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Non-carcinogenic health risk assessment and predicting of pollution indexing of groundwater around Osisioma, Nigeria, using artificial neural networks and multi-linear modeling principles

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Abstract

Non-carcinogenic health risk assessment and prediction of pollution indexing of groundwater around Osisioma, Nigeria, using artificial neural networks and multi-linear modeling principles has been done. Thirty groundwater samples were collected systematically and analyzed for organic and heavy metal pollutants. The results of the analysis showed that the heavy metals and organic pollutants contributed to the pollution of groundwater resources in the locality. 63.3% of the entire water samples had As above the WHO standard, same as Fe (60%), Cr (100%), Pb (56.7%), E (16.7%), X (13.3%), B (40%). Correlation matrix results indicated a weak correlation. For the Principal Component Analysis, PC1 showed that 60% of the entire variable had loadings, PC2 had 40%, PC3 had 30%, PC4 had 10% loadings of parameters within the study area, and that organic pollutants were major contributors to the loadings. The Contamination factor, Pollution load index, Metal pollution index, Geoaccumulation index, Potential ecological risk index, Elemental Contamination Index, and Overall Metal Contamination Index showed no significant pollution, whereas the Heavy Metal Evaluation Index, Pollution Index of Groundwater results showed the worrisome impact of the anthropogenic activities on the groundwater quality. Health risk assessment showed that children are more at risk than adults as it related to taking polluted with a Hazard Quotient and Hazard Index trend is Cr > As > T > E > m-X > o-X > B > Pb > Cu > Fe. This trend is the same for both children and adults. Seven mathematical models were generated for the prediction of pollution indices. Based on the results, this study recommends regular monitoring of groundwater resources and the integration of ANN and MLR modeling approaches for the prediction of pollution indices.

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References

  • Adnan RM, Khosravinia P, Karimi B, Kisi O (2021) Prediction of hydraulics performance in drain envelopes using Kmeans based multivariate adaptive regression spline. Appl Soft Comput 100:107008. https://doi.org/10.1016/j.asoc.2020.107008

    Article  Google Scholar 

  • Agidi BM, Akakuru OC, Aigbadon GO, Schoeneich K, Isreal H, Ofoh I, Njoku J, Esomonu I (2022) Water quality index, hydrogeochemical facies and pollution index of groundwater around Middle Benue Trough, Nigeria. Int J Energy Water Resour. https://doi.org/10.1007/s42108-022-00187-z

    Article  Google Scholar 

  • Ahmed U, Mumtaz R, Anwar H, Shah AA, Irfan R, García-Nieto J (2019) Efficient water quality prediction using supervised machine learning. Water 11(11):2210. https://doi.org/10.3390/w11112210

    Article  CAS  Google Scholar 

  • Ahmed A, Ghosh PK, Hasan M, Rahman A (2020) Surface and groundwater quality assessment and identification of hydrochemical characteristics of a south-western coastal area of Bangladesh. Environ Monit Assess 192:1–15

    Article  Google Scholar 

  • Aisien FA, Okoduwa IG, Aisien ET (2013) Levels of heavy metals in and around scrap car dumpsite at Uwelu, Nigeria. Br J Appl Sci Technol 3(4):1519–1532

    Article  CAS  Google Scholar 

  • Aniwetalu EU, Akakuru OC (2015) Granomeric analysis of mamu formation and Enugu Shale around Ozalla and its environs evidence from field study. IOSR J Appl Geol Geophys 3(2):19–26

    Article  CAS  Google Scholar 

  • Akakuru OC, Akudinobi BEB (2018) Determination of water quality index and irrigation suitability of groundwater sources in parts of coastal aquifers of Eastern Niger Delta, Nigeria. Int J Appl Nat Sci 7(1):1–6

    Google Scholar 

  • Akakuru O, Akudinobi B, Okoroafor P, Maduka E (2017) Application of geographic information system in the hydrochemical evaluation of groundwater in parts of Eastern Niger Delta Nigeria. Am J Environ Policy Manag 3(6):39–45

    Google Scholar 

  • Akakuru OC, Eze CU, Okeke OC, Opara AI, Usman AO, Iheme OK, Ibeneme SI, Iwuoha PO (2022a) Hydrogeochemical evolution, water quality indices, irrigation suitability and pollution index of groundwater (PIG) around Eastern Niger Delta, Nigeria. Int J Energy WAter Resour. https://doi.org/10.1007/s42108-021-00162-0

    Article  Google Scholar 

  • Akakuru OC, Akaolisa CCZ, Aigbadon GO, Eyankware MO, Opara AI, Obasi PN, Ofoh IJ, Njoku AO, Akudinobi BEB (2022b) Integrating machine learning and multi-linear regression modeling approaches in groundwater quality assessment around Obosi, SE Nigeria. Environ Dev Sustain. https://doi.org/10.1007/s10668-022-02679-8

    Article  Google Scholar 

  • Akakuru OC, Adakwa CB, Ikoro DO, Eyankware MO, Opara AI, Njoku AO, Iheme KO, Usman AO (2023) Application of artificial neural network and multi-linear regression techniques in groundwater quality and health risk assessment around Egbema, Southeastern Nigeria. Environ Earth Sci. https://doi.org/10.1007/s12665-023-10753-1

    Article  Google Scholar 

  • Ali S, Khan SU, Gupta SK et al (2021) Health risk assessment due to fluoride exposure from groundwater in rural areas of Agra, India: Monte Carlo simulation. Int J Environ Sci Technol 18:3665–3676. https://doi.org/10.1007/s13762-020-03084-2

    Article  CAS  Google Scholar 

  • Anornu GK, Kabo-bah AT, Anim-Gyampo M (2012) Evaluation of groundwater vulnerability in the Densu River Basin of Ghana. Am J Hum Ecol 1(3):79–86

    Google Scholar 

  • Baalousha WT, McPhee HM, Anderson MJ (2015) Estimation of natural groundwater recharge in Qatar using GIS. In: MODSIM 2015 21st international congress on modelling and simulation

  • Bhutian R, Dipali BK, Khanna DR, Ashutosh G (2017) Geochemical distribution and environmental riskassessment of heavy metals in groundwater of an indus-trial area and its surroundings, Haridwar, India. Energy Ecol Environ 2(2):155–167. https://doi.org/10.1007/s40974-016-0019-6

    Article  Google Scholar 

  • Boateng TK, Opoku F, Akoto O (2019) Heavy metal contamination assessment of groundwater quality: a case study of Oti landfill site, Kumasi. Appl Water Sci 9(33):1–15

    CAS  Google Scholar 

  • Cuesta Cordoba IGA (2011) Using of artificial neural network for evaluation and prediction of some drinking water quality parameters within a water distribution system. Water Manag Water Struct 3:1–11

    Google Scholar 

  • Deng T, Chau KW, Duan HF (2021) Machine learning based marine water quality prediction for coastal hydro-environment management. J Environ Manag 284:112051

    Article  CAS  Google Scholar 

  • Egbueri JC (2019) Evaluation and characterization of the groundwater quality and hydrogeochemistry of Ogbaru farming District in Southeastern Nigeria. SN Appl Sci 1:851. https://doi.org/10.1007/s42452-019-0853-1

    Article  CAS  Google Scholar 

  • Ekemen Keskin T, Özler E, Şander E et al (2020) Prediction of electrical conductivity using ANN and MLR: a case study from Turkey. Acta Geophys 68:811–820. https://doi.org/10.1007/s11600-020-00424-1

    Article  Google Scholar 

  • Enwereuzo OO, Akakuru OC, Uwaoma RC, Elemike EE, Akakuru OU (2021) Self-assembled membrane-polymer nanoparticles of top-notch tissue tolerance for the treatment of gastroesophageal reflux disease. J Nanostruct Chem, pp 1–13

  • Esmaeilzadeh M, Jaafari J, Mohammadi AA, Panahandeh M, Javid A, Javan S (2019) Investigation of the extent of contamination of heavy metals in agricultural soil using statistical analyses and contamination indices. Hum Ecol Risk Assess Int J 25(5):1125–1136. https://doi.org/10.1080/10807039.2018.1460798

    Article  CAS  Google Scholar 

  • Eyankware MO, Akakuru OC (2022) Appraisal of groundwater to risk contamination near an abandoned limestone quarry pit in Nkalagu, Nigeria, using enrichment factor and statistical approaches. Int J Energy Water Resour. https://doi.org/10.1007/s42108-022-00186-0

    Article  Google Scholar 

  • Eyankware MO, Akakuru OC, Ulakpa ROE, Eyankware OE (2021) Sustainable management and characterization of groundwater resource in coastal aquifer of Niger delta basin Nigeria. Sustain Water Resour Manag 7:58. https://doi.org/10.1007/s40899-021-00537-5

    Article  Google Scholar 

  • Eyankware MO, Akakuru OC, Ulakpa ROE, Eyankware EO (2022a) Hydrogeochemical approach in the assessment of coastal aquifer for domestic, industrial, and agricultural utilities in Port Harcourt urban, Southern Nigeria. Int J Energy Water Resour. https://doi.org/10.1007/s42108-022-00184-2

    Article  Google Scholar 

  • Eyankware MO, Akakuru OC, Eyankware EO (2022b) Interpretation of hydrochemical data using various geochemical models: a case study of Enyigba mining district of Abakaliki, Ebonyi State, SE Nigeria. Sustain Water Resour Manag. https://doi.org/10.1007/s40899-022-00613-4

    Article  Google Scholar 

  • Eyankware MO, Akakuru OC, Eyankware EO (2022c) Interpretation of hydrochemical data using various geochemical models: a case study of Enyigba mining district of Abakaliki, Ebonyi State, SE Nigeria. Sustain Water Resour Manag. https://doi.org/10.1007/s40899-022-00613-4

    Article  Google Scholar 

  • Ghaderpoori M, Kamarehie B, Jafari A et al (2020) Health risk assessment of heavy metals in cosmetic products sold in Iran: the Monte Carlo simulation. Environ Sci Pollut Res 27:7588–7595. https://doi.org/10.1007/s11356-019-07423-w

    Article  Google Scholar 

  • Ghorbani M, Aalami M, Naghipour L (2017) Use of artificial neural networks for electrical conductivity modelling in Asi River. Appl Water Sci 7:1761–1772

    Article  CAS  Google Scholar 

  • Guzman J, Shirmohammadi A, Sadeghi A, Wang X, Chu ML, Jha M, Hernandez JE (2015) Uncertainty considerations in calibration and validation of hydrologic and water quality models. Trans ASABE (am Soc Agric Biol Eng) 58(6):1745–1762. https://doi.org/10.13031/trans.58.10710

    Article  Google Scholar 

  • Hakanson L (1980) An ecological risk index for aquatic pollution control a sedimentological approach. Water Res 14:975–1001. https://doi.org/10.1016/0043-1354(80)90143-8

    Article  Google Scholar 

  • Horton RK (1965) An index number system for rating water quality. J Water Pollut Control Feder 37:300–306

    Google Scholar 

  • Ibe FC, Opara AI, Ibe BO, Adindu BC, Ichu BC (2018) Environmental and Health implications of trace metal concentrations in street dust around some electronic repair workshops in Owerri, Southeastern Nigeria. Environ Monit Assess 190(696):1–14

    CAS  Google Scholar 

  • Ibe FC, Opara AI, Ibe BO, Amaobi CE (2019) Application of assessment models for pollution and health risk from effluent discharge into a tropical stream: a case study of Inyishi River, Southeastern Nigeria. Environ Monit Assess 191(753):1–15

    Google Scholar 

  • Ijeh IB (2014) Appraisal of groundwater quality in parts of the Benin formation in Imo River Basin, Southeastern Nigeria, Pacific. J Sci Technol 15(1):433–442

    Google Scholar 

  • Karami MA, Fakhri Y, Rezania S, Alinejad AA, Mohammadi AA, Yousefi M, Ghaderpoori M, Saghi MH, Ahmadpour M (2019) Non-carcinogenic health risk assessment due to fluoride exposure from tea consumption in Iran using Monte Carlo simulation. Int J Environ Res Public Health 16(21):4261. https://doi.org/10.3390/ijerph16214261

    Article  CAS  Google Scholar 

  • Kouadri S, Pande CB, Panneerselvam B et al (2022) Prediction of irrigation groundwater quality parameters using ANN, LSTM, and MLR models. Environ Sci Pollut Res 29:21067–21091. https://doi.org/10.1007/s11356-021-17084-3

    Article  CAS  Google Scholar 

  • Kumar S, Venkatesh AS, Singh R, Udayabhanu G, Saha D (2018) Geochemical signatures and isotopic systematics constraining dynamics of fluoride contamination in groundwater across Jamui district, Indo-Gangetic alluvial plains, India. Chemosphere 205:493–505

    Article  CAS  Google Scholar 

  • Mahmood Y, Mitra G, Vahide O, Ali AM, Mansour B, Ali E (2021) Comparison of LSSVM and RSM in simulating the removal of ciprofloxacin from aqueous solutions using magnetization of functionalized multi-walled carbon nanotubes: Process optimization using GA and RSM techniques. J Environ Chem Eng. https://doi.org/10.1016/j.jece.2021.105677

    Article  Google Scholar 

  • Marghade D, Malpe DB, Duraisamy K et al (2021) Hydrogeochemical evaluation, suitability, and health risk assessment of groundwater in the watershed of Godavari basin, Maharashtra. Central India Environ Sci Pollut Res 28:18471–18494. https://doi.org/10.1007/s11356-020-10032-7

    Article  CAS  Google Scholar 

  • Mazvimavi D, Meijerink AM, Savenije HH, Stein A (2005) Prediction of flow characteristics using multiple regression and neural networks: a case study in Zimbabwe. Phys Chem Earth Parts a/b/c 30(11–16):639–647

    Article  Google Scholar 

  • McKnight US, Fuer SG, Rasmussen JJ, Finkel M, Binning PJ, Bjerg PL (2010) An integrated model for assessing the risk of TCE groundwater contamination to human receptors and surface water ecosystems. Ecol Eng 36(9):1126–1137

    Article  Google Scholar 

  • Mello JMM, Brandao HL, Valerio A, de Souza AAU, de Oliveira D, da Silva A (2019) Biodegradation of BTEX compounds from petrochemical wastewater: kinetic and toxicity. J Water Process Eng 32:100914

    Article  Google Scholar 

  • Mgbenu CN, Egbueri JC (2019) The hydrogeochemical signatures, quality indices and health risk assessment of water resources in Umunya district, southeast Nigeria. Appl Water Sci 9:22. https://doi.org/10.1007/s13201-019-0900-5

    Article  CAS  Google Scholar 

  • Mohammadi A, Yousefi M, Soltani J et al (2018) Using the combined model of gamma test and neuro-fuzzy system for modeling and estimating lead bonds in reservoir sediments. Environ Sci Pollut Res 25:30315–30324. https://doi.org/10.1007/s11356-018-3026-7

    Article  CAS  Google Scholar 

  • Moosavi V, Vafakhah M, Shirmohamadi B (2013) A wavelet-ANFIS hybrid model for groundwater level forecasting for different prediction periods. Water Resour Manag 27:1301–1321

    Article  Google Scholar 

  • Obasi PN, Akakuru OC, Nweke OM, Okolo CM (2022) Groundwater assessment and contaminant migration in fractured shale aquifers of Abakaliki mining areas, Southeast Nigeria. J Min Geol 58(1):211–227

    Google Scholar 

  • Oli IC, Opara AI, Okeke OC, Akaolisa CZ, Akakuru OC, Osi-Okeke I, Udeh HM (2022) Evaluation of aquifer hydraulic conductivity and transmissivity of Ezza/Ikwo area, Southeastern Nigeria, using pumping test and surficial resistivity techniques. Environ Monit Assess 194:719. https://doi.org/10.1007/s10661-022-10341-z

    Article  CAS  Google Scholar 

  • Ononiwu CG, Enwereuzo OO, Akakuru OC, Ejiogu CB, Onumah CU, Achukee CK, Umaefulam TN, Abaekwume NN, Akakuru OU (2021) Generating organic compounds by retrosynthetic pathway via typical Corey’s synthesis. World News of Natural Sciences, pp 88–98

  • Onyekuru SO, Iwuagwu JC, Adaeze UA, Ibeneme SI, Ukaonu C, Okoli AE, Akakuru OC (2021) Calibration of petrophysical evaluation results of clastic reservoirs using core data, in the offshore depobelt, Niger Delta, Nigeria. Model Earth Syst Environ. https://doi.org/10.1007/s40808-021-01285-3

  • Opara AI, Akaolisa CCZ, Akakuru OC, Nkwoada AU, Ibe FC, Verla AW, Chukwuemeka IC (2021) Particulate matter exposure and non-cancerous inhalation health risk assessment of major dumpsites of Owerri metropolis, Nigeria. Environ Anal Health Toxicol. https://doi.org/10.5620/eaht.2021025

    Article  Google Scholar 

  • Opara AI, Osi-Okeke IE, Eyankware MO, Akakuru OC, Oli IC, Udeh H (2022) Use of geo-electric data in the determination of groundwater potentials and vulnerability mapping in the southern Benue Trough Nigeria. Int J Environ Sci Technol. https://doi.org/10.1007/s13762-022-04485-1

    Article  Google Scholar 

  • Ossai EK (2014) Heavy metal distribution in the vicinity of automobile scrap sites in Agbor, Nigeria. J Appl Sci Environ Manag 18(2):263–265

    Google Scholar 

  • Painecur P, Muñoz A, Tume P et al (2022) Distribution of potentially harmful elements in attic dust from the City of Coronel (Chile). Environ Geochem Health 44:1377–1386. https://doi.org/10.1007/s10653-021-01164-x

    Article  CAS  Google Scholar 

  • Palani S, Liong SY, Tkalich P (2008a) An ANN Application for water quality forecasting. Mar Pollut Bull 56:1586–1597. https://doi.org/10.1016/j.marpolbul.2008.05.021

    Article  CAS  Google Scholar 

  • Palani S, Liong SY, Tkalich P (2008b) An ANN application for water quality forecasting. Mar Pollut Bull 56(9):1586–1597

    Article  CAS  Google Scholar 

  • Palani S, Liong SY, Tkalich P (2008c) An ANN Prentice Hall, USA. Application for water quality forecasting. Mar Pollut Bull 56:1586–1597

    Article  CAS  Google Scholar 

  • Qian X, Nguyen HN, Song MM, Hadiono C, Ogden SC, Hammack C, Ming GL (2016) Brain-region-specific organoids using mini-bioreactors for modeling ZIKV exposure. Cell 165(5):1238–1254

    Article  CAS  Google Scholar 

  • Salami ES, Ehetshami M, Karimi-Jashni A, Salari M, Nikbakht SS, Ehteshami A (2016a) A mathematical method and artificial neural network modeling to simulate osmosis membrane’s performance. Model Earth Syst Environ 2:207. https://doi.org/10.1007/s40808-016-0261-0

    Article  Google Scholar 

  • Salami ES, Salari M, Ehteshami M, Beadokhti NT (2016b) Application of artificial neural networks and mathematical modeling for the prediction of water quality variables (case study: southwest of Iran). J Desalin Water Treatm. https://doi.org/10.1080/19443994.2016.1167624

    Article  Google Scholar 

  • Salami E, Salari M, Sheibani SN, Hosseini KM, Teymouri E (2020) Dataset on the assessments the rate of changing of dissolved oxygen and temperature of surface water, case study: California, USA. J Environ Treatm Tech 7(3):843–852

    Google Scholar 

  • Samir SG, Hela T, Mustapha B, Josefina G (2016) Assessment of heavy metals status in northern Tunisia using contamination indices: case of the Ichkeul steams system. Int Res J Public Environ Health 3(9):209–217. https://doi.org/10.15739/irjpeh.16.027

    Article  Google Scholar 

  • Sarkar A, Pandey P (2015) River water quality modelling using artificial neural network technique. Aquatic Procedia 1(4):1070–1077

    Article  Google Scholar 

  • Seyam M, Mogheir Y (2011) Application of artificial neural networks model as analytical tool for groundwater salinity. J Environ Prot 2:56–71

    Article  CAS  Google Scholar 

  • Sham S, Jahani A, Moeinaddini M, Khorasani N, Kalantary S (2020a) Forecasting ozone density in tehran air using a smart data-driven approach. J Health Saf Work 10(4):406–420

    Google Scholar 

  • Sham SR, Ali J, Saba K, Mazaher M, Nematollah K (2021b) The evaluation on artificial neural networks (ANN) and multiple linear regressions (MLR) models for predicting SO2 concentration. Urban Clim. https://doi.org/10.1016/j.uclim.2021.100837

    Article  Google Scholar 

  • Shams SR, Jahani A, Moeinaddini M et al (2020b) Air carbon monoxide forecasting using an artificial neural network in comparison with multiple regression. Model Earth Syst Environ 6:1467–1475. https://doi.org/10.1007/s40808-020-00762-5

    Article  Google Scholar 

  • Shams SR, Jahani A, Kalantary S et al (2021a) Artificial intelligence accuracy assessment in NO2 concentration forecasting of metropolises air. Sci Rep 11:1805. https://doi.org/10.1038/s41598-021-81455-6

    Article  CAS  Google Scholar 

  • Shyu GS, Cheng BY, Chiang CT, Yao PH, Chang TK (2011) Applying factor analysis combined with kriging and information entropy theory for mapping and evaluating the stability of groundwater quality variation in Taiwan. Int J Environ Res Public Health 8(4):1084–1109

    Article  CAS  Google Scholar 

  • Subba Rao N, Sunitha B, Rambabu R, Nageswara Rao PV, Surya Rao P, Spandana BD, Sravanthi M, Marghade D (2018) Quality and degree of pollution of groundwater, using PIG from a rural part of Telangana State India. Appl Water Sci 8:227. https://doi.org/10.1007/s13201-018-3950864-x

    Article  Google Scholar 

  • Sundus SQ, Azizullah C, Sheeraz AM, Qamaruzaman K, Ghazala AJ, Azeem P, Tawfik AS (2021) Assessment of physicochemical characteristics in groundwater quality parameter. Environ Technol Innov. https://doi.org/10.1016/j.eti.2021.101877

    Article  Google Scholar 

  • Tatyana G, Olga V, Rakova IV, Mashkova EV, Nikita EV (2018) Health risk assessment of metal(loid)s exposure via indoor dust from urban area in Chelyabinsk Russia. Int J GEOMATE 16(55):1–7. https://doi.org/10.21660/2019.55.16501

    Article  Google Scholar 

  • Thompson SO, Ogundele OD, Abata EO, Ajayi OM (2019) Heavy metals distribution and pollution indices of scrapyards soils. Int J Curr Res Appl Chem Eng 3(1):9–19

    Google Scholar 

  • Urom OO, Opara AI, Usen OS, Akiang FB, Isreal HO, Ibezim JO, Akakuru OC (2021) Electro-geohydraulic estimation of shallow aquifers of Owerri and environs, Southeastern Nigeria using multiple empirical resistivity equations. Int J Energy Water Resour. https://doi.org/10.1007/s42108-021-00122-8

    Article  Google Scholar 

  • US EPA (1994) Drinking water: maximum contaminant level goal and national primary drinking water regulation for lead and copper. Fed Regist 59(125):33860–33864

    Google Scholar 

  • Usman AO, Omada JI, Omali AO, Akakuru OC (2015) Evaluation of the aquifer characteristics of Nteje and Environs, Anambra Basin, South Eastern, Nigeria. J Nat Sci Res 5(14):99–114

  • Usman AO, Iheme KO, Chinwuko AI, Azuoko G, Akakuru OC (2022a) Hydro-geophysical investigation of groundwater resources within Abakaliki, lower Benue Trough Nigeria. COOU J Phys Sci 5(1):473–491

    Google Scholar 

  • Usman AO, Iheme KO, Chinwuko AI, Azuoko G, Akakuru OC (2022b) Hydro-geophysical investigation of groundwater resources within Abakaliki, Lower Benue Trough Nigeria. COOU J Phys Sci 5(1):473–491

    Google Scholar 

  • Wee VB, Moll HC, Dirks J (2000) Environmental impact of scrapping old cars. Transport Res Part d 5:137–143

    Article  Google Scholar 

  • World Health Organization (WHO) (2017) Guidelines for drinking water quality, 4th edn, WA 675, World Health Organization, Geneva, Switzerland, pp 307–43

  • Wu GD, Lo SL (2008) Predicting real-time coagulant dosage in water treatment by artificial neural networks and adaptive network-based fuzzy inference system". Eng Appl Artif Intell 21(8):118

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Geology, Federal University of Technology, Owerri, Imo State, Nigeria

    Obinna Chigoziem Akakuru & Uzochi Bright Onyeanwuna

  2. Preventions Department, eXclusive Services Inc., 11134 Luschek Drive, Blue Ash, Ohio, 45241, USA

    Uzoma Benedict Njoku & Annabel Uchechukwu Obinna-Akakuru

  3. Department of Geological Sciences, Nnamdi Azikiwe University, Awka, Anambra State, Nigeria

    Bernard E. B. Akudinobi

  4. Department of Geology, Ebonyi State University, Abakaliki, Ebonyi State, Nigeria

    Philip Njoku Obasi

  5. Department of Geology, Faculty of Sciences, Federal University, Lokoja, Kogi State, Nigeria

    Godwin Okumagbe Aigbadon

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  1. Obinna Chigoziem Akakuru
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All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by AOC, ABEB and OU. The first draft of the manuscript was written by AOC, NBU, O-AAU, AG and OPN and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Akakuru, O.C., Njoku, U.B., Obinna-Akakuru, A.U. et al. Non-carcinogenic health risk assessment and predicting of pollution indexing of groundwater around Osisioma, Nigeria, using artificial neural networks and multi-linear modeling principles. Stoch Environ Res Risk Assess 37, 2413–2443 (2023). https://doi.org/10.1007/s00477-023-02398-0

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