https://hdl.handle.net/10259/6168 2026-05-29T16:15:31Z 2026-05-29T16:15:31Z Talpur, Shakeel Ahmed Rashad, Muhammad Ahmed, Aziz Rosatelli, Gianluigi Baloch, Muhammad Yousuf Jat Khan, Aqib Hassan Ali Talpur, Hafeez Ahmed Iqbal, Javed https://hdl.handle.net/10259/11762 2026-05-29T12:15:28Z 2025-01-01T00:00:00Z

Pollution indicators and human health risk assessment of fluoride contaminated drinking groundwater in southern Pakistan Talpur, Shakeel Ahmed; Rashad, Muhammad; Ahmed, Aziz; Rosatelli, Gianluigi; Baloch, Muhammad Yousuf Jat; Khan, Aqib Hassan Ali; Talpur, Hafeez Ahmed; Iqbal, Javed This study investigated fluoride contamination in groundwater and associated health risks in the Badin district of Pakistan. Fifty-seven groundwater samples were analyzed for fluoride, turbidity, iron, and total dissolved solids (TDS). Pollution indices and health risk models were employed to assess contamination levels and potential health impacts. Results showed that 47 % of samples exceeded the WHO fluoride limit of 1.5 mg/L, with a mean concentration of 1.92 mg/L. Spatial analysis revealed high contamination in northern and southern areas. Health risk assessments indicated that children, particularly females, faced the highest risk of fluorosis. TDS, turbidity, and iron levels also exceeded WHO limits in significant portions of the samples. This investigation uniquely combines multiple pollution indicators, spatial analysis, and age-specific health risk assessments, presenting vibrant insights for targeted interventions, policy development, and resource allocation to address this critical public health issue in fluoride-endemic regions

2025-01-01T00:00:00Z Khan, Aqib Hassan Ali Kazmi, Syedah Zoya Mirza, Cyrus Raza Butt, Tayyab Ashfaq Gul, Nida Barros García, Rocío Yousaf, Sohail Iqbal, Mazhar https://hdl.handle.net/10259/11741 2026-05-28T06:12:14Z 2023-01-01T00:00:00Z

Effect of Soil Amendments on the Enzymatic Profile of Soil when Nicotiana alata L. and Petunia hybrida L. were Irrigated with Synthetic Heavy Metal-contaminated Wastewater Khan, Aqib Hassan Ali; Kazmi, Syedah Zoya; Mirza, Cyrus Raza; Butt, Tayyab Ashfaq; Gul, Nida; Barros García, Rocío; Yousaf, Sohail; Iqbal, Mazhar The nutrient cycle and organic matter decomposition are catalyzed by soil enzymes. In this study, enzymatic activities of catalase, dehydrogenase, alkaline phosphatase, and urease are studied in soils amended with compost (C), moss (M), or biochar (B) and irrigated with heavy metal-contaminated wastewater (HM-CW), when Nicotiana alata L. and Petunia hybrida L. was grown in pots. The irrigation of HM-CW reduced the soil enzyme activities. However, combined used of 5% M+C+B, results in the improved soil enzyme activities. In case of N. alata and P. hybrida, catalase activity was 222.03 ± 9.24 and 402.34 ± 10.48 mg KMnO4 g-1 soil h-1, respectively, with M+C+B, which was up to 94% higher than non-amended treatment. Similarly, the M+C+B treatment also showed higher activity for dehydrogenase i.e., 180.24 ± 6.95, and 156.79 ± 8.31 μg TPF g-1 soil h-1 for N. alata and P. hybrida, respectively, that were 73% and 49% higher than non-amended treatment. Alkaline phosphatase production (μg p-nitrophenol g-1 soil h-1) for N. alata with M+C+B was 40.10 ± 1.92 and with C+B was 38.41 ± 2.00, while for P. hybrida with M+C+B was 39.33 ± 2.05, which is signifi cantly higher as compared with the non-amended treatment. Urease activity at M+C+B application in soil with P. hybrida was 83.22 ± 5.54 mg urea g-1 soil h-1, which was much higher than that of N. alata. In general enzyme activity enhanced in the soil with N. alata or P. hybrida along with soil amendments. It shows that application of these organic amendments individually or in combination with N. alata or P. hybrida increased enzyme activities possibly through affecting soil nutrient dynamics

2023-01-01T00:00:00Z Rehman, Hamid Debik, Eyup Ulucan-Altuntas, Kubra Manav-Demir, Neslihan Canci, Baris Iqbal, Mazhar Barros García, Rocío ur Rehman, Wasif Mohanty, Sanjay K Khan, Aqib Hassan Ali https://hdl.handle.net/10259/11737 2026-05-28T00:05:35Z 2025-12-01T00:00:00Z

Bioleaching of waste-derived rare earth elements: An integrated approach with meta-analysis and predictive analytics for scale-up Rehman, Hamid; Debik, Eyup; Ulucan-Altuntas, Kubra; Manav-Demir, Neslihan; Canci, Baris; Iqbal, Mazhar; Barros García, Rocío; ur Rehman, Wasif; Mohanty, Sanjay K; Khan, Aqib Hassan Ali This review provides a comprehensive, data-driven perspective on rare earth element (REE) recoveries from various waste streams by bioleaching, integrating mechanistic insights, microbial performance data, advanced statistical and machine learning tools. A total of 77 observations across 10 waste types were analyzed via Bayesian meta-analysis, yielding an average REE recovery of 56.2 % (95 % credible interval: 51.1–61.0 %). Among the waste types, coal fly ash and electronic waste (e-waste) demonstrated the highest recoveries (76 % and 89 %, respectively). Fungi, particularly Aspergillus and Penicillium, performed better than bacteria, despite being less commonly used in bioleaching studies. Fungal-only systems typically achieved 60–76 % recovery, whereas values above 85 % were reported when fungal bioleaching was combined with chemical or physical pretreatments. Acidophilic bacteria exhibited the highest recovery efficiency among the bacterial species (66 %). The microbial consortia (combinations of fungi and bacteria) achieved up to 76 % recovery efficiency due to synergistic interactions. Importantly, many of the highest recoveries (≥90 %) reported in the literature refer to base metals such as Cu, Ni, and Zn, which are more easily solubilized than REEs; harmonizing claims requires distinguishing organism-only effects from organism + pretreatment strategies, and base metal recoveries from REE recoveries. Structural equation modeling (SEM) revealed that factors such as pH, type of waste, and process parameters, played key roles in determining REE recovery success. Among these, process variables (e.g. pH and pulp density) had the strongest direct influence (β = 0.895). Machine learning models, including support vector machine regression (SVMR) and K-nearest neighbor regression (KNNR), further highlight the importance of metal content, process parameters, and microbial presence. These models performed well, with R² values of 0.87 for SVMR and 0.787 for KNNR. Overall, this integrated approach demonstrates the potential for scaling-up bioleaching processes. By combining biological insights with predictive analytics, this integrated framework demonstrates strong foundation for industrial-scale REE recovery and supports shifting toward a more circular and sustainable economy

2025-12-01T00:00:00Z Wohlleben, Wendel Adam, Veronique Camilleri Lledó, Pau Dekkers, Susan Durand, Cyrille Haase, Andrea Soeteman-Hernandez, Lya G. Livieri, Arianna Martel Martín, Sonia Pizzol, Lisa Pozuelo Rollón, Blanca Prenner, Stefanie Rein, Christian van Someren, Eugene Fransman, Wouter Zabeo, Alex Rumbo Lorenzo, Carlos Schmid, Otmar Hristozov, Danail https://hdl.handle.net/10259/11735 2026-05-28T00:05:37Z 2025-11-01T00:00:00Z

A suite of tools for safe-and-sustainable-by-design advanced materials from the EU projects DIAGONAL, HARMLESS and SUNSHINE Wohlleben, Wendel; Adam, Veronique; Camilleri Lledó, Pau; Dekkers, Susan; Durand, Cyrille; Haase, Andrea; Soeteman-Hernandez, Lya G.; Livieri, Arianna; Martel Martín, Sonia; Pizzol, Lisa; Pozuelo Rollón, Blanca; Prenner, Stefanie; Rein, Christian; van Someren, Eugene; Fransman, Wouter; Zabeo, Alex; Rumbo Lorenzo, Carlos; Schmid, Otmar; Hristozov, Danail Multi-component nanomaterials (MCNM) and High Aspect Ratio Nanomaterials (HARN) are advanced materials that present innovation potential but also challenge the innovation by Safe and Sustainable by Design (SSbD) principles. In 2021 to 2025, three EU-funded sister projects developed and implemented SSbD concepts in digital tools that are applicable to MCNM and HARNs despite their respective unique properties. The projects jointly established a tiered suite of tools that serves both industrial, SME (small and medium enterprise) and regulatory stakeholders. The tools for innovators are tiered by StageGate phases (projects SUNSHINE and HARMLESS) or organized in transversal topics (project DIAGONAL). Also the tools for regulatory preparedness comprise a range from simple to elaborate approaches. Key achievements include the alignment of tools for innovators and for regulators via a high overlap of the questions asked, and the systematic tiering of targeted input that is required. The suite of tools thus supports the OECD's Safe and Sustainable Innovation Approach (SSIA). With specific value to SME innovators, tools were developed that lower the previously perceived hurdles to implementation of SSbD concepts in product development. The suite of tools is demonstrated on three MCNM or HARN case studies provided by partners from industry and SMEs, specifically anti-stick coatings for baking trays (SiC@TiO2), automotive catalysts (doped oxide perovskites) and flexible electronics (Ag nanowires). However, the cases also shed a light on remaining challenges in the SSbD concept that are not solved by tools alone, most notably the uncertainty of decision-support at early stages and the complexity of data gathering at later stages, which also implies a need of increasing data exchange among value chain actors while allowing actors to generate and protect intellectual property

2025-11-01T00:00:00Z