For 60 years, the Environmental Science & Technology research community has helped to define the fields of environmental science and engineering. The research topics have evolved over time to respond to the most pressing societal needs, from treatment technologies and pollution control strategies to address severe environmental pollution, to pollution prevention and industrial ecology to help mitigate emissions, and to defining planetary boundaries for sustainability. Since ES&T launched in 1967, it has helped to create a robust global network of researchers, with researchers from 144 countries now contributing to address critical global environmental and human health challenges. Throughout its six decades, ES&T research has remained highly relevant to understanding, addressing, and advancing solutions to both current and emerging challenges and for developing science-based policies to protect the environment and human health. We are optimistic that the ES&T research community will continue to serve to help shape research and action toward a healthier, resilient, and sustainable planet for all of us in the next 60 years.
Optimizing photocatalytic oxidation (PCO) of volatile organic compounds (VOCs) typically relies on one-variable-at-a-time (OVAT) methods, which overlook crucial interactions and may not result in optimized process conditions. In this study, we apply design of experiments (DoE) to systematically evaluate the effects of relative humidity (RH) and light intensity (LI) on photomineralization of acetone over two SrTiO3 (STO) photocatalysts: cubic (c-STO) and {110}-truncated (trd-STO). Using a three level full-factorial design (RH = 2, 31, or 54%; LI = 0.6, 1.2, or 2.4 mW·cm-2), we reveal statistically significant interactions between RH, LI, and photocatalyst morphology. trd-STO outperformed cubic-STO, exhibiting high reaction rates in a broader optimum range, greater stability, and superior light efficiency under conditions of high humidity. Notably, while a high relative humidity of 54% severely inhibited the acetone conversion using cubic-STO, trd-STO maintained activity. By polynomial regression models and isoresponse surface plots, we determined the optimal operating conditions and highlight that variable interactions are strongly crystal facet-dependent. Our results demonstrate that DoE is a powerful tool for identifying "sweet spots" in VOC photomineralization and to reveal how surface facet engineering impacts photocatalytic behavior under realistic environmental conditions.
Material selection for membrane distillation (MD) remains dominated by empirical trial-and-error. This study presents the first application of Ansys Granta materials informatics to thermally driven membrane separation, integrating database-driven screening, direct contact MD (DCMD) experimental validation, and life cycle assessment (LCA) to identify optimal membrane materials across diverse circular water economy contexts. Twenty-two candidates spanning polymers, biopolymers, and ceramics were evaluated against thermal and mechanical performance, vapor transport efficiency, and chemical compatibility across five aggressive feed environments. LCA at a representative 10,000 m3·day-1 facility scale reveals a counterintuitive lifecycle inversion: PEEK and PES, the two highest production-phase energy materials among all 22 candidates achieving net-positive lifecycle sustainability through robust end-of-life recycling, demonstrate that the production carbon footprint is a misleading proxy for environmental performance, a finding with implications beyond membrane engineering. Three commercial membranespolypropylene (PP), polyvinylidene fluoride (PVDF), and polytetrafluoroethylene (PTFE)validated the informatics predictions through DCMD desalination testing, achieving fluxes of 14 ± 2, 11 ± 3, and 29 ± 4 kg·m-2·h-1 with >99% salt rejection. Predicted flux agreed closely (R2 ≈ 1); styrene-butadiene-styrene (SBS) exhibited the highest theoretical flux (413 kg·m-2·h-1), a theoretical upper bound reflecting intrinsic vapor transmission rather than practical MD performance. Cross-property analysis identified maximum service temperature and tensile strength as the strongest correlated pair (r = 0.67). The multicriteria performance index (Π) reveals fundamentally context-dependent rankings: titania leads under balanced weighting (Π = 0.67), SBS under flux priority (Π = 0.77), and PVC under sustainability priority (Π = 0.77). No universally optimal material exists; this replicable framework replaces single-criterion optimization with transparent, application-specific material guidance for circular water economy MD deployment.
Achieving high biochemical production in biotransformations of renewable resources requires using concentrated cultures that not only generate the product of interest but also produce abundant microbial cell waste. We explored the concept of gaining value from microbial cells by producing intracellular products in tandem with a desired extracellular product. Specifically, we engineered a strain ofNovosphingobium aromaticivorans to extracellularly produce 2-pyrone-4,6-dicarboxylic acid (PDC) from aromatic substrates and to intracellularly accumulate astaxanthin along with coenzyme Q10, all of which are products of industrial interest. Achieving the goal of concurrent production of intracellular and extracellular products required the creative application of bioreactor engineering principles. Although a continuously fed membrane bioreactor (MBR) maximized extracellular product biosynthesis, it had a negative effect on intracellular product accumulation. However, operating the MBR as a sequencing batch reactor (MBR-SBR) with a step-feed resulted in stable concurrent production of both extracellular and intracellular products. With aromatics extracted from poplar biomass, we achieved productivities of 1.14 g of PDC/L-h for the extracellular product and 0.04 mg of astaxanthin/L-h and 0.64 mg of CoQ10/L-h for intracellular products, respectively. Our findings demonstrate that the mode of operation of a bioreactor impacts the simultaneous production of intracellular and extracellular products byN. aromaticivorans.
Produced water (PW), generated during oil and gas extraction, is a complex wastewater characterized by high salinity, hydrocarbons, and heavy metals, making treatment and beneficial reuse challenging. Bioremediation offers a sustainable treatment alternative, but the extreme physicochemical conditions of PW inhibit the growth and activity of most conventional microorganisms. This study evaluates the bioremediation potential and heavy metal tolerance mechanisms of the halophile, Modicisalibacter sp. strain Wilcox, isolated from PW. We examined its growth and benzene, toluene, ethylbenzene, and xylenes (BTEX) degradation capability under elevated salinity in defined media and raw PW, while assessing the effects and fate of metals individually and in multimetal mixtures. Strain Wilcox demonstrated exceptional tolerance to individual metals, including 100 mM arsenate, 100 mM manganese, 12.5 mM cadmium, and 7 mM zinc. Increasing metal concentrations and multimetal mixtures reduced BTEX degradation rates, with toxicity varying by metal species and salinity. In addition to hydrocarbon degradation, the strain removed 75-99% of Mn2+, Zn2+, Se4+, Pb2+, Cr3+, and Cu2+ via biosorption and bioaccumulation. Functional genomic analysis supported these phenotypes, revealing >70 metal resistance genes, 58 osmoregulation genes, and ∼70 genes associated with cross-protection against salt and metal stress, highlighting strain Wilcox's potential for bioremediation of PW.
Locally enhanced electric field treatment (LEEFT) has emerged as a promising chlorine-free approach for water disinfection. However, its practical deployment has been limited by challenges in electrode durability and system scalability. Herein, we report a robust stainless-steel brush designed to enable long-term operation and scalability of LEEFT electrodes. A tubular reactor with coaxial electrodes featuring the brush as the center electrode was developed to combine both macroscale and microscale electric field enhancements. Operational parameters, including waveform, frequency, voltage, and flow rate, were systematically optimized to maximize microbial inactivation while minimizing metal release. Flow cytometry and control experiments revealed electroporation, assisted by reactive oxygen species, as the primary disinfection mechanism. Under optimal unipolar pulse conditions with high duty cycle and frequency, the system achieved efficient inactivation at voltages in the tens of volts range. Notably, the LEEFT system with the brush electrode has remained effective for about half a year with minimal metal release, representing a 10-fold increase in lifespan compared to previous LEEFT configurations. This work demonstrates a scalable, durable, and chemical-free solution for decentralized and sustainable water disinfection.
UV C LEDs are an emerging technology offering wavelength-specific control for microbial inactivation in water and wastewater treatment. As these systems advance, complementary monitoring methods are needed to accurately evaluate the treatment performance and viral persistence in complex effluents. This study developed and evaluated an in-line granular activated carbon (GAC) sampling device designed to concentrate large volumes of wastewater from a full-scale UV C LED reactor. Compared to 1 L grab samples, GAC-concentrated samples recovered significantly higher nucleic acid concentrations (p < 0.001). Viral diversity was also more abundant in GAC-concentrated samples, with 85.7% abundance of Adenoviridae and multiple codetected viral families, whereas grabs had 95% Adenoviridae abundance with minimal diversity of other viral families. Likewise, grab samples were found to be more sensitive to matrix effects compared with the GAC-concentrated samples, with significant negative associations between nucleic acid yield and flow and UV transmittance. Collectively, these findings demonstrate that the in-line GAC approach can overcome the limitations of grab samples, providing a scalable, operationally compatible solution for real-time monitoring of viruses during wastewater treatment.
Probable sources of metal-(loid) contamination in Hurricane Harvey floodwater remnants from diverse land use settings in Houston, Texas, were investigated. The primary novelties of this work are that we (i) analyzed a wide suite of 51 elements, including rare earths and (ii) implemented two independent multivariate statistical techniques to obtain clues to metal-(loid) sources. This approach differs from many previous studies that simply reported the concentrations of a limited number of metals in hurricane floodwaters. Hierarchical cluster analysis and principal component analysis both resolved three major and statistically distinct source categories: crustal materials, vehicular emissions, and the built environment. The crustal source was confirmed using light rare earth ternary diagrams, yttrium/holmium ratios, cerium and europium anomalies, and Oddo-Harkins patterns. The influence of motor vehicles and traffic was identified using enrichment factors and simultaneous barium-cadmium-antimony and gallium-cadmium-antimony three-component variations. Efflux from the built environment was validated via signature elemental ratios and zinc-tin-lead ternary variations. Overall, the deluge appears to have mobilized metal-(loid)-s with vehicular residues and building materials contributing substantially to floodwater contamination beyond natural crustal dissolution. The source attribution framework developed herein provides a generalized approach to identify metal-(loid) sources in any flood-prone urban environment.
Selenium (Se) is an essential micronutrient but toxic at high concentrations, posing challenges for water treatment. This study investigated the removal of selenate (SeO4 2-) and selenite (SeO3 2-) using the strong-base anion-exchange resin IRA-900, particularly in the presence of competing sulfate (SO4 2-). The performance of the commercially available resin IRA-900 was systematically investigated. The batch equilibrium behavior was studied in both single- and binary-component systems, and the kinetic behavior was investigated in single-component systems. Results confirmed a selectivity order of SeO4 2- > SO4 2- > SeO3 2-, indicating preferential SeO4 2- removal over competing SO4 2- but lower affinity for SeO3 2-. The maximum total exchange capacity was determined to be 2.04 mequiv/g. Furthermore, SeO3 2- uptake was found to be pH-dependent, whereas SeO4 2- uptake remained stable across a broad pH range. From a modeling perspective, the Law of Mass Action model effectively described equilibrium data, and a transport-reaction modeling framework captured removal kinetics of oxyanions including film and intraparticle diffusion. Finally, X-ray photoelectron spectroscopy confirmed ion exchange between chloride and Se oxyanions as the primary removal mechanism. These findings provide fundamental insights into the removal of Se oxyanions from aqueous solutions by ion exchange.
Selenium (Se) contamination in flue-gas desulfurization (FGD) wastewater from coal-fired power plants poses significant environmental and regulatory challenges. Here, we developed and optimized a three-dimensional electrochemical reactor (3DER) with carbon-based particle electrodes (PEs) to remove Se-(IV). Compared with conventional two-dimensional systems, the 3DER provides an enlarged electrode surface area, enabling faster removal kinetics and higher resilience without regeneration. Reactor performance was systematically evaluated as a function of PE geometry, recirculation rate, cell potential, and anode-to-cathode (A:C) chamber ratio. The optimized configuration (A:C = 1:2, E cell = -2.1 V, recirculation rate 3.3 mL min-1) balanced cathodic efficiency while minimizing anodic parasitic reactions. In synthetic wastewater containing 0.1 mM Se-(IV), the single-pass 3DER achieved steadily increasing performance, with hourly removal improving from 61.3% in the first hour to 68.1% by the 12th hour. Applied to real FGD wastewater, the system maintained an average hourly removal of 51.7% (4.2 mg of Se L-1 h-1) without regeneration and reached a specific energy consumption as low as 0.03 kWh g-1 Se despite high chloride levels. Competing ions, including Mn and Si, further enhanced the Se reduction by forming oxide layers and rejecting Cl- from the electrode surface. Enhanced kinetics under elevated Se-(IV) loadings yielded a peak removal of 74.4% (17.5 mg of Se L-1 h-1). These results demonstrate robust and efficient removal performance of the 3DER, supporting its promise for selenium-rich wastewater treatment and future scale-up.
On-site water reuse can provide water for nonpotable applications, but ensuring long-term performance and managing treatment failures is challenging without dedicated monitoring personnel. This study proposes a risk-based framework to determine enteric pathogen log-removal targets (LRTs) as a function of operational monitoring frequency. The framework integrates (i) quantitative microbial risk assessment, (ii) modeled pathogen concentrations at three collection scales, and (iii) failure models for three treatment configurations. As an example, LRTs were calculated considering different monitoring frequencies for greywater reuse. Results show that smaller systems require less frequent monitoring due to lower pathogen occurrence compared to larger systems, e.g., >1 day at a 5-people scale vs <500 s for a 1000-people system to meet norovirus risk with a bimodal treatment barrier failing up to four times per year. Incorporating a residual disinfectant or multiple barriers extends the required monitoring intervals. While LRTs are comparable across collection scales, this study highlights a key advantage of small systemsreduced monitoring requirementscontrasting prior work that found no benefits of downsizing in terms of treatment train design. This framework can support technology developers in quantifying trade-offs between treatment and monitoring and aid regulators in establishing monitoring requirements for on-site water reuse.
Stormwater systems increasingly rely on polymer-based materials such as polyvinyl chloride (PVC), polyethylene (PE), high-density polyethylene (HDPE), and polypropylene (PP) due to their durability, low cost, and corrosion resistance. However, these materials are susceptible to photochemical, abiotic chemical (e.g., oxidation/chlorination from disinfectants and oxidants), biological (microbial/enzymatic), and mechanical degradation, resulting in the release of micro- and nanoplastics (MNPs) throughout their service life. This perspective critically examines the mechanisms underlying MNP formation in stormwater infrastructure - including ultraviolet (UV)/photoaging, chemical oxidation, hydraulic abrasion, and bed-load interactions - and evaluates laboratory methods used to study these processes. Standardized tools such as the Taber abrasion, Darmstadt rigs, circulating-loop systems, UV weathering, and chemical aging protocols are evaluated for their ability to simulate real-world conditions and quantify plastic particle release. Existing methods primarily quantify material durability but rarely capture or characterize released MNPs, leading to gaps in emission factor development and poor translation of laboratory results to stormwater environments. Analytical techniques such as μ-FTIR, Raman spectroscopy, SEM/EDX, and Py-GC/MS are reviewed for their complementary roles in particle identification and quantification. Key methodological gaps are identified, including inconsistent sampling protocols, limited detection of nanoplastics (NPs), unrealistic hydraulic simulations, and sparse comparisons between recycled and virgin pipe materials. To address these issues, this perspective proposes a hydraulically realistic circulating-loop platform capable of integrating stormwater-like hydraulics with UV and chemical aging, as well as analytical techniques to quantify MNP emissions from pipe materials under environmentally relevant conditions. This integrated framework supports the development of predictive models that link material degradation to MNP release, thereby advancing sustainable infrastructure design and plastic pollution mitigation in water systems.
Climate change-related increases in organic carbon in surface waters may present challenges in meeting regulatory requirements with regard to drinking water quality. Treatment adaptation that alters natural organic matter (NOM), metal oxides, and water chemistry can have a downstream influence on lead release. We compared the effect of the coagulant and filter type on water quality and lead release in a galvanic lead solder-copper system. Aluminum sulfate (alum), polyaluminum chloride (PACl), anthracite/sand, and granular activated carbon (GAC) were tested in a pilot-scale system. Lead release was evaluated in a bench-scale dump and fill experiment with treated water dosed with 0-2 ppm zinc-orthophosphate. GAC contactors reduced organic carbon in both systems and had a strong protective effect on lead release, likely due to less NOM complexation and improved orthophosphate performance. At equivalent Al doses, organic carbon removal was comparable between PACl and alum, but PACl showed slower GAC exhaustion rates, improving the removal efficiency. PACl was linked with increased galvanic corrosion due to higher CSMR. Zinc-orthophosphate mitigated galvanic corrosion of lead solder. Treatment facilities can decrease lead release by removing NOM, but alternative coagulants that may be considered for enhanced NOM removal can increase the chloride concentration and have detrimental effects as well.
Krypton chloride excimer (KrCl*) lamps emitting at 222 nm have recently been shown to enhance the fluence-normalized rates of micropollutant abatement in UV-oxidation and -reduction systems relative to conventional, 254 nm light sources. Here, we investigated the destruction of short- and long-chain perfluoroalkyl acids under 222 nm irradiation from KrCl* lamps in the presence and absence of sulfite. At pH 12 under anaerobic conditions, all compounds were degraded under 222 nm irradiation with apparent quantum yields (Φapp,PFAS) increasing in the order 0.036 (perfluorobutanesulfonate (PFBS)), 0.124 (perfluorooctanesulfonate (PFOS)), 0.374 (perfluorooctanoic acid (PFOA)), and 0.822 (perfluorobutanoic acid (PFBA)), which are markedly higher than quantum yields reported previously at pH 8.5. Multiple lines of evidence suggest that the observed UV222 only degradation of perfluorocarboxylic acids is due to both direct photolysis and eaq --based destruction, the latter enabled by photolysis of hydroxide ions at pH 12. In contrast, PFBS and PFOS degradation in the UV222 only system is due to eaq --mediated destruction, not true direct photolysis. To compare the effectiveness of 222 nm KrCl* lamps with 254 nm, the UV/sulfite system was tested on two complex water matrices: (i) a reverse osmosis concentrate (ROC) spiked with short- and long-chain perfluoroalkyl acids and (ii) an aqueous film forming foam (AFFF). The extent of PFAS destruction in these complex matrices was greater for 222 nm irradiation relative to 254 nm by up to 6-fold when normalized to incident fluence. Overall, this study provides fundamental insight into the UV-based degradation of perfluoroalkyl acids at 222 nm and suggests that KrCl* lamps may provide improved performance compared to conventional 254 nm sources in UV/sulfite ARP for PFAS destruction in complex water matrices.
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The U.S. Environmental Protection Agency requires replacement of all lead service lines within 10 years, yet accurately identifying buried lead pipes remains a major challenge. Existing detection methods, such as excavations, electrochemical sensors, or ground-penetrating radar, are often expensive, disruptive, or sensitive to environmental noise. We present a noninvasive approach that combines physics-based finite element analysis (FEA) surrogate modeling with machine learning (ML) to detect lead pipes efficiently. A computationally efficient FEA model was developed to simulate the dynamic behavior of buried copper and lead pipes, incorporating key features such as stop-valve openings to enable realistic loading conditions. Transient dynamic simulations analyzed mechanical responses, specifically pipe acceleration, under varying geometries and loading scenarios. Over 13,000 synthetic observations were generated, with added noise and signal masking to reflect real-world sensor limitations. Seven ML models were trained on these acceleration signals to classify pipe material. K-nearest neighbor (KNN) and Extreme Gradient Boosting (XGBoost) achieved the highest performance, each reaching 99.9% classification accuracy. This integrated modeling and ML framework offers a scalable, cost-effective method for utilities to locate and replace lead pipes, supporting regulatory compliance while minimizing operational disruptions and resource expenditures.
Properly operated and maintained drinking water distribution system (DWDS) storage tanks are crucial for allocating safe drinking water, but varying operational processes and infrequent maintenance can result in water quality degradation, including disinfectant residual loss, sediment accumulation, bacterial growth, and potential contamination. This study assessed how the physical, chemical, and hydraulic characteristics of representative chlorinated DWDS tanks relate to bacterial communities in water and sediment; investigated water quality variation by depth within tanks; and explored the infrastructure and management characteristics influencing bacterial community composition in tanks. Bulk water and sediment samples were collected from seven tanks in a chlorinated DWDS system, and 16S rRNA gene amplicon sequencing was used to characterize the bacterial community. Bulk water and sediment communities were distinct, dominated by Alphaproteobacteria and Gammaproteobacteria, respectively. Spatial variations as a function of distance from the treatment plant, tank-specific characteristics, and sediment accumulation were found to shape bacterial communities within tanks. Total coliforms and Escherichia coli were undetectable in all water samples, but genetic signatures indicated the presence of multiple genera associated with opportunistic pathogens (OPs). This study aims to establish a deeper understanding of the bacterial community within DWDS tanks and the impact that tank conditions and characteristics have on DWDS water quality.
Ozonation is one of the most promising advanced oxidation processes to be implemented as quaternary treatment for the removal of micropollutants in wastewater treatment plants. However, there are some knowledge gaps that limit its implementation. First, the removal efficiency is not known for all pollutants, and second, knowledge about degradation byproducts is limited, as well as the toxicity of the treated waters. In this work, the removal efficiency of azathioprine and flutamide is studied, as well as the transformation products formed during ozonation. A lab-scale reactor was used for ozonation of the drugs in pure water, with ambient air as the source for ozone generation and liquid chromatography-ion mobility-high-resolution mass spectrometry for time-resolved process monitoring. Notably, azathioprine and flutamide were not completely removed by ozonation, with 49-54% remaining after the treatment. Furthermore, two transformation products of azathioprine and three of flutamide were identified, including previously unreported nitroaromatic transformation products of flutamide. While both parent compounds showed relatively low predicted toxicity, transformation products of flutamide exhibited higher predicted chronic toxicity. These results highlight the importance of considering transformation products during ozonation and suggest possible nitration reactions when ozone is generated from ambient air. Further experiments are needed to confirm this.
Donnan dialysis (DD) is a promising approach for selectively recovering ammonium ions from wastewater, owing to its simplicity and low energy consumption. However, the role of ion sorption and desorption in cation exchange membranes (CEMs), particularly interactions between ammonium ions (NH4 +) and competing ions (e.g., sodium Na+), has often been overlooked. Our experimental results revealed a shift in the Donnan equilibrium caused by the preoccupied counterions in the CEM. For example, when the feed and draw solutions were in a 1:1 concentration ratio, the expected ammonium recovery efficiency was 50%. However, the NH4Cl-presoaked membrane resulted in an increase of 19.1 ± 0.5% in the solution NH4 + concentration and a decrease of 18.8 ± 0.6% in the Na+ concentration. Conversely, the NaCl-soaked membrane showed an 18.9 ± 1.6% reduction in NH4 + and a 23.0 ± 1.3% increase in Na+. The difference indicated that the ion exchange capacity of the membrane and counterion uptake could shift the equilibrium of the DD process. We further analyzed the process kinetics and developed a nonsteady-state model incorporating ion sorption capacity to describe the behavior. Our results confirmed that presoaked ions shifted the final DD equilibrium, potentially due to differences in their affinity and geometry. To summarize, this study provides new insights into the mechanisms of Donnan dialysis by accounting for ion sorption and offers insights for the design of more efficient and effective separation processes for ammonium recovery.
When samples containing perfluoroalkyl and polyfluoroalkyl substances (PFAS) are filtered prior to analysis, inadvertent adsorption onto membrane materials can result in concentration underestimations. Herein, we systematically examined the adsorption of six PFAS (PFOA, PFOS, PFNA, PFHxS, PFBS, GenX) onto 11 membrane syringe filters, differing in manufacturer, polymer material, diameter, and/or pore size under various experimental conditions. We perform a comprehensive characterization of the membrane materials to determine differences in morphology, zeta potential, porosity, surface area, and roughness. Evaluation of postfiltration PFAS recovery demonstrated significant impacts of filter material and surface area (related to pore size and diameter), initial PFAS concentration, water pH, and the co-occurrence of cations and anions. Longer-chain PFAS more readily adsorb than shorter-chain PFAS for all filter materials under all experimental conditions. Machine learning predictions of Abraham's solute descriptors were used to qualitatively assess the predominant forces governing PFAS adsorption onto different materials. While differences in hydrogen-bonding ability exert influence, hydrophobicity and electrostatic interactions are the main drivers of adsorption, along with significant impacts of the water matrix. We recommend polypropylene, mixed cellulose ester, or glass fiber filters with larger pore sizes and smaller diameters to filter PFAS-containing samples, and we discourage the use of nylon-based filters. These findings offer important insights for optimizing PFAS sample preparation and improving membrane design for effective PFAS removal.