Geochemical Characterization And Risk Assessment Of Arsenic And Other Coexistent Toxic Elements From The Indus Drainage System Of Pakistan

Groundwater is a vital resource of fresh water worldwide specifically in developing countries including Pakistan.Groundwater resources is unique in nature with many aspects,because it is used for drinking,bathing,agriculture,industrial,and other domestic purposes.However,this vital resource is regularly challenged by climate change,growing population,urbanization,industrialization,agricultural practices and mining activities,which may make groundwater resources vulnerable both in terms of quality and quantity.Groundwater contamination through arsenic（As）,and other coexistent toxic elements is a serious environmental issue with significant human health risk reports,in many developing countries including Pakistan,specifically in Indus Basin.Therefore,the aim of this research was to investigate the hydrochemical behavior,environmental risk,and prediction of（As）and other coexistent toxic elements from the Indus,drainage system of Pakistan.The study area selected for the current research was totally unexplored part of the lower Indus Plain.In this research we explored the 3-canal command areas of lower Indus Plain,namely:Nara,Rohri,and Dadu,concerning As and F-.Furthermore,in this research we also investigate the groundwater resources of Karachi,which is industrial zone of the lower Indus Plain,concerning As and other coexistent toxic elements.The research conducted at Nara,canal command area by collecting 61 groundwater samples from different groundwater resources such as tube wells,bore hole,and hand pumps to evaluate the hydrochemistry of groundwater resources concerning（As）contamination and its suitability analysis for drinking and agricultural utility.The findings showed the abundance of cations and anions in decreasing order of Na⁺>Ca²⁺>Mg²⁺>K⁺,and HCO₃^->Cl^->SO₄^2->NO₃-N,respectively,in the groundwater samples collected from the study area.The（As）was detected with low to high concentration levels varied from 5μg to 25μg/L,with mean values of 12.9μg/L in which 28 samples out of61,were higher than 10μg/L recommended by World Health Organization（WHO）,for drinking purposes.Hydrochemical facies results revealed that the groundwater samples were,mixed Na Cl and Ca HCO₃ type,and few samples had mixed Ca Mg Cl type,interpreting the hydrochemical behavior of rock–water interaction.Principal component analysis exposed the mixed anthropogenic and natural sources of contamination for selected parameters in the study area.Gibbs plot exhibit that majority of samples were fall in rock weathering dominance zone,suggesting that the groundwater chemistry is controlled by rock-water interaction.Correlation analysis and graphical relationships between ions reveal that ion exchange and rock weathering such as the dissolution of carbonate,calcite/dolomite,gypsum,anhydrite,halite and dissolution of carbonate minerals controlled the hydrochemistry.Chloro-alkaline indices revealed the ion exchange reactions,indicating the dominance of reverse ion exchange.The water quality index（WQI）results reveal that,28 groundwater resources of the studied regions are not suitable for drinking motive.Moreover,US Salinity diagram,Wilcox diagram,alkali hazard and other agriculture indices indicated majority of the groundwater samples were found to be suitable for irrigation in the study area.Health risk assessment of（As）result of groundwater from various sources had the low mean value of hazard quotient（HQ）and carcinogenic risk（CR）.The（As）concentration was found higher in most of the water samples,demonstrating that（As）concentration low to moderate levels had an impact on local inhabitants in the studied region.In Rohri,canal command the total of 132 groundwater samples were collected from different groundwater resources to investigate the hydrogeochemical behavior of（As）based on different geochemical models as well as to investigate the physicochemical parameters which promote（As）concentration in the aquifers of the study area using machine learning（ML）different models:random forest（RF）,logistic regression（LR）,and artificial neural network（ANN）.Furthermore,principal component analysis,health risk and suitability assessment were performed to understand the source of pollution,groundwater effect on public health and its suitability for drinking purposes.The finding of this study shows that the concentration of（As）in groundwater samples was detected varied from 0.12-104μg/L,with an average value of 22.8μg/L.Principal component analysis results with total variance of（61.89%）expose that the groundwater resources of the study area are contaminated due to geogenic and anthropogenic sources.Such sources are mining activities,agricultural fertilizers,wastewater recharge and rock-water interaction.Hydrochemical facies result show that the groundwater samples:54%were Na HCO3 type,and 46%of the samples are of the mixed Ca Na HCO₃ type.This categorization can be accredited to mineral solubilization,rock/water interaction,and ion exchange processes.Furthermore,it’s also can be linked with evaporation of shallow groundwater,and silicate weathering.Gibbs diagram result shows that rock-water interaction controlled the mechanism of groundwater chemistry.Saturation Index（SI）,result of groundwater samples,shows that groundwater resources of the study area are saturated for carbonate minerals.Such materials include aragonite,calcite,dolomite,and fluorite,with a mean value of（2.886）,（3.031）,（6.135）,and（0.710）,respectively.It reveals that these minerals may contribute to groundwater aquifers as the primary leading source of（As）in the research area.The As release may result from rock-water edge reactions.In the current investigation,we identify the possible synthesis of CO₃-containing minerals and their participation in（As）discharge under favorable（alkaline）conditions while dealing with groundwater data.To evaluate the variables which promote（As）levels in groundwater resources within the current research area,the mean decrease in impurity（MDI）,as well as the permutation feature had been utilized using machine learning（ML）models.The（As）pollution in groundwater could be accurately predicted using（RF）model,which outperforms than（ANN）and（LR）,in three model assessment results due to its high accuracy,high sensitivity and lee error rate.Based on these results the RF,model has a potential to be employed as a reputable method for predicting（As）levels in groundwater within the research region having an accuracy,sensitivity and error rate of 86%,91%,and 14%,respectively.Similarly,the accuracy,sensitivity,and error rate of ANN was 84%,82%and 18%respectively,while the accuracy sensitivity,and error rate of LR was 76%,76%,and 29%,respectively.The（As）contamination in the current research region is promoted by the key variables like TDS,Na⁺,HCO₃-,p H,and EC,while the variables that are lower in the plot and displayed a minor value of mean decrease in impurity（MDI）,suggest that such variable has no role in（As）contamination in the study area.Human health risk assessment results show hazard quotient（HQ）value for children in the study area ranges between(4.79E^-03 to 4.18E⁺⁰⁰)with mean value of(1.39E⁺⁰⁰),while for adults the（HQ）values varied from(6.09E^-04 to 5.30E^-01)with an average value of(1.76E^-01).The cancer risk（CR）value for children in the study area ranges between(2.16E^-06 to 1.88E-03)with an average value of(6.24E^-04),similarly for an adult the（CR）value varied between(2.74E^-07 to 2.39E^-04)with mean value of(7.93E^-05).The（HQ）value of（As）in groundwater samples was higher than the permitted limit recommended by United State Environmental Protection Agency（USEPA）for children living in the study area.Based on WQI result the quality of groundwater resources for drinking purpose is categorized in different classes in which 43 samples belong to very poor category,26samples belong to poor category,55 samples belong to good category and 8 samples belong to excellent category for drinking purposes.From the result its concluded that most of the samples belong poor category and posing an adverse health effect on the population of the study area.The study conducted in Dadu;canal command area collected 170 samples to investigate hydrogeochemistry of groundwater with elevated F^-levels.Furthermore,machine learning models（ML）were used to predict the influencing factors which promote F^-.Random Forest,Logistic Regression,and Artificial Neural Networks were used and compared.The concentration of F-in groundwater samples detected varied from0.5 to 6.35 mg/L with mean value of 1.82 mg/L respectively.Hydrochemical facies result show that water type of the groundwater resources of the study area belong to belong to mixed Ca Na HCO₃ followed by Ca HCO₃ type while few samples lie Na Cl type.In the case of cations,almost all the samples lie in zone B（no dominant zone）,zone C（magnesium type）,and zone D（sodium type）except one sample in and zone A（calcium type）.Whereas in the case of anions,most of the samples fall in zone F（sulfate type）,zone E（bicarbonate type）,zone B（no dominant zone）and zone G（chloride type）.It is observed that Na⁺and Ca²⁺are dominant in cations,whereas SO₄^2-and HCO₃^-in anions chemistry.Sodium dominance on other cations indicates the existence of ion exchange activities because of rock weathering.Also,the dominance of sulfate and bicarbonate shows ion contributions from silica weathering in the study area.Gibbs diagram reveal that rock water interaction control the hydrochemistry of groundwater.Saturation index of mineral phases result show that groundwater resources of the study area were saturated for calcite,dolomite,fluorite,and goethite minerals due to their positive（SI）values.Gypsum was found in equilibrium condition in the groundwater water of the study area.However,halite mineral was found in under-saturation state.The positive SI values of minerals shows that these minerals had a significant role in the contamination of groundwater resources of the study area,which promotes F^-contamination.The permutation feature,as well as the MDI,was used to identify the variables affecting F^-in the research region.The RF algorithm bettered then ANN and LR algorithms findings,indicating that the RF model could be a reliable technique to predict groundwater F^-in the study area.The accuracy,sensitivity,and error rate of（LR）,was 0.90,0.81,and 0.1.The RF accuracy,sensitivity,and error rate was perceived with 0.94,0.97,and 0.06.While the accuracy,sensitivity,and error rate of 0.92,0.88,0.05,respectively.Based on the comparison RF is the most reliable model for prediction of（F^-）in the current research area.As a result,the model’s most important variables have the greatest MDI values,such as Alkalinity,TDS,HCO₃-,CO₃,Cl^-,Turbidity,SO₄^2-,Ca²⁺,Mg²⁺,Hardness,Na⁺,EC,and K⁺have a vital role in the contamination of F^-in the study area.Furthermore,for RF to consistently forecast groundwater fluoride inside the research region.Human health risk assessment result show that among 170 samples 53 samples exceeded the HQ value for children in the study area.The ADI value for adults was observed to vary from 5.71E-03 to 120E-01 with a mean value of 4.10E-02,while the HQ values of groundwater samples for adults varied from 9.52E-02 to 2.00E+00 with the mean value of 6.83E-01,among 170 samples 27 samples show high HQ values for adults in the study area.As a result,it is concluded that children were on high hazard due to F^-pollution in drinking groundwater as compared to adults,whose pose dental and skeletal fluoresces.WQI results reveal that 46.62%of samples belong to good category,43.75%of samples belong to poor category,and 6.25%samples belong to very poor category.As an outcome,the50%samples of GW from the research zone were inappropriate for ingestion motives.The research conducted in Karachi,Sindh,Pakistan,concerning（As）and other coexistent toxic elements（TEs）,contamination in drinking groundwater resources.The total of（143）samples were collected from various drinking groundwater resources to investigate the levels of As and other coexistent（TEs）,like Mn,Pb,Zn,Cu,Ni and Fe2+,along with basic water quality parameters like p H,TDS and electrical conductivity（EC）.The results show the mean concentration of（TEs）and other physiochemical parameters:p H（7.86）,TDS（500.15 mg/L）,EC（511.23μS/cm）,As（39.49μg/L）,Mn（0.19 mg/L）,Pb（0.05 mg/L）,Zn（1.07 mg/L）,Cu（0.41 mg/L）,Ni（0.03 mg/L）and Fe（0.26 mg/L）,respectively.The（TEs）such as As（91%）,Mn（14%）,Pb（97%）,Fe（45%）,Zn（15%）,samples were beyond the permitted limit recommended by World Health Organization（WHO）,for ingestion motive.Principal component analysis（PCA）results with total variability of（60.154%）reveal that the groundwater resources of the study area are contaminated due to（30.9%）geogenic sources,（31.3%）anthropogenic sources,and（37.6%）of a mixed type,including both geogenic and anthropogenic sources.Such sources may include rock-water interaction,mining actions,agricultural practices,domestic sewage,and industrial effluent in the study area.Saturation indices results show that the aquifers of the study area are saturated with lead hydroxide,zinc hydroxide,and goethite minerals,indicating that these minerals have a vital role in the contamination of groundwater resources of the study area.Health risk assessment results predicted the non-carcinogenic risk（HQ）values of（TEs）were found within the permissible limit（<1）,except As(1.58E⁺⁰⁰)for children,while carcinogenic risk（CR）values of all selected（TEs）were lower than the maximum threshold CR value(1×10^-4).