropogenic pressures. However, maps shown in figure 2 illustrate the spatial distribution of geochemical anomalies of 234 Th, 226 Ra, 210 Pb, 228 Th, 288 Ra, 40 K, Cd, Cu, Pb, Zn, Mg, and Mn, as well as organic matter in surface sediments at the various sites studied. Warm colors (red, orange, yellow) indicate high concentration levels, while cool colors (purple, blue) indicate values well below the average, represented in green. The studied sites are identified by their GPS coordinates. For example, the Tchilassi River is located at a latitude of -4.71 and a longitude of 11.88. The Loukonzi Lagoon is located between -4.72 and -4.80 latitude and around 11.83 longitude; the Rouge River between -4.80 and -4.84 latitude and 11.84 longitude; the Songolo River between -4.82 and -4.84 latitude and 11.85 longitude; and finally, the Mvassa Lagoon, located between -4.84 and -4.88 latitude and 11.89 longitude. 4. Conclusion The joint assessment of the distribution of natural radionuclides and heavy metals in coastal sediments along the Congolese coastline has revealed a complex environmental dynamic resulting from the interaction between natural processes and increasing anthropogenic pressures. The concentrations measured show that, despite a predominance of natural radionuclides generally below the reference thresholds defined by UNSCEAR, certain localized areas, notably Mvassa for 210 Pb and Loukonzi for 232 Th, exhibit abnormally high levels, suggesting a combined influence of mineralogy, atmospheric inputs, and hydro-sedimentary processes. At the same time, metal contamination shows a geochemical signal marked by significant enrichment in Cd and Pb, localized Zn contamination, and a significant footprint from industrial, port, oil, and metallurgical activities. The spatial distribution of heavy metals is not random: it reflects the strong influence of grain size, organic matter, deposition dynamics, and proximity to anthropogenic sources, confirming the predominance of human inputs over natural inputs in certain coastal areas. The integration of multivariate analyses (PCA) and Pearson correlations has identified three major categories of sources: (i) a natural source linked to lithology, controlling radionuclides and major elements; (ii) an anthropogenic source associated with toxic metals (Cd, Pb, Cu) and atmospheric 210 Pb; and (iii) a mixed source, resulting from the interaction between natural processes, redox conditions, and anthropogenic disturbances. This classification confirms the value of a cross-disciplinary approach, using robust statistical tools and integrated geochemical analyses, to understand contamination mechanisms and characterize sensitive estuarine and coastal environments. Overall, this study demonstrates the need to strengthen environmental monitoring, particularly in the Mvassa and Loukonzi sectors, where abnormal geochemical signals indicate increased ecosystem vulnerability. It also provides essential scientific information to guide sustainable management policies for Congo's coastal areas. This study paves the way for several avenues that deserve further exploration in order to improve understanding of contamination processes and strengthen the resilience of coastal ecosystems, such as: a temporal and geochronological approach using 210 Pb and 137 Cs to reconstruct the historical evolution of metal and radionuclide inputs, providing a temporal perspective that is essential for remediation strategies; mineralogical characterization and geochemical speciation of metals to accurately assess their mobility, bioavailability, and potential for transfer to food chains. Ultimately, this study provides a solid scientific framework for understanding the mechanisms of transfer and accumulation of radionuclides and heavy metals in coastal sediments in the Congo. It highlights the crucial importance of proactive environmental management and continuous monitoring of ecosystems that are vulnerable to anthropogenic pressures. The proposed perspectives pave the way for more integrative research capable of providing long-term support for strategies to protect and enhance the Congolese coastline. Declarations Acknowledgements This work was carried out within the framework of the PhD Sandwich program of the International Atomic Energy Agency (IAEA). The authors would like to thank the Moroccan authorities for hosting the fellowship at the National Centre for Nuclear Energy, Science and Technology (CNESTEN). The authors are also grateful to the anonymous reviewers for their suggestions and comments, which allowed to significantly improving the present paper. Authors' contributions Preparation of equipment for the data collection: Freddy Cacharel KAYA, Hilaire ELENGA, Guy Blanchard DALLOU and Aimé Christian KAYATH. Sample collection: Freddy Cacharel KAYA. Sample preparation and analysis: Freddy Cacharel KAYA, Hasna AIT BOUH, Abdelmourhit LAISSAOUI, Mohammed SEBBAR, Azzouz BENKDAD (gamma analysis) and Sana SAID (metal analysis by AAS). Funding acquisition: Freddy Cacharel KAYA Writing of the original draft: Freddy Cacharel KAYA. Map production: Jémima Consolé BOUNKOUTA and Freddy Cacharel KAYA. Supervision: Hilaire ELENGA, Abdelmourhit LAISSAOUI and Hasna AIT BOUH. Writing, review and editing of the final draft: All authors. Funding This work was supported by the Atomic Energy Agency (IAEA). Data availability No datasets were generated or analysed during the current study. Ethical approval : All authors have read, understood, and have complied as applicable with the statement on "Ethical responsibilities of Authors" as found in the Instructions for Authors. Competing interests The authors declare no competing interests. References Alloway, B. J. et Ayres, D. C. (1997). Chemical principles of environmental pollution. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8330803","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":558454242,"identity":"dd17581b-0db9-41a5-b6fa-daabf4f5295a","order_by":0,"name":"Freddy Cacharel KAYA","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0UlEQVRIiWNgGAWjYDAC5gNsEkBKjoGBhwFCEwRsCWwGQMoYqsWYOC0JQCqxgWgt/G0MbAd+ttmlbzh+9uCDDwwG+QS1SBxjYG/sbUvO3XAmL9lwBoOBZQMhLQbyDewNvG3MuRsO5JhJ8zD8MSBoiwEbA9vBv2316Qbn34C0GBCnJZm37XCCwY0cIrUA/cJmLHPuuOHMG2+MDWcYEKEFFGKSb8qq5fnO5xg++FBBhBagpg8MjGwMDAoHwO4kQgME/GFgkG8gWvUoGAWjYBSMNAAAQM82FrdEQQEAAAAASUVORK5CYII=","orcid":"https://orcid.org/0009-0005-0995-4913","institution":"Marien Ngouabi University, Faculty of Sciences and Techniques, Brazzaville, Republic of Congo","correspondingAuthor":true,"prefix":"","firstName":"Freddy","middleName":"Cacharel","lastName":"KAYA","suffix":""},{"id":558454243,"identity":"abe54b71-198c-40f0-979d-f1b5b6d5e9e7","order_by":1,"name":"Hasna AIT BOUH","email":"","orcid":"","institution":"Centre National de l'Energie, des Sciences et des Techniques Nucléaires, Rabat, Morocco","correspondingAuthor":false,"prefix":"","firstName":"Hasna","middleName":"AIT","lastName":"BOUH","suffix":""},{"id":558454244,"identity":"85cebfd0-5eaa-4d37-b459-4bf32f48030a","order_by":2,"name":"Jémina Consolé BOUNKOUTA","email":"","orcid":"","institution":"Marien Ngouabi University, Faculty of Sciences and Techniques, Brazzaville, Republic of Congo","correspondingAuthor":false,"prefix":"","firstName":"Jémina","middleName":"Consolé","lastName":"BOUNKOUTA","suffix":""},{"id":558454245,"identity":"887cc579-5225-4760-9e74-0ffeec9ac633","order_by":3,"name":"Abdelmourhit LAISSAOUI","email":"","orcid":"","institution":"Centre National de l'Energie, des Sciences et des Techniques Nucléaires, Rabat, Morocco","correspondingAuthor":false,"prefix":"","firstName":"Abdelmourhit","middleName":"","lastName":"LAISSAOUI","suffix":""},{"id":558454246,"identity":"4a8c033a-6522-4b6f-971f-a9a3b5c6b8eb","order_by":4,"name":"Hilaire ELENGA","email":"","orcid":"","institution":"Marien Ngouabi University, Faculty of Sciences and Techniques, Brazzaville, Republic of Congo","correspondingAuthor":false,"prefix":"","firstName":"Hilaire","middleName":"","lastName":"ELENGA","suffix":""},{"id":558454247,"identity":"f3a072ab-1698-4f47-b2fd-a5871e6774f6","order_by":5,"name":"Guy Blanchard DALLOU","email":"","orcid":"","institution":"Marien Ngouabi University, Faculty of Sciences and Techniques, Brazzaville, Republic of Congo","correspondingAuthor":false,"prefix":"","firstName":"Guy","middleName":"Blanchard","lastName":"DALLOU","suffix":""},{"id":558454248,"identity":"c80aaa32-4afc-42c7-aee7-fb65962b0f7f","order_by":6,"name":"Sana SAID","email":"","orcid":"","institution":"Centre National de l'Energie, des Sciences et des Techniques Nucléaires, Rabat, Morocco","correspondingAuthor":false,"prefix":"","firstName":"Sana","middleName":"","lastName":"SAID","suffix":""},{"id":558454249,"identity":"af02e140-c5ca-49cf-8e29-1d28e600e4e3","order_by":7,"name":"Azzouz BENKDAD","email":"","orcid":"","institution":"Centre National de l'Energie, des Sciences et des Techniques Nucléaires, Rabat, Morocco","correspondingAuthor":false,"prefix":"","firstName":"Azzouz","middleName":"","lastName":"BENKDAD","suffix":""},{"id":558454250,"identity":"d9e4a870-6cd0-48d9-9d02-bdd2f2d3507c","order_by":8,"name":"Mohammed SEBBAR","email":"","orcid":"","institution":"Centre National de l'Energie, des Sciences et des Techniques Nucléaires, Rabat, Morocco","correspondingAuthor":false,"prefix":"","firstName":"Mohammed","middleName":"","lastName":"SEBBAR","suffix":""},{"id":558454251,"identity":"39ff69aa-4144-43ac-b70d-4a3715fa1a27","order_by":9,"name":"Aimé Christian KAYATH","email":"","orcid":"","institution":"Marien Ngouabi University, Faculty of Sciences and Techniques, Brazzaville, Republic of Congo","correspondingAuthor":false,"prefix":"","firstName":"Aimé","middleName":"Christian","lastName":"KAYATH","suffix":""}],"badges":[],"createdAt":"2025-12-10 20:54:03","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":true,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":true},"doi":"10.21203/rs.3.rs-8330803/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8330803/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":98039619,"identity":"9c8a0122-b76b-45ad-ae74-7606715e7450","added_by":"auto","created_at":"2025-12-12 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16:40:37","extension":"html","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":178162,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8330803/v1/9c7e669e78a8ab9c286060d6.html"},{"id":98039616,"identity":"5282b273-8860-4f83-8f8f-9e61bee7904e","added_by":"auto","created_at":"2025-12-12 06:57:42","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1112969,"visible":true,"origin":"","legend":"\u003cp\u003eLocation of the study area and sampling points.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8330803/v1/8932165871384bde5647e613.png"},{"id":98427087,"identity":"bc15a36a-4af6-48c5-9d06-028409190e0e","added_by":"auto","created_at":"2025-12-17 16:39:32","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":676975,"visible":true,"origin":"","legend":"\u003cp\u003eContour lines showing the geochemical distribution of natural radionuclides, heavy metals, and organic matter in surface sediments.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8330803/v1/22458b1540c3bb08abe3f965.png"},{"id":98444541,"identity":"cced3c55-cf88-47a3-9eab-d38bd7fc3bc8","added_by":"auto","created_at":"2025-12-17 17:16:20","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2874983,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8330803/v1/d30b35a4-c042-4f00-ae3a-20444ff4d0a9.pdf"},{"id":98427534,"identity":"a3d22e49-0737-4d81-b66c-f44e9f00b25d","added_by":"auto","created_at":"2025-12-17 16:40:37","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1667312,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGeochemical dynamics and origin of natural radionuclides and heavy metals in current coastal sedimentary systems in the Republic of Congo.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"SupplementarymaterialArticleFreddyKAYAHM.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8330803/v1/d2b001ef559fa0a827a1eef4.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eGeochemical dynamics and origin of natural radionuclides and heavy metals in current coastal sedimentary systems in the Republic of Congo\u003c/p\u003e","fulltext":[{"header":"Highlights","content":"\u003cp\u003e- Localized radionuclide enrichments (Pb and Th);\u003c/p\u003e\u003cp\u003e- Significant contamination in heavy metals (Cd and Pb);\u003c/p\u003e\u003cp\u003e- Multifactorial geochemical control;\u003c/p\u003e\u003cp\u003e- Coexistence of both lithogenic and anthropogenic sources.\u003c/p\u003e"},{"header":"1. Introduction","content":"\u003cp\u003ePrimordial naturally occurring radioactive metals, also known as geogenic or telluric metals, such as \u003csup\u003e238\u003c/sup\u003eU, \u003csup\u003e235\u003c/sup\u003eU, \u003csup\u003e232\u003c/sup\u003eTh, and \u003csup\u003e40\u003c/sup\u003eK, as well as their decay products; stable heavy metals (Ag, As, Cd, Co, Cr, Cu, Hg, Ni, Pb, Se, Sn, V, Y, Zn, etc.) are present in low concentrations in the Earth's crust and soils, mainly in trace amounts since the formation of the Earth (IAEA, 2017; Callender, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Alloway and Ayres, 1997). Their redistribution on the surface of continents occurs via three main natural phenomena: the weathering of outcropping rocks, the dissolution or leaching of rocks by groundwater, and volcanic eruptions (IAEA, 2017).\u003c/p\u003e \u003cp\u003eFurthermore, anthropogenic industrial activities such as mining and oil extraction, energy production, agriculture, livestock farming, fishing, and maritime traffic are major sources of radionuclides and heavy metals in terrestrial environmental compartments (Cook et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Chalghmi, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; IARC, 2012; Persson and Holm, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; IRSN, 2002, 2010; Carvalho, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2006\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). These emissions, which, combined with the effects of climate change (marine acidification, anoxia, coastal erosion, sea level rise), weaken ecosystems and public health (IAEA, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; IARC, 2012; USEPA, 2002).\u003c/p\u003e \u003cp\u003eSediments, which are veritable environmental archives, make it possible to monitor the levels of radioactive and non-radioactive pollutants in aquatic systems, whose behavior, mobility and toxicity are strongly modulated by ion chemistry and various processes such as adsorption, co-precipitation, or fixation on colloids (Madadi et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; IAEA, 2017; Strady, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Aranguren, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Callender, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2003\u003c/span\u003e), that is to say, to a large extent, depend on their type of binding forms, in particular exchangeable forms, carbonates, iron and manganese oxides, sulfides and organic matter, as well as the residual fraction.\u003c/p\u003e \u003cp\u003eNevertheless, in the regional context, anthropogenic pressure is high in the Congo coastal sedimentary basin (oil, ports, industry, agriculture). However, studies on radioactive and metal contamination and the detailed geochemistry of marine-coastal sediments remain very limited.\u003c/p\u003e \u003cp\u003eIn this context, the objective of this study is to characterize the distribution and levels of natural radionuclides and heavy metals in recent sediments in the coastal systems of the Republic of Congo, with a view to elucidating their origin and the biogeochemical, hydrodynamic, and anthropogenic processes that determine their behavior, accumulation, and spatial distribution. This investigation responds to an essential need for reference data, which is currently almost non-existent for this region, and constitutes an important contribution to the understanding of the sedimentary and environmental dynamics of the Congolese coastline, as well as to a detailed geochemical interpretation.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003e2.1. Description of the study area\u003c/h2\u003e\n \u003cp\u003eThe present study was conducted along the Congolese coastline of the southern Atlantic Ocean. This coastline stretches from southwest Gabon to northeast Angola over a length of around 170 km (Callec et al., \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e ; Godgenger et al., \u003cspan class=\"CitationRef\"\u003e2009\u003c/span\u003e). Details on the description of this study area and the sampling sites (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e) are described in our previous studies (Kaya et al., \u003cspan class=\"CitationRef\"\u003e2024a\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003eb\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003e2.2. Sampling protocol\u003c/h2\u003e\n \u003cp\u003eThe sampling protocol used in this study is that proposed by the International Atomic Energy Agency (IAEA, 2003, 2024), described in our previous studies (Kaya et al., \u003cspan class=\"CitationRef\"\u003e2024a\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003eb\u003c/span\u003e), as well as the description of the samples.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n \u003ch2\u003e2.3. Sample preparation, radionuclides and heavy metals measurement.\u003c/h2\u003e\n \u003cp\u003eThe sample preparation protocol is based on the International Atomic Energy Agency process (IAEA, 2003, 2024), details of which are given in the work of Kaya et al. (\u003cspan class=\"CitationRef\"\u003e2024a\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003eb\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eHowever, the measurement of natural radionuclide activities was carried out at the gamma spectrometry laboratory of the Centre National de l\u0026apos;Energie, des Sciences et des Techniques Nucl\u0026eacute;aires (CNESTEN) in Morocco, where an ORTEC high-purity germanium (GeHP) detector was used. Details of the performance, detector capacity, analysis procedure and energy lines for measuring the radionuclide activities of \u003csup\u003e238\u003c/sup\u003eU(\u003csup\u003e234\u003c/sup\u003eTh), \u003csup\u003e226\u003c/sup\u003eRa(\u003csup\u003e214\u003c/sup\u003eBi), \u003csup\u003e228\u003c/sup\u003eRa(\u003csup\u003e228\u003c/sup\u003eAc), \u003csup\u003e228\u003c/sup\u003eTh(\u003csup\u003e212\u003c/sup\u003eBi), \u003csup\u003e210\u003c/sup\u003ePb and \u003csup\u003e40\u003c/sup\u003eK are described in our previous work (Kaya et al., \u003cspan class=\"CitationRef\"\u003e2024a\u003c/span\u003e). A reference material (IAEA-326 and IAEA-327) (IAEA, 2001) was used for quality control of the measurement procedure.\u003c/p\u003e\n \u003cp\u003eHeavy metals were also analyzed in the CNESTEN-Morocco elemental analysis laboratories using the destructive single-element atomic absorption spectrometry (AAS) method with flame. The measuring device is a Thermo Scientific iCE 3500 SERIES. Heavy metal concentrations were determined using Thermo SOLAAR software. The analysis was performed in duplicate and the average was recorded. Further information on the description of the equipment, the measurement principle, the physical and chemical sample preparation procedure, and the reference material (Marine Sediment IAEA 433) used are detailed in our previous study (Kaya et al., \u003cspan class=\"CitationRef\"\u003e2024b\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n \u003ch2\u003e2.4. Organic matter content analysis\u003c/h2\u003e\n \u003cp\u003eThe organic matter content was determined using the loss-on-ignition (LOI) method and expressed as the percentage weight loss after combustion (Heiri et al., \u003cspan class=\"CitationRef\"\u003e2001\u003c/span\u003e; IAEA, 2024) as the formula below:\u003c/p\u003e\n \u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\n \u003cdiv class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e$$\\:Loss\\:on\\:ignition=\\frac{dry\\:mass\\:before\\:combustion\\:-\\:dry\\:mass\\:after\\:combustion}{dry\\:mass\\:before\\:combustion}\\:\\times\\:100$$\u003c/div\u003e\n \u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\n \u003c/div\u003e\n \u003cp\u003eThe measurement protocol (IAEA, 2024) consists of weighing 3g of the sample in porcelain crucibles and calcining it in a Thermolyne Furnace series 30400 incinerator (calcimeter) at a temperature of 500\u0026deg;C for 6 hours. After 6 hours of calcination, the sample is cooled to 100\u0026deg;C and transferred to a desiccator where it is cooled to room temperature before being weighed again.\u003c/p\u003e\u003cspan\u003e\n \u003ch2\u003e\u003cstrong\u003e2.5 Origin of natural radionuclides and heavy metals in surface sediments: Application of Pearson\u0026rsquo;s statistical analyses and Principal Component analysis (PCA).\u003c/strong\u003e\u003c/h2\u003e\n \u003c/span\u003e\n \u003cp\u003eThe interrelationship and dependence between radionuclides, heavy metals, their relative weights, and parameters such as organic matter and particle size in different environmental matrices are often assessed using a multivariate statistical method. In this study, Pearson\u0026apos;s correlation and principal component analysis (PCA) were applied to evaluate the relationship between radionuclides, heavy metals, and organic matter (OM) in order to deduce their origins in sediments.\u003c/p\u003e\n \u003cp\u003ePearson\u0026apos;s correlation matrix is a statistical measure that provides correlation values to assess the degree of linear relationship between two variables. Values range from \u0026minus;\u0026thinsp;1 to +\u0026thinsp;1, with values closer to -1 or +\u0026thinsp;1 indicating a stronger correlation. A positive correlation indicates that the variables increase or decrease together, while a negative correlation indicates that one variable increases and the other decreases. Values close to zero indicate no correlation.\u003c/p\u003e\n \u003cp\u003ePrincipal component analysis (PCA) is the most appropriate tool for finding relationships between variables and parameters (Jolly et al., \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e; De Bartolomeo et al., \u003cspan class=\"CitationRef\"\u003e2004\u003c/span\u003e), and is also used to interpret the different sources of pollutants or contaminants in various environmental matrices (Kaya et al., \u003cspan class=\"CitationRef\"\u003e2024b\u003c/span\u003e; Karadeniz et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e; Ustaoğlu et Yuksel, 2024; Yazman et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e; Jolly et al., \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e). The covariance matrix was calculated to determine how the variables vary together. Next, the VARIMAX method was applied to improve interpretation by maximizing correlations between variables and components. Bartlett\u0026apos;s sphericity test and the Kaiser-Meyer-Olkin (KMO) criteria were used for validation and examination of the association between radionuclides, heavy metals, and organic matter. Statistical analysis of the study was performed using SPSS Statistics 17.0 software.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"3. Results and discussion","content":"\u003cp\u003eThe activities of natural radionuclides (expressed in Bq/kg), concentrations of trace metals (Cd, Cu, Pb, Zn, Mg, and Mn, in mg/kg), and organic matter content (% OM) measured in surface sediments in the study area as well as their spatial distribution are presented in Table 1, Figure 2.\u003c/p\u003e\n\u003cp\u003eTable 1: Natural radionuclide activies (Bq/kg), trace metal concentrations (mg/kg) and OM (%) content in surface sediments of coastal zone of the Republic of Congo.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"713\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003eSites\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003csup\u003e234\u003c/sup\u003eTh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003csup\u003e226\u003c/sup\u003eRa\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003csup\u003e210\u003c/sup\u003ePb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003csup\u003e228\u003c/sup\u003eTh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003csup\u003e228\u003c/sup\u003eRa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003csup\u003e40\u003c/sup\u003eK\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003eCd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003ePb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003eCu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eMg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eMn\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eZn\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eO.M\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003eTchilassi river\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eLTCH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e10,0\u0026nbsp;\u0026plusmn;\u0026nbsp;3,1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e5,1 \u0026plusmn; 0,7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e8,4 \u0026plusmn; 3,9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e4,8 \u0026plusmn; 0,3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e6,4 \u0026plusmn; 0,9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e40,8 \u0026plusmn; 3,9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e0,1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e24,5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e15,5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e83,5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e116,6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e28,6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e15,6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003eLoukonzi lagoon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eRLK02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e29,3\u0026nbsp;\u0026plusmn;\u0026nbsp;2,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e17,6 \u0026plusmn; 1,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e38,4 \u0026plusmn; 2,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e76,0 \u0026plusmn; 3,9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e80,5\u0026nbsp;\u0026plusmn;\u0026nbsp;4,9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e107,2 \u0026plusmn; 6,8\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e0,05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e26,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e34,4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e311,9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e171,9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e51,9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e14,8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eRLK05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e26,5\u0026nbsp;\u0026plusmn;\u0026nbsp;1,9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e14,1 \u0026plusmn; 1,2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e66, 3 \u0026plusmn; 3,1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e62,3 \u0026plusmn; 3,4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e87,5 \u0026plusmn; 6,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e122,7 \u0026plusmn; 9,6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e0,32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e18,7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e32,8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1093,8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e173,1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e28,9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e20,7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eRLK07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e28,9 \u0026plusmn; 5,7\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e14,9 \u0026plusmn; 1,6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e34,5 \u0026plusmn; 7,3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e56,4 \u0026plusmn; 3,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e66,7 \u0026plusmn; 4,4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e96,9 \u0026plusmn; 8,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e0,04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e33,1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e31,1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e352,4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e157,8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e68,5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e15,4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003eRed river\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eRR01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e31,9 \u0026plusmn; 4,7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e15,2 \u0026plusmn; 1,4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e28,7 \u0026plusmn; 6,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e29,2 \u0026plusmn; 1,6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e34,8 \u0026plusmn; 2,5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e46,4 \u0026plusmn; 4,9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e0,48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e30,2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e17,7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e186,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e92,7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e78,6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e8,4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eRR02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e19,5 \u0026plusmn; 1,5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e13,9 \u0026plusmn; 0,9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e27,9 \u0026plusmn; 2,9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e20,9 \u0026plusmn; 1,1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e25,2 \u0026plusmn; 2,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e34,5 \u0026plusmn; 2,1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e0,05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e29,1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e14,3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e144,2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e100,5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e40,9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e6,6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eRR03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e9,0 \u0026plusmn; 1,4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e9,0 \u0026plusmn; 0,6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e17,5 \u0026plusmn; 2,2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e10,0 \u0026plusmn; 1,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e17,1 \u0026plusmn; 1,6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e26,8 \u0026plusmn; 2,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e0,11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e36,9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e17,3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e111,5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e89,2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e39,8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e4,5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003eSongolo river\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eRS01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e33,7 \u0026plusmn; 1,8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e4,9 \u0026plusmn; 0,5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e9,6 \u0026plusmn; 1,8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e5,5 \u0026plusmn; 0,4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e9,3 \u0026plusmn; 1,1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e63,8 \u0026plusmn; 4,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e0,07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e19,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e10,8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e217,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e77,1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e49,6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e6,0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eRS05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e12,9 \u0026plusmn; 1,9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e6,7 \u0026plusmn; 0,6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e35,1 \u0026plusmn; 2,4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e10,0 \u0026plusmn; 0,5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e11,8 \u0026plusmn; 1,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e133,3 \u0026plusmn; 7,7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e0,03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e34,1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e15,8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1312,1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e130,9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e133,4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e5,5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eRS06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e15,4 \u0026plusmn; 1,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e7,1 \u0026plusmn; 0,5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e30,1 \u0026plusmn; 1,7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e12,0 \u0026plusmn; 0,6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e14,5 \u0026plusmn; 1,1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e71,5 \u0026plusmn; 4,5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e0,05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e13,7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e15,7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1129,7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e110,1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e97,7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e11,2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003eMvassa lagoon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eMV01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e15,0 \u0026plusmn; 3,3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e7,9 \u0026plusmn; 0,8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e79,6 \u0026plusmn; 6,4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e7,2 \u0026plusmn; 0,4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e8,5 \u0026plusmn; 1,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e93,6 \u0026plusmn; 6,8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e2,23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e25,9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e15,1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e974,3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e53,3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e34,5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e7,9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eMV03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e8,7 \u0026plusmn; 1,2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e6,2 \u0026plusmn; 0,5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e53,5 \u0026plusmn; 2,4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e5,3 \u0026plusmn; 0,3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e9,3 \u0026plusmn; 1,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e38,3 \u0026plusmn; 2,9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e0,06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e37,8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e15,5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e226,5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e56,6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e54,8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e5,3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eMV04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e13,7 \u0026plusmn; 2,7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e5,4 \u0026plusmn; 0,6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e77,8 \u0026plusmn; 6,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e5,1 \u0026plusmn; 0,3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e6,9 \u0026plusmn; 1,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e62,9 \u0026plusmn; 4,8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e0,04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e44,9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e4,6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1004,8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e51,4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e62,4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e7,7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003eMin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e8,7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e4,9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e8,4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e4,8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e6,5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e26,8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e0,03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e13,7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e4,6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e83,5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e51,4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e28,6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e4,53\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003eMax\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e33,7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e17,6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e79,6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e87,5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e133,3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e2,2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e44,9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e34,4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1312,1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e173,1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e133,4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e20,68\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e19,6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e9,9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e23,4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e29,1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e72,2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e0,3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e28,7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e18,5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e549,8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e106,2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e59,2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e10,0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e3.1 Geochemical inventory of natural radionuclides in surface sediments: concentration, distribution and origin.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\u003cstrong\u003eUranium-238 series (\u003csup\u003e238\u003c/sup\u003eU, \u003csup\u003e226\u003c/sup\u003eRa, \u003csup\u003e210\u003c/sup\u003ePb)\u003c/strong\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003csup\u003e238\u003c/sup\u003eU activities vary between 8.7 \u0026plusmn; 1.2 Bq/kg and 33.7 \u0026plusmn; 1.8 Bq/kg, with an average of 19.6 \u0026plusmn; 5.3 Bq/kg, below the UNSCEAR reference value (35 Bq/kg). The highest concentrations are observed in Loukonzi and Songolo, while the lowest occur in Tchilassi and Mvassa. The conservative behavior of \u003csup\u003e238\u003c/sup\u003eU in estuarine environments explains the low levels observed: the radionuclide remains mostly dissolved and its adsorption onto particles is limited. According to Jeambrun (2012), uranium preferentially binds to organic matter, carbonates, or phosphates; thus, the low organic matter content in Mvassa and Tchilassi directly influences the low fixation of \u003csup\u003e238\u003c/sup\u003eU. Its spatial variability reflects the effect of salinity, pH, mineralogy, and hydrological dynamics, which control the reduction of U(VI) to U(IV) and its precipitation (IAEA, 2023; IRSN, 2010).\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e226\u003c/sup\u003eRa, determined from its descendants \u003csup\u003e212\u003c/sup\u003eBi and \u003csup\u003e214\u003c/sup\u003ePb (609 keV and 351 keV), exhibits very low activity levels (4.9 \u0026plusmn; 0.5 \u0026ndash; 17.6 \u0026plusmn; 1.0 Bq/kg; average 9.9 \u0026plusmn; 0.8 Bq/kg), all below the UNSCEAR threshold (35 Bq/kg). Radium is not very mobile and is strongly adsorbed by clays and organic matter. According to studies conducted by the International Atomic Energy Agency (IAEA, 2014) and the work of Cuvier (2015), the behavior of radium depends on competition with other ions (Ca\u003csup\u003e2+\u003c/sup\u003e, Ba\u003csup\u003e2+\u003c/sup\u003e, Mg\u003csup\u003e2+\u003c/sup\u003e), salinity, and ionic strength. This explains the variations observed between sites. The higher mobility of radium compared to uranium therefore indicates a tendency for diffusion from sediments into water.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e210\u003c/sup\u003ePb shows high variability : 8.4 \u0026plusmn; 3.9 Bq/kg and 79.6 \u0026plusmn; 6.4 Bq/kg, with an average (39.0 \u0026plusmn; 3.7 Bq/kg) above the UNSCEAR limit (35 Bq/kg). The highest levels are found in Mvassa (70.3 \u0026plusmn; 4.9 Bq/kg) and Loukonzi (46.4 \u0026plusmn; 4.1 Bq/kg), areas identified as potentially sensitive. \u003csup\u003e210\u003c/sup\u003ePb is strongly influenced by atmospheric inputs via the decay of \u003csup\u003e222\u003c/sup\u003eRn, explaining the excess \u003csup\u003e210\u003c/sup\u003ePb enrichment (\u003csup\u003e210\u003c/sup\u003ePb\u003csub\u003eex\u003c/sub\u003e) (Laissaoui et al., 2018; IAEA, 2017; El Mamoney and Khater, 2004; Miralles, 2004). Its strong affinity for fine particles and organic matter explains the high values in lagoon environments with low hydrodynamics. The absence of a \u003csup\u003e210\u003c/sup\u003ePb/\u003csup\u003e226\u003c/sup\u003eRa equilibrium (ratios 1.6 - 14.5) confirms an uncontrolled external contribution and geochemical conditions favoring its fixation (Kaya et al., 2024a).\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\u003cstrong\u003eThorium-232 series (\u0026sup2;\u0026sup3;\u0026sup2;Th, \u0026sup2;\u0026sup2;⁸Ra, \u0026sup2;\u0026sup2;⁸Th)\u003c/strong\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eConcentrations of \u003csup\u003e232\u003c/sup\u003eTh(\u003csup\u003e228\u003c/sup\u003eRa) vary between 6.5 \u0026plusmn; 0.9 and 87.5 \u0026plusmn; 6.0 Bq/kg, with an average of 29.1 \u0026plusmn; 2.0 Bq/kg. An exceptional enrichment is observed in Loukonzi (78.2 \u0026plusmn; 5.1 Bq/kg), above the UNSCEAR threshold (30 Bq/kg). It is known that \u003csup\u003e228\u003c/sup\u003eRa is depleted in estuarine sediments, but that after radioactive decay of 232Th in the solid grains of the sediments, a fraction of the \u003csup\u003e228\u003c/sup\u003eRa recoil atoms penetrate the aqueous interstitial space and eventually reach the overlying water column (El Mamoney and Khater, 2004). Thorium is a very immobile element, strongly associated with heavy minerals (ilmenite, zircon, rutile) and clays. This could explain its enrichment in the Loukonzi lagoon, which reflects the presence of variegated clays rich in heavy metals, a possible influence of black sands (titanium-bearing minerals), a probable contribution linked to the calcareous-sandstone point of Nkounda described by Callec et al. (2015), or even industrial effluents. However, geochemistry indicates a predominantly lithogenic origin, consistent with the low mobility of Th. On the other hand, \u003csup\u003e228\u003c/sup\u003eTh (56.4 \u0026plusmn; 3.0 - 76.0 \u0026plusmn; 3.8 Bq/kg) follows the distribution of \u003csup\u003e228\u003c/sup\u003eRa, confirming mineralogical control and a common origin.\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\u003cstrong\u003ePotassium-40 series (⁴⁰K)\u003c/strong\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eThe activities of \u003csup\u003e40\u003c/sup\u003eK (26.8 \u0026plusmn; 2.0 \u0026ndash; 133.3 \u0026plusmn; 7.7 Bq/kg) remain well below the UNSCEAR limit (400 Bq/kg). According to Love et al. (2003) and Court (2014), \u003csup\u003e40\u003c/sup\u003eK is an excellent marker for clays and silts. The low concentrations at Tchilassi and Red rivers could be explained by strong hydrodynamics, preventing the accumulation of fine particles. The contrasts between sites reflect mineralogical variations (clays vs. sands).\u003c/p\u003e\n\u003cp\u003eUltimately, areas rich in clay (Loukonzi lagoon, Red River) reveal enrichment in \u003csup\u003e238\u003c/sup\u003eU, \u003csup\u003e226\u003c/sup\u003eRa, and thorium. These areas reflect low hydrodynamics, resulting in the accumulation of fine particles and enrichment in radionuclides.\u003c/p\u003e\n\u003cp\u003eThe sandy areas (Songolo, Tchilassi, and Mvassa) show lower activity, dominated by \u003csup\u003e40\u003c/sup\u003eK and isolated heavy minerals. These areas are characterized by high dispersion and low retention.\u003c/p\u003e\n\u003cp\u003eThe very high \u003csup\u003e210\u003c/sup\u003ePb/\u003csup\u003e226\u003c/sup\u003eRa ratios indicate a dominant atmospheric contribution (Kaya et al., 2024a). On the other hand, those with \u003csup\u003e238\u003c/sup\u003eU/\u003csup\u003e226\u003c/sup\u003eRa \u0026gt; 1 reflect the loss of Ra through diffusion, reflecting the greater solubility of radium (El Mamoney and Khater, 2004). Ratios of \u003csup\u003e226\u003c/sup\u003eRa/\u003csup\u003e228\u003c/sup\u003eRa \u0026lt; 1 refer to areas of sedimentary accumulation (Arriola-Vel\u0026aacute;squez et al., 2021), and those between \u003csup\u003e40\u003c/sup\u003eK/\u003csup\u003e232\u003c/sup\u003eTh or \u003csup\u003e40\u003c/sup\u003eK/\u003csup\u003e238\u003c/sup\u003eU indicate sandy mineralogy rich in heavy minerals (Satyanarayan Bramha et al., 2025).\u003c/p\u003e\n\u003cp\u003eThe coastal sedimentary environments of the Congo have mainly natural radionuclide levels, which are generally below UNSCEAR thresholds (UNSCEAR, 2000), with the exception of \u003csup\u003e210\u003c/sup\u003ePb in Mvassa and \u003csup\u003e232\u003c/sup\u003eTh in Loukonzi. Spatial distribution is controlled by: mineralogy (clays, sands), hydro-sedimentary dynamics, physicochemical parameters (pH, salinity, OM), atmospheric inputs for \u003csup\u003e210\u003c/sup\u003ePb, and some limited anthropogenic influences. These results suggest geochemical behavior consistent with the properties of each radionuclide and highlight the need for targeted environmental monitoring in sensitive areas (Mvassa, Loukonzi).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2 Geochemical inventory of heavy metals in surface sediments: concentration, distribution, behavior and origin.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHeavy metals of geochemical interest (Mg, Mn) and environmental interest (Cd, Cu, Pb, Zn) were analyzed in surface sediments using atomic absorption spectrometry (AAS). This single-element technique did not allow for the quantification of a wider range of elements, but the results obtained (Table 1) provide a representative overview of metal contamination in the study area.\u003c/p\u003e\n\u003cp\u003eThe concentrations are in descending order: Mg \u0026gt; Mn \u0026gt; Zn \u0026gt; Pb \u0026gt; Cu \u0026gt; Cd. However, two elements, Cd and Pb, significantly exceed the local natural geochemical background levels: Cd: 0.4 mg/kg (geochemical background: 0.1 mg/kg)\u0026nbsp;; Pb: 28.8 mg/kg (geochemical background: 20.68 mg/kg)\u003c/p\u003e\n\u003cp\u003eThe highest levels were recorded:\u003c/p\u003e\n\u003cul class=\"decimal_type\"\u003e\n \u003cli\u003eFor Cd: Mvassa lagoon (2.22 mg/kg), Red River (0.5 mg/kg), Loukonzi lagoon (0.32 mg/kg).\u003c/li\u003e\n \u003cli\u003eFor Pb: Mvassa lagoon (44.9 mg/kg), Red River (36.9 mg/kg), Songolo River (34.1 mg/kg);\u003c/li\u003e\n \u003cli\u003eLoukonzi lagoon (33.1 mg/kg), Tchilassi River (24.5 mg/kg).\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eZinc (Zn) levels are generally lower than the geochemical background, with the notable exception of the Songolo River, where the average is 93.6 mg/kg, compared to a geochemical background of 82.4 mg/kg (Kaya et al., 2024b).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe enrichment of Cd and Pb relative to the geochemical background indicates a disruption of natural flows, typical of environments subject to industrial discharges. The most contaminated sites (Mvassa, Songolo, Rouge) are located in the direct area of influence of the Ndjeno oil terminal, the gas-fired power plant, petrochemical, metallurgical and fertilizer industries, the autonomous port and ship maintenance activities. These activities are known to emit Cd (refineries, hydrocarbon combustion, chemical industries) and Pb (metallurgy, fuels, batteries, atmospheric deposits). The simultaneous presence of stable Pb and \u003csup\u003e210\u003c/sup\u003ePb, confirmed by other studies (Tamponnet 2009; Kaya et al., 2024), reinforces the hypothesis of atmospheric dispersion followed by deposition in sediments.\u003c/p\u003e\n\u003cp\u003eThe geochemical anomaly in Zn recorded in the Songolo River reflects enrichment influenced by both the lithology of the sediments and anthropogenic pressure (Kaya et al., 2024b), which can be explained by the presence of shipyards, ship scrap, and metal waste; landfills rich in plastics, rubber, and batteries, identified as major sources of Zn (Jimenez, 2016); a possible lithogenic contribution (alteration of Zn-bearing minerals). This overlap of natural and anthropogenic sources is consistent with the observations of Mohajane and Manjoro (2022), Chahouri et al. (2023) and Jolly et al. (2023).\u003c/p\u003e\n\u003cp\u003eHowever, the low concentrations recorded in the Tchilassi and Red Rivers can be explained by a vigorous hydrodynamic regime; a grain size fraction dominated by sand; and a low retention capacity for fine particles, which are the main carriers of heavy metals (Kaya et al., 2024b). According to the Fondriest Environmental (2014), sands have low adsorption capacity, which limits the accumulation of metals in sediments.\u003c/p\u003e\n\u003cp\u003eFinally, sediments from the Congolese coastline show significant enrichment in Cd and Pb; localized Zn contamination; a strong influence from industrial, port, oil, and metallurgical activities (Kaya et al., 2024b); and a geochemical impact that depends on grain size, hydrosedimentary dynamics, and proximity to anthropogenic sources. Thus, the overall geochemical footprint highlights a clear dominance of anthropogenic sources over natural inputs in several coastal areas.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3 Influence of organic matter on the geochemical distribution of heavy metals\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe organic matter (OM %) content measured in sediments varies between 4.5% and 20.7%, with an average of 10.3% (Table 1). The sites with the highest OM content are the Tchilassi River and Loukonzi Lagoon. Conversely, the Songolo River, Red River and Mvassa Lagoon have relatively low values. Organic matter plays a major role in the adsorption of heavy metals, the complexation of metal cations (Cu\u003csup\u003e2+\u003c/sup\u003e, Pb\u003csup\u003e2+\u003c/sup\u003e, Zn\u003csup\u003e2+\u003c/sup\u003e, Cd\u003csup\u003e2+\u003c/sup\u003e), and the trapping of metals in fine, anoxic sediments. Thus, sites rich in organic matter are generally conducive to increased heavy metal accumulation. However, industrial sites (Songolo, Mvassa) show lower organic matter concentrations, which can be explained by regular dredging operations that reduce the organic fraction and intense microbial degradation of matter in distorse environments (Mejjad et al., 2018; Mirsa, 2012) and high hydrodynamics that export fine particles rich in organic matter.\u003c/p\u003e\n\u003cp\u003eThe variability of heavy metals therefore reflects the availability of organic matter, grain size (the finer the sediments, the more metals they retain), and proximity to sources of pollution. As a result, areas rich in organic matter act as geochemical traps, while areas poor in organic matter but close to industry (Songolo, Mvassa) may show anomalies linked to recent inputs, explained by the rapid circulation of particles and direct discharges.\u003c/p\u003e\n\u003cp\u003eFurthermore, the distribution of heavy metals in coastal sediments is not random; it results from the interaction between anthropogenic inputs, organic matter content, hydrosedimentary dynamics, and local mineralogy. These factors determine each site\u0026apos;s capacity to accumulate, transport, or release heavy metals into the coastal ecosystem.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.4 Correlation between radionuclides, heavy metals, and organic matter in surface sediments along the Congolese South Atlantic coastline.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe correlation between variables makes it possible to trace their common source. The interdependence between natural radionuclides and heavy metals, as well as organic matter in surface sediments, was assessed using statistical methods such as Pearson\u0026apos;s correlation and principal component analysis (PCA).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePearson correlations\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTable 2 presents Pearson\u0026apos;s correlation coefficients between radionuclides, heavy metals, and organic matter in surface sediments in the study area. These correlations allow us to explore the geochemical behavior of elements by identifying associations between variables that may share a common origin, mode of transport, or similar geochemical affinity. The following observations were made:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eModerate correlations (\u0026rho; \u0026lt; 0.05): indicators of natural or mixed associations\u0026nbsp;\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eModerate positive correlations were observed between several radionuclides and organic matter: \u003csup\u003e234\u003c/sup\u003eTh-\u003csup\u003e226\u003c/sup\u003eRa (0.61), \u003csup\u003e234\u003c/sup\u003eTh-\u003csup\u003e228\u003c/sup\u003eTh (0.63), \u003csup\u003e234\u003c/sup\u003eTh-\u003csup\u003e228\u003c/sup\u003eRa (0.62), \u003csup\u003e234\u003c/sup\u003eTh-OM (0.61), \u003csup\u003e226\u003c/sup\u003eRa-Mn (0.65), \u003csup\u003e226\u003c/sup\u003eRa-OM (0.59), \u003csup\u003e210\u003c/sup\u003ePb-Mg (0.60), \u003csup\u003e40\u003c/sup\u003eK-Mn (0.60). These associations suggest similar mobility or geochemical behavior in the sedimentary environment. In particular, organic matter (OM) plays a key role in the trapping and complexation of radionuclides (\u003csup\u003e234\u003c/sup\u003eTh, \u003csup\u003e226\u003c/sup\u003eRa) and certain major geochemical elements (Mg, Mn, K). The link between Ra and Mn could reflect co-precipitation in oxyhydroxide phases, which is common in diagenetic environments. The \u003csup\u003e210\u003c/sup\u003ePb-Mg correlation is typical of sorption on clay and organic phases, with Mg often present in silicates.\u003c/p\u003e\n\u003cp\u003eTable 2: Pearson correlation of different variables in surface sediment samples.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"623\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 42px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003csup\u003e234\u003c/sup\u003eTh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003csup\u003e226\u003c/sup\u003eRa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003csup\u003e210\u003c/sup\u003ePb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003csup\u003e228\u003c/sup\u003eTh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003csup\u003e228\u003c/sup\u003eRa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e\u003csup\u003e40\u003c/sup\u003eK\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eCd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003ePb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003eCu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003eMg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003eMn\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003eZn\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003eOM\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003csup\u003e234\u003c/sup\u003eTh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003csup\u003e226\u003c/sup\u003eRa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.61\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003csup\u003e210\u003c/sup\u003ePb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e-0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003csup\u003e228\u003c/sup\u003eTh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.63\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.88\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003csup\u003e228\u003c/sup\u003eRa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.62\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.85\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.99\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003csup\u003e40\u003c/sup\u003eK\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003eCd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e-0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e-0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e-0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e-0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003ePb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e-0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e-0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e-0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e-0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e-0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e-0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003eCu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.78\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.93\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.93\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e-0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e-0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003eMg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e-0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e-0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.60\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e-0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.70\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e-0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e-0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003eMn\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.65\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e-0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.83\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.83\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.60\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e-0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e-0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.87\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003eZn\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e-0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e-0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e-0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e-0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e-0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e-0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e-0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003eOM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.61\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.59\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e-0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.78\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.79\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e-0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e-0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.78\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.84\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"13\" valign=\"top\" style=\"width: 590px;\"\u003e\n \u003cp\u003e** (the bilateral correlation is significant at the 0.01 level).\u003c/p\u003e\n \u003cp\u003e* (the bilateral correlation is significant at the 0.05 level).\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cul\u003e\n \u003cli\u003eStrong correlations (\u0026rho; \u0026lt; 0.01): signs of a common origin and coupled behaviors\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eVery strong correlations were found between thorium and radium radionuclides and certain trace metals: \u003csup\u003e226\u003c/sup\u003eRa-\u003csup\u003e228\u003c/sup\u003eTh (0.88), \u003csup\u003e226\u003c/sup\u003eRa-\u003csup\u003e228\u003c/sup\u003eRa (0.85), \u003csup\u003e226\u003c/sup\u003eRa-Cu (0.78), \u003csup\u003e228\u003c/sup\u003eTh-\u003csup\u003e228\u003c/sup\u003eRa (0.99), \u003csup\u003e228\u003c/sup\u003eTh-Cu (0.93), \u003csup\u003e228\u003c/sup\u003eRa-Cu (0.93). These correlations indicate a probable common source for these elements, or at least an association in the same sedimentary compartment, dominated by organic matter and metal oxides.\u003c/p\u003e\n\u003cp\u003eCopper (Cu), although non-radioactive, shares geochemical behavior similar to actinides and decay products due to its strong affinity for organic ligands and Fe and Mn oxyhydroxides.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe Ra-Th-Cu system appears to be structured by mixed anthropogenic inputs (industrial or urban discharges) and natural geochemical processes.\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eThe central role of organic matter (OM) and Mn in elementary associations\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eThe strong correlations between \u003csup\u003e228\u003c/sup\u003eTh, \u003csup\u003e228\u003c/sup\u003eRa, and Cu with Mn and OM reinforce the idea of coupled behavior in sediments: \u003csup\u003e228\u003c/sup\u003eTh-Mn (0.83), \u003csup\u003e228\u003c/sup\u003eTh-OM (0.78), \u003csup\u003e228\u003c/sup\u003eRa-Mn (0.83), \u003csup\u003e228\u003c/sup\u003eRa-OM (0.79), Cu-Mn (0.87), Cu-OM (0.78), Mn-OM (0.84). These data indicate that Mn and organic matter act as major geochemical vectors for the trapping of these elements. Mn, in the form of oxyhydroxides, is known to effectively adsorb radionuclides and trace metals before being remobilized under reducing conditions. OM, on the other hand, plays an essential role in the sorption, complexation, and stabilization of metals and radionuclides, particularly in biologically productive lagoon environments.\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eGeochemical and environmental implications\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eThese cross-correlations between radionuclides (\u003csup\u003e234\u003c/sup\u003eTh, \u003csup\u003e226\u003c/sup\u003eRa, \u003csup\u003e228\u003c/sup\u003eRa, \u003csup\u003e228\u003c/sup\u003eTh, \u003csup\u003e210\u003c/sup\u003ePb), heavy metals of environmental interest (Cu, Pb, Cd) and geochemical elements (Mn, Mg, \u003csup\u003e40\u003c/sup\u003eK), as well as organic matter, reveal complex interactions governed by both natural and anthropogenic processes:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003ecorrelations with Mn and OM reflect diagenetic and biogeochemical processes controlling the mobility of elements;\u003c/li\u003e\n \u003cli\u003estrong Cu-Ra-Th associations reveal potential industrial contamination linked to metallurgical, port, or urban discharges\u0026nbsp;;\u003c/li\u003e\n \u003cli\u003eThe involvement of Mg, \u003csup\u003e40\u003c/sup\u003eK, and other major elements suggests an influence of the petrographic nature of the sediments and source rocks.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eThese results corroborate the conclusions of previous studies conducted in similar coastal environments, notably in Agadir Bay (Chahouri et al., 2023) and Oualidia Lagoon (Mejjad et al., 2018) in Morocco, the South African Atlantic coast (Mohajane et Manjoro, 2022), and the estuarine areas of Bangladesh (Jolly et al., 2023), where similar distribution patterns are observed, highlighting the strong dependence of metal concentrations on local sedimentary conditions and anthropogenic pressures.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePrincipal component analysis (PCA)\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003ePrincipal component analysis (PCA), supported by statistical validity tests (Kaiser-Meyer-Olkin index and Bartlett\u0026apos;s sphericity test), was applied to the measured variables in order to identify latent structures and multivariate relationships in the data. The results are presented in Table\u0026nbsp;3.\u003c/p\u003e\n\u003cp\u003ePCA, after Varimax rotation with Kaiser normalization, allowed the extraction of four (04) principal components, all characterized by eigenvalues greater than 1, together explaining 85.81% of the total observed variance. With the exception of \u003csup\u003e234\u003c/sup\u003eTh (extraction values \u0026lt; 0.6), all variables have a high representation quality, ranging from 72% to 99%, indicating their relevance in the structuring of the components.\u003c/p\u003e\n\u003cp\u003eComponent 1 accounts for 44.99% of the variance and highlights mixed geochemical signatures and accumulation linked to organic matter. It is the most influential component and includes the following elements: \u003csup\u003e226\u003c/sup\u003eRa (0.89), \u003csup\u003e228\u003c/sup\u003eTh (0.99), \u003csup\u003e228\u003c/sup\u003eRa (0.99), Cu (0.94), Mn (0.84), OM (0.74) and, to a lesser extent, \u003csup\u003e234\u003c/sup\u003eTh (0.62). This association highlights strongly coupled geochemical behaviors characteristic of a reducing system rich in organic matter and influenced by mixed inputs:\u0026nbsp;\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eMn, an element sensitive to redox conditions, is a tracer of early diagenesis (IAEA, 2024; Mejjad et al., 2020), promoting the precipitation of oxyhydroxides capable of trapping numerous metal cations;\u003c/li\u003e\n \u003cli\u003eCu has a strong affinity for organic ligands and Fe/Mn oxyhydroxide phases, which explains its co-variation with OM and Mn. Its presence may also indicate anthropogenic inputs (industrial and urban waste) (Chahouri et al., 2023; Jolly et al., 2023; Mohajane et Manjoro, 2022) but also natural mobilization from sediments;\u003c/li\u003e\n \u003cli\u003eRadionuclides \u003csup\u003e226\u003c/sup\u003eRa, \u003csup\u003e228\u003c/sup\u003eRa, and \u003csup\u003e228\u003c/sup\u003eTh, although present in low concentrations, show a very strong correlation, indicating a common lithogenic origin, probably linked to the mineralogy of source rocks and fine sediments.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eThis component therefore reflects a synergy between natural processes (diagenesis, organo-metallic affinity, radioactive decay) and localized anthropogenic activities, linked to the sedimentary and biogeochemical dynamics of the area.\u003c/p\u003e\n\u003cp\u003eComponent 2 accounts for 18.62% of the variance and explains lithogenic inputs altered by industrial activities. It includes \u003csup\u003e40\u003c/sup\u003eK, Mg, and Zn, elements that represent predominantly lithogenic geochemical behaviors. \u003csup\u003e40\u003c/sup\u003eK and Mg are associated with silicate minerals (feldspars, micas, chlorites) (Arriola-Vel\u0026aacute;squez et al., 2021; Strady, 2010; Aranguren, 2008; Love et al., 2003) present in reworked or continental sediments. Zn, although also of natural origin, is often locally enriched by anthropogenic activities (Jolly et al., 2023), particularly by metal discharges, antifouling paints, and ferrous debris from old ships at the Songolo site (Kaya et al., 2024b).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis component therefore illustrates hybrid geochemical behavior, where natural lithogenic inputs are modified or reinforced by localized anthropogenic activities, particularly in port and industrial areas.\u003c/p\u003e\n\u003cp\u003eComponent 3 accounts for 12.68% of the variance and is a marker of active industrial pollution dominated by a strong correlation between \u003csup\u003e210\u003c/sup\u003ePb (0.82) and Cd (0.85). These two elements are recognized as environmental markers sensitive to anthropogenic pollution. Cd, a highly toxic element (IARC, 2012; USEPA, 2002), is a classic contaminant of coastal and estuarine environments, generally originating from industrial sources: energy production, refining, batteries, phosphate fertilizers, chemical discharges, etc. (IARC, 2012; Chalghmi, 2015; IRSN, 2004). \u003csup\u003e210\u003c/sup\u003ePb, a natural isotope in the uranium decay chain, can also be found in excess in areas subject to human activity (Kaya et al., 2024a), particularly in industrialized areas or areas with high organic sedimentation (IAEA, 2017, 2024).\u003c/p\u003e\n\u003cp\u003eThis component reflects a clear signature of industrial contamination, particularly in areas of oil, chemical, or port activity, where these elements are mobilized, transported, and trapped in sediments (as in the case of the Mvassa lagoon).\u003c/p\u003e\n\u003cp\u003eComponent 4, which accounts for only 9.52% of the variance, highlights an exclusively anthropogenic origin of lead (Pb: 0.95), an element typically associated with industrial and urban pollution. According to the work of Moubakou Diahou (2024), Cook and al. (2018), and Cuvier (2015), Pb is released into the environment through atmospheric emissions (Ferreira-Batista\u0026nbsp;et De Miguel, 2005), oil production, natural gas combustion, and construction and infrastructure debris. Its significant accumulation in the sediments of the Mvassa and Loukonzi lagoons can be linked to the proximity of the gas-fired power plant, the Njeno oil terminal located near the Mvassa lagoon, and the major construction zones of the Nkounda Special Economic Complex extending toward the Loukonzi lagoon. This component therefore reflects targeted and localized pollution, mainly resulting from recent industrial activities.\u003c/p\u003e\n\u003cp\u003eUltimately, the joint integration of ACP and Pearson correlation analysis made it possible to group the elements according to their geochemical affinities and probable sources, highlighting three main origins for the elements studied:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003enatural origin, linked to sediment lithology (\u003csup\u003e40\u003c/sup\u003eK, Mg, Ra, Th), this source controls the background distribution of radionuclides and major elements;\u003c/li\u003e\n \u003cli\u003eanthropogenic origin, dominated by metals such as Cd, Pb, Cu, and \u003csup\u003e210\u003c/sup\u003ePb, which is directly linked to industrial, energy, and urban activities in the region, affecting the quality of sediments and aquatic ecosystems;\u003c/li\u003e\n \u003cli\u003efinally, a mixed origin, reflecting an interaction between natural and anthropogenic processes. This source is particularly visible in the first component, where lithogenic radionuclides interact with metal pollutants (Cu, Zn, Mn) and organic matter, highlighting the importance of redox conditions and sediment composition in controlling the distribution of contaminants.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eTable 3: Component matrices after VARIMAX rotation with Kaiser normalization and variable representation quality in surface samples\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"415\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 227px;\"\u003e\n \u003cp\u003eComponents\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eExtraction\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003csup\u003e234\u003c/sup\u003eTh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.62\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e-0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e-0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e-0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003csup\u003e226\u003c/sup\u003eRa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.89\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e-0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e-0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003csup\u003e210\u003c/sup\u003ePb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.82\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003csup\u003e228\u003c/sup\u003eTh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.99\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e-0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003csup\u003e228\u003c/sup\u003eRa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.99\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e-0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003csup\u003e40\u003c/sup\u003eK\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.78\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e-0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eCd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e-0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e-0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.85\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e-0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003ePb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e-0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e-0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.95\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eCu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.94\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e-0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eMg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e-0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.90\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e-0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eMn\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.84\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e-0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e-0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eZn\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e-0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.76\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e-0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eOM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.74\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e-0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eEigenvalue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e5.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e2.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e% Total variance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e44.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e18.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e12.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e9.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eThese results highlight the value of combining robust statistical tools with in-depth geochemical and environmental analysis to assess sediment quality and detect sources of pollution in estuarine environments. They also provide scientific support for the implementation of environmental management measures and the monitoring of vulnerable ecosystems exposed to increasing anthropogenic pressures.\u003c/p\u003e\n\u003cp\u003eHowever, maps shown in figure 2 illustrate the spatial distribution of geochemical anomalies of \u003csup\u003e234\u003c/sup\u003eTh, \u003csup\u003e226\u003c/sup\u003eRa, \u003csup\u003e210\u003c/sup\u003ePb, \u003csup\u003e228\u003c/sup\u003eTh, \u003csup\u003e288\u003c/sup\u003eRa, \u003csup\u003e40\u003c/sup\u003eK, Cd, Cu, Pb, Zn, Mg, and Mn, as well as organic matter in surface sediments at the various sites studied. Warm colors (red, orange, yellow) indicate high concentration levels, while cool colors (purple, blue) indicate values well below the average, represented in green. The studied sites are identified by their GPS coordinates. For example, the Tchilassi River is located at a latitude of -4.71 and a longitude of 11.88. The Loukonzi Lagoon is located between -4.72 and -4.80 latitude and around 11.83 longitude; the Rouge River between -4.80 and -4.84 latitude and 11.84 longitude; the Songolo River between -4.82 and -4.84 latitude and 11.85 longitude; and finally, the Mvassa Lagoon, located between -4.84 and -4.88 latitude and 11.89 longitude.\u003c/p\u003e"},{"header":"4. Conclusion","content":"\u003cp\u003eThe joint assessment of the distribution of natural radionuclides and heavy metals in coastal sediments along the Congolese coastline has revealed a complex environmental dynamic resulting from the interaction between natural processes and increasing anthropogenic pressures. The concentrations measured show that, despite a predominance of natural radionuclides generally below the reference thresholds defined by UNSCEAR, certain localized areas, notably Mvassa for \u003csup\u003e210\u003c/sup\u003ePb and Loukonzi for \u003csup\u003e232\u003c/sup\u003eTh, exhibit abnormally high levels, suggesting a combined influence of mineralogy, atmospheric inputs, and hydro-sedimentary processes.\u003c/p\u003e \u003cp\u003eAt the same time, metal contamination shows a geochemical signal marked by significant enrichment in Cd and Pb, localized Zn contamination, and a significant footprint from industrial, port, oil, and metallurgical activities. The spatial distribution of heavy metals is not random: it reflects the strong influence of grain size, organic matter, deposition dynamics, and proximity to anthropogenic sources, confirming the predominance of human inputs over natural inputs in certain coastal areas.\u003c/p\u003e \u003cp\u003eThe integration of multivariate analyses (PCA) and Pearson correlations has identified three major categories of sources: (i) a natural source linked to lithology, controlling radionuclides and major elements; (ii) an anthropogenic source associated with toxic metals (Cd, Pb, Cu) and atmospheric \u003csup\u003e210\u003c/sup\u003ePb; and (iii) a mixed source, resulting from the interaction between natural processes, redox conditions, and anthropogenic disturbances. This classification confirms the value of a cross-disciplinary approach, using robust statistical tools and integrated geochemical analyses, to understand contamination mechanisms and characterize sensitive estuarine and coastal environments.\u003c/p\u003e \u003cp\u003eOverall, this study demonstrates the need to strengthen environmental monitoring, particularly in the Mvassa and Loukonzi sectors, where abnormal geochemical signals indicate increased ecosystem vulnerability. It also provides essential scientific information to guide sustainable management policies for Congo's coastal areas.\u003c/p\u003e \u003cp\u003eThis study paves the way for several avenues that deserve further exploration in order to improve understanding of contamination processes and strengthen the resilience of coastal ecosystems, such as:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003ea temporal and geochronological approach using \u003csup\u003e210\u003c/sup\u003ePb and \u003csup\u003e137\u003c/sup\u003eCs to reconstruct the historical evolution of metal and radionuclide inputs, providing a temporal perspective that is essential for remediation strategies;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003emineralogical characterization and geochemical speciation of metals to accurately assess their mobility, bioavailability, and potential for transfer to food chains.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eUltimately, this study provides a solid scientific framework for understanding the mechanisms of transfer and accumulation of radionuclides and heavy metals in coastal sediments in the Congo. It highlights the crucial importance of proactive environmental management and continuous monitoring of ecosystems that are vulnerable to anthropogenic pressures. The proposed perspectives pave the way for more integrative research capable of providing long-term support for strategies to protect and enhance the Congolese coastline.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was carried out within the framework of the PhD Sandwich program of the International Atomic Energy Agency (IAEA). The authors would like to thank the Moroccan authorities for hosting the fellowship at the National Centre for Nuclear Energy, Science and Technology (CNESTEN). The authors are also grateful to the anonymous reviewers for their suggestions and comments, which allowed to significantly improving the present paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePreparation of equipment for the data collection: Freddy Cacharel KAYA, Hilaire ELENGA, Guy Blanchard DALLOU and Aim\u0026eacute; Christian KAYATH.\u003c/p\u003e\n\u003cp\u003eSample collection: Freddy Cacharel KAYA.\u003c/p\u003e\n\u003cp\u003eSample preparation and analysis: Freddy Cacharel KAYA, Hasna AIT BOUH, Abdelmourhit LAISSAOUI, Mohammed SEBBAR, Azzouz BENKDAD (gamma analysis) and Sana SAID (metal analysis by AAS).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFunding acquisition: Freddy Cacharel KAYA\u003c/p\u003e\n\u003cp\u003eWriting of the original draft: Freddy Cacharel KAYA.\u003c/p\u003e\n\u003cp\u003eMap production: J\u0026eacute;mima Consol\u0026eacute; BOUNKOUTA and Freddy Cacharel KAYA.\u003c/p\u003e\n\u003cp\u003eSupervision: Hilaire ELENGA, Abdelmourhit LAISSAOUI and Hasna AIT BOUH.\u003c/p\u003e\n\u003cp\u003eWriting, review and editing of the final draft: All authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Atomic Energy Agency (IAEA).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo datasets were generated or analysed during the current study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u0026nbsp;:\u003c/strong\u003e All authors have read, understood, and have complied as applicable with the statement on \u0026quot;Ethical responsibilities of Authors\u0026quot; as found in the Instructions for Authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAlloway, B. 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Investigation of groundwater quality in the Southern Coast of the Black Sea: application of computational health risk assessment in Giresun, T\u0026uuml;rkiye. \u003cem\u003eEnvironmental Science and Pollution Research\u003c/em\u003e. 31, 52306\u0026ndash;52325. https://doi.org/10.1007/s11356-024-34712-w.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[{"identity":"c7bb1e73-62b0-40a6-b2f8-61768d1d7344","identifier":"10.13039/501100004493","name":"International Atomic Energy Agency","awardNumber":"TC RAF0062, EVT2104624-0001-ZAI","order_by":0}],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Marien Ngouabi University, Faculty of Sciences and Techniques","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Natural radionuclide, heavy metal, coastal sediment, geochemical dynamics, localized enrichment, lithogenic and anthropogenic sources","lastPublishedDoi":"10.21203/rs.3.rs-8330803/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8330803/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study aims to characterize the geochemical distribution, levels, and origin of natural radionuclides (\u003csup\u003e238\u003c/sup\u003eU, \u003csup\u003e226\u003c/sup\u003eRa, \u003csup\u003e210\u003c/sup\u003ePb, \u003csup\u003e232\u003c/sup\u003eTh, and \u003csup\u003e40\u003c/sup\u003eK) and heavy metals (Cd, Pb, Zn, Mn, Mg, and Cu) in recent sediment samples from the coast of the Republic of Congo, an environment subject to significant human pressure but still understudied. Surface samples were collected in river and lagoon estuaries, then analyzed by gamma spectrometry (GeHP) for radionuclides and by atomic absorption spectroscopy (AAS) for heavy metals. Additional analyses of organic matter (LOI), Pearson correlations, and ACP allowed us to determine the origin and geochemical dynamics of the elements. The results show activities that are mostly below the UNSCEAR thresholds, except for notable enrichments in \u003csup\u003e210\u003c/sup\u003ePb at Mvassa and \u003csup\u003e232\u003c/sup\u003eTh at Loukonzi lagoons. The metals show significant contamination in Cd and Pb, associated with industrial, port, and petroleum activities. The spatial distribution is controlled by grain size, hydrodynamics, organic matter, and atmospheric inputs. These results highlight the coexistence of lithogenic and anthropogenic sources and emphasize the need for enhanced environmental monitoring in sensitive areas to anticipate the growing impacts of industrial pressures and climate change.\u003c/p\u003e","manuscriptTitle":"Geochemical dynamics and origin of natural radionuclides and heavy metals in current coastal sedimentary systems in the Republic of Congo","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-12 06:57:37","doi":"10.21203/rs.3.rs-8330803/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7d909caf-eaba-48f4-9889-cc92233e6c32","owner":[],"postedDate":"December 12th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":59533038,"name":"Environmental Chemistry"},{"id":59533039,"name":"Geochemistry"}],"tags":[],"updatedAt":"2025-12-12T06:57:38+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-12 06:57:37","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8330803","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8330803","identity":"rs-8330803","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}