Current Pollution Reports最新文献

Purpose of Review

Over the past 2 decades, due to eutrophication and other factors, algal toxins in water bodies have become increasingly prevalent, posing a significant threat to aquatic ecosystems and human health. The complex properties of algal toxins and the potential environmental risks they pose urgently demand comprehensive research and effective solutions. 

Recent Findings

Currently, the methods to address this issue mainly cover physical, chemical, and biological means. Oxidation, photocatalysis, and adsorption have emerged as the primary techniques. However, each has its own advantages and disadvantages in terms of removal efficiency, cost, and environmental impact. Previous studies were mostly small-scale laboratory explorations and failed to analyze the overall research trends of algal toxins from a macroscopic perspective. This study, by employing bibliometrics and patent analysis methods, comprehensively examines the research status and development trends of treating algal toxins in water. 

Summary

This study carried out a data-driven analysis of 3354 papers and 380 patents from the Web of Science Core Collection and Derwent Innovation Index databases up until 2023. The keyword co-occurrence network analysis and technology classification jointly revealed the main knowledge structure of algal toxin research, which is formed and interconnected by contaminants, treatment processes, toxicity, and degradation characteristics. Moreover, current research indicates that oxidation, photocatalysis, and adsorption are the main removal methods. Further exploration found that hot areas include the low-carbon degradation of algal toxins in eutrophic waters. In recent years, cylindrospermopsin and nodularin have become hot pollutants in algal toxin treatment. Currently, the research focuses more on the removal mechanism of algal toxins and the risk assessment under the exposure to cylindrospermopsin and nodularin. This study also summarizes the removal efficiencies and principles of physical, chemical, and biological methods in the algal toxin removal process, providing key information and guidance for researchers to have a deeper understanding of the field of treating algal toxins in water. 

Purpose of Review

This review aims to reveal the pollution characteristics of bioaerosols across various working and living environments and evaluate existing control technologies. This will help enhance public awareness of bioaerosol pollution and the available control methods, and promote the diversity, efficiency, and operability of these technologies.

Recent Findings

Bioaerosols exhibit varying concentrations and community distributions across different environments due to diverse emission sources and environmental factors. Exposure to airborne pathogens poses health hazards, highlighting necessity for efficient antimicrobial techniques. While various technologies exhibit effective bactericidal capabilities, they also encounter numerous limitations in practical applications.

Summary

It is crucial to establish microbial risk assessment methods and develop efficient and low-cost control measures across various fields to create safe and healthy environments. This work lays the foundation for future research on bioaerosol pollution and control technologies, offering valuable insights for bioaerosol management and the protection of public health.

Purpose of Review

Air quality modelling and forecasting have been well recognised to play important roles in environmental research as well as government policy assessments and management strategies. To address the recent progresses in air quality modelling, we conduct a literature review focusing on air quality forecasting models and reanalysis datasets.

Recent Findings

First of all, the implementation of three-dimensional adaptive meshes/horizontal resolution-variable grids in air quality models offers a crucial insight on multi-scale simulations down to the hectometre level. These models balance high accuracy with computational efficiency. Secondly, current reanalysis still has limitations in its horizontal resolution (dozens of kilometres) that are insufficient to support the analysis and management of air pollution at factory levels or neighbourhood scales. The development of adaptive mesh resolution method provides a promising way to deal with this issue and allows the construction of the chemistry reanalysis at ultra-high resolutions (< 1 km). However, the use of adaptive mesh method in data assimilation is currently still restricted to the column-based one-dimensional models. Thirdly, the application of graphics processing units to air quality predictions enables more optimised resource usage and enhances model performance through hardware acceleration effects, while machine learning methods can both maintain the consistency with numerical solutions and increase the accuracy of air quality predictions for specific chemical species. Furthermore, parameters that describe more complicated processes and mechanisms have been added into pre-existing physical and chemical parameterisations to enable more accurate representation of various small-scale features, such as the parameterisation of inorganic chemistry on the surface of aerosols, as well as various photolysis schemes.

Summary

The increase of resolution brings computational burdens and shifts the boundary of resolved and sub-grid phenomena in air quality prediction, which in turn stimulates the development and usage of new technologies (e.g. adaptive mesh techniques, graphics processing unit acceleration, machine learning methods). They are conducive to the improvement of prediction accuracies and the acquisition of new insights on atmospheric physical and chemical mechanisms. However, new challenges also ensued, including the selection criteria for mesh refinement, the acquisition of high-resolution observational data and the integration of artificial intelligence-hybrid air quality models. More efforts are required to develop the adaptive irregular mesh grid data assimilation method to overcome the resolution problems of current chemical reanalysis.

Purpose of Review

This review aims to explore the application of scenario setting in life cycle assessment (LCA) studies related to wastewater treatment. Given the variability in LCA results based on different scenario settings, this paper seeks to categorize these settings, assess their impact, and provide a reference for future research in optimizing wastewater treatment industry.

Recent Findings

To achieve a more comprehensive understanding of the wastewater treatment field, recent studies have incorporated a more diverse range of scenarios for comparative analysis. These scenarios can generally be categorized into small-scale and large-scale scenarios, including those set up to compare different wastewater treatment technologies, demonstrate the potential of new versus traditional processes, predict future developments, and analyze regional impacts spanning entire countries, among others. Scenario setting plays a critical role throughout the LCA process, influencing model construction, data analysis, and result interpretation.

Summary

The motivation behind scenario setting lies in comparison, and it can be integrated throughout LCA research, serving distinct roles at various stages. This review categorizes scenario setting into three steps: baseline scenario setting, main scenario setting, and supplementary scenario setting. Proper scenario setting is crucial for enhancing the accuracy and depth of wastewater treatment life cycle assessments, enabling researchers to provide valuable insights into the environmental, economic, and social impacts of wastewater treatment technologies. This structured approach supports decision-makers in optimizing treatment processes and developing more sustainable wastewater management policies.

Purpose of Review

Beta-blockers are drugs generally used to treat cardiovascular disorders. They commonly occur in water environments and cause significant threats to aquatic organisms. Therefore, removing these compounds from the environment is essential for maintaining environmental stability. The microbial biodegradation of beta-blockers has recently gained more attention due to their applicability, environment-friendliness, and cost-effectiveness. In this context, this review aims to identify the existing microorganisms and the pathways involved in the biodegradation of beta-blockers.

Recent Findings

The finding suggested that microorganisms, including archaea, bacteria, and fungi, are the major groups involved in the biodegradation of atenolol, metoprolol, and propranolol. Generally, microbes transform these complex compounds into less harmful metabolites; for instance, in biodegradation pathways of atenolol, metoprolol, and propanol transformed into atenolol acid, metoprolol acid, and carboxylic acid, respectively.

Summary

This review critically exposes the biodegradation process of beta-blockers using microorganisms and their pathways. Although numerous metabolites and enzymes have already been identified in the biodegradation of beta-blockers, several enzymes and metabolites still need to be explored.

Purpose of Review

The urgent need for a transition toward a sustainable and greener future is underscored by the projected risk of a global temperature increase of up to 3 °C above pre-industrial levels, driven by rising carbon emissions. Algae biorefineries offer a promising solution to these challenges. However, the high production and downstream processing costs continue to hinder successful commercialization. This review provides a comprehensive overview of several AI-driven innovations: phenotypic screening for strain improvement, monitoring of environmental parameters, machine learning for optimizing dewatering efficiency, predictive modeling for algae growth and yield, and AI-controlled drying systems for biomass preservation.

Recent Findings

Integrating machine learning algorithms and predictive modeling can transform algae cultivation by automating the process with continuous monitoring and feedback systems, significantly reducing labor costs while enhancing process economics and efficiency. Accurate prediction of optimal harvesting times can further decrease harvesting costs, address key scalability issues, and facilitate the broader commercialization of algae for diverse biotechnological applications.

Summary

In the future, smart biorefineries that integrate artificial intelligence into algae production facilities will be pivotal in enhancing process efficiency and economics within circular and sustainable frameworks. While AI continues to impact various fields to ease human effort, ethical considerations must remain central to its use, especially as this sector grows rapidly.

Graphical Abstract

Purpose of Review

The silicon (Si) biogeochemical cycle in ecosystems is tightly linked with other elemental cycles and plays a key role in addressing ecological challenges such as water quality deterioration, climate warming, and biodiversity reduction. As transitional zones between aquatic and terrestrial ecosystems, riparian wetlands possess unique eco-environmental characteristics that enable them to regulate the flow and forms of terrestrial Si into aquatic ecosystems. This paper systematically reviews the characteristics of the Si biogeochemical cycle in riparian wetlands, emphasizing the influence of environmental factors on Si transformation. Additionally, it highlights key knowledge gaps in the Si cycle within riparian wetlands that warrant further research.

Recent Findings

Si is considered “quasi-essential” for plant growth. During growth, plants not only assimilate CO₂ from the atmosphere but also convert dissolved Si into biogenic silicon (BSi). Enhancing the ability of plants to assimilate CO₂ through Si uptake is regarded as an effective approach to mitigating climate warming. BSi plays a dominant role in Si fluxes from terrestrial to aquatic ecosystems, with riparian wetlands serving as primary sites for BSi formation. The distinct hydrological characteristics of riparian wetlands have significant impacts on Si movement and transformation. Additionally, factors such as vegetation composition, soil physicochemical properties, and human activities further influence the Si cycle.

Summary

This review summarizes the characteristics of riparian wetlands, as well as the forms and distribution of Si within these ecosystems. It then emphasizes the biogeochemical processes of Si, the characteristics of Si cycle, and the factors that influence it. This review also identifies knowledge gaps and outlines priorities for future research.

Purpose of Review

This paper offers a thorough overview of the processes of nutrient enrichment by biochar and how biochar as a nutrient carrier can effectively improve agricultural productivity. The distributions of nutrients in biochar and the dynamics of nutrients in soil are also reviewed in detail.

Recent Findings

The application of biochar improves soil health by changing the soil’s biological and physico-chemical characteristics of the soil, such as its structure, cation exchange capacity and microbial biomass carbon. Additionally, biochar produced from low pyrolysis temperatures can enhance nutrient retention in soils and be utilized as a carbon-based fertilizer.

Summary

The maintenance of an adequate amount of organic matter in soil and a dynamic biogeochemical cycle of essential nutrients are key components of sustainable soil management. Biochar is a carbonized biomass derived from various feedstock materials, including wood and crop residues, manures, biosolids and animal carcasses. Biochar has been used for more than two decades as a soil amendment to improve soil physicochemical conditions and mitigate soil contamination. Nutrient-enriched biochar-based fertilizers (NEBBF) can be prepared using various nutrient enrichment procedures and have the potential to increase soil fertility and crop productivity. The application of NEBBF, which is a carbon-based nutrient source, has been shown to enhance microbial activity, thereby increasing the efficiency of nutrient use compared to conventional non-carbon-based synthetic fertilizers. This review identified key research gaps and discussed the importance and necessity of biochar as a nutrient carrier in agriculture.

Purpose of Review

Dust events are global meteorological disasters, affecting approximately 330 million people across 151 countries, from sub-Saharan Africa to northern China and Australia, with profound impacts on ecosystems, human health, and socioeconomics. The WMO airborne dust bulletin 2023 indicates that, dust concentrations in the most severely affected regions worldwide exceeded long-term averages, causing significant impacts on the global environment, economy, and public health.

Recent Findings

In recent years, as climate change has led to an increasing frequency and intensity of extreme weather events, research on the interactions between dust aerosols and the climate system, as well as their impacts on human health, has gradually become a hot topic. Studies have revealed the critical role of direct radiative feedback from East Asian dust in exacerbating dust-related air pollution in northern China. Other research highlights the combined effects of Arctic Sea ice anomalies, La Niña events, and a warmer northwestern Atlantic in creating loose, dry surface conditions across Mongolia, along with the formation of the strongest Mongolian cyclone in the past decade, which provided favorable dynamical disturbances and transport conditions for dust events. Furthermore, dust events have been shown to significantly increase the mortality risk from respiratory diseases, particularly chronic lower respiratory diseases and chronic obstructive pulmonary disease (COPD). Circulatory disease mortality risks, including ischemic stroke and hypertensive heart disease, have also risen. These findings underscore the importance of further exploring the interactions between dust aerosols and regional climate, as well as their multidimensional impacts on human health.

Summary

Dust events, as a global arid meteorological disaster, affect vast regions worldwide. In China, the severe spring dust storm of 2021 caused significant adverse impacts and economic losses across many northern cities. To enhance global awareness of dust events, strengthen international cooperation, and mitigate their impacts, the United Nations (UN) has designated 2025–2034 as the "UN Decade for Combating Sand and Dust Storms". Implementing effective dust control policies, building climate-resilient health systems, and enhancing efforts in risk mitigation, prevention, response, and recovery can significantly reduce health risks. This review aims to summarize recent advances in research on the impacts of dust on climate and human health. It contributes to expanding our understanding of the climatic effects of dust aerosols and provides crucial scientific evidence for addressing climate change and developing strategies to mitigate health risks associated with dust exposure.

Purpose of Review

This review explores the potential of wastewater as a substrate for the production of clean, renewable energy in the form of hydrogen. The rich organic composition of wastewater pollutants provides an ideal medium for microbial biotransformation processes, enabling the conversion of these compounds into biohydrogen. Among others, emphasis is placed on the metabolic diversity of microorganisms, whose unique capabilities drive efficient hydrogen production. The review highlights advancements in microbial engineering for biohydrogen production, the role of diverse wastewater types, and the integration of hydrogen production with wastewater treatment as a sustainable energy recovery strategy.

Recent Findings

Recent advancements include using genetically engineered microbes to enhance hydrogen yield, optimizing reactor designs for scaling up production, and integrating microbial consortia to improve efficiency. Studies demonstrate significant hydrogen yields from wastewater, including municipal, industrial, and agricultural effluents, often accompanied by simultaneous pollutant removal. Furthermore, incorporating nanoparticles yields higher hydrogen production.

Summary

This review examines the three primary mechanisms for biohydrogen production—photofermentation, dark fermentation, and biophotolysis—and the advances in developing genetically modified microorganisms to enhance hydrogen yields. It underscores microorganisms’ versatility in utilizing wastewater as a substrate for hydrogen production, showcasing their ability to efficiently transform organic pollutants into renewable energy. These advancements highlight integrating biohydrogen production with wastewater treatment as a sustainable solution to energy and environmental challenges.

Graphical Abstract