Seasonal Dynamics Of Jarosite Crystallinity And Implications For Heavy Metal Bioavailability In Agricultural Soils: Insights Into Crop Uptake And Bioremediation Strategies

Seasonal Dynamics Of Jarosite Crystallinity And Implications For Heavy Metal Bioavailability In Agricultural Soils: Insights Into Crop Uptake And Bioremediation Strategies | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Seasonal Dynamics Of Jarosite Crystallinity And Implications For Heavy Metal Bioavailability In Agricultural Soils: Insights Into Crop Uptake And Bioremediation Strategies Vaseem Akhtar, Dinesh Kulhary This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7537199/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Jarosite, a secondary sulfate mineral prevalent in acid mine drainage (AMD) systems and hydrometallurgical zinc-processing wastes, serves as a transient repository for heavy metals such as lead (Pb), arsenic (As), cadmium (Cd), and zinc (Zn). However, its stability is profoundly influenced by seasonal environmental fluctuations. This study investigated the crystal-chemical transformations of jarosite-rich industrial waste across wet (monsoon) and dry seasons, elucidating their ramifications for heavy metal mobility, soil contamination, crop bioaccumulation, and human health risks. Soil and waste samples were collected from a jarosite dump (Site A), adjacent agricultural soil (Site B), and a reference site (Site C) during peak dry (March 2025) and wet (July 2025) periods. Analyses encompassed physicochemical properties (pH, EC, organic carbon, CEC), X-ray diffraction for mineralogy, ICP-MS for total and bioavailable metals, BCR sequential extraction for speciation, batch dissolution experiments simulating seasonal conditions, crop metal accumulation in wheat and maize, bioaccessibility assessments, and pilot remediation trials using lime, biochar, and bentonite. Results revealed heightened jarosite dissolution and reduced crystallinity (from 0.87 to 0.80) in the dry season, fostering transformation to goethite and anglesite, with Pb and As shifting from residual (65–75%) to labile fractions (45–55%). Bioavailable Pb and As at Site A surged from 5.59 and 2.08 mg/kg (wet) to 19.52 and 7.74 mg/kg (dry), respectively. Batch experiments confirmed amplified metal release (up to 70% Pb, 54% As) at elevated temperatures (45°C) and pH (7.5). Crop grains from Site B exhibited elevated accumulation (e.g., 2.5 mg/kg Pb in wheat), yielding hazard quotients exceeding 1 for children, indicating non-carcinogenic risks. Remediation amendments reduced bioavailable metals by 55–65%, enhancing pH and CEC. These findings underscore the vulnerability of semi-arid mining ecosystems to seasonal dynamics, advocating tailored waste management and bioremediation strategies to mitigate contamination and foster sustainable agricultural practices in affected regions. Jarosite heavy metal mobility industrial waste seasonal dynamics Rajasthan soils acid mine drainage Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 INTRODUCTION Jarosite [(KFe₃(SO₄)₂(OH)₆] is the typical secondary mineral in the acid mine drainage (AMD) systems and industrial wastes generated in the course of hydrometallurgical processing of zinc (Pappu et al., 2007). Jarosite is an acidic sulfate-rich mineral, and a major environmental geochemistry player because it has the capacity to sequester heavy metals and metalloids, including lead (Pb), arsenic (As), cadmium (Cd), and zinc (Zn) in its crystal structure by either substitution or adsorption (Jaume, 2020). This entrapment makes jarosite a short-term trap of toxic pollutants, which lowers the immediate bioavailability of the pollutants in mining-affected waters. However, the stability of jarosite is highly susceptible to the environmental factors like pH, temperature, redox potential and moisture which fluctuate seasonally particularly in semi-arid regions like the Dariba mining district in the state of Rajasthan, India (Jung & Thornton, 1997). These changes may cause the dissolution or conversion to other secondary phases (e.g. goethite, FeOOH, or anglesite, PbSO 4 ) that may release sequestered heavy metals to the surrounding soils and water bodies, which has a high environmental and health risk (Asta et al., 2009; Weisener et al., 2008). Dariba mining area, one of the largest zinc and lead mining regions of India, has been generating large amounts of jarosite-rich wastes as by-products of hydrometallurgical zinc recovery. This waste is normally buried in landfills or open dumps and is exposed to the soils and hydrological systems of the area which can cause pollution of the area due to the movement of the leachate (Pappu et al., 2007; Kumar & Golani, 2023). The semi-arid climatic conditions of the region, the extreme variations in temperature (10℃ in winter and 45℃ in summer) and the concentrated monsoon precipitation (600–800 mm per annum) makes the region an active environment, which influences the crystal-chemical behaviour of jarosite. During the dry season, the arid terrain and hot weather may promote dehydration of minerals and lattice dissolution, but in the monsoon seasons, the dissolution or leaching may be promoted, which may affect the mobility of heavy metals (Hammarstrom et al., 2001). Such seasonal processes are critical to long-term environmental impacts of the jarosite wastes in the sense that they will define the equilibrium between metal sequestration and release, which has implications on the soil quality, groundwater safety, and ecosystem health. Jarosite-rich waste has become a major problem in mining areas all over the world and has been found to cause soil and water contamination in places like Spain, Australia and China (Asta et al., 2009; Jung & Thornton, 1997; Weisener et al., 2008). This is made worse by the fact that the waste dumps in Dariba are near agricultural lands and heavy metals that might be released by jarosite might be concentrated in crops and thus enter the food chain and cause health hazards (Kumar & Golani, 2023). As has been previously noted, jarosite has been noted to have a dual nature of being a scavenger and a source of heavy metals, and its behavior is dependent upon environmental conditions (Das et al., 1996). Nevertheless, there is a paucity of research examining seasonal changes of the crystal-chemical characteristics of jarosite and their individual effects on the mobility of heavy metals in semi-arid mining areas such as Dariba. Such knowledge is essential in the prediction of high-risk phases of contamination and site-specific and locally oriented remediation strategies that are dependent on local climatic conditions. This gap is tried to be filled in the present paper, which studies the seasonal crystal-chemical transformation of jarosite-rich industrial waste in the Dariba mining area and its implication on the mobility of heavy metals in soil. The findings will be applied to recommend certain waste management practices that will minimize heavy metals, save the soil and water resources, and promote sustainable development in the mining regions. MATERIALS AND METHODS Study Area The work was done in the Dariba mining region, Rajasthan, India, one of the main zinc and lead mining regions that produces jarosite-rich smelting wastes. The climate here is semi-arid in nature with wet (June-September) and dry (October-May) seasons. It gets an average annual rainfall of 600–800 mm, concentrated during the monsoons and the annual temperature varies between 10℃ in winter and 45℃ in summer (Kumar & Golani, 2023). The soils are mostly sandy loam with low organic carbon (< 1%), pH 5.5–7.5 that indicates the dry climate and the impact of mining industry (Adimalla & Wu, 2019). Sampling Design Soil and waste samples were collected from three sites: (1) a jarosite-waste rich dump (Site A), (2) adjacent agricultural soil (Site B), and (3) an uncontaminated reference soil (Site C). Sampling was conducted during the peak dry season (March 2025) and wet season (July 2025) to capture seasonal variability. At each site, composite samples (0–10 cm depth for soil, surface waste for Site A) were collected using a stainless steel auger. Each composite sample was created by mixing five subsamples from a 1 m² area to ensure representativeness. Samples were stored in polyethylene bags, transported at 4°C to prevent microbial alteration, and processed within 48 hours. A total of 30 samples were collected, ensuring robust spatial and temporal coverage. Soil and Waste Properties Soil pH and electrical conductivity (EC) were measured in a 1:2.5 soil-water slurry using a calibrated pH meter and EC meter. Samples were agitated for 30 minutes and allowed to settle before measurement. Organic carbon content was determined using the Walkley-Black wet oxidation method. 1g of oven dried soil sample was mixed with 10 mL of 1N potassium dichromate (K2Cr2O7) and 10 mL of 5M H2SO4. The suspension was stirred in circular motion and allowed to remain undisturbed for 30 minutes. The excess dichromate was titrated against 0.5 M ferrous ammonium sulfate (FAS). The Organic carbon content percentage was calculated by the formula: $$\:\text{O}\text{r}\text{g}\text{a}\text{n}\text{i}\text{c}\:\text{c}\text{a}\text{r}\text{b}\text{o}\text{n}\:\left(\text{\%}\right)=\text{M}\:\text{x}\:\frac{(\text{V}1-\text{V}2)}{\text{W}}\:\text{x}\:0.30$$ here, M is the molarity of the FAS solution (from blank titration), V1 is the volume of FAS required in blank titration, V2 is the volume FAS required in actual titration, W is the weight (g) of the oven-dried soil sample (Ramamoorthi & Meena, 2018). Particle size distribution was analyzed using the hydrometer method to confirm sandy loam texture (Huluka & Miller, 2014). 50g of oven dried soil was taken into a 300-mL beaker. Deionized water was added approximately within 10 cm of the rim. 50 mL of dispensing agent (75mM sodium carbonate and 50mM sodium metaphosphate) was added and let soak for 20 min. The mixture was blended to a suspension with electric blender. The soil suspension was diluted to 1 Litre with deionized water and the hydrometer levels were recorded at the solution surface at exactly 40 seconds (R1st) and 8h (R2nd). Cation exchange capacity (CEC) was measured using the ammonium acetate method (pH 7.0) to assess soil's metal retention capacity (Sumner & Miller, 1996). The soil samples(0.5–10g) were saturated with 25 mL NH 4 OAc (1M, pH 7) solution. After shaking and subsequent centrifugation, the supernatant was collected for analysis of exchangeable cations. The residues were then washed with 30 mL ethanol (97%) and centrifuged, and the supernatant was discarded. This was repeated to total three washes. After discarding the last ethanol, the tubes with soil were weighed to calculate entrained ethanol mass in the soil, and samples were saturated with 30 mL KCl (1 M). The samples were shaken and subsequently centrifuged. The supernatant was analyzed for NH 4 -N. The CEC values were calculated from the measured molar concentration of NH 4 -N in the supernatant after correction for the volume of entrained ethanol. Mineralogical Characterization Mineralogical analysis was conducted using X-ray diffraction (XRD) on a Bruker D8 Advance diffractometer with Cu Kα radiation (λ = 1.5406 Å). Samples were air-dried at 25°C, ground to < 63 µm using an agate mortar, and scanned from 5° to 70° 2θ at a step size of 0.02° and a scan speed of 1°/min. Phase identification was performed using the Joint Committee on Powder Diffraction Standards (JCPDS) database, with Rietveld refinement to quantify phase abundance (Das et al., 1996). Chemical Analysis Total concentrations of Fe, Pb, Zn, As, and Cd were determined using inductively coupled plasma mass spectrometry (ICP-MS, Agilent 7900) after aqua regia digestion (ISO 11466). Approximately 0.5 g of sample was digested in 12 mL aqua regia (3:1 HCl:HNO₃) at 95°C for 2 hours, filtered, and diluted to 50 mL with deionized water. Calibration was performed using multi-element standards, with detection limits of 0.01 mg/kg for Pb, As, and Cd, and 8 mg/kg for Zn (Pappu et al., 2007). Bioavailable fractions were extracted using 0.01 M CaCl₂ (1:10 soil: solution ratio, shaken for 2 hours at 25°C), filtered (0.45 µm), and analyzed via ICP-MS (ShokunbI et al., 2020). The BCR sequential extraction procedure was applied to categorize metals into four fractions: (1) acid-soluble (0.11 M acetic acid), (2) reducible (0.5 M hydroxylamine hydrochloride), (3) oxidizable (1 M ammonium acetate after H₂O₂ digestion), and (4) residual (aqua regia digestion) (ShokunbI et al., 2020). Each extraction step was performed in triplicate, and recoveries were validated against certified reference materials (CRM BCR-701). Batch Dissolution Experiment Batch dissolution experiments were conducted to simulate seasonal conditions (pH 5.5–7.5, 10–45°C) and evaluate jarosite stability and metal release. Synthetic K-jarosite was prepared following Drouet & Navrotsky (2003) by dissolving Fe₂(SO₄)₃ and K₂SO₄ in deionized water at 95°C and pH 1.5, followed by filtration and drying. Experiments used 1 g of sample (field or synthetic jarosite) in 50 mL of deionized water, with pH adjusted using 0.1 M NaOH or HCl. Solutions were agitated at 150 rpm in a temperature-controlled shaker (10°C for wet season, 45°C for dry season). Aliquots were sampled at 24 and 48 hours, filtered (0.45 µm), and analyzed for dissolved Pb, Zn, As, and Cd via ICP-MS. Crop Sampling and Metal Bioaccumulation Analysis To assess heavy metal accumulation in local crops, samples were collected from agricultural fields adjacent to the jarosite-rich waste dump, wheat ( Triticum aestivum ) during the dry (March 2025) and maize ( Zea mays ) (Site B) during the wet (July-August 2025) seasons. At each site, five composite samples of mature grains were collected from 1m² area, oven-dried at 60°C, and ground to < 0.5 mm. Samples (0.5 g) were digested using a 3:1 HNO₃:HClO₄ mixture at 120°C for 3 hours, filtered, and analyzed for Pb, As, Cd, Cu, and Ni via ICP-MS (US EPA, 2015). Bioaccessibility of metals, reflecting potential human uptake via ingestion, was evaluated using the Simple Bioaccessibility Extraction Test (SBET). A 0.4 M glycine solution (pH 1.5) was used to simulate gastric conditions, with 1g of crop sample extracted at 37°C for 1 hour, followed by filtration and ICP-MS analysis (Rodrigues et al., 2018). Human health risk was assessed by calculating the Hazard Quotient (HQ) for each metal, defined as the ratio of the estimated daily intake (EDI) to the reference dose (RfD), using standard ingestion rates for adults (0.1 kg/day) and children (0.2 kg/day) (Benson, 2014). Pilot-Scale Remediation Trial Pilot-scale remediation trials were conducted to evaluate the efficacy of pH adjustment and soil amendments for immobilizing heavy metals during the dry season (March 2025). Three 1m² plots at Site-A were treated with: (1) lime (CaCO₃) to raise soil pH to 7.0–7.5, (2) biochar derived from rice husk (5% w/w), and (3) bentonite clay (5% w/w). Lime was applied at 2 t/ha, mixed into the top 10 cm of soil, and irrigated to promote reaction (Bolan et al., 2014). Biochar and bentonite were incorporated similarly, with biochar sourced locally to ensure cost-effectiveness (Ahmad et al., 2014). Control plots received no amendments. After 30 days, composite soil samples (0–10 cm) were collected and analyzed for bioavailable metals using 0.01 M CaCl₂ extraction and ICP-MS. Changes in soil pH and cation exchange capacity (CEC) were measured to assess amendment impacts (Sumner & Miller, 1996). RESULTS Soil and Waste Properties Analysis of soil and waste properties revealed distinct characteristics across the three sampling sites (Site A: jarosite-rich waste dump; Site B: adjacent agricultural soil; Site C: uncontaminated reference soil) and between the wet and dry seasons. As summarized in Table 1 , soil pH exhibited a range from 5.44 at Site A to 7.04 ± 0.18 at Site C. Site A consistently demonstrated higher acidity, with pH values averaging 5.44 ± 0.08 in the dry season and slightly increasing to 5.76 ± 0.08 in the wet season, a direct consequence of the presence and weathering of jarosite. In contrast, Site B maintained a near-neutral pH (averaging 6.14 ± 0.16 in dry season and 6.2 ± 0.2 in wet season), while Site C, the uncontaminated reference site, showed a slightly alkaline pH (averaging 7.04 ± 0.18 in dry season and 7.06 ± 0.11 in wet season), reflecting natural soil conditions in the region. Electrical conductivity (EC) measurements further highlighted the impact of the industrial waste. Site A recorded significantly elevated EC values, ranging from 2.624 ± 0.5 mS/cm in dry season to 2.16 ± 0.23 in wet season, indicative of high sulfate content originating from jarosite dissolution. This contrasts sharply with Site C, which exhibited low EC values (0.38 ± 0.06 mS/cm in dry season while 0.396 ± 0.01 in wet season), typical of uncontaminated soils. Site B showed intermediate EC values (1.176 ± 0.26 mS/cm in dry season while 1.142 ± 0.21 mS/cm during wet season), suggesting some influence from the nearby waste dump. Seasonal variations in EC were also observed, with wet season samples generally showing slightly lower EC values, likely due to the diluting effect of increased rainfall (Kumar & Golani, 2023). Organic carbon content was consistently low across all sites, typically less than 0.8%, which is characteristic of the sandy loam soils prevalent in the Dariba region and consistent with previous observations (Adimalla & Wu, 2019). Cation exchange capacity (CEC) varied from 8.7 ± 0.33 to 11.34 ± 0.41 cmol/kg. Site A displayed the lowest CEC values (8.7 ± 0.33 in Dry season while 8.88 ± 0.53 cmol/kg in wet season), primarily attributable to its low clay content and the dominance of mineral waste. Sites B and C showed progressively higher CEC values (10.16 ± 0.46 and 11.34 ± 0.41 cmol/kg, respectively in dry season while 10.56 ± 0.39 and 11.12 ± 0.45 cmol/kg, respectively in wet season), reflecting their higher soil organic matter and clay content, which contribute to greater metal retention capacity. Table 1 Soil Properties by Site and Season pH EC (mS/cm) Organic Carbon (%) CEC (cmol/kg) Dry Season Site A 5.44 ± 0.08 2.624 ± 0.5 0.62 ± 0.12 8.7 ± 0.33 Site B 6.14 ± 0.16 1.176 ± 0.26 0.624 ± 0.118 10.16 ± 0.46 Site C 7.04 ± 0.18 0.38 ± 0.06 0.604 ± 0.1 11.34 ± 0.41 Wet Season Site A 5.76 ± 0.08 2.16 ± 0.23 0.512 ± 0.11 8.88 ± 0.53 Site B 6.2 ± 0.2 1.142 ± 0.21 0.556 ± 0.16 10.56 ± 0.39 Site C 7.06 ± 0.11 0.396 ± 0.01 0.558 ± 0.13 11.12 ± 0.45 **Note: Value represented as Mean ± SD. Mineralogical Changes X-ray diffraction (XRD) analysis confirmed the dominance of jarosite at Site A, the industrial waste dump, with Rietveld analysis indicating its abundance ranging from 70–85%. Alongside jarosite, goethite (FeOOH) and anglesite (PbSO₄) were detected, particularly in samples collected during the dry season (March 2025), with their proportions ranging from 5–10% and 3–8%, respectively. This suggests a seasonal transformation of jarosite into these secondary phases. Notably, jarosite crystallinity, a measure of the order within its crystal lattice, was observed to be highest in the wet season samples (July 2025) and significantly declined in the dry season. This reduction in crystallinity during the dry season is indicative of thermal-induced amorphization and structural degradation of jarosite, consistent with findings from other studies on jarosite stability under varying environmental conditions (Jung & Thornton, 1997). In contrast, Sites B (adjacent agricultural soil) and C (uncontaminated reference soil) showed no detectable presence of jarosite. Their mineralogical composition was dominated by quartz (60–70%) and various clay minerals (20–30%), reflecting the natural geological background of the region. This clear distinction in mineralogy underscores the localized impact of the industrial waste on Site A. Table 2 Mineralogical Composition of soil samples as per collection site and season Sr. No Site Season Jarosite (%) Goethite (%) Anglesite (%) Quartz (%) Clay Minerals (%) Jarosite Crystallinity 1 Site A Wet 75.6 4.9 2.5 3 0.8 0.87 2 Site A Dry 70.9 9.3 6 3.5 0.1 0.8 3 Site B Wet 0.8 0.2 0.2 61.8 23 nan 4 Site B Dry 0.5 0.4 0.3 66.1 21.4 nan 5 Site C Wet 0.3 0.4 0.5 67.9 22 nan 6 Site C Dry 0.5 0.6 0 66.1 21.7 nan Chemical Composition and Heavy Metal Speciation Inductively Coupled Plasma Mass Spectrometry (ICP-MS) analysis revealed significant variations in the total concentrations of heavy metals across the sampling sites. As detailed in Table 3 , Site A, the jarosite-rich waste dump, exhibited markedly elevated concentrations of iron (Fe), zinc (Zn), lead (Pb), arsenic (As), and cadmium (Cd). Specifically, over both the seasons span average concentrations at Site A were 23.9 ± 0.08% for Fe, 7.9 ± 0.04% for Zn, 2.3 ± 0.008% for Pb, 0.79 ± 0.004% for As, and 0.19 ± 0.0019% for Cd. These values are substantially higher than those observed at Site B (adjacent agricultural soil), which had lower concentrations, and Site C (uncontaminated reference soil), where only trace levels of these metals were detected. This gradient in metal concentrations clearly demonstrates the localized impact of the mining waste on the surrounding environment. Table 3 Total Heavy Metal Concentrations in soil as per collection site and season Site A Site B Site C Fe (%) Wet Season 24.0140 ± 0.0848 2.0498 ± 0.0694 0.9816 ± 0.0606 Dry Season 23.9661 ± 0.0767 1.9746 ± 0.0837 1.0319 ± 0.0716 Zn (%) Wet Season 7.8973 ± 0.0486 0.8005 ± 0.0451 0.2009 ± 0.0106 Dry Season 7.9062 ± 0.0556 0.8262 ± 0.0197 0.1967 ± 0.0103 Pb (%) Wet Season 2.3040 ± 0.0029 0.2977 ± 0.0079 0.03002 ± 0.0009 Dry Season 2.2986 ± 0.0112 0.3021 ± 0.0082 0.02902 ± 0.0005 As (%) Wet Season 0.7968 ± 0.0066 0.1016 ± 0.0049 0.01016 ± 0.0007 Dry Season 0.7970 ± 0.0032 0.0987 ± 0.0014 0.01020 ± 0.0001 Cd (%) Wet Season 0.1986 ± 0.0018 0.0198 ± 0.0031 0.00301 ± 0.00004 Dry Season 0.1989 ± 0.0021 0.0188 ± 0.0018 0.00295 ± 0.00006 **Note: Value represented as Mean ± SD. To understand the mobility and potential bioavailability of the heavy metals, the Community Bureau of Reference (BCR) sequential extraction procedure was applied to samples from Site A. The results, presented in Table 4 , provide insights into the speciation of Pb, As, and Cd across four fractions: acid-soluble, reducible, oxidizable, and residual. In the wet season, Pb and As were predominantly found in the residual fraction (65–75%), indicating their strong binding within stable mineral phases, likely jarosite. However, a significant shift was observed in the dry season, with 45–55% of Pb and As migrating to the more mobile acid-soluble and reducible fractions (p < 0.01). This shift suggests a decrease in the stability of the metal-bearing phases, leading to an increased risk of environmental release. In both seasons, cadmium (Cd) was consistently more mobile, with 25–35% in the acid-soluble fraction, reflecting its weaker binding to the solid matrix compared to Pb and As (ShokunbI et al., 2020). Table 4 BCR Sequential Extraction Results for Site A (Heavy Metal Fractions) Site Season Metal Acid-soluble (%) Reducible (%) Oxidizable (%) Residual (%) Site A Wet Season Pb 13.0 10.9 5.3 74.5 Site A Wet Season As 14.8 14.0 6.5 66.0 Site A Wet Season Cd 31.8 24.4 15.6 25.0 Site A Dry Season Pb 20.2 29.5 11.3 41.6 Site A Dry Season As 21.6 27.6 12.7 36.8 Site A Dry Season Cd 34.7 27.8 19.7 28.9 The bioavailability of Pb and As at Site A was observed to be highly sensitive to seasonal variations, as indicated in Table 5 . Bioavailable concentrations of Pb were much higher at Site A in the dry season (19.52 ± 1.37 mg/kg) than the wet season (5.59 ± 0.93 mg/kg). Similarly, bioavailable concentration of As increased from 2.08 ± 0.21 mg/kg in the wet season to 7.74 ± 0.9 mg/kg in the dry season. Site B exhibited moderate bioavailability, while Site C had negligible extractable metals, further emphasizing the localized contamination. Table 5 Bioavailable Heavy Metal Concentrations by Site and Season Site A Site B Site C Pb (mg/kg) Wet Season 5.59 ± 0.93 2.41 ± 0.21 0.048 ± 0.0048 Dry Season 19.52 ± 1.37 7.79 ± 0.76 0.052 ± 0.0093 As (mg/kg) Wet Season 2.08 ± 0.21 1.38 ± 0.26 0.029 ± 0.0047 Dry Season 7.74 ± 0.9 2.88 ± 0.46 0.035 ± 0.0088 Batch Dissolution Experiments Batch dissolution experiments were conducted to simulate the seasonal conditions and to directly assess the stability of jarosite and the release of heavy metals under controlled parameters. The results, presented in Table 6 , demonstrate a clear correlation between environmental conditions (pH and temperature) and the extent of metal release. Dissolution was found to be highest under conditions simulating the dry season, specifically at pH 7.5 and 45°C. Under these conditions, a significant proportion of heavy metals was released from the jarosite-rich samples, with approximately 70% of Pb and 54% of As being released within 48 hours. This high release is a result of oxidation of jarosite to more soluble secondary phases, predominantly goethite. On the other hand, in a wet season-like condition (pH 5.5 and 10℃), the dissolution of jarosite was minimal and the release of metal was less than 8 percent of all the heavy metals tested. This shows the stabilizing nature of the low temperatures and acidic conditions on jarosite as could be anticipated of its formation conditions. Interestingly, even under these minimal dissolution conditions, a slight increase in As mobility was observed at pH 5.5, which can be attributed to sulfate-arsenate exchange mechanisms, where arsenate ions compete with sulfate ions for binding sites within the mineral structure, leading to its release into the solution (Asta et al., 2009). The findings from these batch experiments corroborate the field observations, reinforcing the understanding that dry season conditions, characterized by higher temperatures and potentially higher pH due to evaporation and reduced rainfall, significantly enhance jarosite dissolution and subsequent heavy metal mobilization. Table 6 provides the heavy metal release percentages under different batch dissolution conditions, emphasizing the critical role of temperature and pH in controlling metal mobility. Table 6 Heavy metal release from batch dissolution experiment under different parameters pH Temperature (°C) Time (hours) Pb Release (%) As Release (%) Cd Release (%) Zn Release (%) 5.5 10 24 6.1 8.9 6.2 4.8 5.5 10 48 5.5 6.5 4.2 5.6 5.5 45 24 32.0 39.2 15.3 24.5 5.5 45 48 36.6 29.2 17.7 12.8 7.5 10 24 26.1 35.5 21.5 14.4 7.5 10 48 32.2 27.8 19.4 15.5 7.5 45 24 69.8 55.1 41.0 37.6 7.5 45 48 70.4 52.2 43.0 35.9 Crop Metal Accumulation and Human Health Risk Assessment Analysis of wheat and maize grains from Site B revealed significant heavy metal accumulation, with higher concentrations in the dry season crop (Table 7 ). In dry season, wheat grains were found to have heavy metal accumulation 2.5 ± 0.2 mg/kg Pb, 0.9 ± 0.1 mg/kg As, and 0.3 ± 0.02 mg/Kg Cd. Meanwhile in the wet season, Maize grains present an accumulation of 1.2 ± 0.1 mg/kg Pb, 0.7 ± 0.1 mg/kg As, and 0.2 ± 0.03 mg/kg. Table 7 Heavy Metal accumulation in Wheat and Maize Grains from Site B (mg/kg dry weight) Wheat Maize Pb (mg/kg) 2.5 ± 0.2 1.2 ± 0.1 As (mg/kg) 0.9 ± 0.1 0.7 ± 0.1 Cd (mg/kg) 0.3 ± 0.02 0.2 ± 0.03 Bioaccessibility analysis (Table 8 ) indicated that 40–50% of Pb, As and Cd in grains were bioaccessible. Table 8 Bioaccessible Heavy Metal Concentrations in Crops at Site B Wheat Maize Pb (mg/kg) 1.2 0.9 As (mg/kg) 0.4 0.3 Cd (mg/kg) 0.1 0.08 Hazard Quotients (HQ) (Table 9 ) showed that Pb and As posed non-carcinogenic risks (HQ > 1) for children, as for wheat consumption (Pb HQ: 1.8; As HQ: 1.3), and for maize consumption (Pb HQ: 1.4; As HQ: 1.0), highlighting significant health risks (US EPA, 2000). Table 9 Hazard Quotient (HQ) for Heavy Metals in Crops Wheat Maize Adult Child Adult Child Pb HQ 0.9 1.8 0.7 1.4 As HQ 0.7 1.3 0.5 1 Cd HQ 0.2 0.4 0.1 0.3 Pilot-Scale Remediation Trials Pilot-scale trials demonstrated significant reductions in bioavailable metals at Site A during the dry season. Lime treatment increased soil pH from 5.5 to 7.2, reducing bioavailable Pb by 60% (from 16.5 to 6.6 mg/kg), As by 55% (from 6.6 to 3.0 mg/kg) and Cd by 57% (from 2.1 to 0.9 mg/kg). Biochar treatment increased soil pH from 5.5 to 6.0, reducing bioavailable Pb by 65% (from 16.5 to 5.8 mg/kg), As by 61% (from 6.6 to 2.6 mg/kg) and Cd by 62% (from 2.1 to 0.8 mg/kg). Bentonite amendments were equally effective, as it increased soil pH from 5.5 to 6.2, reducing Pb by 62% (from 16.5 to 6.3 mg/kg), As by 58% (from 6.6 to 2.8 mg/kg) and Cd by 57% (from 2.1 to 0.9 mg/kg). Lime and bentonite raised EC slightly due to added ions, but all amendments were cost-effective, supporting scalability. Table 13 Bioavailable Heavy Metal Concentrations Post-Remediation (Dry Season, Site A) Control Lime Biochar Bentonite pH 5.5 7.2 6 6.2 CEC (cmol/kg) 8.7 9 10.4 9.8 Pb (mg/kg) 16.5 6.6 5.8 6.3 As (mg/kg) 6.6 3 2.6 2.8 Cd (mg/kg) 2.1 0.9 0.8 0.9 DISCUSSION This study highlights the seasonal variation in the geochemical nature of jarosite in the Dariba mining regions, with wet-season conditions promoting mineralogical stability and preventing heavy metal mobilization, while dry-season aridity causing dissolution and increased bioavailability. The crystallinity indices calculated with the help of XRD, which have decreased by 0.87 in the monsoon phase to 0.8 in the desiccation process, confirm the hypothesis that the lattice perturbations are induced by thermal and evaporative stressors, thus, resulting in the metamorphosis of the primary phase into ancillary phases, such as goethite and anglesite. This paradigm finds similarity with similar terrains that are plagued with acid mine drainage, in which periodic precipitation-drought patterns lead to periodic mineral efflorescence and its mobilization (Elwood Madden et al., 2004; Murray et al., 2014). In addition, the BCR fractionation indicates the rearrangement of Pb and As out of recalcitrant residual moieties (65–75% in set conditions) to labile acid-soluble and reducible compartments (45–55% in arid situations), which underlines the role of pH increase and desiccation as the drivers of structural integrity disruption (Vithana, Sullivan, Burton, & Bush, 2015; Liu et al., 2022). These transmutations are not unusual, but instead are analogous to reported instabilities in schwertmannite-jarosite assemblages during long-term field exposures where sediment-water boundaries accelerate goethite nucleation at the cost of progenitor sulfates (Murray et al., 2014; Root et al. 2015). This is corroborated by the batch dissolution tests, which shows an accelerated emancipation of Pb (70%) and As (54%) under xerothermic conditions (pH 7.5, 45°C), likely because of isomorphic substitution of arsenate-sulfate (Burton et al., 2021). Such kinetics means that evaporative concentration over long dry periods increases ionic activities causing the equilibrium to shift towards dissolution which is further enhanced in semi-arid environments when monsoon dilution temporarily lowers the acidity levels. Putting it to agronomic implications, the increased bioavailable fractions of Lead (16.5 mg/kg dry vs. 5.8 mg/kg wet) and Arsenic (6.6 mg/kg dry vs. 2.8 mg/kg wet) in Site A, and leakage to neighboring Site B, presents greater uptake in staple crops. Wheat and maize grains in site B had high accumulation (2.5 mg/kg Pb in wheat) leading to health risks with Hazard Quotients over 1 for children (Pb HQ: 1.8; As HQ: 1.3) (Saini & Dhawan, 1988), hence implying chronic exposure risks through food consumption (Arora et al., 2008). This heavy metal uptake and accumulation pattern is common in farming areas aligned with mining regions. Here agricultural products produced by the use of wastewater massively load metallic loads, trigger bioaccumulation in food chains and threaten trophic integrity (Asdeo, 2014; Shetty, Jagadeesha, & Salmataj, 2025). Further, the bioaccessibility (40–50%) highlights the potential of gastro-intestinal solubilization, raising health concerns in populations that are in close proximity to mining sites (Shabalala, Ngwenya, & Timana, 2022). The Rajasthan’s sandy loam with low CEC (8.7–11.3 cmol/kg) present little to none barrier against this metal dissolution. The pilot remediation assays provide an optimistic outlook of attenuation, whereby lime, biochar, and bentonite resulted in 55–65 of bioavailable Pb, As, and Cd during dry season, along with increase in pH increase (5.5 to 6.0-7.2) and CEC (8.7 to 9.0-10.4 cmol/kg). Lime’s alkalinity probably increases the precipitation of hydroxides, and the biochar carbonaceous porosity and phyllosilicate interlayers of bentonite offer adsorptive capacities (Wang et al., 2021; Afzal et al., 2024). This synergistic performance aligns with previous research, where mixed amendments of bentonite-biochar decreased the mobility of Cd in calcareous soils (Boostani, Najafi-Ghiri, & Khalili, 2025). In a similar manner, zeolite-biochar mixtures have been proven to be biologically harmless in metalliferous soils, strengthening soil microbiota and promoting plant regeneration with no additional phytotoxicity (Głąb, Gondek, & Mierzwa–Hersztek, 2021). The expansive nature of the bentonite together with the recalcitrant carbon of biochar, further minimizes the leaching as it increases the hydraulic retention, which is a major strategy in the uncertain hydrology of Dariba (Haider et al., 2019). However, there are some drawbacks: the amendments need long-term testing to see how well they withstand repeated wetting and drying, and using them on large tailings areas requires cost analysis to check if local materials can be used. CONCLUSIONS This inquiry clarifies the essential role of seasonal hydrological and thermal fluxes in modifying jarosite's crystallochemical persistence and associated heavy metal release, with dry-season dissolution precipitating heightened bioavailability and agronomical hazards. The empirical data—encompassing mineralogical transformations, metal speciation, and crop bioaccumulation—underscores the necessity for stewardship paradigms to hinder ecological degradation and safeguard environmental well-being. Pilot study using lime, biochar, and bentonite offer a cost-effective option for heavy metal remediation, potentially reducing the contamination fluxes in semi-arid mining regions. Future studies should look into the bioremediation options utilizing rhizospheric microbiomes, isotopic tracing of metal sources, and models for long-term spread under climate shifts to build stronger fixes. Declarations CONFLICTS OF INTREST There is no conflict of interests to declare Author Contribution Vaseem Akhtar has written the original manuscript, collected data and prepared the figures. Dinesh Kulhary has written, edited and supervised the original manuscript. All authors reviewed the manuscript. ACKNOWLEDGEMENTS The authors sincerely thank Mr. P.B. Saxena (H.O.D. Chemistry department Allen Career Institute) for his invaluable support. Additionally, Akhtar extends special appreciation to Mr. Vijay Soni (Senior Vice President, Allen Career Institute), Mr. Vinit Gangwal (Vice President, Allen Career Institute), and Mr. Yogesh Malav (Vice President, Allen Career Institute) for their generous assistance and contributions. Data Availability Data will be made available upon request from the authors. References Adimalla, N., & Wu, J. (2019). Groundwater quality and associated health risks in a semi-arid region of south India: Implication to sustainable groundwater management. Human and ecological risk assessment: an international journal, 25(1–2), 191–216. Afzal, S., Alghanem, S. M. S., Alsudays, I. M., Malik, Z., Abbasi, G. H., Ali, A., Noreen, S., Ali, M., Irfan, M., & Rizwan, M. (2024). Effect of biochar, zeolite and bentonite on physiological and biochemical parameters and lead and zinc uptake by maize (Zea mays L.) plants grown in contaminated soil. Journal of Hazardous Materials, 469, Article 133927. 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(2025). Physico-Chemical Characterization and Environmental Implications of Jarosite Waste from Zinc Hydrometallurgical Processing. Asian Journal of Chemistry, 37 (8), 1995–2001. doi:10.14233/ajchem.2025.33897 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-7537199","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":517407919,"identity":"a2c39833-ff42-4141-b4b9-8ecbe7aaeb9f","order_by":0,"name":"Vaseem Akhtar","email":"","orcid":"","institution":"Career Point University","correspondingAuthor":false,"prefix":"","firstName":"Vaseem","middleName":"","lastName":"Akhtar","suffix":""},{"id":517407922,"identity":"c4b4fb80-66db-4c1f-b374-cf21bcae67f4","order_by":1,"name":"Dinesh 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1","display":"","copyAsset":false,"role":"figure","size":250850,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA)\u003c/strong\u003e Soil pH, \u003cstrong\u003eB)\u003c/strong\u003e Soil Electrical conductivity (EC), \u003cstrong\u003eC)\u003c/strong\u003e Soil Organic content, and \u003cstrong\u003eD)\u003c/strong\u003e Soil Cation exchange capacity (CEC) Properties by Site and Season.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7537199/v1/29e7754b98b0a888f141df65.png"},{"id":91934978,"identity":"3bc20b32-dd3b-4dc7-bbc1-abf6cec18e4a","added_by":"auto","created_at":"2025-09-23 02:42:02","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":83584,"visible":true,"origin":"","legend":"\u003cp\u003eXRD spectra of soil samples from Site A in Dry and Wet Seasons\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7537199/v1/71f931c717ff3a98c4ce0cd4.png"},{"id":91934981,"identity":"f888e688-8855-45a8-8671-dc9481e2df75","added_by":"auto","created_at":"2025-09-23 02:42:02","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":74262,"visible":true,"origin":"","legend":"\u003cp\u003eXRD spectra of soil samples from Site B in Dry and Wet Seasons.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7537199/v1/b58a539c298ba379329b1271.png"},{"id":91936494,"identity":"e4fc5b36-0a8a-4ded-8b11-4f4f4e0e883a","added_by":"auto","created_at":"2025-09-23 02:50:02","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":73587,"visible":true,"origin":"","legend":"\u003cp\u003eXRD spectra of soil samples from Site C in Dry and Wet Seasons.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7537199/v1/16918489370db4194beb038b.png"},{"id":91934987,"identity":"c3848055-ec3b-4900-8e41-8260d9d5ba69","added_by":"auto","created_at":"2025-09-23 02:42:02","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":290021,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA) \u003c/strong\u003eFe (%), \u003cstrong\u003eB) \u003c/strong\u003eZn (%),\u003cstrong\u003e C)\u003c/strong\u003e Pb (%), \u003cstrong\u003eD) \u003c/strong\u003eAs (%),\u003cstrong\u003e \u003c/strong\u003eand \u003cstrong\u003eE) \u003c/strong\u003eCd (%) Metal Concentrations in soil as per collection site and season\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7537199/v1/0f6167e72d55e88328829d02.png"},{"id":91934989,"identity":"eefad1f5-0f21-482f-86cb-a079fdadbacd","added_by":"auto","created_at":"2025-09-23 02:42:02","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":97442,"visible":true,"origin":"","legend":"\u003cp\u003eBioavailable\u003cstrong\u003e A) \u003c/strong\u003ePb and \u003cstrong\u003eB) \u003c/strong\u003eAs metal concentrations (mg/kg) in soil as per collection site and season\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-7537199/v1/fb81f7ed6c5b8c55a1a67fa8.png"},{"id":91934991,"identity":"8dfbd44a-f59c-42c1-8243-3e58bbf0322e","added_by":"auto","created_at":"2025-09-23 02:42:02","extension":"jpeg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":62019,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHeavy metal accumulation (mg/kg) in Wheat and Maize Grains from Site B.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage7.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7537199/v1/0947a20d0898fe5bb799e7ae.jpeg"},{"id":95314404,"identity":"31af2f4d-cf7e-481a-b020-de6b8e80ebca","added_by":"auto","created_at":"2025-11-06 15:52:47","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2133944,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7537199/v1/e193cfd4-15c8-4309-9ef5-9f69d600bf57.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Seasonal Dynamics Of Jarosite Crystallinity And Implications For Heavy Metal Bioavailability In Agricultural Soils: Insights Into Crop Uptake And Bioremediation Strategies","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eJarosite [(KFe₃(SO₄)₂(OH)₆] is the typical secondary mineral in the acid mine drainage (AMD) systems and industrial wastes generated in the course of hydrometallurgical processing of zinc (Pappu et al., 2007). Jarosite is an acidic sulfate-rich mineral, and a major environmental geochemistry player because it has the capacity to sequester heavy metals and metalloids, including lead (Pb), arsenic (As), cadmium (Cd), and zinc (Zn) in its crystal structure by either substitution or adsorption (Jaume, 2020). This entrapment makes jarosite a short-term trap of toxic pollutants, which lowers the immediate bioavailability of the pollutants in mining-affected waters. However, the stability of jarosite is highly susceptible to the environmental factors like pH, temperature, redox potential and moisture which fluctuate seasonally particularly in semi-arid regions like the Dariba mining district in the state of Rajasthan, India (Jung \u0026amp; Thornton, 1997). These changes may cause the dissolution or conversion to other secondary phases (e.g. goethite, FeOOH, or anglesite, PbSO\u003csub\u003e4\u003c/sub\u003e) that may release sequestered heavy metals to the surrounding soils and water bodies, which has a high environmental and health risk (Asta et al., 2009; Weisener et al., 2008).\u003c/p\u003e\u003cp\u003eDariba mining area, one of the largest zinc and lead mining regions of India, has been generating large amounts of jarosite-rich wastes as by-products of hydrometallurgical zinc recovery. This waste is normally buried in landfills or open dumps and is exposed to the soils and hydrological systems of the area which can cause pollution of the area due to the movement of the leachate (Pappu et al., 2007; Kumar \u0026amp; Golani, 2023). The semi-arid climatic conditions of the region, the extreme variations in temperature (10℃ in winter and 45℃ in summer) and the concentrated monsoon precipitation (600\u0026ndash;800 mm per annum) makes the region an active environment, which influences the crystal-chemical behaviour of jarosite. During the dry season, the arid terrain and hot weather may promote dehydration of minerals and lattice dissolution, but in the monsoon seasons, the dissolution or leaching may be promoted, which may affect the mobility of heavy metals (Hammarstrom et al., 2001). Such seasonal processes are critical to long-term environmental impacts of the jarosite wastes in the sense that they will define the equilibrium between metal sequestration and release, which has implications on the soil quality, groundwater safety, and ecosystem health.\u003c/p\u003e\u003cp\u003eJarosite-rich waste has become a major problem in mining areas all over the world and has been found to cause soil and water contamination in places like Spain, Australia and China (Asta et al., 2009; Jung \u0026amp; Thornton, 1997; Weisener et al., 2008). This is made worse by the fact that the waste dumps in Dariba are near agricultural lands and heavy metals that might be released by jarosite might be concentrated in crops and thus enter the food chain and cause health hazards (Kumar \u0026amp; Golani, 2023). As has been previously noted, jarosite has been noted to have a dual nature of being a scavenger and a source of heavy metals, and its behavior is dependent upon environmental conditions (Das et al., 1996). Nevertheless, there is a paucity of research examining seasonal changes of the crystal-chemical characteristics of jarosite and their individual effects on the mobility of heavy metals in semi-arid mining areas such as Dariba. Such knowledge is essential in the prediction of high-risk phases of contamination and site-specific and locally oriented remediation strategies that are dependent on local climatic conditions. This gap is tried to be filled in the present paper, which studies the seasonal crystal-chemical transformation of jarosite-rich industrial waste in the Dariba mining area and its implication on the mobility of heavy metals in soil. The findings will be applied to recommend certain waste management practices that will minimize heavy metals, save the soil and water resources, and promote sustainable development in the mining regions.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy Area\u003c/h2\u003e\u003cp\u003eThe work was done in the Dariba mining region, Rajasthan, India, one of the main zinc and lead mining regions that produces jarosite-rich smelting wastes. The climate here is semi-arid in nature with wet (June-September) and dry (October-May) seasons. It gets an average annual rainfall of 600\u0026ndash;800 mm, concentrated during the monsoons and the annual temperature varies between 10℃ in winter and 45℃ in summer (Kumar \u0026amp; Golani, 2023). The soils are mostly sandy loam with low organic carbon (\u0026lt;\u0026thinsp;1%), pH 5.5\u0026ndash;7.5 that indicates the dry climate and the impact of mining industry (Adimalla \u0026amp; Wu, 2019).\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eSampling Design\u003c/h3\u003e\n\u003cp\u003eSoil and waste samples were collected from three sites: (1) a jarosite-waste rich dump (Site A), (2) adjacent agricultural soil (Site B), and (3) an uncontaminated reference soil (Site C). Sampling was conducted during the peak dry season (March 2025) and wet season (July 2025) to capture seasonal variability. At each site, composite samples (0\u0026ndash;10 cm depth for soil, surface waste for Site A) were collected using a stainless steel auger. Each composite sample was created by mixing five subsamples from a 1 m\u0026sup2; area to ensure representativeness. Samples were stored in polyethylene bags, transported at 4\u0026deg;C to prevent microbial alteration, and processed within 48 hours. A total of 30 samples were collected, ensuring robust spatial and temporal coverage.\u003c/p\u003e\n\u003ch3\u003eSoil and Waste Properties\u003c/h3\u003e\n\u003cp\u003e\u003cb\u003eSoil pH and electrical conductivity (EC)\u003c/b\u003e were measured in a 1:2.5 soil-water slurry using a calibrated pH meter and EC meter. Samples were agitated for 30 minutes and allowed to settle before measurement.\u003c/p\u003e\u003cp\u003e\u003cb\u003eOrganic carbon content\u003c/b\u003e was determined using the Walkley-Black wet oxidation method. 1g of oven dried soil sample was mixed with 10 mL of 1N potassium dichromate (K2Cr2O7) and 10 mL of 5M H2SO4. The suspension was stirred in circular motion and allowed to remain undisturbed for 30 minutes. The excess dichromate was titrated against 0.5 M ferrous ammonium sulfate (FAS). The Organic carbon content percentage was calculated by the formula:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:\\text{O}\\text{r}\\text{g}\\text{a}\\text{n}\\text{i}\\text{c}\\:\\text{c}\\text{a}\\text{r}\\text{b}\\text{o}\\text{n}\\:\\left(\\text{\\%}\\right)=\\text{M}\\:\\text{x}\\:\\frac{(\\text{V}1-\\text{V}2)}{\\text{W}}\\:\\text{x}\\:0.30$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003ehere, M is the molarity of the FAS solution (from blank titration), V1 is the volume of FAS required in blank titration, V2 is the volume FAS required in actual titration, W is the weight (g) of the oven-dried soil sample (Ramamoorthi \u0026amp; Meena, 2018).\u003c/p\u003e\u003cp\u003e\u003cb\u003eParticle size distribution\u003c/b\u003e was analyzed using the hydrometer method to confirm sandy loam texture (Huluka \u0026amp; Miller, 2014). 50g of oven dried soil was taken into a 300-mL beaker. Deionized water was added approximately within 10 cm of the rim. 50 mL of dispensing agent (75mM sodium carbonate and 50mM sodium metaphosphate) was added and let soak for 20 min. The mixture was blended to a suspension with electric blender. The soil suspension was diluted to 1 Litre with deionized water and the hydrometer levels were recorded at the solution surface at exactly 40 seconds (R1st) and 8h (R2nd).\u003c/p\u003e\u003cp\u003e\u003cb\u003eCation exchange capacity (CEC)\u003c/b\u003e was measured using the ammonium acetate method (pH 7.0) to assess soil's metal retention capacity (Sumner \u0026amp; Miller, 1996). The soil samples(0.5\u0026ndash;10g) were saturated with 25 mL NH\u003csub\u003e4\u003c/sub\u003eOAc (1M, pH 7) solution. After shaking and subsequent centrifugation, the supernatant was collected for analysis of exchangeable cations. The residues were then washed with 30 mL ethanol (97%) and centrifuged, and the supernatant was discarded. This was repeated to total three washes. After discarding the last ethanol, the tubes with soil were weighed to calculate entrained ethanol mass in the soil, and samples were saturated with 30 mL KCl (1 M). The samples were shaken and subsequently centrifuged. The supernatant was analyzed for NH\u003csub\u003e4\u003c/sub\u003e-N. The CEC values were calculated from the measured molar concentration of NH\u003csub\u003e4\u003c/sub\u003e-N in the supernatant after correction for the volume of entrained ethanol.\u003c/p\u003e\n\u003ch3\u003eMineralogical Characterization\u003c/h3\u003e\n\u003cp\u003eMineralogical analysis was conducted using X-ray diffraction (XRD) on a Bruker D8 Advance diffractometer with Cu Kα radiation (λ\u0026thinsp;=\u0026thinsp;1.5406 \u0026Aring;). Samples were air-dried at 25\u0026deg;C, ground to \u0026lt;\u0026thinsp;63 \u0026micro;m using an agate mortar, and scanned from 5\u0026deg; to 70\u0026deg; 2θ at a step size of 0.02\u0026deg; and a scan speed of 1\u0026deg;/min. Phase identification was performed using the Joint Committee on Powder Diffraction Standards (JCPDS) database, with Rietveld refinement to quantify phase abundance (Das et al., 1996).\u003c/p\u003e\n\u003ch3\u003eChemical Analysis\u003c/h3\u003e\n\u003cp\u003eTotal concentrations of Fe, Pb, Zn, As, and Cd were determined using inductively coupled plasma mass spectrometry (ICP-MS, Agilent 7900) after aqua regia digestion (ISO 11466). Approximately 0.5 g of sample was digested in 12 mL aqua regia (3:1 HCl:HNO₃) at 95\u0026deg;C for 2 hours, filtered, and diluted to 50 mL with deionized water. Calibration was performed using multi-element standards, with detection limits of 0.01 mg/kg for Pb, As, and Cd, and 8 mg/kg for Zn (Pappu et al., 2007).\u003c/p\u003e\u003cp\u003eBioavailable fractions were extracted using 0.01 M CaCl₂ (1:10 soil: solution ratio, shaken for 2 hours at 25\u0026deg;C), filtered (0.45 \u0026micro;m), and analyzed via ICP-MS (ShokunbI et al., 2020). The BCR sequential extraction procedure was applied to categorize metals into four fractions: (1) acid-soluble (0.11 M acetic acid), (2) reducible (0.5 M hydroxylamine hydrochloride), (3) oxidizable (1 M ammonium acetate after H₂O₂ digestion), and (4) residual (aqua regia digestion) (ShokunbI et al., 2020). Each extraction step was performed in triplicate, and recoveries were validated against certified reference materials (CRM BCR-701).\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eBatch Dissolution Experiment\u003c/h2\u003e\u003cp\u003eBatch dissolution experiments were conducted to simulate seasonal conditions (pH 5.5\u0026ndash;7.5, 10\u0026ndash;45\u0026deg;C) and evaluate jarosite stability and metal release. Synthetic K-jarosite was prepared following Drouet \u0026amp; Navrotsky (2003) by dissolving Fe₂(SO₄)₃ and K₂SO₄ in deionized water at 95\u0026deg;C and pH 1.5, followed by filtration and drying. Experiments used 1 g of sample (field or synthetic jarosite) in 50 mL of deionized water, with pH adjusted using 0.1 M NaOH or HCl. Solutions were agitated at 150 rpm in a temperature-controlled shaker (10\u0026deg;C for wet season, 45\u0026deg;C for dry season). Aliquots were sampled at 24 and 48 hours, filtered (0.45 \u0026micro;m), and analyzed for dissolved Pb, Zn, As, and Cd via ICP-MS.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eCrop Sampling and Metal Bioaccumulation Analysis\u003c/h3\u003e\n\u003cp\u003eTo assess heavy metal accumulation in local crops, samples were collected from agricultural fields adjacent to the jarosite-rich waste dump, wheat (\u003cem\u003eTriticum aestivum\u003c/em\u003e) during the dry (March 2025) and maize (\u003cem\u003eZea mays\u003c/em\u003e) (Site B) during the wet (July-August 2025) seasons. At each site, five composite samples of mature grains were collected from 1m\u0026sup2; area, oven-dried at 60\u0026deg;C, and ground to \u0026lt;\u0026thinsp;0.5 mm. Samples (0.5 g) were digested using a 3:1 HNO₃:HClO₄ mixture at 120\u0026deg;C for 3 hours, filtered, and analyzed for Pb, As, Cd, Cu, and Ni via ICP-MS (US EPA, 2015). Bioaccessibility of metals, reflecting potential human uptake via ingestion, was evaluated using the Simple Bioaccessibility Extraction Test (SBET). A 0.4 M glycine solution (pH 1.5) was used to simulate gastric conditions, with 1g of crop sample extracted at 37\u0026deg;C for 1 hour, followed by filtration and ICP-MS analysis (Rodrigues et al., 2018). Human health risk was assessed by calculating the Hazard Quotient (HQ) for each metal, defined as the ratio of the estimated daily intake (EDI) to the reference dose (RfD), using standard ingestion rates for adults (0.1 kg/day) and children (0.2 kg/day) (Benson, 2014).\u003c/p\u003e\n\u003ch3\u003ePilot-Scale Remediation Trial\u003c/h3\u003e\n\u003cp\u003ePilot-scale remediation trials were conducted to evaluate the efficacy of pH adjustment and soil amendments for immobilizing heavy metals during the dry season (March 2025). Three 1m\u0026sup2; plots at Site-A were treated with: (1) lime (CaCO₃) to raise soil pH to 7.0\u0026ndash;7.5, (2) biochar derived from rice husk (5% w/w), and (3) bentonite clay (5% w/w). Lime was applied at 2 t/ha, mixed into the top 10 cm of soil, and irrigated to promote reaction (Bolan et al., 2014). Biochar and bentonite were incorporated similarly, with biochar sourced locally to ensure cost-effectiveness (Ahmad et al., 2014). Control plots received no amendments. After 30 days, composite soil samples (0\u0026ndash;10 cm) were collected and analyzed for bioavailable metals using 0.01 M CaCl₂ extraction and ICP-MS. Changes in soil pH and cation exchange capacity (CEC) were measured to assess amendment impacts (Sumner \u0026amp; Miller, 1996).\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eSoil and Waste Properties\u003c/h2\u003e\u003cp\u003eAnalysis of soil and waste properties revealed distinct characteristics across the three sampling sites (Site A: jarosite-rich waste dump; Site B: adjacent agricultural soil; Site C: uncontaminated reference soil) and between the wet and dry seasons. As summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, soil pH exhibited a range from 5.44 at Site A to 7.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18 at Site C. Site A consistently demonstrated higher acidity, with pH values averaging 5.44\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08 in the dry season and slightly increasing to 5.76\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08 in the wet season, a direct consequence of the presence and weathering of jarosite. In contrast, Site B maintained a near-neutral pH (averaging 6.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16 in dry season and 6.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2 in wet season), while Site C, the uncontaminated reference site, showed a slightly alkaline pH (averaging 7.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18 in dry season and 7.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11 in wet season), reflecting natural soil conditions in the region. Electrical conductivity (EC) measurements further highlighted the impact of the industrial waste. Site A recorded significantly elevated EC values, ranging from 2.624\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5 mS/cm in dry season to 2.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23 in wet season, indicative of high sulfate content originating from jarosite dissolution. This contrasts sharply with Site C, which exhibited low EC values (0.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06 mS/cm in dry season while 0.396\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01 in wet season), typical of uncontaminated soils. Site B showed intermediate EC values (1.176\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26 mS/cm in dry season while 1.142\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21 mS/cm during wet season), suggesting some influence from the nearby waste dump. Seasonal variations in EC were also observed, with wet season samples generally showing slightly lower EC values, likely due to the diluting effect of increased rainfall (Kumar \u0026amp; Golani, 2023). Organic carbon content was consistently low across all sites, typically less than 0.8%, which is characteristic of the sandy loam soils prevalent in the Dariba region and consistent with previous observations (Adimalla \u0026amp; Wu, 2019). Cation exchange capacity (CEC) varied from 8.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.33 to 11.34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.41 cmol/kg. Site A displayed the lowest CEC values (8.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.33 in Dry season while 8.88\u0026thinsp;\u0026plusmn;\u0026thinsp;0.53 cmol/kg in wet season), primarily attributable to its low clay content and the dominance of mineral waste. Sites B and C showed progressively higher CEC values (10.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46 and 11.34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.41 cmol/kg, respectively in dry season while 10.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.39 and 11.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.45 cmol/kg, respectively in wet season), reflecting their higher soil organic matter and clay content, which contribute to greater metal retention capacity.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSoil Properties by Site and Season\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003epH\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eEC (mS/cm)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eOrganic Carbon (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eCEC (cmol/kg)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003eDry Season\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eSite A\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e5.44\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e2.624\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e0.62\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e\u003cp\u003e8.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.33\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eSite B\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e6.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e1.176\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e0.624\u0026thinsp;\u0026plusmn;\u0026thinsp;0.118\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e\u003cp\u003e10.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eSite C\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e7.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e0.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e0.604\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e\u003cp\u003e11.34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.41\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003eWet Season\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eSite A\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e5.76\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e2.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e0.512\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e\u003cp\u003e8.88\u0026thinsp;\u0026plusmn;\u0026thinsp;0.53\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eSite B\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e6.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e1.142\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e0.556\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e\u003cp\u003e10.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.39\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eSite C\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e7.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e0.396\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e0.558\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e\u003cp\u003e11.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.45\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003e**Note: Value represented as Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD.\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eMineralogical Changes\u003c/h2\u003e\u003cp\u003eX-ray diffraction (XRD) analysis confirmed the dominance of jarosite at Site A, the industrial waste dump, with Rietveld analysis indicating its abundance ranging from 70\u0026ndash;85%. Alongside jarosite, goethite (FeOOH) and anglesite (PbSO₄) were detected, particularly in samples collected during the dry season (March 2025), with their proportions ranging from 5\u0026ndash;10% and 3\u0026ndash;8%, respectively. This suggests a seasonal transformation of jarosite into these secondary phases. Notably, jarosite crystallinity, a measure of the order within its crystal lattice, was observed to be highest in the wet season samples (July 2025) and significantly declined in the dry season. This reduction in crystallinity during the dry season is indicative of thermal-induced amorphization and structural degradation of jarosite, consistent with findings from other studies on jarosite stability under varying environmental conditions (Jung \u0026amp; Thornton, 1997). In contrast, Sites B (adjacent agricultural soil) and C (uncontaminated reference soil) showed no detectable presence of jarosite. Their mineralogical composition was dominated by quartz (60\u0026ndash;70%) and various clay minerals (20\u0026ndash;30%), reflecting the natural geological background of the region. This clear distinction in mineralogy underscores the localized impact of the industrial waste on Site A.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMineralogical Composition of soil samples as per collection site and season\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"9\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" 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=\"left\" 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=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSr. No\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSite\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSeason\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eJarosite (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eGoethite (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eAnglesite (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eQuartz (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eClay Minerals (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eJarosite Crystallinity\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSite A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eWet\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e75.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e4.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.87\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSite A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDry\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e70.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e9.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSite B\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eWet\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e61.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003enan\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSite B\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDry\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e66.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e21.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003enan\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSite C\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eWet\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e67.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003enan\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSite C\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDry\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e66.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e21.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003enan\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eChemical Composition and Heavy Metal Speciation\u003c/h2\u003e\u003cp\u003eInductively Coupled Plasma Mass Spectrometry (ICP-MS) analysis revealed significant variations in the total concentrations of heavy metals across the sampling sites. As detailed in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Site A, the jarosite-rich waste dump, exhibited markedly elevated concentrations of iron (Fe), zinc (Zn), lead (Pb), arsenic (As), and cadmium (Cd). Specifically, over both the seasons span average concentrations at Site A were 23.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08% for Fe, 7.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04% for Zn, 2.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.008% for Pb, 0.79\u0026thinsp;\u0026plusmn;\u0026thinsp;0.004% for As, and 0.19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0019% for Cd. These values are substantially higher than those observed at Site B (adjacent agricultural soil), which had lower concentrations, and Site C (uncontaminated reference soil), where only trace levels of these metals were detected. This gradient in metal concentrations clearly demonstrates the localized impact of the mining waste on the surrounding environment.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eTotal Heavy Metal Concentrations in soil as per collection site and season\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSite A\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSite B\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSite C\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cem\u003eFe (%)\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eWet Season\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e24.0140\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0848\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e2.0498\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0694\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e0.9816\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0606\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eDry Season\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e23.9661\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0767\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e1.9746\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0837\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e1.0319\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0716\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cem\u003eZn (%)\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eWet Season\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e7.8973\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0486\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e0.8005\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0451\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e0.2009\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0106\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eDry Season\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e7.9062\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0556\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e0.8262\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0197\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e0.1967\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0103\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cem\u003ePb (%)\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eWet Season\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e2.3040\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0029\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e0.2977\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0079\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e0.03002\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0009\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eDry Season\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e2.2986\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0112\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e0.3021\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0082\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e0.02902\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0005\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cem\u003eAs (%)\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eWet Season\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e0.7968\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0066\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e0.1016\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0049\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e0.01016\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0007\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eDry Season\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e0.7970\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0032\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e0.0987\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0014\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e0.01020\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cem\u003eCd (%)\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eWet Season\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e0.1986\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0018\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e0.0198\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0031\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e0.00301\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00004\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eDry Season\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e0.1989\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e0.0188\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0018\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e0.00295\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00006\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003e**Note: Value represented as Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD.\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTo understand the mobility and potential bioavailability of the heavy metals, the Community Bureau of Reference (BCR) sequential extraction procedure was applied to samples from Site A. The results, presented in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, provide insights into the speciation of Pb, As, and Cd across four fractions: acid-soluble, reducible, oxidizable, and residual. In the wet season, Pb and As were predominantly found in the residual fraction (65\u0026ndash;75%), indicating their strong binding within stable mineral phases, likely jarosite. However, a significant shift was observed in the dry season, with 45\u0026ndash;55% of Pb and As migrating to the more mobile acid-soluble and reducible fractions (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). This shift suggests a decrease in the stability of the metal-bearing phases, leading to an increased risk of environmental release. In both seasons, cadmium (Cd) was consistently more mobile, with 25\u0026ndash;35% in the acid-soluble fraction, reflecting its weaker binding to the solid matrix compared to Pb and As (ShokunbI et al., 2020).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eBCR Sequential Extraction Results for Site A (Heavy Metal Fractions)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" 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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSite\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSeason\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMetal\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAcid-soluble (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eReducible (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eOxidizable (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eResidual (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSite A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWet Season\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePb\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e13.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e10.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e5.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e74.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSite A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWet Season\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e14.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e14.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e6.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e66.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSite A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWet Season\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCd\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e31.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e24.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e15.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e25.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSite A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDry Season\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePb\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e20.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e29.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e11.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e41.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSite A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDry Season\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e21.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e27.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e12.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e36.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSite A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDry Season\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCd\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e34.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e27.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e19.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e28.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe bioavailability of Pb and As at Site A was observed to be highly sensitive to seasonal variations, as indicated in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. Bioavailable concentrations of Pb were much higher at Site A in the dry season (19.52\u0026thinsp;\u0026plusmn;\u0026thinsp;1.37 mg/kg) than the wet season (5.59\u0026thinsp;\u0026plusmn;\u0026thinsp;0.93 mg/kg). Similarly, bioavailable concentration of As increased from 2.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21 mg/kg in the wet season to 7.74\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9 mg/kg in the dry season. Site B exhibited moderate bioavailability, while Site C had negligible extractable metals, further emphasizing the localized contamination.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eBioavailable Heavy Metal Concentrations by Site and Season\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSite A\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSite B\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSite C\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePb (mg/kg)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eWet Season\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e5.59\u0026thinsp;\u0026plusmn;\u0026thinsp;0.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e2.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e0.048\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0048\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eDry Season\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e19.52\u0026thinsp;\u0026plusmn;\u0026thinsp;1.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e7.79\u0026thinsp;\u0026plusmn;\u0026thinsp;0.76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e0.052\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0093\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAs (mg/kg)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eWet Season\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e2.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e1.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e0.029\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0047\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eDry Season\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e7.74\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e2.88\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e0.035\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0088\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eBatch Dissolution Experiments\u003c/h2\u003e\u003cp\u003eBatch dissolution experiments were conducted to simulate the seasonal conditions and to directly assess the stability of jarosite and the release of heavy metals under controlled parameters. The results, presented in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, demonstrate a clear correlation between environmental conditions (pH and temperature) and the extent of metal release. Dissolution was found to be highest under conditions simulating the dry season, specifically at pH 7.5 and 45\u0026deg;C. Under these conditions, a significant proportion of heavy metals was released from the jarosite-rich samples, with approximately 70% of Pb and 54% of As being released within 48 hours. This high release is a result of oxidation of jarosite to more soluble secondary phases, predominantly goethite. On the other hand, in a wet season-like condition (pH 5.5 and 10℃), the dissolution of jarosite was minimal and the release of metal was less than 8 percent of all the heavy metals tested. This shows the stabilizing nature of the low temperatures and acidic conditions on jarosite as could be anticipated of its formation conditions. Interestingly, even under these minimal dissolution conditions, a slight increase in As mobility was observed at pH 5.5, which can be attributed to sulfate-arsenate exchange mechanisms, where arsenate ions compete with sulfate ions for binding sites within the mineral structure, leading to its release into the solution (Asta et al., 2009). The findings from these batch experiments corroborate the field observations, reinforcing the understanding that dry season conditions, characterized by higher temperatures and potentially higher pH due to evaporation and reduced rainfall, significantly enhance jarosite dissolution and subsequent heavy metal mobilization. Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e provides the heavy metal release percentages under different batch dissolution conditions, emphasizing the critical role of temperature and pH in controlling metal mobility.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eHeavy metal release from batch dissolution experiment under different parameters\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003epH\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTemperature (\u0026deg;C)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTime (hours)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePb Release (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAs Release (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eCd Release (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eZn Release (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e6.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e8.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e6.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e4.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e5.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e6.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e4.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e5.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e32.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e39.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e15.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e24.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e36.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e29.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e17.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e12.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e7.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e26.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e35.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e21.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e14.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e7.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e32.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e27.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e19.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e15.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e7.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e69.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e55.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e41.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e37.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e7.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e70.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e52.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e43.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e35.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eCrop Metal Accumulation and Human Health Risk Assessment\u003c/h2\u003e\u003cp\u003eAnalysis of wheat and maize grains from Site B revealed significant heavy metal accumulation, with higher concentrations in the dry season crop (Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). In dry season, wheat grains were found to have heavy metal accumulation 2.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2 mg/kg Pb, 0.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1 mg/kg As, and 0.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02 mg/Kg Cd. Meanwhile in the wet season, Maize grains present an accumulation of 1.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1 mg/kg Pb, 0.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1 mg/kg As, and 0.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03 mg/kg.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eHeavy Metal accumulation in Wheat and Maize Grains from Site B (mg/kg dry weight)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\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\u003eWheat\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMaize\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePb (mg/kg)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e2.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e1.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAs (mg/kg)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e0.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e0.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCd (mg/kg)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e0.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e0.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eBioaccessibility analysis (Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e) indicated that 40\u0026ndash;50% of Pb, As and Cd in grains were bioaccessible.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eBioaccessible Heavy Metal Concentrations in Crops at Site B\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWheat\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMaize\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePb (mg/kg)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAs (mg/kg)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCd (mg/kg)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.08\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eHazard Quotients (HQ) (Table\u0026nbsp;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e) showed that Pb and As posed non-carcinogenic risks (HQ\u0026thinsp;\u0026gt;\u0026thinsp;1) for children, as for wheat consumption (Pb HQ: 1.8; As HQ: 1.3), and for maize consumption (Pb HQ: 1.4; As HQ: 1.0), highlighting significant health risks (US EPA, 2000).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eHazard Quotient (HQ) for Heavy Metals in Crops\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\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=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eWheat\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eMaize\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAdult\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eChild\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAdult\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eChild\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePb HQ\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAs HQ\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCd HQ\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003ePilot-Scale Remediation Trials\u003c/h2\u003e\u003cp\u003ePilot-scale trials demonstrated significant reductions in bioavailable metals at Site A during the dry season. Lime treatment increased soil pH from 5.5 to 7.2, reducing bioavailable Pb by 60% (from 16.5 to 6.6 mg/kg), As by 55% (from 6.6 to 3.0 mg/kg) and Cd by 57% (from 2.1 to 0.9 mg/kg). Biochar treatment increased soil pH from 5.5 to 6.0, reducing bioavailable Pb by 65% (from 16.5 to 5.8 mg/kg), As by 61% (from 6.6 to 2.6 mg/kg) and Cd by 62% (from 2.1 to 0.8 mg/kg). Bentonite amendments were equally effective, as it increased soil pH from 5.5 to 6.2, reducing Pb by 62% (from 16.5 to 6.3 mg/kg), As by 58% (from 6.6 to 2.8 mg/kg) and Cd by 57% (from 2.1 to 0.9 mg/kg). Lime and bentonite raised EC slightly due to added ions, but all amendments were cost-effective, supporting scalability.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab10\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 13\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eBioavailable Heavy Metal Concentrations Post-Remediation (Dry Season, Site A)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\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=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\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\u003eControl\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLime\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBiochar\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eBentonite\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003epH\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e5.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e6.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCEC (cmol/kg)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e8.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e9.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePb (mg/kg)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e16.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e6.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAs (mg/kg)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e2.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCd (mg/kg)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis study highlights the seasonal variation in the geochemical nature of jarosite in the Dariba mining regions, with wet-season conditions promoting mineralogical stability and preventing heavy metal mobilization, while dry-season aridity causing dissolution and increased bioavailability. The crystallinity indices calculated with the help of XRD, which have decreased by 0.87 in the monsoon phase to 0.8 in the desiccation process, confirm the hypothesis that the lattice perturbations are induced by thermal and evaporative stressors, thus, resulting in the metamorphosis of the primary phase into ancillary phases, such as goethite and anglesite. This paradigm finds similarity with similar terrains that are plagued with acid mine drainage, in which periodic precipitation-drought patterns lead to periodic mineral efflorescence and its mobilization (Elwood Madden et al., 2004; Murray et al., 2014). In addition, the BCR fractionation indicates the rearrangement of Pb and As out of recalcitrant residual moieties (65\u0026ndash;75% in set conditions) to labile acid-soluble and reducible compartments (45\u0026ndash;55% in arid situations), which underlines the role of pH increase and desiccation as the drivers of structural integrity disruption (Vithana, Sullivan, Burton, \u0026amp; Bush, 2015; Liu et al., 2022). These transmutations are not unusual, but instead are analogous to reported instabilities in schwertmannite-jarosite assemblages during long-term field exposures where sediment-water boundaries accelerate goethite nucleation at the cost of progenitor sulfates (Murray et al., 2014; Root et al. 2015). This is corroborated by the batch dissolution tests, which shows an accelerated emancipation of Pb (70%) and As (54%) under xerothermic conditions (pH 7.5, 45\u0026deg;C), likely because of isomorphic substitution of arsenate-sulfate (Burton et al., 2021). Such kinetics means that evaporative concentration over long dry periods increases ionic activities causing the equilibrium to shift towards dissolution which is further enhanced in semi-arid environments when monsoon dilution temporarily lowers the acidity levels.\u003c/p\u003e\u003cp\u003ePutting it to agronomic implications, the increased bioavailable fractions of Lead (16.5 mg/kg dry vs. 5.8 mg/kg wet) and Arsenic (6.6 mg/kg dry vs. 2.8 mg/kg wet) in Site A, and leakage to neighboring Site B, presents greater uptake in staple crops. Wheat and maize grains in site B had high accumulation (2.5 mg/kg Pb in wheat) leading to health risks with Hazard Quotients over 1 for children (Pb HQ: 1.8; As HQ: 1.3) (Saini \u0026amp; Dhawan, 1988), hence implying chronic exposure risks through food consumption (Arora et al., 2008). This heavy metal uptake and accumulation pattern is common in farming areas aligned with mining regions. Here agricultural products produced by the use of wastewater massively load metallic loads, trigger bioaccumulation in food chains and threaten trophic integrity (Asdeo, 2014; Shetty, Jagadeesha, \u0026amp; Salmataj, 2025). Further, the bioaccessibility (40\u0026ndash;50%) highlights the potential of gastro-intestinal solubilization, raising health concerns in populations that are in close proximity to mining sites (Shabalala, Ngwenya, \u0026amp; Timana, 2022). The Rajasthan\u0026rsquo;s sandy loam with low CEC (8.7\u0026ndash;11.3 cmol/kg) present little to none barrier against this metal dissolution.\u003c/p\u003e\u003cp\u003eThe pilot remediation assays provide an optimistic outlook of attenuation, whereby lime, biochar, and bentonite resulted in 55\u0026ndash;65 of bioavailable Pb, As, and Cd during dry season, along with increase in pH increase (5.5 to 6.0-7.2) and CEC (8.7 to 9.0-10.4 cmol/kg). Lime\u0026rsquo;s alkalinity probably increases the precipitation of hydroxides, and the biochar carbonaceous porosity and phyllosilicate interlayers of bentonite offer adsorptive capacities (Wang et al., 2021; Afzal et al., 2024). This synergistic performance aligns with previous research, where mixed amendments of bentonite-biochar decreased the mobility of Cd in calcareous soils (Boostani, Najafi-Ghiri, \u0026amp; Khalili, 2025). In a similar manner, zeolite-biochar mixtures have been proven to be biologically harmless in metalliferous soils, strengthening soil microbiota and promoting plant regeneration with no additional phytotoxicity (Głąb, Gondek, \u0026amp; Mierzwa\u0026ndash;Hersztek, 2021). The expansive nature of the bentonite together with the recalcitrant carbon of biochar, further minimizes the leaching as it increases the hydraulic retention, which is a major strategy in the uncertain hydrology of Dariba (Haider et al., 2019). However, there are some drawbacks: the amendments need long-term testing to see how well they withstand repeated wetting and drying, and using them on large tailings areas requires cost analysis to check if local materials can be used.\u003c/p\u003e"},{"header":"CONCLUSIONS","content":"\u003cp\u003eThis inquiry clarifies the essential role of seasonal hydrological and thermal fluxes in modifying jarosite's crystallochemical persistence and associated heavy metal release, with dry-season dissolution precipitating heightened bioavailability and agronomical hazards. The empirical data\u0026mdash;encompassing mineralogical transformations, metal speciation, and crop bioaccumulation\u0026mdash;underscores the necessity for stewardship paradigms to hinder ecological degradation and safeguard environmental well-being. Pilot study using lime, biochar, and bentonite offer a cost-effective option for heavy metal remediation, potentially reducing the contamination fluxes in semi-arid mining regions. Future studies should look into the bioremediation options utilizing rhizospheric microbiomes, isotopic tracing of metal sources, and models for long-term spread under climate shifts to build stronger fixes.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eCONFLICTS OF INTREST\u003c/h2\u003e\n\u003cp\u003eThere is no conflict of interests to declare\u0026nbsp;\u003cbr\u003e \u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eVaseem Akhtar has written the original manuscript, collected data and prepared the figures. Dinesh Kulhary has written, edited and supervised the original manuscript. All authors reviewed the manuscript.\u003c/p\u003e\u003ch2\u003eACKNOWLEDGEMENTS\u003c/h2\u003e\u003cp\u003eThe authors sincerely thank Mr. P.B. Saxena (H.O.D. Chemistry department Allen Career Institute) for his invaluable support. Additionally, Akhtar extends special appreciation to Mr. Vijay Soni (Senior Vice President, Allen Career Institute), Mr. Vinit Gangwal (Vice President, Allen Career Institute), and Mr. Yogesh Malav (Vice President, Allen Career Institute) for their generous assistance and contributions.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eData will be made available upon request from the authors.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAdimalla, N., \u0026amp; Wu, J. (2019). Groundwater quality and associated health risks in a semi-arid region of south India: Implication to sustainable groundwater management. Human and ecological risk assessment: an international journal, 25(1\u0026ndash;2), 191\u0026ndash;216.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAfzal, S., Alghanem, S. M. S., Alsudays, I. M., Malik, Z., Abbasi, G. H., Ali, A., Noreen, S., Ali, M., Irfan, M., \u0026amp; Rizwan, M. (2024). Effect of biochar, zeolite and bentonite on physiological and biochemical parameters and lead and zinc uptake by maize (Zea mays L.) plants grown in contaminated soil. Journal of Hazardous Materials, 469, Article 133927.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eArora, M., Kiran, B., Rani, S., Rani, A., Kaur, B., \u0026amp; Mittal, N. (2008). Heavy metal accumulation in vegetables irrigated with water from different sources. Food Chemistry, 111(4), 811\u0026ndash;815.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAsdeo, A. (2014). Toxic metal contamination of staple crops (wheat and millet) in periurban area of Western Rajasthan. International Refereed Journal of Engineering and Science, 3(4), 08\u0026ndash;18.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAsta, M. P., Cama, J., Mart\u0026iacute;nez, M., \u0026amp; Gim\u0026eacute;nez, J. (2009). 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Evaluation of a single extraction test to estimate the human oral bioaccessibility of potentially toxic elements in soils: Towards more robust risk assessment. Science of The Total Environment, 635, 188\u0026ndash;202.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRoot, R. A., Hayes, S. M., Hammond, C. M., Maier, R. M., \u0026amp; Chorover, J. (2015). Toxic metal(loid) speciation during weathering of iron sulfide mine tailings under semi-arid climate. Applied geochemistry : journal of the International Association of Geochemistry and Cosmochemistry, 62, 131\u0026ndash;149.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSaini, R. S., \u0026amp; Dhawan, S. S. (1988). Accumulation of cadmium by plants of Dariba Mines, Rajasthan, India. Environmental Geochemistry and Health, 10(3\u0026ndash;4), 87\u0026ndash;92.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eShabalala, A. N., Ngwenya, P. D., \u0026amp; Timana, M. (2022). 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Microbial dissolution of silver jarosite: Examining its trace metal behaviour in reduced environments. Geomicrobiology Journal, 25(7\u0026ndash;8), 415\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAkhtar, V., \u0026amp; Kulhary, D. (2025). Physico-Chemical Characterization and Environmental Implications of Jarosite Waste from Zinc Hydrometallurgical Processing. \u003cem\u003eAsian Journal of Chemistry, 37\u003c/em\u003e(8), 1995\u0026ndash;2001. doi:10.14233/ajchem.2025.33897\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Jarosite, heavy metal mobility, industrial waste, seasonal dynamics, Rajasthan soils, acid mine drainage","lastPublishedDoi":"10.21203/rs.3.rs-7537199/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7537199/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eJarosite, a secondary sulfate mineral prevalent in acid mine drainage (AMD) systems and hydrometallurgical zinc-processing wastes, serves as a transient repository for heavy metals such as lead (Pb), arsenic (As), cadmium (Cd), and zinc (Zn). However, its stability is profoundly influenced by seasonal environmental fluctuations. This study investigated the crystal-chemical transformations of jarosite-rich industrial waste across wet (monsoon) and dry seasons, elucidating their ramifications for heavy metal mobility, soil contamination, crop bioaccumulation, and human health risks. Soil and waste samples were collected from a jarosite dump (Site A), adjacent agricultural soil (Site B), and a reference site (Site C) during peak dry (March 2025) and wet (July 2025) periods. Analyses encompassed physicochemical properties (pH, EC, organic carbon, CEC), X-ray diffraction for mineralogy, ICP-MS for total and bioavailable metals, BCR sequential extraction for speciation, batch dissolution experiments simulating seasonal conditions, crop metal accumulation in wheat and maize, bioaccessibility assessments, and pilot remediation trials using lime, biochar, and bentonite. Results revealed heightened jarosite dissolution and reduced crystallinity (from 0.87 to 0.80) in the dry season, fostering transformation to goethite and anglesite, with Pb and As shifting from residual (65\u0026ndash;75%) to labile fractions (45\u0026ndash;55%). Bioavailable Pb and As at Site A surged from 5.59 and 2.08 mg/kg (wet) to 19.52 and 7.74 mg/kg (dry), respectively. Batch experiments confirmed amplified metal release (up to 70% Pb, 54% As) at elevated temperatures (45\u0026deg;C) and pH (7.5). Crop grains from Site B exhibited elevated accumulation (e.g., 2.5 mg/kg Pb in wheat), yielding hazard quotients exceeding 1 for children, indicating non-carcinogenic risks. Remediation amendments reduced bioavailable metals by 55\u0026ndash;65%, enhancing pH and CEC. These findings underscore the vulnerability of semi-arid mining ecosystems to seasonal dynamics, advocating tailored waste management and bioremediation strategies to mitigate contamination and foster sustainable agricultural practices in affected regions.\u003c/p\u003e","manuscriptTitle":"Seasonal Dynamics Of Jarosite Crystallinity And Implications For Heavy Metal Bioavailability In Agricultural Soils: Insights Into Crop Uptake And Bioremediation Strategies","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-23 02:41:57","doi":"10.21203/rs.3.rs-7537199/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f8cee6da-ec35-4740-92df-3aebb46ec863","owner":[],"postedDate":"September 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-11-06T10:23:55+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-23 02:41:57","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7537199","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7537199","identity":"rs-7537199","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}