ACS ES&T engineering最新文献

Microalgae-based wastewater treatment has resulted in a paradigm shift toward nutrient removal and simultaneous resource recovery. However, traditionally used microalgal biomass quantification methods are time-consuming and costly, limiting their large-scale use. The aim of this study is to develop a simple and cost-effective image-based method for microalgae quantification, replacing cumbersome traditional techniques. In this study, preprocessed microalgae images and associated optical density data were utilized as inputs. Three feature extraction methods were compared alongside eight machine learning (ML) models, including linear regression (LR), random forest (RF), AdaBoost, gradient boosting (GB), and various neural networks. Among these algorithms, LR with principal component analysis achieved an R² value of 0.97 with the lowest error of 0.039. Combining image analysis and ML removes the need for expensive equipment in microalgae quantification. Sensitivity analysis was performed by varying the train–test splitting ratio. Training time was included in the evaluation, and accounting for energy consumption in the study leads to the achievement of high model performance and energy-efficient ML model utilization.

Microalgae offer a compelling platform for the production of commodity products, due to their superior photosynthetic efficiency, adaptability to nonarable lands and nonpotable water, and their capacity to produce a versatile array of bioproducts, including biofuels and biomaterials. However, the scalability of microalgae as a bioresource has been hindered by challenges such as costly biomass production related to vulnerability to pond crashes during large-scale cultivation. This study presents a pipeline for the genetic engineering and pilot-scale production of biodiesel and thermoplastic polyurethane precursors in the extremophile species Chlamydomonas pacifica. This extremophile microalga exhibits exceptional resilience to high pH (>11.5), high salinity (up to 2% NaCl), and elevated temperatures (up to 42 °C). Initially, we evolved this strain to also have a high tolerance to high light intensity (>2000 μE/m²/s) through mutagenesis, breeding, and selection. We subsequently genetically engineered C. pacifica to significantly enhance lipid production by 28% and starch accumulation by 27%, all without affecting its growth rate. We demonstrated the scalability of these engineered strains by cultivating them in pilot-scale raceway ponds and converting the resulting biomass into biodiesel and thermoplastic polyurethanes. This study showcases the complete cycle of transforming a newly discovered species into a commercially relevant commodity production strain. This research underscores the potential of extremophile algae, including C. pacifica, as a key species for the burgeoning sustainable bioeconomy, offering a viable path forward in mitigating environmental challenges and supporting global bioproduct demands.

Digested livestock wastewater contains high concentrations of NH₄⁺–N and residual pathogens, and the Anammox process is a cost-effective process for treating wastewater with high NH₄⁺–N concentrations. However, advanced nitrogen and pathogen removal from high-strength wastewater by Anammox-based processes, without the addition of an external carbon source, is still a challenge. In this study, a partial nitritation-Anammox coupled with partial denitrification (PN-APD) process was constructed using a step-feed mode to treat digested livestock wastewater. The PN effluent served as the first feeding. Digested livestock wastewater served as the second feeding, providing a carbon source for the APD process. The PN-APD process achieved a nitrogen removal efficiency (NRE) of 97.0 ± 1.3%, with total inorganic nitrogen concentrations of 14.8 ± 4.2 mg N/L in the effluent. The suitable biodegradable COD/NO_x^––N ratio of the APD process after the second feeding is key to achieving advanced nitrogen removal, and the suitable ratio ranges between 0.6 and 1.2. The second feeding had no significant influence on Anammox bacteria abundance, with Candidatus Kuenenia being the dominant species. The PN-APD process also removed total coliforms and enterococci by 3.3 ± 0.3 and 3.0 ± 0.3 log, respectively, meeting wastewater discharge standards without further disinfection. This study provides a novel approach for the cost-effective simultaneous advanced removal of nitrogen and pathogens from high-strength digested livestock wastewater.

Microalgae offer a compelling platform for the production of commodity products, due to their superior photosynthetic efficiency, adaptability to nonarable lands and nonpotable water, and their capacity to produce a versatile array of bioproducts, including biofuels and biomaterials. However, the scalability of microalgae as a bioresource has been hindered by challenges such as costly biomass production related to vulnerability to pond crashes during large-scale cultivation. This study presents a pipeline for the genetic engineering and pilot-scale production of biodiesel and thermoplastic polyurethane precursors in the extremophile species Chlamydomonas pacifica. This extremophile microalga exhibits exceptional resilience to high pH (>11.5), high salinity (up to 2% NaCl), and elevated temperatures (up to 42 °C). Initially, we evolved this strain to also have a high tolerance to high light intensity (>2000 μE/m²/s) through mutagenesis, breeding, and selection. We subsequently genetically engineered C. pacifica to significantly enhance lipid production by 28% and starch accumulation by 27%, all without affecting its growth rate. We demonstrated the scalability of these engineered strains by cultivating them in pilot-scale raceway ponds and converting the resulting biomass into biodiesel and thermoplastic polyurethanes. This study showcases the complete cycle of transforming a newly discovered species into a commercially relevant commodity production strain. This research underscores the potential of extremophile algae, including C. pacifica, as a key species for the burgeoning sustainable bioeconomy, offering a viable path forward in mitigating environmental challenges and supporting global bioproduct demands.

Cr(VI) contamination is a significant environmental issue, whereas existing remediation technologies, whether physical, chemical, or biological, have many limitations, such as extensive engineering work, high energy consumption, secondary pollution, and incomplete treatment. Here, we report a Cr(VI) remediation method that integrates a natural magnetite/pyrrhotite composite (NMPC) with electrokinetic processes to enhance the remediation efficiency and stability, in which the electron-donating ability of NMPC was utilized to boost the reduction and immobilization of Cr(VI). The XRD analysis shows that NMPC is composed of magnetite and pyrrhotite. A highest 100% Cr(VI) removal efficiency and a TCr removal efficiency over 95% are achieved when treating Cr(VI) contaminants. The remediation stability analysis shows that the redissolution ratio of Cr(VI) in the NMPC-enhanced treatment decreased by more than 62%, indicating that the Cr-containing products were stable and resistant to releasing Cr. Furthermore, the Cr-containing products are analyzed by SEM-EDS, Raman, XRD, and XPS. The results show that the distribution of Cr and Fe is highly correlated and Cr is immobilized in the mineral phase. These results demonstrate that NMPC enhances the removal of Cr(VI) and promotes the immobilization of Cr, thus reducing the risk of Cr reoxidation and contributing to a more durable remediation effect.

Toxicity determination based on electrochemically active bacteria (EAB) shows great prospects for early warning of water pollution. However, the lifetime and reusability of EAB in toxicity determination remain uncertain. This study performed continuous toxicity determination by using an automatic water toxicity determination system based on EAB. Results demonstrated that EAB are capable of rapid responses to common heavy metal pollutants and make a full recovery after refreshment. Despite changes in microbial communities, EAB maintain a similar current generation capacity and toxicity sensitivity even after 20 continuous toxicity tests. The main reason for the stable performance was unchanged gene functions, as the toxicity tests did not result in a decrease in genes related to current generation or an increase in genes related to resistance. This study first reported that EAB possess a prolonged lifetime and good reusability in water toxicity determination, providing a basis for the continuous determination for water toxicity and the online monitoring of industrial wastewater toxicity based on EAB.

Feammox, an innovative and energy-efficient biological ammonium removal technology, has attracted significant attention in recent years. Defined as the anaerobic ammonium oxidation coupled with Fe(III) reduction, Feammox involves Fe(III)-reducing microbes that oxidize ammonium to nitrite using ferric ions. Identified in diverse ecosystems, such as freshwater, marine, natural wetlands, and wastewater ecosystems, Feammox plays a vital role in the global nitrogen cycle. Numerous studies have investigated its performance, influencing factors, reaction mechanisms, and engineering applications. However, our understanding of the functional microorganisms and key genes involved in Feammox remains limited and controversial. Clearly identifying and characterizing the functional microorganisms responsible for the Feammox process are essential for its practical application in wastewater treatment. Therefore, this review critically analyzes and summarizes recent advances in Feammox research, with a focus on functional microorganisms, key genes, and regulation strategies. Initially, the review discusses the functional microorganisms of Feammox from the perspective of microbial cooperation. It then delves into the enzymatic and genetic mechanisms involved as well as the critical factors affecting Feammox microbial activity. Finally, regulation strategies to enhance the Feammox efficiency are systematically outlined. This comprehensive analysis of current Feammox research provides a clearer and more complete understanding of microbial Feammox, deepens the knowledge of its mechanisms, and establishes a solid foundation for its engineering application.

Hydroxyl radical (^•OH)-dominated Fenton-like reactions offer a promising strategy for the degradation of refractory organic pollutants. However, the application of nitrogen-doped carbon (NC) catalysts for ^•OH generation is hindered by the loss of active nitrogen species during high-temperature synthesis (900–1200 °C), and an effective strategy to promote the homolytic cleavage of hydrogen peroxide (H₂O₂) remains necessary. Herein, an NC catalyst with abundant active nitrogen for enhanced ^•OH generation was prepared from zeolitic imidazolate frameworks by low-temperature pyrolysis at 800 °C, followed by acid-washing. Theoretical calculations and experimental results demonstrated that pyridinic and pyrrolic N significantly enhance the homolytic cleavage of H₂O₂, leading to selective and efficient generation of ^•OH, while graphitic N favors the less effective heterolytic cleavage pathway. Building on this finding, the active N species were precisely regulated by adjusting the pyrolysis temperature, resulting in the optimized NC-800 catalyst achieving 91.13% total organic carbon removal for extracting wastewater from spent lithium-ion battery recycling. Moreover, the activity of NC-800 was restored after simple thermal treatment, demonstrating excellent regeneration capability. This study sheds light on strengthening the pathways of NC catalysts through manipulating nitrogen species and provides an efficient approach for wastewater treatment.

Achieving the real-time detection of hydrogen sulfide (H₂S) based on metal oxide semiconductor (MOS) gas sensors is of great significance for rapid disease diagnosis. However, the high-power consumption and poor selectivity severely limit its practice application. In this study, a platinum nanoparticle (Pt NPs)-loaded porous metal–organic framework (MOF)-derived SnO₂ material was successfully synthesized to optimize the H₂S-sensing performance at room temperature. The optimized Pt-loaded porous SnO₂-based gas sensor exhibited remarkably high sensitivity (712–10 ppm), fast response (21 s), good selectivity, and extremely low detection limit for H₂S (10 ppb) at room temperature. The in-depth analysis demonstrated that the porous structure of Sn-MOF can provide adequate active reaction sites for gas molecules. Moreover, the uniform distribution of surface-loaded Pt NPs can initiate electron and chemical sensitization effects, thereby improving the sensing performance. The successful application of Pt NPs provides a novel approach to improve the room-temperature (RT) sensing performance of metal-oxide-semiconductor-based gas sensors.