Environmental Science and Ecotechnology最新文献

Molecular oxygen (O₂) is an environmentally friendly, cost-effective, and non-toxic oxidant. Activation of O₂ generates various highly oxidative reactive oxygen species (ROS), which efficiently degrade pollutants with minimal environmental impact. Despite extensive research on the application of O₂ activation in environmental remediation, a comprehensive review addressing this topic is currently lacking. This review provides an informative overview of recent advancements in O₂ activation, focusing on three primary strategies: photocatalytic activation, chemical activation, and electrochemical activation of O₂. We elucidate the respective mechanisms of these activation methods and discuss their advantages and disadvantages. Additionally, we thoroughly analyze the influence of oxygen supply, reactive temperature, and pH on the O₂ activation process. From electron transfer and energy transfer perspectives, we explore the pathways for ROS generation during O₂ activation. Finally, we address the challenges faced by researchers in this field and discuss future prospects for utilizing O₂ activation in pollution control applications. This detailed analysis enhances our understanding and provides valuable insights for the practical implementation of organic pollutant degradation.

Regulating electron transfer in predominantly fermentative microbiomes has broad implications in environmental, chemical, food, and medical fields. Here we demonstrate electrochemical control in fermenting food waste, digestate, and wastewater to improve lactic acid production. We hypothesize that applying anodic potential will expedite and direct fermentation towards lactic acid. Continued operation that introduced epi/endophytic communities (Lactococcus, Lactobacillus, Weissella) to pure culture Lactiplantibacillus plantarum reactors with static electrodes was associated with the loss of anode-induced process intensification despite 80% L. plantarum retention. Employing fluidized electrodes discouraged biofilm formation and extended electrode influence to planktonic gram-positive fermenters using mediated extracellular electron transfer. While short-term experiments differentially enriched Lactococcus and Klebsiella spp., longer-term operations indicated convergent microbiomes and product spectra. These results highlight a functional resilience of environmental fermentative microbiomes to perturbations in redox potential, underscoring the need to better understand electrode induced polymicrobial interactions and physiological impacts to engineer tunable open-culture or synthetic consortia.

Organic matter is crucial in aerosol–climate interactions, yet the physicochemical properties and origins of organic aerosols remain poorly understood. Here we show the seasonal characteristics of submicron organic aerosols in Arctic Svalbard during spring and summer, emphasizing their connection to transport patterns and particle size distribution. Microbial-derived organic matter (MOM) and terrestrial-derived organic matter (TOM) accounted for over 90% of the total organic mass in Arctic aerosols during these seasons, comprising carbohydrate/protein-like and lignin/tannin-like compounds, respectively. In spring, aerosols showed high TOM and low MOM intensities due to biomass-burning influx in the central Arctic. In contrast, summer exhibited elevated MOM intensity, attributed to the shift in predominant atmospheric transport from the central Arctic to the biologically active Greenland Sea. MOM and TOM were associated with Aitken mode particles (<100 nm diameter) and accumulation mode particles (>100 nm diameter), respectively. This association is linked to the molecular size of biomolecules, impacting the number concentrations of corresponding aerosol classes. These findings highlight the importance of considering seasonal atmospheric transport patterns and organic source-dependent particle size distributions in assessing aerosol properties in the changing Arctic.

Nanoscale zerovalent iron (nZVI) has garnered significant attention as an efficient advanced oxidation activator, but its practical application is hindered by aggregation and oxidation. Coating nZVI with carbon can effectively addresses these issues. A simple and scalable production method for carbon-coated nZVI composite is highly desirable. The anti-oxidation and catalytic performance of carbon-coated nZVI composite merit in-depth research. In this study, a highly stable carbon-coated core-shell nZVI composite (Fe⁰@RF-C) was successfully prepared using a simple method combining phenolic resin embedding and carbothermal reduction. Fe⁰@RF-C was employed as a heterogeneous persulfate (PS) activator for degrading 2,4-dihydroxybenzophenone (BP-1), an emerging contaminant. Compared to commercial nZVI, Fe⁰@RF-C exhibited superior PS activation performance and oxidation resistance. Nearly 95% of BP-1 was removed within 10 min in the Fe⁰@RF-C/PS system. The carbon layer promotes the enrichment of BP-1 and accelerates its degradation through singlet oxygen oxidation and direct electron transfer processes. This study provides a straightforward approach for designing highly stable carbon-coated nZVI composite and elucidates the enhanced catalytic performance mechanism by carbon layers.

The application of low-condensation diesel in cold regions with extremely low ambient temperatures (−14 to −29 °C) has enabled the operation of diesel vehicles. Still, it may contribute to heavy haze pollution in cold regions during winter. Here we examine pollutant emissions from low-condensation diesel in China. We measure the emissions of elemental carbon (EC), organic carbon (OC), and elements, including heavy metals such as arsenic (As). Our results show that low-condensation diesel increased EC and OC emissions by 2.5 and 2.6 times compared to normal diesel fuel, respectively. Indicators of vehicular sources, including EC, As, lead (Pb), cadmium (Cd), chromium (Cr), nickel (Ni), and manganese (Mn), increased by approximately 20.2–162.5% when using low-condensation diesel. Seasonal variation of vehicular source indicators, observed at road site ambient environments revealed the enhancement of PM_2.5 pollution by the application of low-condensation diesel in winter. These findings suggest that −35# diesel, a low-cetane index diesel, may enhance air pollution in winter, according to a dynamometer test conducted in laboratory. It raises questions about whether higher emissions are released if −35# diesel is applied to running vehicles in real-world cold ambient environments.

Carbon mitigation technologies lead to air quality improvement and health co-benefits, while the practical effects of the technologies are dependent on the energy composition, technological advancements, and economic development. In China, mitigation technologies such as end-of-pipe treatment, renewable energy adoption, carbon capture and storage (CCS), and sector electrification demonstrate significant promise in meeting carbon reduction targets. However, the optimization of these technologies for maximum co-benefits remains unclear. Here, we employ an integrated assessment model (AIM/enduse, CAM-chem, IMED|HEL) to analyze air quality shifts and their corresponding health and economic impacts at the provincial level in China within the two-degree target. Our findings reveal that a combination of end-of-pipe technology, renewable energy utilization, and electrification yields the most promising results in air quality improvement, with a reduction of fine particulate matter (PM_2.5) by −34.6 μg m⁻³ and ozone by −18.3 ppb in 2050 compared to the reference scenario. In contrast, CCS technology demonstrates comparatively modest improvements in air quality (−9.4 μg m⁻³ for PM_2.5 and −2.4 ppb for ozone) and cumulative premature deaths reduction (−3.4 million from 2010 to 2050) compared to the end-of-pipe scenario. Notably, densely populated regions such as Henan, Hebei, Shandong, and Sichuan experience the most health and economic benefits. This study aims to project effective future mitigation technologies and climate policies on air quality improvement and carbon mitigation. Furthermore, it seeks to delineate detailed provincial-level air pollution control strategies, offering valuable guidance for policymakers and stakeholders in pursuing sustainable and health-conscious environmental management.

Harmful cyanobacterial blooms (HCBs) pose a global ecological threat. Ultraviolet C (UVC) irradiation at 254 nm is a promising method for controlling cyanobacterial proliferation, but the growth suppression is temporary. Resuscitation remains a challenge with UVC application, necessitating alternative strategies for lethal effects. Here, we show synergistic inhibition of Microcystis aeruginosa using ultraviolet A (UVA) pre-irradiation before UVC. We find that low-dosage UVA pre-irradiation (1.5 J cm⁻²) combined with UVC (0.085 J cm⁻²) reduces 85% more cell densities compared to UVC alone (0.085 J cm⁻²) and triggers mazEF-mediated regulated cell death (RCD), which led to cell lysis, while high-dosage UVA pre-irradiations (7.5 and 14.7 J cm⁻²) increase cell densities by 75–155%. Our oxygen evolution tests and transcriptomic analysis indicate that UVA pre-irradiation damages photosystem I (PSI) and, when combined with UVC-induced PSII damage, synergistically inhibits photosynthesis. However, higher UVA dosages activate the SOS response, facilitating the repair of UVC-induced DNA damage. This study highlights the impact of UVA pre-irradiation on UVC suppression of cyanobacteria and proposes a practical strategy for improved HCBs control.

Bisphenol A, a hazardous endocrine disruptor, poses significant environmental and human health threats, demanding efficient removal approaches. Traditional biological methods struggle to treat BPA wastewater with high chloride (Cl⁻) levels due to the toxicity of high Cl⁻ to microorganisms. While persulfate-based advanced oxidation processes (PS-AOPs) have shown promise in removing BPA from high Cl⁻ wastewater, their widespread application is always limited by the high energy and chemical usage costs. Here we show that peroxymonosulfate (PMS) degrades BPA in situ under high Cl⁻ concentrations. BPA was completely removed in 30 min with 0.3 mM PMS and 60 mM Cl⁻. Non-radical reactive species, notably free chlorine species, including dissolved Cl₂(l), HClO, and ClO⁻ dominate the removal of BPA at temperatures ranging from 15 to 60 °C. Besides, free radicals, including ^•OH and Cl₂^•−, contribute minimally to BPA removal at 60 °C. Based on the elementary kinetic models, the production rate constant of Cl₂(l) (32.5 M⁻¹ s⁻¹) is much higher than HClO (6.5 × 10⁻⁴ M⁻¹ s⁻¹), and its degradation rate with BPA (2 × 10⁷ M⁻¹ s⁻¹) is also much faster than HClO (18 M⁻¹ s⁻¹). Furthermore, the degradation of BPA by Cl₂(l) and HClO were enlarged by 10- and 18-fold at 60 °C compared to room temperature, suggesting waste heat utilization can enhance treatment performance. Overall, this research provides valuable insights into the effectiveness of direct PMS introduction for removing organic micropollutants from high Cl⁻ wastewater. It further underscores the critical kinetics and mechanisms within the PMS/Cl⁻ system, presenting a cost-effective and environmentally sustainable alternative for wastewater treatment.

Rainfall data with high spatial and temporal resolutions are essential for urban hydrological modeling. Ubiquitous surveillance cameras can continuously record rainfall events through video and audio, so they have been recognized as potential rain gauges to supplement professional rainfall observation networks. Since video-based rainfall estimation methods can be affected by variable backgrounds and lighting conditions, audio-based approaches could be a supplement without suffering from these conditions. However, most audio-based approaches focus on rainfall-level classification rather than rainfall intensity estimation. Here, we introduce a dataset named Surveillance Audio Rainfall Intensity Dataset (SARID) and a deep learning model for estimating rainfall intensity. First, we created the dataset through audio of six real-world rainfall events. This dataset's audio recordings are segmented into 12,066 pieces and annotated with rainfall intensity and environmental information, such as underlying surfaces, temperature, humidity, and wind. Then, we developed a deep learning-based baseline using Mel-Frequency Cepstral Coefficients (MFCC) and Transformer architecture to estimate rainfall intensity from surveillance audio. Validated from ground truth data, our baseline achieves a root mean absolute error of 0.88 mm h^-1 and a coefficient of correlation of 0.765. Our findings demonstrate the potential of surveillance audio-based models as practical and effective tools for rainfall observation systems, initiating a new chapter in rainfall intensity estimation. It offers a novel data source for high-resolution hydrological sensing and contributes to the broader landscape of urban sensing, emergency response, and resilience.

Intensive ecological interventions have been carried out in highly polluted shallow lakes to improve their environments and restore their ecosystems. However, certain treatments, such as dredging polluted sediment and stocking fish, can impact the aquatic communities, including benthos and fishes. These impacts can alter the composition and characteristics of aquatic communities, which makes community-based ecological assessments challenging. Here we develop a bacteria-based index of biotic integrity (IBI) that can clearly indicate the restoration of aquatic ecosystems with minimal artificial interventions. We applied this method to a restored shallow lake during 3-year intensive ecological interventions. The interventions reduced nutrients and heavy metals by 27.1% and 16.7% in the sediment, while the total organic carbon (TOC) increased by 8.0% due to the proliferation of macrophytes. Additionally, the abundance of sulfur-related metabolic pathways decreased by 10.5% as the responses to improved ecosystem. The score of bacteria-based IBI, which is calculated based on the diversity, composition, and function of benthic bacterial communities, increased from 0.62 in 2018 to 0.81 in 2021. Our study not only provides an applicable method for aquatic ecological assessment under intensive artificial interventions but also extends the application of IBI to complex application scenarios, such as ecosystems with significantly different aquatic communities and comparisons between different basins.