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PurposeThis study aims to introduce the University Handprint Framework – a novel method for quantifying the external positive impacts (“handprints”) of sustainability actions undertaken by higher education institutions. It aims to fill a critical gap in current sustainability tracking systems by enabling universities to measure their contributions to societal and environmental outcomes beyond campus boundaries. Design/methodology/approachThe study presents a case study of a project-based sustainability course that partnered students with external organizations to implement climate-related solutions. The study calculated the university’s potential handprint associated with the course and informed the development of the University Handprint Framework. Data challenges, such as availability, tracking, attribution and double counting of emissions, were addressed in the method’s development to ensure methodological rigor. FindingsThis study results revealed that the course enabled partner organizations to reduce greenhouse gas emissions by an estimated 7.04E + 05 kg CO2-eq, which demonstrated a quantifiable, university-enabled carbon handprint beyond campus boundaries. Practical implicationsThe framework offers universities a practical tool to highlight their broader societal contributions and can inform policy, reporting and investment in sustainability education and research. Given universities’ pivotal role in research dissemination, sustainability education and climate change mitigation, showcasing these positive impacts is essential. Originality/valueThis is the first known framework tailored to higher education that enables structured quantification of both potential (ex ante) and realized (ex-post) handprints. It complements existing tools and adds a new dimension to sustainability planning and impact tracking in academia. 

Abstract Traditional health surveillance methods play a critical role in public health safety but are limited by the data collection speed, coverage, and resource requirements. Wastewater‐based epidemiology (WBE) has emerged as a cost‐effective and rapid tool for detecting infectious diseases through sewage analysis of disease biomarkers. Recent advances in big data analytics have enhanced public health monitoring by enabling predictive modeling and early risk detection. This paper explores the application of machine learning (ML) in WBE data analytics, with a focus on infectious disease surveillance and forecasting. We highlight the advantages of ML‐driven WBE prediction models, including their ability to process multimodal data, predict disease trends, and evaluate policy impacts through scenario simulations. We also examine challenges such as data quality, model interpretability, and integration with existing public health infrastructure. The integration of ML WBE data analytics enables rapid health data collection, analysis, and interpretation that are not feasible in current surveillance approaches. By leveraging ML and WBE, decision makers can reduce cognitive biases and enhance data‐driven responses to public health threats. As global health risks evolve, the synergy between WBE, ML, and data‐driven decision‐making holds significant potential for improving public health outcomes. 

ABSTRACT This study explores how a sieving step of waste cellulosic fiber and fine (WCFF) mixture affects the performance of WCFF‐loaded polypropylene (PP) composites and whether the separation of fines from fibers offers an added benefit. The WCFF samples were downsized, and four different filler size ranges were sieved using a series of mesh sizes from 4 to 0.85 mm. The WCFF/PP composites were then compounded at 20 wt.% loading of WCFF using a twin‐screw extruder. Incorporating WCFF increased the tensile strength to 41.28 MPa and the modulus to 3207 MPa, accounting for 28% and 38% enhancements, respectively. Interestingly, the greatest improvements were associated with the nonsieved WCFF case, and the sieved WCFF fibers provided only marginal enhancements over virgin PP. The outperformance of nonsieved WCFF was attributed to the synergistic reinforcement of hybrid fibers and fines as well as the maintenance of longer fibers in the system. However, the strain at break and impact strength of PP decreased after introducing WCFF. Moreover, the complex viscosity and storage modulus increased with an increase in the filler size, due to the formation of a more effective percolative network. The PP's crystallinity exhibited a relatively strong dependency on the sieving, where WCFF samples with short‐aspect‐ratio fillers promoted the crystallinity significantly. It was also found that the WCFF degradation onset temperature increased once it was incorporated into PP. This study suggests that waste cellulosic feedstocks can be utilized as a reinforcement without additional sieving to manufacture high‐performance and cost‐effective composites. 

Introducing facile regenerability into adsorbent materials can potentially increase sustainability in water treatment systems enabled by extended use. Herein, we detail our recent syntheses of dynamic nanostructured worm-gel materials and their implementation as regenerable adsorbents for water treatment. Photo-controlled atom transfer radical polymerization-induced self-assembly (PhotoATR-PISA) was employed to synthesize various polymer nanostructures, including dispersed spheres, worms, and vesicles, and nanostructured worm-gels, via the synthesis and simultaneous in situ assembly of BAB triblock copolymers. Two dynamic, disulfide-functionalized macroinitiators (SS-MI-1 and 2)with different degree of polymerization and one nondynamic macroinitiator (CC-MI) were synthesized via polymerization of oligo(ethylene glycol methyl ether methacrylate) (OEGMA). PhotoATR-PISA was then implemented via the chain extension fromSS-MI-1, 2 and CC-MI with glycidyl methacrylate (GMA) or benzyl methacrylate (BMA) forming BAB-type triblock copolymer nanoparticles in situ. The final morphology in PhotoATR-PISA was influenced not only by conventional factors such as solids content and block DP but also by unimer exchange rates yielding arrested, nanostructured worm-gels in many instances and arrested vesicle-gels in one instance. These PISA-gel materials were implemented as adsorbents for phenanthrene, a model compound registered as a priority pollutant by the US EPA, from aqueous solutions. The chemical tunability of these materials enabled enhanced, targeted removal of phenanthrene facilitated by π−π interactions, as evidenced by the increased adsorption capacities of PBMA-based PISA-gels when compared to PGMA. Furthermore, the dynamicity of disulfide worm-gels (SS-WG) enabled disulfide exchange-induced regeneration stimulated by UV light. This UV-responsive exchange was investigated for POEGMA macroinitiators as well as dissolved triblock copolymers, dispersed nanoparticles, and SS-WG materials. Finally, the regenerability of the PNT-saturated SS-WG adsorbents induced by UV irradiation (λ = 365 nm) was examined and compared with control worm-gels absent of disulfides, demonstrating enhanced recovery of adsorption capacity under mild irradiation conditions. 

Microbial cell factories offer an eco-friendly alternative for transforming raw materials into commercially valuable products because of their reduced carbon impact compared to conventional industrial procedures. These systems often depend on lignocellulosic feedstocks, mainly pentose and hexose sugars. One major hurdle when utilizing these sugars, especially glucose, is balancing carbon allocation to satisfy energy, cofactor, and other essential component needs for cellular proliferation while maintaining a robust yield. Nearly half or more of this carbon is inevitably lost as CO2 during the biosynthesis of regular metabolic necessities. This loss lowers the production yield and compromises the benefit of reducing greenhouse gas emissions—a fundamental advantage of biomanufacturing. This review paper posits the perspectives of using CO2 from the atmosphere, industrial wastes, or the exhausted gases generated in microbial fermentation as a feedstock for biomanufacturing. Achieving the carbon-neutral or -negative goals is addressed under two main strategies. The one-step strategy uses novel metabolic pathway design and engineering approaches to directly fix the CO2 toward the synthesis of the desired products. Due to the limitation of the yield and efficiency in one-step fixation, the two-step strategy aims to integrate firstly the electrochemical conversion of the exhausted CO2 into C1/C2 products such as formate, methanol, acetate, and ethanol, and a second fermentation process to utilize the CO2-derived C1/C2 chemicals or co-utilize C5/C6 sugars and C1/C2 chemicals for product formation. The potential and challenges of using CO2 as a feedstock for future biomanufacturing of fuels and chemicals are also discussed. 

Smart, multi-stimuli-responsive nanogels that possess dynamic covalent bonds (DCBs) exhibit reversibility under equilibrium conditions allowing for controlled disassembly and release of cargo. These nanomaterials have innumerable applications in areas including drug delivery, sensors, soft actuators, smart surfaces, and environmental remediation. In this work, we implement one-pot, photo-controlled atom transfer radical polymerization-induced self-assembly (PhotoATR-PISA), mediated by UV light (λ = 365 nm) and parts per million (ppm) levels (ca. <20 ppm) of a copper(II) bromide catalyst, to fabricate dual crosslinked, polymeric nanogels with tunable orthogonal reversible covalent (TORC-NGs) core-crosslinks (CCLs). These TORC-NGs were crosslinked efficiently via coumarin photodimerization which occured simultaneously during polymerization using coumarin-functionalized methacrylate crosslinkers (CouMA). At the same time, crosslinking of nanocarriers with N,N-cystamine bismethacrylamide (CBMA) introduced orthogonal, redox-responsive, disulfide CCLs. Furthermore, incorporation of poly(glycidyl methacrylate) (PGMA) core-forming segments provided a simple handle for switchable solubility through acid-catalyzed ring-opening hydrolysis of pendant epoxide groups. In this way, the kinetics of release were tailored by the pH of the surrounding media. Thus, these TORC-NG systems showed coupled pH-, redox- and photo-responsive controlled release and disassembly behavior with full release of cargo only observed in the right sequence of stimuli and only when all three are utilized. The multi-stimuli-responsive nature of these TORC-NGs was successfully utilized herein for the controlled encapsulation and on-demand AND-gate release of hydrophobic Nile Red fluorescent reporters used as drug simulants. Various TORC-NG morphologies were synthesized in this report including nanosphere, worm-like and tubesome NGs showing variable release characteristics.