The investment decisions of enterprises are affected by environmental regulations designed to protect the environment, so environmental regulations may change companies\' investment behavior in environmental protection. This study focuses on the River Chief System (RCS)1, an innovative environmental regulation related to river governance which officially launched in China in 2014. Based on data collected from heavy-polluting companies in the Yangtze River Delta, we use the difference-in-differences model (DID Model)2 and focus on RCS\'s impacts on micro-environmental protection investments. Our findings reveal that the RCS is conducive to expanding the scale of enterprises\' environmental protection investments. Industrial structural upgrades appear to have a masking effect wherein the one-sided pursuit of industrial structural upgrades may slow economic growth and cause enterprises to reduce the scale of environmental investments. We recommend that the allocation of environmental investment should be based on the characteristics of local markets and public participation, and maintain a balance between secondary and tertiary industries, government and business incentives.

Modifying cells with polymers on the surface can enable them to gain or enhance function with various applications, wherein the atom transfer radical polymerization (ATRP) has garnered significant potential due to its biocompatibility. However, specifically initiating ATRP from the cell surface for in-situ modification remains challenging. This study established a bacterial surface-initiated ATRP method and further applied it for enhanced Cr(VI) removal. The cell surface specificity was facilely achieved by cell surface labelling with azide substrates, following alkynyl ATRP initiator specifically anchoring with azide-alkyne click chemistry. Then, the ATRP polymerization was initiated from the cell surface, and different polymers were successfully applied to in-situ modification. Further analysis revealed that the modification of Shewanella oneidensis with poly (4-vinyl pyridine) and sodium polymethacrylate improved the heavy metal tolerance and enhanced the Cr(VI) removal rate of 2.6 times from 0.088 h-1 to 0.314 h-1. This work provided a novel idea for bacterial surface modification and would extend the application of ATRP in bioremediation.

BACKGROUND: As persistent organic pollutants (POPs), the accumulation of p-acetylaminophenol (PAT) and p-aminophenol (PAP) in water can seriously damage the health of plants and animals, ultimately leading to threats to human health and safety. Electrochemical sensors have the advantages of being fast, inexpensive, and accurate compared to the complex, expensive, and cumbersome conventional analytical methods. In this study, we designed and synthesized composites with two-dimensional/three-dimensional (2D/3D) porous structures to construct an efficient electrochemical platform for the simultaneous detection of PAT and PAP.
RESULTS: In this work, a novel 3D foamy birnessite Na0.55Mn2O4·1.5H2O@C (SMOH@C) was synthesized, which was composited with 2D ordered mesoporous nanosheets (mNPC) to construct electrochemical sensors detecting PAT and PAP simultaneously. The prepared 2D/3D porous structure of mNPC/SMOH@C increased the exposure of active sites due to its large specific surface area. The introduction of a 3D carbon skeleton altered the charge transfer rate of SMOH@C, and the rich pore structure and oxygen-rich vacancies created favorable conditions for the diffusion and adsorption of PAP and PAT, which enabled the sensitive detection of PAT and PAP. The constructed mNPC/SMOH@C electrochemical sensor could simultaneously detect PAT (1 × 10-7 - 1 × 10-4 M) and PAP (5 × 10-8 - 1 × 10-4 M) with detection limits of 20.4 nM and 30.1 nM, respectively. The sensor has good repeatability (RSD <4 %) and reproducibility (RSD <4 %), and satisfactory recoveries (96.7-102.8 %) were obtained in the analysis of natural water samples.
CONCLUSIONS: In this paper, for the first time, we present the synthesis of 3D foam birnessite and its composite with mNPC for the electrochemical simultaneous detection of PAT and PAP. Our proposed strategy for fabricating 2D/3D porous composites lays the foundation for the design and synthesis of other porous materials. In addition, this study provides new ideas for developing efficient and practical electrochemical sensors for detecting pollutants in aquatic environments.

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The Ba River in Vietnam has been facing pollution due to waste generation from agricultural and urban areas. This study focuses on evaluating the spatiotemporal variations in river water quality based on physicochemical characteristics and pesticide parameters for different seasons in 2022-2023. The results indicate that the concentrations of most parameters in the rainy season were higher than those in the early-dry and dry seasons due to the non-point sources in agricultural areas. Notably, the analysis of pesticide residue in both the rainy and dry seasons revealed low levels of chlorpyrifos (ethyl), and deltamethrin was detected in the only rainy season. The results from the hierarchical cluster analysis and water quality index show that the water quality at Ben Mong, An Khe, and Ba River Bridges was classified as moderately to highly polluted. These areas should focus on regular water quality monitoring and appropriate pollution source management. PRACTITIONER POINTS: Agriculture activities strongly affected the water quality of the Highland Ba River of Vietnam. Chlorpyrifos and deltamethrin pesticides (0.0074-0.0218 μg/L) were detected in Ba River. Non-point pollution sources significantly influenced water quality in the Ba River. Variations in river water quality mainly depend on seasons and locations. Water quality index values in rainy seasons (26-88) are lower than that in dry season (37-92).

Water pollution has become a major concern in recent years, affecting over 2 billion people worldwide, according to UNESCO. This pollution can occur by either naturally, such as algal blooms, or man-made when toxic substances are released into water bodies like lakes, rivers, springs, and oceans. To address this issue and monitor surface-level water pollution in local water bodies, an informative real-time vision-based surveillance system has been developed in conjunction with large language models (LLMs). This system has an integrated camera connected to a Raspberry Pi for processing input frames and is further linked to LLMs for generating contextual information regarding the type, causes, and impact of pollutants on both human health and the environment. This multi-model setup enables local authorities to monitor water pollution and take necessary steps to mitigate it. To train the vision model, seven major types of pollutants found in water bodies like algal bloom, synthetic foams, dead fishes, oil spills, wooden logs, industrial waste run-offs, and trashes were used for achieving accurate detection. ChatGPT API has been integrated with the model to generate contextual information about pollution detected. Thus, the multi-model system can conduct surveillance over water bodies and autonomously alert local authorities to take immediate action, eliminating the need for human intervention. PRACTITIONER POINTS: Combines cameras and LLMs with Raspberry Pi for processing and generating pollutant information. Uses YOLOv5 to detect algal blooms, synthetic foams, dead fish, oil spills, and industrial waste. Supports various modules and environments, including drones and mobile apps for broad monitoring. Educates on environmental healthand alerts authorities about water pollution.

The chemical tolerance of ketoenamine covalent organic frameworks (COFs) is excellent; however, the tight crystal structure and low surface area limit their applications in the field of catalysis. In this work, a porous single-atom iron catalyst (FeSAC) with a core-shell structure and high surface area was synthesized by using Schiff base COF nanospheres as the core and ketoenamine COF nanosheets growth on the surfaces. Surface defects were created using sodium cyanoborohydride etching treatment to increase specific surface area. The dye degradation experiments by peroxymonosulfate (PMS) catalyzed by the FeSAC proved that methylene blue can be degraded with a degradation rate constant of 0.125 min-1 under the conditions of 0.1 g L-1 catalyst dosage and 0.05 g L-1 peroxymonosulfate. The FeSAC/PMS system effectively degrades various pollutants in the pH range of 4-10 with over 80% efficiency for four cycles and can be recovered by soaking in iron salt solution. Free radical quenching experiments confirmed that singlet oxygen and superoxide radicals are the main active species for catalysis.

Water pollution with heavy metals owing to industrial and agricultural activities have become a critical dilemma to humans, plants as well as the marine environment. Therefore, it is of great importance that the carcinogenic heavy metals present in wastewater to be eliminated through designing treatment technologies that can remove multiple pollutants. A novel green magnetic nano-composite called (Carbonized Chitosan-Fe3O4-SiO2) was synthesized using Co-precipitation method to adsorb a mixture of heavy metal ions included; cobalt (Co2+), nickel (Ni2+) and copper (Cu2+) ions from aqueous solutions. The novelty of this study was the synthesis of a new nano-composite which was green with magnetic properties to be more sustainable and environmentally friendly. Its magnetic properties made it separated easily from solutions after accomplishment of the adsorption process using a magnet. Extended Freundlich isotherm was the best fitted model with maximum adsorption capacity of the metal ions mixture 2908.92 mg/g. Different experimental parameters have been studied included the initial concentration for a mixture of nickel, cobalt and copper metal ions (0.05-0.1 molar), dosage of adsorbent (0.5-3.5 g/L) and contact time (6-90 min) to investigate their changing effect on the removal percents of the heavy metal ions mixture from aqueous solutions. The experimental adsorption percent of cobalt ion ranged from 1.58 to 64.28%, nickel ion adsorption percent ranged from 10.68 to 94.12% and copper ion adsorption percent ranged from 4.41 to 76.23% at pH = 9 were based on the combination of the adsorption process parameters.

The textile industry is discharging high concentrations of anionic and cationic azo dyes into the nearby environment, which can cause adverse effects on public health, and the aquatic environment. Therefore, this study aimed to develop giant reed biochar and apply for the removal of Basic blue 41 (BB41) and Eriochrome black T (EBT) azo dyes from water. Characterization techniques such as BET surface area analyzer, Fourier-transform infrared spectroscopy (FT-IR), Raman spectroscopy, X-ray diffraction (XRD), scanning electron microscopy (SEM), and thermal gravimetric analyzer (TGA) were applied for biochar description. The biochar exhibits a high fixed carbon content (80.4%), a low ash content (3.8%), a large surface area (429.0 m2/g), and good thermal stability. High removal efficiencies of BB41 98.6% and EBT 82.5% were recorded at the specific experimental condition. The experimental data were fitted with the Langmuir isotherm model at R2 0.99 for both dyes whereas the adsorption kinetics revealed the pseudo-second-order kinetics at R2 ∼ 1 and 0.99 for BB41 and EBT, respectively. Furthermore, four regenerations of biochar with adsorption performances of BB41 and EBT dyes were found to be 94.7% and 79.1%, respectively. Finally, this adsorbent can be considered an economically viable material for the removal of synthetic dyes from wastewater systems. In conclusion, the study findings showed that the adsorbent material is promising to apply for water and wastewater treatment but still, the study of adsorption interaction and modifications of the surface functionalities are essential to accommodate multipollutant removal from real water systems.

Water scarcity and increasing urbanization are forcing municipalities to consider alternative water sources, such as stormwater, to fill in water supply gaps or address hydromodification of receiving urban streams. Mounting evidence suggests that stormwater is often contaminated with human feces, even in stormwater drainage systems separate from sanitary sewers. Pinpointing sources of human contamination in drainage networks is challenging given the diverse sources of fecal pollution that can impact these systems and the non-specificity of traditional fecal indicator bacteria (FIB) for identifying these host sources. As such, we used a toolbox approach that encompassed microbial source tracking (MST), FIB monitoring, and bacterial pathogen monitoring to investigate microbial contamination of stormwater in an urban municipality. We demonstrate that human sewage frequently contaminated stormwater (in >50% of routine samples), based on the presence of the human fecal marker HF183, and often exceeded microbial water quality criteria. Arcobacter butzleri, a pathogen of emerging concern, was also detected in >50% of routine samples, with 75% of these pathogen-positive samples also being positive for the human fecal marker HF183, suggesting human municipal sewage as the likely source for this pathogen. MST and FIB were used to track human fecal pollution in the drainage network to the most likely point source of contamination, for which a sewage cross-connection was identified and confirmed using tracer dyes. These results point to the ubiquitous presence of human sewage in stormwater and also provide municipalities with the tools to identify sources of anthropogenic contamination in storm drainage networks.IMPORTANCEWater scarcity, increased urbanization, and population growth are driving municipalities worldwide to consider stormwater as an alternative water source in urban environments. However, many studies suggest that stormwater is relatively poor in terms of microbial water quality, is frequently contaminated with human sewage, and therefore could represent a potential health risk depending on the type of exposure (e.g., irrigation of community gardens). Traditional monitoring of water quality based on fecal bacteria does not provide any information about the sources of fecal pollution contaminating stormwater (i.e., animals/human feces). Herein, we present a case study that uses fecal bacterial monitoring, microbial source tracking, and bacterial pathogen analysis to identify a cross-connection that contributed to human fecal intrusion into an urban stormwater network. This microbial toolbox approach can be useful for municipalities in identifying infrastructure problems in stormwater drainage networks to reduce risks associated with water reuse.