● Advances, challenges, and opportunities for catalytic water pollutant reduction. ● Cases of Pd-based catalysts for nitrate, chlorate, and perchlorate reduction. ● New functionalities developed by screening and design of catalytic metal sites. ● Facile catalyst preparation approaches for convenient catalyst optimization. ● Rational design and non-decorative effort are essential for future work.
In this paper, we discuss the previous advances, current challenges, and future opportunities for the research of catalytic reduction of water pollutants. We present five case studies on the development of palladium-based catalysts for nitrate, chlorate, and perchlorate reduction with hydrogen gas under ambient conditions. We emphasize the realization of new functionalities through the screening and design of catalytic metal sites, including (i) platinum group metal (PGM) nanoparticles, (ii) the secondary metals for improving the reaction rate and product selectivity of nitrate reduction, (iii) oxygen-atom-transfer metal oxides for chlorate and perchlorate reduction, and (iv) ligand-enhanced coordination complexes for substantial activity enhancement. We also highlight the facile catalyst preparation approach that brought significant convenience to catalyst optimization. Based on our own studies, we then discuss directions of the catalyst research effort that are not immediately necessary or desirable, including (1) systematic study on the downstream aspects of under-developed catalysts, (2) random integration with hot concepts without a clear rationale, and (3) excessive and decorative experiments. We further address some general concerns regarding using H2 and PGMs in the catalytic system. Finally, we recommend future catalyst development in both “fundamental” and “applied” aspects. The purpose of this perspective is to remove major misconceptions about reductive catalysis research and bring back significant innovations for both scientific advancements and engineering applications to benefit environmental protection.
● IEM ion/ion selectivities of charge, valence, & specific ion are critically assessed. ● Ion/molecule selectivities of ion/solvent and ion/uncharged solute are reviewed. ● Approaches to advance the selectivities through sorption and migration are analyzed. ● The permeability-selectivity tradeoff appears to be pervasive. ● Ion/molecule selectivities are comparatively underdeveloped and poorly understood.
Ion-exchange membranes (IEMs) are utilized in numerous established, emergent, and emerging applications for water, energy, and the environment. This article reviews the five different types of IEM selectivity, namely charge, valence, specific ion, ion/solvent, and ion/uncharged solute selectivities. Technological pathways to advance the selectivities through the sorption and migration mechanisms of transport in IEM are critically analyzed. Because of the underlying principles governing transport, efforts to enhance selectivity by tuning the membrane structural and chemical properties are almost always accompanied by a concomitant decline in permeability of the desired ion. Suppressing the undesired crossover of solvent and neutral species is crucial to realize the practical implementation of several technologies, including bioelectrochemical systems, hypersaline electrodialysis desalination, fuel cells, and redox flow batteries, but the ion/solvent and ion/uncharged solute selectivities are relatively understudied, compared to the ion/ion selectivities. Deepening fundamental understanding of the transport phenomena, specifically the factors underpinning structure-property-performance relationships, will be vital to guide the informed development of more selective IEMs. Innovations in material and membrane design offer opportunities to utilize ion discrimination mechanisms that are radically different from conventional IEMs and potentially depart from the putative permeability-selectivity tradeoff. Advancements in IEM selectivity can contribute to meeting the aqueous separation needs of water, energy, and environmental challenges.
● Reducing environmental impacts through socioeconomic structural transitions. ● Simulation of looping the dynamic material cycle should be concerned. ● Transboundary effects of socioeconomic transitions need to be analyzed. ● Facilitating interregional cooperation and synergetic control mechanisms.
Rapid socioeconomic development has caused numerous environmental impacts. Human production and consumption activities are the underlying drivers of resource uses, environmental emissions, and associated environmental impacts (e.g., ecosystem quality and human health). Reducing environmental impacts requires an understanding of the complex interactions between socioeconomic system and environmental system. Existing studies have explored the relationships among human society, economic system, and environmental system. However, it is unclear about the research progress in the effects of socioeconomic activities on environmental impacts and the potential directions of future research. This critical review finds that existing studies have identified critical regions, sectors, and transmission pathways for resource uses, environmental emissions, and environmental impacts from supply chain perspectives. Moreover, scholars have characterized the impacts of socioeconomic transitions on resource uses and environmental emissions. However, existing studies overlook the dynamic nature of the interconnections among human society, economic system, and environmental system. In addition, the effects of socioeconomic structural transitions on environmental impacts remain unknown. This review proposes four prospects and possible solutions that will contribute to a better understanding of the complex interactions among human society, economic system, and environmental system. They can help identify more effective solutions to reduce environmental impacts through socioeconomic transitions.
● Anthropogenic circularity science is an emerging interdisciplinary field. ● Anthropogenic circularity was one effective strategy against metal criticality. ● Carbon neutrality is becoming the new industry paradigm around the world. ● Growing circularity could potentially minimize the CO2 emission.
Resource depletion and environmental degradation have fueled a burgeoning discipline of anthropogenic circularity since the 2010s. It generally consists of waste reuse, remanufacturing, recycling, and recovery. Circular economy and “zero-waste” cities are sweeping the globe in their current practices to address the world’s grand concerns linked to resources, the environment, and industry. Meanwhile, metal criticality and carbon neutrality, which have become increasingly popular in recent years, denote the material's feature and state, respectively. The goal of this article is to determine how circularity, criticality, and neutrality are related. Upscale anthropogenic circularity has the potential to expand the metal supply and, as a result, reduce metal criticality. China barely accomplished 15 % of its potential emission reduction by recycling iron, copper, and aluminum. Anthropogenic circularity has a lot of room to achieve a win-win objective, which is to reduce metal criticality while also achieving carbon neutrality in a near closed-loop cycle. Major barriers or challenges for conducting anthropogenic circularity are deriving from the inadequacy of life-cycle insight governance and the emergence of anthropogenic circularity discipline. Material flow analysis and life cycle assessment are the central methodologies to identify the hidden problems. Mineral processing and smelting, as well as end-of-life management, are indicated as critical priority areas for enhancing anthropogenic circularity.
● A novel deep learning framework for short-term water demand forecasting. ● Model prediction accuracy outperforms other traditional deep learning models. ● Wavelet multi-resolution analysis automatically extracts key water demand features. ● An analysis is performed to explain the improved mechanism of the proposed method.
Short-term water demand forecasting provides guidance on real-time water allocation in the water supply network, which help water utilities reduce energy cost and avoid potential accidents. Although a variety of methods have been proposed to improve forecast accuracy, it is still difficult for statistical models to learn the periodic patterns due to the chaotic nature of the water demand data with high temporal resolution. To overcome this issue from the perspective of improving data predictability, we proposed a hybrid Wavelet-CNN-LSTM model, that combines time-frequency decomposition characteristics of Wavelet Multi-Resolution Analysis (MRA) and implement it into an advanced deep learning model, CNN-LSTM. Four models - ANN, Conv1D, LSTM, GRUN - are used to compare with Wavelet-CNN-LSTM, and the results show that Wavelet-CNN-LSTM outperforms the other models both in single-step and multi-steps prediction. Besides, further mechanistic analysis revealed that MRA produce significant effect on improving model accuracy.
● Used a double-stage attention mechanism model to predict ozone. ● The model can autonomously select the appropriate time series for forecasting. ● The model outperforms other machine learning models and WRF-CMAQ. ● We used the model to analyze the driving factors of VOCs that cause ozone pollution.
Ozone is becoming a significant air pollutant in some regions, and VOCs are essential for ozone prediction as necessary ozone precursors. In this study, we proposed a recurrent neural network based on a double-stage attention mechanism model to predict ozone, selected an appropriate time series for prediction through the input attention and temporal attention mechanisms, and analyzed the cause of ozone generation according to the contribution of feature parameters. The experimental data show that our model had an RMSE of 7.71 μg/m3 and a mean absolute error of 5.97 μg/m3 for 1-h predictions. The DA-RNN model predicted ozone closer to observations than the other models. Based on the importance of the characteristics, we found that the ozone pollution in the Jinshan Industrial Zone mainly comes from the emissions of petrochemical enterprises, and the good generalization performance of the model is proved through testing multiple stations. Our experimental results demonstrate the validity and promising application of the DA-RNN model in predicting atmospheric pollutants and investigating their causes.
● Emotional responses to visibility-reducing haze was assessed in a controlled lab. ● Valence and arousal have non-linear responses to pollution-caused low visibility. ● Repetitive exposure aggravates negative emotions in severely polluted conditions. ● Emotional bias to pollution relates with gender, decisiveness, attitude to clean air.
A growing number of studies have shown that impaired visibility caused by particulate matter pollution influences emotional wellbeing. However, evidence is still scant on how this effect varies across individuals and over repetitive visual exposure in a controlled environment. Herein, we designed a lab-based experiment (41 subjects, 6 blocks) where participants were presented with real-scene images of 12 different PM2.5 concentrations in each block. Emotional valence (negative to positive) and arousal (calm to excited) were self-rated by participants per image, and the response time for each rating was recorded. We find that as pollution level increases from 10 to 260 µg/m3, valence scores decrease, whereas arousal scores decline first and then bounce back, following a U-shaped trend. When air quality deteriorates, individual variability decreases in hedonic valence but increases in arousal. Over blocks, repetitive visual exposure increases valence at a moderate pollution level but aggravates negative emotions in severely polluted conditions (> 150 µg/m3). Finally, we find females, people who are slow in making responses, and those who are highly aroused by clean air tend to express more negative responses (so-called negativity bias) to ambient pollution than their respective counterparts. These results provide deeper insights into individual-level emotional responses to dirty air in a controlled environment. Although the findings in our pilot study should only be directly applied to the conditions assessed herein, we introduce a framework that can be replicated in different regions to assess the impact of air pollution on local emotional wellbeing.
● Term of manganese-oxidizing microorganisms should be reconsidered. ● Visible light induces heterotrophic bacteria to produce superoxide. ● Heterotrophic bacteria oxidize Mn(II) ions with a fast oxidation rate. ● Superoxide oxidizing Mn(II) ions is an unintended side reaction of bacteria. ● Superoxide is an important oxidation force of Mn(II) in the environment.
Manganese oxides are widely distributed in soils and sediments, affecting the migration and transformation of heavy metals and organic pollutants. The microbial conversion of soluble Mn(II) into insoluble Mn(III/IV) oxides is considered to be the initial source of manganese oxides in the environment; however, whether this process is related to a physiological role remains unclear. Here, we explored the microbial manganese oxidation process under visible light by using coastal surface seawater microorganisms. Visible light greatly promotes the oxidation rate of Mn(II), and the average rate reaches 64 μmol/(L·d). The generated manganese oxides were then conducive to Mn(II) oxidation, thus the rapid manganese oxidation was the result of the combined action of biotic and abiotic, and biological function accounts for 88 % ± 4 %. Extracellular superoxide produced by microorganisms induced by visible light is the decisive factor for the rapid manganese oxidation in our study. But the production of these superoxides does not require the presence of Mn(II) ions, the Mn(II) oxidation process was more like an unintentional side reaction, which did not affect the growth of microorganisms. More than 70 % of heterotrophic microorganisms in nature are capable of producing superoxide, based on the oxidizing properties of free radicals, all these bacteria can participate in the geochemical cycle of manganese. What’s more, the superoxide oxidation pathway might be a significant natural source of manganese oxide.
● Recent advances in the electrochemical decontamination of PFAS are reviewed. ● Underlying mechanisms and impacting factors of these processes are discussed. ● Several novel couped systems and electrode materials are emphasized. ● Major knowledge gaps and research prospects on PFAS removal are identified.
Per- and polyfluoroalkyl substances (PFAS) pose serious human health and environmental risks due to their persistence and toxicity. Among the available PFAS remediation options, the electrochemical approach is promising with better control. In this review, recent advances in the decontamination of PFAS from water using several state-of-the-art electrochemical strategies, including electro-oxidation, electro-adsorption, and electro-coagulation, were systematically reviewed. We aimed to elucidate their design principles, underlying working mechanisms, and the effects of operation factors (e.g., solution pH, applied voltage, and reactor configuration). The recent developments of innovative electrochemical systems and novel electrode materials were highlighted. In addition, the development of coupled processes that could overcome the shortcomings of low efficiency and high energy consumption of conventional electrochemical systems was also emphasized. This review identified several major knowledge gaps and challenges in the scalability and adaptability of efficient electrochemical systems for PFAS remediation. Materials science and system design developments are forging a path toward sustainable treatment of PFAS-contaminated water through electrochemical technologies.
● Biofilm formation was enhanced by exogenous AHLs. ● EPS production and microbial adhesive strength of biofilm were promoted. ● Exogenous AHLs improved the performance of biofilters treating toluene.
Biofilters are typical biofilm reactors, and they usually have poor biofilm formation resulting in limited reactor performance. Exogenous acylated homoserine lactones (AHLs) can enhance biofilm formation in many bioreactors based on quorum sensing regulation. However, their effect on biofilm in biofilters utilized for volatile organic compound (VOC) removal is unknown and needs to be investigated. In this study, the effects of the exogenous AHLs on biofilters for gaseous toluene removal were investigated. Analysis of biofilms in biofilters showed that the addition of exogenous AHLs considerably enhanced biofilm growth; the average biofilm concentration increased by 18%. Furthermore, the average biofilm coverage proportions in biofilters with and without exogenous AHLs were 17 % and 13 %, respectively, demonstrating the positive effect of exogenous AHLs on biofilm coverage. In particular, exogenous AHLs promoted the production of extracellular polymeric substances and the microbial adhesive strength of the biofilm. In addition, the exogenous AHLs showed no significant effect on the gaseous toluene removal efficiency of the biofilter. These results show that exogenous AHLs can enhance biofilm formation and can guide the application of exogenous AHLs in VOC biofilters.
● Present a general concept called “salinity exchange”. ● Salts transferred from seawater to treated wastewater until completely switch. ● Process demonstrated using a laboratory-scale electrodialysis system. ● High-quality desalinated water obtained at ~1 mL/min consuming < 1 kWh/m 3 energy.
Two-thirds of the world’s population has limited access to potable water. As we continue to use up our freshwater resources, new and improved techniques for potable water production are warranted. Here, we present a general concept called “salinity exchange” that transfers salts from seawater or brackish water to treated wastewater until their salinity values approximately switch, thus producing wastewater with an increased salinity for discharge and desalinated seawater as the potable water source. We have demonstrated this process using electrodialysis. Salinity exchange has been successfully achieved between influents of different salinities under various operating conditions. Laboratory-scale salinity exchange electrodialysis (SEE) systems can produce high-quality desalinated water at ~1 mL/min with an energy consumption less than 1 kWh/m3. SEE has also been operated using real water, and the challenges of its implementation at a larger scale are evaluated.
● B[a]P, nicotine and phenanthrene molecules altered the secondary structure of Aβ42. ● β-content of the peptide was significantly enhanced in the presence of the PAHs. ● Nicotine made stable cluster with Aβ42 peptide via hydrogen bonds. ● Phenanthrene due to its small size, interfered with the Aβ42 monomer more strongly.
Recent studies have correlated the chronic impact of ambient environmental pollutants like polycyclic aromatic hydrocarbons (PAHs) with the progression of neurodegenerative disorders, either by using statistical data from various cities, or via tracking biomarkers during in-vivo experiments. Among different neurodegenerative disorders, PAHs are known to cause increased risk for Alzheimer’s disease, related to the development of amyloid beta (Aβ) peptide oligomers. However, the complex molecular interactions between peptide monomers and organic pollutants remains obscured. In this work, we performed an atomistic molecular dynamics study via GROMACS to investigate the structure of Aβ42 peptide monomer in the presence of benzo[a]pyrene, nicotine, and phenanthrene. Interestingly the results revealed strong hydrophobic, and hydrogen-bond based interactions between Aβ peptides and these environmental pollutants that resulted in the formation of stable intermolecular clusters. The strong interactions affected the secondary structure of the Aβ42 peptide in the presence of the organic pollutants, with almost 50 % decrease in the α-helix and 2 %–10 % increase in the β-sheets of the peptide. Overall, the undergoing changes in the secondary structure of the peptide monomer in the presence of the pollutants under the study indicates an enhanced formation of Aβ peptide oligomers, and consequent progression of Alzheimer’s disease.
● China has pledged ambitious carbon peak and neutrality goals for mitigating global climate change. ● Major challenges to achieve carbon neutrality in China are summarized. ● The new opportunities along the pathway of China’s carbon neutrality are discussed from four aspects. ● Five policy suggestions for China are provided.
China is the largest developing economy and carbon dioxide emitter in the world, the carbon neutrality goal of which will have a profound influence on the mitigation pathway of global climate change. The transition towards a carbon-neutral society is integrated into the construction of ecological civilization in China, and brings profound implications for China’s socioeconomic development. Here, we not only summarize the major challenges in achieving carbon neutrality in China, but also identify the four potential new opportunities: namely, the acceleration of technology innovations, narrowing regional disparity by reshaping the value of resources, transforming the industrial structure, and co-benefits of pollution and carbon mitigation. Finally, we provide five policy suggestions and highlight the importance of balancing economic growth and carbon mitigation, and the joint efforts among the government, the enterprises, and the residents.
