Comparison of Inorganic Contamination of Pyrometallurgy and Hydrometallurgy Sites at Obuasi

Comparison of Inorganic Contamination of Pyrometallurgy and Hydrometallurgy Sites at Obuasi | 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 Article Comparison of Inorganic Contamination of Pyrometallurgy and Hydrometallurgy Sites at Obuasi Williams Donkor, Herbert Adjei, Kingsley Mbayenya Nanim This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7321357/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 12 You are reading this latest preprint version Abstract This study investigates inorganic pollutant concentrations in streams and sediments affected by pyrometallurgical and hydrometallurgical gold ore processing at the Obuasi mine, Ghana. Water and sediment samples were analyzed for pH, major anions (NO₃⁻, Cl⁻, SO₄²⁻), cations (Na⁺, K⁺, Ca²⁺, Mg²⁺), and trace metals (As, Cu, Fe, Zn, Pb). Water pH ranged between 5.80 and 7.50, with elevated anion and metal levels across both sites. Pyrometallurgical effluents exhibited higher trace metal concentrations (0.01–5.00 mg/L) and markedly elevated SO₄²⁻ (0.85–945.50 mg/L), while hydrometallurgical effluents showed greater NO₃⁻ (0.01–95.39 mg/L) and Cl⁻ (1.00–49.05 mg/L) concentrations. In water, Ca²⁺ and SO₄²⁻ were the dominant cation and anion, respectively. Sediments from hydrometallurgical zones contained substantially higher levels of most parameters, excluding pH, NO₃⁻, Cl⁻, Na⁺, and Mg²⁺. Average sediment concentrations of Ca²⁺, Mg²⁺, As, and Fe ranged from 3,217 to 46,026 mg/kg. Overall, pyrometallurgical processes contributed greater pollutant loads to water, whereas hydrometallurgical processes resulted in higher sediment contamination. These contrasting geochemical patterns underscore the influence of ore processing methods on pollutant partitioning between water and sediments, with implications for environmental monitoring and remediation in mining regions. Physical sciences/Chemistry Earth and environmental sciences/Environmental sciences Pyrometallurgy Hydrometallurgy Inorganic Contaminants Sediment Contamination Pollution Load Index Environmental Pollution Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 1. INTRODUCTION Gold mining has historically been one of the major economic drivers of Ghana, and the Obuasi Gold Mine, located along the Ashanti volcanic belt, has played a pivotal role since the late 19th century. The mine has seen shifts in processing technologies, transitioning from pyrometallurgical operations that utilized roasting and smelting to the more recent adoption of hydrometallurgical techniques involving chemical leaching and precipitation. These changes were partly due to environmental and economic concerns associated with the former method (Marsden and House, 2006 ). The release of trace metals and contaminants from mining operations has raised environmental concerns, especially for surface water and sediment quality. This study aims to evaluate and compare inorganic contamination levels associated with each technique, aiming to inform sustainable mining and remediation strategies.Recent studies on hydrometallurgy and pyrometallurgy, has revealed that each of these processes comes with its own negative effects in the sense that they emit or produce contaminants and other health hazards which contribute to health effects on the residents of the Obuasi community. Also, these contaminants are not so environmentally friendly because pyrometallurgy releases greenhouse gases such as carbon dioxide, arsenious oxide, hydrogen sulfide and hydrogen gas associated with the high-temperature processes in large amounts which tend to deplete the ozone layer and reduce the oxygen content of the atmosphere. Aside the health effects of hydrometallurgy, another one is the depletion of the soil’s ability to sustain plant and animal lives due to the leaching of waste materials from the deposition sites of hydrometallurgy and pyrometallurgy waste such as tailing dams, holding ponds, stockpiles. The change over from pyrometallurgy to hydrometallurgy is actually intended to improve environmental quality, however, the pollution legacies over the years suggest that the pollutants from these sources may linger in the environment. Key questions to answer are; To what extent do these pollutions exist in the current environment? To what extent do the two metallurgic forms compare with each other in the environment? This study aims to understand the environmental impact of metallurgical processes at the Obuasi Mine, identify potential contamination sources, and assess mitigation measures. Understanding contaminants' variations will help propose effective remediation strategies. The research could have broader implications for the mining industry, promoting responsible practices and protecting natural resources and biodiversity. The project compares inorganic contaminations from pyrometallurgy and hydrometallurgy, using laboratory tests to compare heavy metal concentrations in streams and sediments. The Pollution Load Index (PLI) will be used to assess the environmental impact. 2. MATERIALS AND METHODS Study Area Obuasi is located between latitude 5.35N and 5.65N and longitude 6.35N and 6.90N, and in the southern part of the Ashanti Region, Ghana. The study area is located in Obuasi, in the Ashanti Region of Ghana as seen in the Fig. 1.1 below. The region experiences a semi-equatorial climate with a twofold maximum rainfall regime. The municipality covers 162.4 km and has a degraded, semi-deciduous forest with tall trees and multiple layers of flora. The mean annual temperature is 25°C. Sampling sites were chosen from streams influenced by both historical pyrometallurgical operations (notably the Pompora Treatment Plant) and current hydrometallurgical operations (Sansu Treatment Plant). Obuasi, located in Ghana's Ashanti Region, has a The Obuasi mine is predominantly underlained by Paleo-Proterozoic Birimian and Tarkwaian rocks. The Birimian in Ghana has two litho-stratigraphic systems: metavolcanic and metasedimentary groups and a younger arenaceous and clastic Tarkwaian group. Low-grade tholeiitic basalts with intercalated pyroclastic rocks, minor andesitic and felsic flows, and chemical sediments dominate the metavolcanic group (Kesse, 1985 ). Low-grade metamorphosed volcaniclastics, wackes, and argillites are part of the metasedimentary rocks and partly contemporaneous with the volcanic group The Tarkwaian group includes polymictic and quartz pebble conglomerates, sandstones, minor argillites, siltstones, and tuffs (Kesse, 1985 ). The Birimian rocks are intruded by hornblende-rich granitoids known as the belt type that are closely associated with the volcanic rocks and; and mica–rich granitoids referred to as basin type which tend to border the volcanic belt and are in the metasediment units, (Leube et al. 1990 ; Taylor et al. 1992; Hirdes et al. 1992). Gold in the Ashanti belt occurs as quartz reefs in metasediments or vein/lode deposits along the metasediment-metavolcanic contact (Kesse 1985 ). The metavolcanic and metasedimentary groups are separated by a broad shear zone, which at times contain visible calcite minerals associated with quartz bodies (Kesse 1985 ; Leube et al. 1990 ). Arsenopyrite and pyrite dominate primary gold ores, with minor quartz and graphitic schist regions (Osae et al. 1995 ). Sometimes metavolcanic and metasedimentary rocks have ankerite. The Obuasi geological map is illustrated in Fig. 1.1. Sampling and Analysis The data used for this work was a secondary one which was obtained by sampling carefully at selected areas at or near the pyrometallurgical and hydrometallurgical sites. Water and sediment samples were collected from 14 selected points near the treatment facilities. Figure 3.1 shows a rough map of the Obuasi region that depicts the pyrometallurgical (Pompora Treatment Plant or P.T.P.) and hydrometallurgical plant (Sulphide Treatment Plant or S.T.P.) sites and the areas where the water and stream sediment samples were collected. Water Sampling Water samples were collected from fourteen curated settings in the stream drainage basin, including towns surrounding operational hydrometallurgical sites (P15, P17, P18, P19, P20 and P21) and tailings dam facilities as well as defunct pyrometallurgical sites (P1, P3, P4, P5, P6, P7, P9 and P10). The samples were processed by the Environmental Laboratory of the Anglo-Gold Ashanti mine in Obuasi, Ghana, and acidified with concentrated HNO 3 to prevent metal precipitation. Water samples were collected in 500 mL bottles, filtered, acidified, and analyzed for physicochemical parameters using atomic absorption spectrometry (AAS) and ion chromatography. Sediment samples were oven-dried, sieved, and digested in aqua regia before elemental analysis. Quality control was ensured through replicate analyses and standard additions. Analysis of samples The study used various methods to measure pH, trace metals, cations, and anions in water samples. The Hanna microcomputer conductivity meter was used for pH measurement, while the Varian 55B atomic absorption spectrometer was used for trace metal and cation examination. Alkalinity was determined by titrating with hydrochloric acid and standardizing against Na2CO3 solution. Replicate analyses were conducted to determine analytical precision and relative errors, with results within 10% of anticipated limits. The parameters were correlated using the Spearman rank correlation approach. Evaluation Indices Analysis of the total contents of heavy metals in the soil may not always be a sufficient method of assessment (Cairo et al. 2005; Hong-gui et al. 2012 ; Kowalska et al. 2016 ; Long et al. 1995 ). Therefore, for the assessment of heavy metal enrichment and its relationship with soil properties many computational tools have been applied (Gong et al. 2008 ; Mazurek et al. 2017 ). The total content, as well as statistical mechanisms and the relationship between the content of heavy metals and soil properties, such as correlation or regression, does not provide comprehensive information on the degree of soil contamination (Kowalska et al. 2016 ; Liu et al. 2016 ). In the case of comparisons of the content of heavy metals to the limiting values given in the literature, it is possible to only approximately determine the probability of contamination and this does not provide holistic information on the state of soil quality (Cairo et al. 2005; Jiang et al. 2014 ; Nannoni and Protano 2016 ; Zhiyuan et al. 2011 ). The key to the effective assessment of soil contamination with heavy metals (Cu, Pb, Zn, Fe, Sb, As) lies in the use of pollution indices. Pollution indices are widely considered a useful tool for the comprehensive evaluation of the degree of contamination. Moreover, they can have a great importance in the assessment of soil quality and the prediction of future ecosystem sustainability, especially in the case of farmlands. Eighteen indices previously described by several authors (Igeo, PI, EF, Cf, PIsum, PINemerow, PLI, PIave, PIVector, PIN, MEC, CSI, MERMQ, Cdeg, RI, mCd and ExF) as well as the newly published Biogeochemical Index (BGI). Pollution Load Index (PLI) The index assesses the concentration or extent of heavy metals in soil, determining if they are natural processes or anthropogenic activities. It allows comparison of pollution in different soil sites, including pyrometallurgical and hydrometallurgical sites. Heavy metal pollution is visible in urban centers and farmland, but also outside these areas. The trend analysis of heavy metal content in soils traces back to industrialization and fertilizer use in the last decade, indicating a permanent increase in heavy metal accumulation. Accurate instruments are needed to detect and stop soil degradation. For the total assessment of the degree of contamination in soil, the PLI is also used. This index provides an easy way to prove the deterioration of the soil conditions as a result of the accumulation of heavy metals (Varol 2011 ). PLI is calculated as a geometric average of PI based on the following formula: \(\:PLI=\:\sqrt[n]{{PI}_{1}\times\:{PI}_{2}\times\:{PI}_{3}\times\:\dots\:{PI}_{n}}\) ……………………………………………………. \(\:\left[3.1\right]\) $$\:where\:n\:is\:the\:total\:number\:of\:analysed\:heavy\:metals\:present\:in\:the\:water\:body\:or\:area.$$ \(\:PI=\text{c}\text{a}\text{l}\text{c}\text{u}\text{l}\text{a}\text{t}\text{e}\text{d}\:\text{v}\text{a}\text{l}\text{u}\text{e}\text{s}\:\text{f}\text{o}\text{r}\:\text{t}\text{h}\text{e}\:\text{S}\text{i}\text{n}\text{g}\text{l}\text{e}\:\text{P}\text{o}\text{l}\text{l}\text{u}\text{t}\text{i}\text{o}\text{n}\:\text{I}\text{n}\text{d}\text{e}\text{x}\:\text{a}\text{s};\:\frac{{C}_{n}}{GB}\) ………………………. \(\:\left[3.2\right]\) $$\:\:where\:{C}_{n}\:is\:the\:\text{c}\text{o}\text{n}\text{t}\text{e}\text{n}\text{t}\:\text{o}\text{f}\:\text{h}\text{e}\text{a}\text{v}\text{y}\:\text{m}\text{e}\text{t}\text{a}\text{l}\:\text{i}\text{n}\:\text{s}\text{o}\text{i}\text{l}\:\text{a}\text{n}\text{d}\:\text{G}\text{B}\:\text{v}\text{a}\text{l}\text{u}\text{e}\text{s}\:\text{o}\text{f}\:\text{t}\text{h}\text{e}\:\text{g}\text{e}\text{o}\text{c}\text{h}\text{e}\text{m}\text{i}\text{c}\text{a}\text{l}\:\text{b}\text{a}\text{c}\text{k}\text{g}\text{r}\text{o}\text{u}\text{n}\text{d}.$$ The PLI (Pollution Level Index) is a tool used for environmental management and monitoring, indicating the degree of pollution in a water body or area. A 1 indicates unpolluted, while values greater than 1 indicate varying pollution levels. The higher the PLI, the greater the pollution load. However, it should be used in conjunction with other methods to gain a comprehensive understanding of an area's pollution status. Movement Cycle of Contaminants Pyrometallurgy process contaminants can move from treatment plants into air or water, unlike hydrometallurgy which can only move from treatment plants into water or stream. This is due to the high concentration of gaseous contaminants produced from the pyrometallurgical process. Contaminants can also move directly into water or streams as liquid effluents. Hydrometallurgical contamination starts from treatment plants and is discharged into streams. Other sources of contamination include mine spoils, leakages, improper tailing storage facilities, and surface runoffs from rainwater. Contaminants move between water bodies and soil sediments through precipitation and dissolution. This is illustrated in the Fig. 3 below; 3. RESULTS AND DISCUSSION Levels of Parameters in Water Samples Water samples from pyrometallurgical sites showed elevated concentrations of sulfate, copper, and arsenic, while hydrometallurgical sites had higher levels of nitrate and chloride. The pH ranged from 6.2 to 8.9, with pyrometallurgical areas showing more neutral to slightly alkaline values due to historical carbonate buffering during ore processing. Factors influencing water concentration include mine spoils, proximity to treatment plant sites, weather, and pH. Lower pH values and concentrations of As, Cu, Fe, and Zn in hydrometallurgical sites may be due to sodium hypochlorite (NaClO) to suppress aqueous solution concentration. High NO3¬- values at sampling sites may be due to CN- detoxification, while low NO3¬- concentrations at pyrometallurgical sites may be due to high mobility of the radical. Calcium carbonate during ore treatment counteracted weathering of sulfide minerals, raising pH levels to near neutral values. Figure 4 Comparative mean levels of parameters in the water samples from both pyrometallurgical and hydrometallurgical sites Levels of Parameters in Sediment Samples Sediment analysis revealed a reverse trend: hydrometallurgical sites had markedly higher arsenic (10,849.83 mg/kg), copper (200.83 mg/kg), and iron (46,026.17 mg/kg) concentrations. These results in Fig. 5 suggest that while pyrometallurgical processes contributed to immediate water pollution, hydrometallurgical processes are associated with long-term accumulation of metals in sediment. PLI values further confirmed that sediment contamination was more significant at hydrometallurgical sites. The sediments at the pyrometallurgical and hydrometallurgical sites have a higher mean pH value of 7.28, attributed to the presence of carbonates in the soils. This may have resulted in the adsorption of metals through metal complex formation and sulphide precipitation. The hydrometallurgical site is currently under active metallurgical processes, leading to higher concentrations of parameters like SO 4 2− , K + , As, Cu, Pb, Fe, and Zn. Low NO 3 − concentrations may be due to high mobility of radicals, while low Cl − concentrations may be due to low usage. Correlation and Environmental Behavior The correlation matrix provided in Tables I and II illustrates the associations of specific parameters in the water samples for both sites. According to Osae et al. ( 1995 ), As, Cu, and Fe are components of primary ores, whereas NO 3 − , Cl − , and SO 4 2− are frequently produced during metallurgical processes related to ore beneficiation (Marsden and House, 2006 ). These assumptions guided the selection of the correlation matrix's parameters. pH was also chosen because it regulates the adsorption or desorption of trace metals in the environment (Amonoo-Neizer et al. 1995 ; Smedley et al. 1996 ; Smedley and Kinniburgh 2001 ). Metals like arsenic and copper showed strong positive correlations with pH and anions, highlighting complex geochemical interactions. The positive correlation between trace metals in a mineral is likely due to their primary ore sources and their preservation in tailing materials at pyrometallurgical sites. This allows them to be mobilized into nearby water. The correlation between trace metals and Cl- and NO3- at hydrometallurgical sites is also due to their metallurgical source. At hydrometallurgical sites, except for Fe, all parameters correlated positively due to continuous metallurgical activities. The correlation of Fe may be due to its high percentage at crystal levels and primary ore. Table I Correlation coefficient matrix of selected parameters in water from the pyrometallurgical site pH As Cu Fe Zn Pb NO 3 − SO 4 2− Cl − pH 0.8 0.89 0.77 0.01 ND 0.35 0.45 0.94 NO 3 − 0.35 -0.12 -0.02 0.03 0.45 ND 0.53 0.21 SO 4 2− 0.45 -0.04 -0.33 -0.21 0.24 ND 0.53 0.29 Cl − 0.94 0.82 0.85 0.81 0.08 ND 0.21 0.29 Table II Correlation coefficient matrix of selected parameters in water from the hydrometallurgical site As Cu Fe Zn Pb pH NO 3 − Cl − SO 4 2− pH 0.69 0.60 -0.44 0.99 0.20 0.70 0.37 0.90 NO3- 1.00 0.60 0.04 0.97 0.20 0.70 0.87 0.49 Cl- 0.88 0.90 0.34 0.98 0.90 0.37 0.87 0.32 SO42- 0.49 0.12 0.04 0.97 0.69 0.90 0.49 0.32 Pollution Load Index The PLI provides information on metal contamination levels in each sample location. The CF computation showed higher pollution in sediments at the hydrometallurgical site due to high concentrations of As, Cu, Fe, Zn, and Pb as shown in the Fig. 6 below. Water bodies at the pyro site had higher pollution levels, except for naturally abundant Fe, which was higher at the hydro site. The CF computation also revealed higher levels of trace metal pollution in water bodies as shown in the Fig. 7 below. From various computations and comparisons, there is the need to compare the intensities or degree of these pollutions or contaminations within the sediments (soils) and waterbodies. Figure 8 below shows the degree of the various metallurgical processes in their various pollution environment. It can be observed that the degree of pyrometallurgical contamination is lower than hydrometallurgical contamination within the soil sediments. This can be explained with the contamination pathways of the various metallurgical processes to get into the sediments which illustrates that the assertion that ‘the longer the pathway of the metals, the lesser their degree of contamination. Again, the contamination degree of the pyrometallurgical process is higher in the waterbodies than the hydrometallurgical process. 4. CONCLUSION In the Obuasi gold mining region, pyrometallurgical and hydrometallurgical operations are linked to significant levels of inorganic parameter contamination in stream and sediments. The concentration of trace metals such as As, Fe, and Cu in streams is more significant than in the sediments. The study found that pyrometallurgical sites have higher levels of parameters in water samples, while hydrometallurgical sites have higher levels in sediments. The study suggests that pyrometallurgical pre-treatment of gold ores needs to be remedied to prevent mining waste from deteriorating and entering the water environment. Recommendations include strengthening environmental policies, regular monitoring of mining activities, remediation application, and capping tailing dams to prevent runoff during rainfall and escaping to the atmosphere. Declarations Competing Interest The authors have no relevant financial or non-financial interests to disclose. Ethical Approval Permission to access sampling sites and conduct this study was granted by AngloGold Ashanti/Obuasi Gold Mine Management prior to the commencement of fieldwork. The study did not involve human or animal subjects and therefore did not require institutional ethical clearance. Consent to Participate Not applicable. This study did not involve any human participants requiring informed consent. Consent to Publish The authors obtained approval from AngloGold Ashanti/Obuasi Gold Mine Management to use the data obtained through sampling and laboratory analysis. All authors have reviewed and consented to the publication of this manuscript. Funding The authors declare that no funds, grants, or other support were received during the preparation of this manuscript. Author Contribution All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Williams Donkor, Herbert Adjei, and Kingsley Mbayenya Nanim. The first draft of the manuscript was written by Williams Donkor and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. ACKNOWLEDGEMENTS The authors acknowledge the Almighty God for strength and guidance throughout the duration of this work. Special thanks to Prof. Gordon Foli for his unwavering support and mentorship, and to Derrick Owusu for his technical contributions. The authors also express gratitude to their families, friends, and all individuals who contributed in diverse ways toward the successful completion of this study. Data Availability Part of the data used in this study has been provided in the body of the text whiles others are confidential and cannot be made public. References Amonoo-Neizer, E. H., Nyamah, D. & Bakiamoh, S. B. Mercury and arsenic pollution in soil and biological samples around the mining town of Obuasi. Ghana. Water Air & Soil. Pollution . 91 (3–4), 363–373. https://doi.org/10.1007/BF00666270 (1995). Caeiro, S. et al. Assessing heavy metal contamination in Sado Estuary sediment: An index analysis approach. Ecol. Ind. 5 (2), 151–169. https://doi.org/10.1016/j.ecolind.2005.02.001 (2005). Foli, G. & Nude, P. M. Concentration levels of some inorganic contaminants in streams and sediments in areas of pyrometallurgical and hydrometallurgical activities at the Obuasi gold mine, Ghana. Environ. Earth Sci. 65 (3), 753–763. https://doi.org/10.1007/s12665-011-1121-0 (2012). Gong, Q., Deng, J., Xiang, Y., Wang, Q. & Yang, L. Calculating pollution indices by heavy metals in ecological geochemistry assessment and a case study in parks of Beijing. J. China Univ. Geosci. 19 (3), 230–241. https://doi.org/10.1016/S1002-0705(08)60042-4 (2008). Hong-gui, D., Teng-feng, G., Ming-hui, L. & Xu, D. Comprehensive assessment model on heavy metal pollution in soil. Int. J. Electrochem. Sci. 7 (6), 5286–5296 (2012). Jiang, X., Lu, W. X., Zhao, H. Q., Yang, Q. C. & Yang, Z. P. Potential ecological risk assessment and prediction of soil heavy-metal pollution around coal gangue dump. Nat. Hazards Earth Syst. Sci. 14 (6), 1599–1610. https://doi.org/10.5194/nhess-14-1599-2014 (2014). Kesse, G. O. Rock and mineral resources of Ghana. Balkema. (1985). Kowalska, J. et al. Soil pollution indices conditioned by medieval metallurgical activity: A case study from Krakow (Poland). Environ. Pollut. 218 , 1023–1036. https://doi.org/10.1016/j.envpol.2016.08.053 (2016). Leube, A., Hirdes, W., Mauer, R. & Kesse, G. O. The Early Proterozoic Birimian Supergroup of Ghana and some aspects of its associated gold mineralisation. Precambrian Res. 46 (1–2), 139–165. https://doi.org/10.1016/0301-9268(90)90070-7 (1990). Liu, R., Wang, M., Chen, W. & Peng, C. Spatial pattern of heavy metals accumulation risk in urban soils of Beijing and its influencing factors. Environ. Pollut. 210 , 174–181. https://doi.org/10.1016/j.envpol.2015.11.044 (2016). Long, E. R., MacDonald, D. D., Smith, S. L. & Calder, F. D. Incidence of adverse biological effects within ranges of chemical concentrations in marine and estuarine sediments. Environ. Manage. 19 (1), 81–97. https://doi.org/10.1007/BF02472006 (1995). Marsden, J. & House, I. The chemistry of gold extraction (2nd ed.). Society for Mining, Metallurgy, and Exploration. (2006). Mazurek, R. et al. Assessment of heavy metals contamination in surface layers of Roztocze National Park forest soils (SE Poland) by indices of pollution. Chemosphere 168 , 839–850. https://doi.org/10.1016/j.chemosphere.2016.10.117 (2017). Nannoni, F. & Protano, G. Chemical and biological methods to evaluate the availability of heavy metals in soils of the Siena urban area (Italy). Sci. Total Environ. 568 , 1–10. https://doi.org/10.1016/j.scitotenv.2016.05.177 (2016). Osae, S., Kase, K. & Yamamoto, M. A geochemical study of the Ashanti gold deposit at Obuasi, Ghana. Earth Sci. Rep. Okayama Univ. 2 (1), 81–90 (1995). Smedley, P. L., Edmunds, W. M. & Pelig-Ba, K. B. Mobility of arsenic in groundwater in the Obuasi area of Ghana. In J. D. Appleton, R. Fuge, & G. J. H. McCall (Eds.), Environmental geochemistry and health (pp. 163–181). Geological Society. (1996). https://doi.org/10.1144/GSL.SP.1996.113.01.15 Smedley, P. L. & Kinniburgh, D. G. A review of the source, behaviour and distribution of arsenic in natural waters. Appl. Geochem. 17 (5), 517–568. https://doi.org/10.1016/S0883-2927(02)00018-5 (2001). Varol, M. Assessment of heavy metal contamination in sediments of the Tigris River (Turkey) using pollution indices and multivariate statistical techniques. J. Hazard. Mater. 195 , 355–364. https://doi.org/10.1016/j.jhazmat.2011.08.051 (2011). Zhiyuan, W., Dengfeng, W., Huiping, Z. & Zhiping, Q. Assessment of soil heavy metal pollution with principal component analysis and geoaccumulation index. Procedia Environ. Sci. 10 , 1946–1952. https://doi.org/10.1016/j.proenv.2011.09.305 (2011). Additional Declarations No competing interests reported. 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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-7321357","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":507113660,"identity":"94fc8dc7-4225-4986-b495-b194993b6f07","order_by":0,"name":"Williams Donkor","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/klEQVRIie3OsWrDMBCA4TMGdxF4jSjkGVQMhpJBryIhaJaSxYuHNhgKyuKQNYE+REKXjjYCZxFkFRQKWjJ17lzbnTIIu1sJ+ofjOPjgAHy+fxmDoACYxu3aLX2T/j5AElyEvwSNJZxUYwk5isZu80+WnE5VsHtXlEJYfyB4XjiJPs/v9jpbpEZAcNCKlxCJGYJj5iKpeUyxlSxLTfuYlYohQOktgoYXA4S/bVRPKIL4e5gcWrKH7jGpghJQ1JInJ6H6/IC3miUTI0i9k3Neqii5fyWVk+CVaHCZs2m8qa1dyxm9Wb1Y85UvneSiqp9hN4gaAy5b/p34fD7ftfYDQ3Za3ybfC90AAAAASUVORK5CYII=","orcid":"","institution":"Kwame Nkrumah University of Science and Technology","correspondingAuthor":true,"prefix":"","firstName":"Williams","middleName":"","lastName":"Donkor","suffix":""},{"id":507113662,"identity":"c91a8e57-d86f-4a60-a77a-0d0b3e912f11","order_by":1,"name":"Herbert Adjei","email":"","orcid":"","institution":"Kwame Nkrumah University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Herbert","middleName":"","lastName":"Adjei","suffix":""},{"id":507113665,"identity":"3aac8201-ed1b-4098-a83c-0a163dc8e1d1","order_by":2,"name":"Kingsley Mbayenya Nanim","email":"","orcid":"","institution":"Kwame Nkrumah University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Kingsley","middleName":"Mbayenya","lastName":"Nanim","suffix":""}],"badges":[],"createdAt":"2025-08-07 18:38:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7321357/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7321357/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":90203418,"identity":"dff24353-a6ac-4390-bbef-afbe50ac93af","added_by":"auto","created_at":"2025-08-29 20:03:47","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":63181,"visible":true,"origin":"","legend":"\u003cp\u003eGeology of study area (modified after Kesse, 1985)\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7321357/v1/9cc3f2b94a2efe1c26aceac4.jpg"},{"id":90203419,"identity":"5f7170db-f0f6-4c64-b9b0-8ae35288133f","added_by":"auto","created_at":"2025-08-29 20:03:47","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":121545,"visible":true,"origin":"","legend":"\u003cp\u003eParts of the Obuasi area showing ore treatment plants, drainage and sampling locations (Foli and Nude 2012)\u003c/p\u003e","description":"","filename":"Picture2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7321357/v1/4e347138f4936d9d9f61d9e2.jpg"},{"id":90203992,"identity":"dcde75df-1c29-4328-98ad-0006955a3085","added_by":"auto","created_at":"2025-08-29 20:11:48","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":35613,"visible":true,"origin":"","legend":"\u003cp\u003eMovement cycle of contaminants\u003c/p\u003e","description":"","filename":"Picture3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7321357/v1/a8ad7e412673ec23801aaedd.jpg"},{"id":90204361,"identity":"46895936-de5e-4d24-a1e3-7c368ba9258b","added_by":"auto","created_at":"2025-08-29 20:27:48","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":128311,"visible":true,"origin":"","legend":"\u003cp\u003eComparative mean levels of parameters in the water samples from both pyrometallurgical and hydrometallurgical sites\u003c/p\u003e","description":"","filename":"Picture4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7321357/v1/39c30b83c493661b17b5499b.jpg"},{"id":90203422,"identity":"80a91359-7738-407c-ba88-e038e97ea332","added_by":"auto","created_at":"2025-08-29 20:03:48","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":171288,"visible":true,"origin":"","legend":"\u003cp\u003eComparative mean levels of parameters in the sediment samples from both pyrometallurgical and hydrometallurgical sites\u003c/p\u003e","description":"","filename":"Picture5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7321357/v1/aa4f68fed7aee2dc98426c8b.jpg"},{"id":90203429,"identity":"7823f548-baf1-4e4c-a6a8-ffec092df72d","added_by":"auto","created_at":"2025-08-29 20:03:48","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":97752,"visible":true,"origin":"","legend":"\u003cp\u003ePollution index/ Contamination values evaluated from mean trace metal concentrations in stream sediments\u003c/p\u003e","description":"","filename":"Picture6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7321357/v1/cf2e5b823f806a0f3e5e7afc.jpg"},{"id":90203430,"identity":"65615f12-f8b1-4a45-8127-5a1a7f5d4d35","added_by":"auto","created_at":"2025-08-29 20:03:48","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":138630,"visible":true,"origin":"","legend":"\u003cp\u003ePollution index/ Contamination values evaluated from mean trace metal concentrations in water\u003c/p\u003e","description":"","filename":"Picture7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7321357/v1/d08b2991a644d303c239874d.jpg"},{"id":90203997,"identity":"c8b885e6-435c-47a8-9ded-ce88ab81c7cf","added_by":"auto","created_at":"2025-08-29 20:11:48","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":129921,"visible":true,"origin":"","legend":"\u003cp\u003ePollution load index of trace metal concentrations both in sediments and water at the extraction sites\u003c/p\u003e","description":"","filename":"Picture8.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7321357/v1/1b2205cc80dd2b94c6ad6ecd.jpg"},{"id":90204540,"identity":"9933001d-a39d-4818-9308-315c04acbb23","added_by":"auto","created_at":"2025-08-29 20:35:49","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1532213,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7321357/v1/a1fcf441-d555-4164-b1fd-abd809fc5220.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eComparison of Inorganic Contamination of Pyrometallurgy and Hydrometallurgy Sites at Obuasi\u003c/p\u003e","fulltext":[{"header":"1. INTRODUCTION","content":"\u003cp\u003eGold mining has historically been one of the major economic drivers of Ghana, and the Obuasi Gold Mine, located along the Ashanti volcanic belt, has played a pivotal role since the late 19th century. The mine has seen shifts in processing technologies, transitioning from pyrometallurgical operations that utilized roasting and smelting to the more recent adoption of hydrometallurgical techniques involving chemical leaching and precipitation. These changes were partly due to environmental and economic concerns associated with the former method (Marsden and House, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2006\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe release of trace metals and contaminants from mining operations has raised environmental concerns, especially for surface water and sediment quality. This study aims to evaluate and compare inorganic contamination levels associated with each technique, aiming to inform sustainable mining and remediation strategies.Recent studies on hydrometallurgy and pyrometallurgy, has revealed that each of these processes comes with its own negative effects in the sense that they emit or produce contaminants and other health hazards which contribute to health effects on the residents of the Obuasi community. Also, these contaminants are not so environmentally friendly because pyrometallurgy releases greenhouse gases such as carbon dioxide, arsenious oxide, hydrogen sulfide and hydrogen gas associated with the high-temperature processes in large amounts which tend to deplete the ozone layer and reduce the oxygen content of the atmosphere. Aside the health effects of hydrometallurgy, another one is the depletion of the soil\u0026rsquo;s ability to sustain plant and animal lives due to the leaching of waste materials from the deposition sites of hydrometallurgy and pyrometallurgy waste such as tailing dams, holding ponds, stockpiles. The change over from pyrometallurgy to hydrometallurgy is actually intended to improve environmental quality, however, the pollution legacies over the years suggest that the pollutants from these sources may linger in the environment. Key questions to answer are; To what extent do these pollutions exist in the current environment? To what extent do the two metallurgic forms compare with each other in the environment?\u003c/p\u003e\u003cp\u003eThis study aims to understand the environmental impact of metallurgical processes at the Obuasi Mine, identify potential contamination sources, and assess mitigation measures. Understanding contaminants' variations will help propose effective remediation strategies. The research could have broader implications for the mining industry, promoting responsible practices and protecting natural resources and biodiversity. The project compares inorganic contaminations from pyrometallurgy and hydrometallurgy, using laboratory tests to compare heavy metal concentrations in streams and sediments. The Pollution Load Index (PLI) will be used to assess the environmental impact.\u003c/p\u003e"},{"header":"2. MATERIALS AND METHODS","content":"\u003cp\u003e\u003cb\u003eStudy Area\u003c/b\u003e\u003c/p\u003e\u003cp\u003eObuasi is located between latitude 5.35N and 5.65N and longitude 6.35N and 6.90N, and in the southern part of the Ashanti Region, Ghana. The study area is located in Obuasi, in the Ashanti Region of Ghana as seen in the Fig.\u0026nbsp;1.1 below. The region experiences a semi-equatorial climate with a twofold maximum rainfall regime. The municipality covers 162.4 km and has a degraded, semi-deciduous forest with tall trees and multiple layers of flora. The mean annual temperature is 25\u0026deg;C.\u003c/p\u003e\u003cp\u003eSampling sites were chosen from streams influenced by both historical pyrometallurgical operations (notably the Pompora Treatment Plant) and current hydrometallurgical operations (Sansu Treatment Plant). Obuasi, located in Ghana's Ashanti Region, has a\u003c/p\u003e\u003cp\u003eThe Obuasi mine is predominantly underlained by Paleo-Proterozoic Birimian and Tarkwaian rocks. The Birimian in Ghana has two litho-stratigraphic systems: metavolcanic and metasedimentary groups and a younger arenaceous and clastic Tarkwaian group. Low-grade tholeiitic basalts with intercalated pyroclastic rocks, minor andesitic and felsic flows, and chemical sediments dominate the metavolcanic group (Kesse, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e1985\u003c/span\u003e). Low-grade metamorphosed volcaniclastics, wackes, and argillites are part of the metasedimentary rocks and partly contemporaneous with the volcanic group The Tarkwaian group includes polymictic and quartz pebble conglomerates, sandstones, minor argillites, siltstones, and tuffs (Kesse, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e1985\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe Birimian rocks are intruded by hornblende-rich granitoids known as the belt type that are closely associated with the volcanic rocks and; and mica\u0026ndash;rich granitoids referred to as basin type which tend to border the volcanic belt and are in the metasediment units, (Leube et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e1990\u003c/span\u003e; Taylor et al. 1992; Hirdes et al. 1992). Gold in the Ashanti belt occurs as quartz reefs in metasediments or vein/lode deposits along the metasediment-metavolcanic contact (Kesse \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e1985\u003c/span\u003e). The metavolcanic and metasedimentary groups are separated by a broad shear zone, which at times contain visible calcite minerals associated with quartz bodies (Kesse \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e1985\u003c/span\u003e; Leube et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e1990\u003c/span\u003e). Arsenopyrite and pyrite dominate primary gold ores, with minor quartz and graphitic schist regions (Osae et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1995\u003c/span\u003e). Sometimes metavolcanic and metasedimentary rocks have ankerite. The Obuasi geological map is illustrated in Fig.\u0026nbsp;1.1.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eSampling and Analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe data used for this work was a secondary one which was obtained by sampling carefully at selected areas at or near the pyrometallurgical and hydrometallurgical sites. Water and sediment samples were collected from 14 selected points near the treatment facilities. Figure\u0026nbsp;3.1 shows a rough map of the Obuasi region that depicts the pyrometallurgical (Pompora Treatment Plant or P.T.P.) and hydrometallurgical plant (Sulphide Treatment Plant or S.T.P.) sites and the areas where the water and stream sediment samples were collected.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eWater Sampling\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWater samples were collected from fourteen curated settings in the stream drainage basin, including towns surrounding operational hydrometallurgical sites (P15, P17, P18, P19, P20 and P21) and tailings dam facilities as well as defunct pyrometallurgical sites (P1, P3, P4, P5, P6, P7, P9 and P10). The samples were processed by the Environmental Laboratory of the Anglo-Gold Ashanti mine in Obuasi, Ghana, and acidified with concentrated HNO\u003csub\u003e3\u003c/sub\u003e to prevent metal precipitation.\u003c/p\u003e\u003cp\u003eWater samples were collected in 500 mL bottles, filtered, acidified, and analyzed for physicochemical parameters using atomic absorption spectrometry (AAS) and ion chromatography. Sediment samples were oven-dried, sieved, and digested in aqua regia before elemental analysis. Quality control was ensured through replicate analyses and standard additions.\u003c/p\u003e\u003cp\u003e\u003cb\u003eAnalysis of samples\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe study used various methods to measure pH, trace metals, cations, and anions in water samples. The Hanna microcomputer conductivity meter was used for pH measurement, while the Varian 55B atomic absorption spectrometer was used for trace metal and cation examination. Alkalinity was determined by titrating with hydrochloric acid and standardizing against Na2CO3 solution. Replicate analyses were conducted to determine analytical precision and relative errors, with results within 10% of anticipated limits. The parameters were correlated using the Spearman rank correlation approach.\u003c/p\u003e\u003cp\u003e\u003cb\u003eEvaluation Indices\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAnalysis of the total contents of heavy metals in the soil may not always be a sufficient method of assessment (Cairo et al. 2005; Hong-gui et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Kowalska et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Long et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e1995\u003c/span\u003e). Therefore, for the assessment of heavy metal enrichment and its relationship with soil properties many computational tools have been applied (Gong et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Mazurek et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The total content, as well as statistical mechanisms and the relationship between the content of heavy metals and soil properties, such as correlation or regression, does not provide comprehensive information on the degree of soil contamination (Kowalska et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Liu et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). In the case of comparisons of the content of heavy metals to the limiting values given in the literature, it is possible to only approximately determine the probability of contamination and this does not provide holistic information on the state of soil quality (Cairo et al. 2005; Jiang et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Nannoni and Protano \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Zhiyuan et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). The key to the effective assessment of soil contamination with heavy metals (Cu, Pb, Zn, Fe, Sb, As) lies in the use of pollution indices.\u003c/p\u003e\u003cp\u003ePollution indices are widely considered a useful tool for the comprehensive evaluation of the degree of contamination. Moreover, they can have a great importance in the assessment of soil quality and the prediction of future ecosystem sustainability, especially in the case of farmlands. Eighteen indices previously described by several authors (Igeo, PI, EF, Cf, PIsum, PINemerow, PLI, PIave, PIVector, PIN, MEC, CSI, MERMQ, Cdeg, RI, mCd and ExF) as well as the newly published Biogeochemical Index (BGI).\u003c/p\u003e\u003cp\u003e\u003cb\u003ePollution Load Index (PLI)\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe index assesses the concentration or extent of heavy metals in soil, determining if they are natural processes or anthropogenic activities. It allows comparison of pollution in different soil sites, including pyrometallurgical and hydrometallurgical sites. Heavy metal pollution is visible in urban centers and farmland, but also outside these areas. The trend analysis of heavy metal content in soils traces back to industrialization and fertilizer use in the last decade, indicating a permanent increase in heavy metal accumulation. Accurate instruments are needed to detect and stop soil degradation. For the total assessment of the degree of contamination in soil, the PLI is also used. This index provides an easy way to prove the deterioration of the soil conditions as a result of the accumulation of heavy metals (Varol \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). PLI is calculated as a geometric average of PI based on the following formula:\u003c/p\u003e\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:PLI=\\:\\sqrt[n]{{PI}_{1}\\times\\:{PI}_{2}\\times\\:{PI}_{3}\\times\\:\\dots\\:{PI}_{n}}\\)\u003c/span\u003e\u003c/span\u003e\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;.\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\left[3.1\\right]\\)\u003c/span\u003e\u003c/span\u003e\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:where\\:n\\:is\\:the\\:total\\:number\\:of\\:analysed\\:heavy\\:metals\\:present\\:in\\:the\\:water\\:body\\:or\\:area.$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:PI=\\text{c}\\text{a}\\text{l}\\text{c}\\text{u}\\text{l}\\text{a}\\text{t}\\text{e}\\text{d}\\:\\text{v}\\text{a}\\text{l}\\text{u}\\text{e}\\text{s}\\:\\text{f}\\text{o}\\text{r}\\:\\text{t}\\text{h}\\text{e}\\:\\text{S}\\text{i}\\text{n}\\text{g}\\text{l}\\text{e}\\:\\text{P}\\text{o}\\text{l}\\text{l}\\text{u}\\text{t}\\text{i}\\text{o}\\text{n}\\:\\text{I}\\text{n}\\text{d}\\text{e}\\text{x}\\:\\text{a}\\text{s};\\:\\frac{{C}_{n}}{GB}\\)\u003c/span\u003e\u003c/span\u003e\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;.\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\left[3.2\\right]\\)\u003c/span\u003e\u003c/span\u003e\u003cdiv id=\"Equb\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e\n$$\\:\\:where\\:{C}_{n}\\:is\\:the\\:\\text{c}\\text{o}\\text{n}\\text{t}\\text{e}\\text{n}\\text{t}\\:\\text{o}\\text{f}\\:\\text{h}\\text{e}\\text{a}\\text{v}\\text{y}\\:\\text{m}\\text{e}\\text{t}\\text{a}\\text{l}\\:\\text{i}\\text{n}\\:\\text{s}\\text{o}\\text{i}\\text{l}\\:\\text{a}\\text{n}\\text{d}\\:\\text{G}\\text{B}\\:\\text{v}\\text{a}\\text{l}\\text{u}\\text{e}\\text{s}\\:\\text{o}\\text{f}\\:\\text{t}\\text{h}\\text{e}\\:\\text{g}\\text{e}\\text{o}\\text{c}\\text{h}\\text{e}\\text{m}\\text{i}\\text{c}\\text{a}\\text{l}\\:\\text{b}\\text{a}\\text{c}\\text{k}\\text{g}\\text{r}\\text{o}\\text{u}\\text{n}\\text{d}.$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe PLI (Pollution Level Index) is a tool used for environmental management and monitoring, indicating the degree of pollution in a water body or area. A 1 indicates unpolluted, while values greater than 1 indicate varying pollution levels. The higher the PLI, the greater the pollution load. However, it should be used in conjunction with other methods to gain a comprehensive understanding of an area's pollution status.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMovement Cycle of Contaminants\u003c/b\u003e\u003c/p\u003e\u003cp\u003ePyrometallurgy process contaminants can move from treatment plants into air or water, unlike hydrometallurgy which can only move from treatment plants into water or stream. This is due to the high concentration of gaseous contaminants produced from the pyrometallurgical process. Contaminants can also move directly into water or streams as liquid effluents. Hydrometallurgical contamination starts from treatment plants and is discharged into streams. Other sources of contamination include mine spoils, leakages, improper tailing storage facilities, and surface runoffs from rainwater. Contaminants move between water bodies and soil sediments through precipitation and dissolution. This is illustrated in the Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e below;\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"3. RESULTS AND DISCUSSION","content":"\u003cp\u003e\u003cb\u003eLevels of Parameters in Water Samples\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWater samples from pyrometallurgical sites showed elevated concentrations of sulfate, copper, and arsenic, while hydrometallurgical sites had higher levels of nitrate and chloride. The pH ranged from 6.2 to 8.9, with pyrometallurgical areas showing more neutral to slightly alkaline values due to historical carbonate buffering during ore processing. Factors influencing water concentration include mine spoils, proximity to treatment plant sites, weather, and pH. Lower pH values and concentrations of As, Cu, Fe, and Zn in hydrometallurgical sites may be due to sodium hypochlorite (NaClO) to suppress aqueous solution concentration. High NO3\u0026not;- values at sampling sites may be due to CN- detoxification, while low NO3\u0026not;- concentrations at pyrometallurgical sites may be due to high mobility of the radical. Calcium carbonate during ore treatment counteracted weathering of sulfide minerals, raising pH levels to near neutral values.\u003c/p\u003e\u003cp\u003eFigure 4 Comparative mean levels of parameters in the water samples from both pyrometallurgical and hydrometallurgical sites\u003c/p\u003e\u003cp\u003e\u003cb\u003eLevels of Parameters in Sediment Samples\u003c/b\u003e\u003c/p\u003e\u003cp\u003eSediment analysis revealed a reverse trend: hydrometallurgical sites had markedly higher arsenic (10,849.83 mg/kg), copper (200.83 mg/kg), and iron (46,026.17 mg/kg) concentrations. These results in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003e suggest that while pyrometallurgical processes contributed to immediate water pollution, hydrometallurgical processes are associated with long-term accumulation of metals in sediment. PLI values further confirmed that sediment contamination was more significant at hydrometallurgical sites. The sediments at the pyrometallurgical and hydrometallurgical sites have a higher mean pH value of 7.28, attributed to the presence of carbonates in the soils. This may have resulted in the adsorption of metals through metal complex formation and sulphide precipitation. The hydrometallurgical site is currently under active metallurgical processes, leading to higher concentrations of parameters like SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e, K\u003csup\u003e+\u003c/sup\u003e, As, Cu, Pb, Fe, and Zn. Low NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e concentrations may be due to high mobility of radicals, while low Cl\u003csup\u003e\u0026minus;\u003c/sup\u003e concentrations may be due to low usage.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eCorrelation and Environmental Behavior\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe correlation matrix provided in Tables I and II illustrates the associations of specific parameters in the water samples for both sites. According to Osae et al. (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1995\u003c/span\u003e), As, Cu, and Fe are components of primary ores, whereas NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e, Cl\u003csup\u003e\u0026minus;\u003c/sup\u003e, and SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e are frequently produced during metallurgical processes related to ore beneficiation (Marsden and House, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). These assumptions guided the selection of the correlation matrix's parameters. pH was also chosen because it regulates the adsorption or desorption of trace metals in the environment (Amonoo-Neizer et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1995\u003c/span\u003e; Smedley et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e1996\u003c/span\u003e; Smedley and Kinniburgh \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). Metals like arsenic and copper showed strong positive correlations with pH and anions, highlighting complex geochemical interactions. The positive correlation between trace metals in a mineral is likely due to their primary ore sources and their preservation in tailing materials at pyrometallurgical sites. This allows them to be mobilized into nearby water. The correlation between trace metals and Cl- and NO3- at hydrometallurgical sites is also due to their metallurgical source. At hydrometallurgical sites, except for Fe, all parameters correlated positively due to continuous metallurgical activities. The correlation of Fe may be due to its high percentage at crystal levels and primary ore.\u003c/p\u003e\u003cp\u003eTable I Correlation coefficient matrix of selected parameters in water from the pyrometallurgical site\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e\u003ccolgroup cols=\"10\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003epH\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAs\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCu\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eFe\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eZn\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003ePb\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eNO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eSO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003eCl\u003csup\u003e\u0026minus;\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003epH\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.77\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eND\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.94\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eND\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.21\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-0.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-0.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eND\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.29\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCl\u003csup\u003e\u0026minus;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eND\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTable II Correlation coefficient matrix of selected parameters in water from the hydrometallurgical site\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabb\" border=\"1\"\u003e\u003ccolgroup cols=\"10\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAs\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCu\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFe\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eZn\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePb\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003epH\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eNO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eCl\u003csup\u003e\u0026minus;\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003eSO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003epH\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.90\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNO3-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.49\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCl-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.32\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSO42-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"10\"\u003e\u003cb\u003ePollution Load Index\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003cp\u003eThe PLI provides information on metal contamination levels in each sample location. The CF computation showed higher pollution in sediments at the hydrometallurgical site due to high concentrations of As, Cu, Fe, Zn, and Pb as shown in the Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e6\u003c/span\u003e below. Water bodies at the pyro site had higher pollution levels, except for naturally abundant Fe, which was higher at the hydro site. The CF computation also revealed higher levels of trace metal pollution in water bodies as shown in the Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e7\u003c/span\u003e below.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFrom various computations and comparisons, there is the need to compare the intensities or degree of these pollutions or contaminations within the sediments (soils) and waterbodies. Figure\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e8\u003c/span\u003e below shows the degree of the various metallurgical processes in their various pollution environment. It can be observed that the degree of pyrometallurgical contamination is lower than hydrometallurgical contamination within the soil sediments. This can be explained with the contamination pathways of the various metallurgical processes to get into the sediments which illustrates that the assertion that \u0026lsquo;the longer the pathway of the metals, the lesser their degree of contamination. Again, the contamination degree of the pyrometallurgical process is higher in the waterbodies than the hydrometallurgical process.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"4. CONCLUSION","content":"\u003cp\u003eIn the Obuasi gold mining region, pyrometallurgical and hydrometallurgical operations are linked to significant levels of inorganic parameter contamination in stream and sediments. The concentration of trace metals such as As, Fe, and Cu in streams is more significant than in the sediments. The study found that pyrometallurgical sites have higher levels of parameters in water samples, while hydrometallurgical sites have higher levels in sediments. The study suggests that pyrometallurgical pre-treatment of gold ores needs to be remedied to prevent mining waste from deteriorating and entering the water environment. Recommendations include strengthening environmental policies, regular monitoring of mining activities, remediation application, and capping tailing dams to prevent runoff during rainfall and escaping to the atmosphere.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eCompeting Interest\u003c/h2\u003e\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eEthical Approval\u003c/h2\u003e\u003cp\u003ePermission to access sampling sites and conduct this study was granted by AngloGold Ashanti/Obuasi Gold Mine Management prior to the commencement of fieldwork. The study did not involve human or animal subjects and therefore did not require institutional ethical clearance.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConsent to Participate\u003c/strong\u003e\u003cp\u003eNot applicable. This study did not involve any human participants requiring informed consent.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConsent to Publish\u003c/strong\u003e\u003cp\u003eThe authors obtained approval from AngloGold Ashanti/Obuasi Gold Mine Management to use the data obtained through sampling and laboratory analysis. All authors have reviewed and consented to the publication of this manuscript.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eThe authors declare that no funds, grants, or other support were received during the preparation of this manuscript.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAll authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Williams Donkor, Herbert Adjei, and Kingsley Mbayenya Nanim. The first draft of the manuscript was written by Williams Donkor and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eACKNOWLEDGEMENTS\u003c/h2\u003e\u003cp\u003eThe authors acknowledge the Almighty God for strength and guidance throughout the duration of this work. Special thanks to Prof. Gordon Foli for his unwavering support and mentorship, and to Derrick Owusu for his technical contributions. The authors also express gratitude to their families, friends, and all individuals who contributed in diverse ways toward the successful completion of this study.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003ePart of the data used in this study has been provided in the body of the text whiles others are confidential and cannot be made public.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAmonoo-Neizer, E. H., Nyamah, D. \u0026amp; Bakiamoh, S. B. Mercury and arsenic pollution in soil and biological samples around the mining town of Obuasi. \u003cem\u003eGhana. Water Air \u0026amp; Soil. Pollution\u003c/em\u003e. \u003cb\u003e91\u003c/b\u003e (3\u0026ndash;4), 363\u0026ndash;373. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/BF00666270\u003c/span\u003e\u003cspan address=\"10.1007/BF00666270\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (1995).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCaeiro, S. et al. Assessing heavy metal contamination in Sado Estuary sediment: An index analysis approach. \u003cem\u003eEcol. Ind.\u003c/em\u003e \u003cb\u003e5\u003c/b\u003e (2), 151\u0026ndash;169. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.ecolind.2005.02.001\u003c/span\u003e\u003cspan address=\"10.1016/j.ecolind.2005.02.001\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2005).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFoli, G. \u0026amp; Nude, P. M. Concentration levels of some inorganic contaminants in streams and sediments in areas of pyrometallurgical and hydrometallurgical activities at the Obuasi gold mine, Ghana. \u003cem\u003eEnviron. Earth Sci.\u003c/em\u003e \u003cb\u003e65\u003c/b\u003e (3), 753\u0026ndash;763. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s12665-011-1121-0\u003c/span\u003e\u003cspan address=\"10.1007/s12665-011-1121-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2012).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGong, Q., Deng, J., Xiang, Y., Wang, Q. \u0026amp; Yang, L. Calculating pollution indices by heavy metals in ecological geochemistry assessment and a case study in parks of Beijing. \u003cem\u003eJ. China Univ. Geosci.\u003c/em\u003e \u003cb\u003e19\u003c/b\u003e (3), 230\u0026ndash;241. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/S1002-0705(08)60042-4\u003c/span\u003e\u003cspan address=\"10.1016/S1002-0705(08)60042-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2008).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHong-gui, D., Teng-feng, G., Ming-hui, L. \u0026amp; Xu, D. Comprehensive assessment model on heavy metal pollution in soil. \u003cem\u003eInt. J. Electrochem. Sci.\u003c/em\u003e \u003cb\u003e7\u003c/b\u003e (6), 5286\u0026ndash;5296 (2012).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJiang, X., Lu, W. X., Zhao, H. Q., Yang, Q. C. \u0026amp; Yang, Z. P. Potential ecological risk assessment and prediction of soil heavy-metal pollution around coal gangue dump. \u003cem\u003eNat. Hazards Earth Syst. Sci.\u003c/em\u003e \u003cb\u003e14\u003c/b\u003e (6), 1599\u0026ndash;1610. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.5194/nhess-14-1599-2014\u003c/span\u003e\u003cspan address=\"10.5194/nhess-14-1599-2014\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2014).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKesse, G. O. Rock and mineral resources of Ghana. Balkema. (1985).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKowalska, J. et al. Soil pollution indices conditioned by medieval metallurgical activity: A case study from Krakow (Poland). \u003cem\u003eEnviron. Pollut.\u003c/em\u003e \u003cb\u003e218\u003c/b\u003e, 1023\u0026ndash;1036. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.envpol.2016.08.053\u003c/span\u003e\u003cspan address=\"10.1016/j.envpol.2016.08.053\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2016).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLeube, A., Hirdes, W., Mauer, R. \u0026amp; Kesse, G. O. The Early Proterozoic Birimian Supergroup of Ghana and some aspects of its associated gold mineralisation. \u003cem\u003ePrecambrian Res.\u003c/em\u003e \u003cb\u003e46\u003c/b\u003e (1\u0026ndash;2), 139\u0026ndash;165. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/0301-9268(90)90070-7\u003c/span\u003e\u003cspan address=\"10.1016/0301-9268(90)90070-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (1990).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLiu, R., Wang, M., Chen, W. \u0026amp; Peng, C. Spatial pattern of heavy metals accumulation risk in urban soils of Beijing and its influencing factors. \u003cem\u003eEnviron. Pollut.\u003c/em\u003e \u003cb\u003e210\u003c/b\u003e, 174\u0026ndash;181. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.envpol.2015.11.044\u003c/span\u003e\u003cspan address=\"10.1016/j.envpol.2015.11.044\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2016).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLong, E. R., MacDonald, D. D., Smith, S. L. \u0026amp; Calder, F. D. Incidence of adverse biological effects within ranges of chemical concentrations in marine and estuarine sediments. \u003cem\u003eEnviron. Manage.\u003c/em\u003e \u003cb\u003e19\u003c/b\u003e (1), 81\u0026ndash;97. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/BF02472006\u003c/span\u003e\u003cspan address=\"10.1007/BF02472006\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (1995).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMarsden, J. \u0026amp; House, I. The chemistry of gold extraction (2nd ed.). \u003cem\u003eSociety for Mining, Metallurgy, and Exploration.\u003c/em\u003e (2006).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMazurek, R. et al. Assessment of heavy metals contamination in surface layers of Roztocze National Park forest soils (SE Poland) by indices of pollution. \u003cem\u003eChemosphere\u003c/em\u003e \u003cb\u003e168\u003c/b\u003e, 839\u0026ndash;850. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.chemosphere.2016.10.117\u003c/span\u003e\u003cspan address=\"10.1016/j.chemosphere.2016.10.117\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2017).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNannoni, F. \u0026amp; Protano, G. Chemical and biological methods to evaluate the availability of heavy metals in soils of the Siena urban area (Italy). \u003cem\u003eSci. Total Environ.\u003c/em\u003e \u003cb\u003e568\u003c/b\u003e, 1\u0026ndash;10. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.scitotenv.2016.05.177\u003c/span\u003e\u003cspan address=\"10.1016/j.scitotenv.2016.05.177\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2016).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOsae, S., Kase, K. \u0026amp; Yamamoto, M. A geochemical study of the Ashanti gold deposit at Obuasi, Ghana. \u003cem\u003eEarth Sci. Rep. Okayama Univ.\u003c/em\u003e \u003cb\u003e2\u003c/b\u003e (1), 81\u0026ndash;90 (1995).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSmedley, P. L., Edmunds, W. M. \u0026amp; Pelig-Ba, K. B. Mobility of arsenic in groundwater in the Obuasi area of Ghana. In J. D. Appleton, R. Fuge, \u0026amp; G. J. H. McCall (Eds.), \u003cem\u003eEnvironmental geochemistry and health\u003c/em\u003e (pp. 163\u0026ndash;181). Geological Society. (1996). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1144/GSL.SP.1996.113.01.15\u003c/span\u003e\u003cspan address=\"10.1144/GSL.SP.1996.113.01.15\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSmedley, P. L. \u0026amp; Kinniburgh, D. G. A review of the source, behaviour and distribution of arsenic in natural waters. \u003cem\u003eAppl. Geochem.\u003c/em\u003e \u003cb\u003e17\u003c/b\u003e (5), 517\u0026ndash;568. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/S0883-2927(02)00018-5\u003c/span\u003e\u003cspan address=\"10.1016/S0883-2927(02)00018-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2001).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVarol, M. Assessment of heavy metal contamination in sediments of the Tigris River (Turkey) using pollution indices and multivariate statistical techniques. \u003cem\u003eJ. Hazard. Mater.\u003c/em\u003e \u003cb\u003e195\u003c/b\u003e, 355\u0026ndash;364. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jhazmat.2011.08.051\u003c/span\u003e\u003cspan address=\"10.1016/j.jhazmat.2011.08.051\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2011).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhiyuan, W., Dengfeng, W., Huiping, Z. \u0026amp; Zhiping, Q. Assessment of soil heavy metal pollution with principal component analysis and geoaccumulation index. \u003cem\u003eProcedia Environ. Sci.\u003c/em\u003e \u003cb\u003e10\u003c/b\u003e, 1946\u0026ndash;1952. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.proenv.2011.09.305\u003c/span\u003e\u003cspan address=\"10.1016/j.proenv.2011.09.305\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2011).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Pyrometallurgy, Hydrometallurgy, Inorganic Contaminants, Sediment Contamination, Pollution Load Index, Environmental Pollution","lastPublishedDoi":"10.21203/rs.3.rs-7321357/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7321357/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study investigates inorganic pollutant concentrations in streams and sediments affected by pyrometallurgical and hydrometallurgical gold ore processing at the Obuasi mine, Ghana. Water and sediment samples were analyzed for pH, major anions (NO₃⁻, Cl⁻, SO₄\u0026sup2;⁻), cations (Na⁺, K⁺, Ca\u0026sup2;⁺, Mg\u0026sup2;⁺), and trace metals (As, Cu, Fe, Zn, Pb). Water pH ranged between 5.80 and 7.50, with elevated anion and metal levels across both sites. Pyrometallurgical effluents exhibited higher trace metal concentrations (0.01\u0026ndash;5.00 mg/L) and markedly elevated SO₄\u0026sup2;⁻ (0.85\u0026ndash;945.50 mg/L), while hydrometallurgical effluents showed greater NO₃⁻ (0.01\u0026ndash;95.39 mg/L) and Cl⁻ (1.00\u0026ndash;49.05 mg/L) concentrations. In water, Ca\u0026sup2;⁺ and SO₄\u0026sup2;⁻ were the dominant cation and anion, respectively. Sediments from hydrometallurgical zones contained substantially higher levels of most parameters, excluding pH, NO₃⁻, Cl⁻, Na⁺, and Mg\u0026sup2;⁺. Average sediment concentrations of Ca\u0026sup2;⁺, Mg\u0026sup2;⁺, As, and Fe ranged from 3,217 to 46,026 mg/kg. Overall, pyrometallurgical processes contributed greater pollutant loads to water, whereas hydrometallurgical processes resulted in higher sediment contamination. These contrasting geochemical patterns underscore the influence of ore processing methods on pollutant partitioning between water and sediments, with implications for environmental monitoring and remediation in mining regions.\u003c/p\u003e","manuscriptTitle":"Comparison of Inorganic Contamination of Pyrometallurgy and Hydrometallurgy Sites at Obuasi","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-29 20:03:43","doi":"10.21203/rs.3.rs-7321357/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-13T06:37:10+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-09T23:57:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"215217132473624967746627003522414542432","date":"2025-10-02T09:49:40+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-29T13:49:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"175280930615011335505641106089215672581","date":"2025-09-28T09:10:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"253924203076257620921830219001123164597","date":"2025-09-02T17:45:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"122682013365345186911501425550565335161","date":"2025-08-28T21:18:53+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-20T13:46:49+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-20T13:45:23+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-08-20T12:21:35+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-18T13:14:09+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-08-18T13:06:09+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6803f267-6327-4d1e-8374-e705fe6610e6","owner":[],"postedDate":"August 29th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":53923560,"name":"Physical sciences/Chemistry"},{"id":53923561,"name":"Earth and environmental sciences/Environmental sciences"}],"tags":[],"updatedAt":"2025-10-27T11:00:28+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-29 20:03:43","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7321357","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7321357","identity":"rs-7321357","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}