Environmental Pollution Control Research Articles

[Characteristics of Microorganisms and Antibiotic Resistance Genes of the Riparian Soil in the Lanzhou Section of the Yellow River].

Riparian soil is a critical area of watersheds. The characteristics of biological contaminants in riparian soil affect the pollution control of the watershed water environment. Thus, the microbial community structure, antibiotic resistance genes (ARGs), and mobile genetic elements (MGEs) in the riparian soil of the Lanzhou section of the Yellow River were investigated by analyzing the characteristics of soil samples collected from farmland, mountains, and industrial land. The results showed that the Proteobacteria, Bacteroidetes, and Actinobacteria were the dominant phyla in the riparian soil of Lanzhou section of the Yellow River. The microbial structure in the riparian soil was significantly correlated with the land use type (P < 0.05). The α diversity index of bacterial communities in land types was in the order of farmland > mountain > industry. Sulfonamide-typed ARGs were the most dominant genes in the soil of the Lanzhou section of the Yellow River Basin, among which the sul1 gene had the highest abundance, 20-36 000 times that of other detected ARGs. Moreover, the total absolute abundance of ARGs in industrial soil was the highest. Principal coordinate analysis (PCoA) displayed that the ARGs characteristics had a significant correlation with land types (P < 0.05), and intl1 and tnpA-04 drove the diffuseness of sulfonamide and tetracycline ARGs, respectively. Redundancy analysis (RDA) demonstrated that the content of inorganic salt ions and total phosphorus in the soil of the riparian zone of the Yellow River Lanzhou section were the main environmental factors, modifying the distribution of the microbial structure. Halobacterota and Acidobacteriota were the main microflora that drove the structural change in ARGs.

Carbon Dots Derived from Jaggery Via Direct Heating: A Sensitive Platform for Ferric Ion Fluorescent Sensing

Carbon Dots Derived from Jaggery Via Direct Heating: A Sensitive Platform for Ferric Ion Fluorescent Sensing

Boosting photocatalytic activity in ternary lamellar hierarchical structured ZnFe2O4/polymeric carbon nitride by constructing an electronic bridge

Photocatalytic technology is one of the ideal approaches for clean energy production and environmental pollution control in the future. However, the rapid recombination of photo-generated charge carriers is a bottleneck problem of low solar energy conversion efficiency. Herein, a magnetic ZnFe2O4/Pt/polymeric carbon nitride (PCN) semiconductor catalyst is designed and prepared for high-performance photocatalytic hydrogen production reaction and photocatalytic degradation rate of RhB. It exhibits 339.31 μmol·g−1·h−1 hydrogen production rate and 96.08 % photocatalytic degradation rate of RhB within 120 min under visible light. The introduction of Pt, constructing an electronic bridge, accelerated the transfer of photo-generated carriers, meanwhile, the smaller band gap of the ternary composites enabled the generation of more photo-generated electrons. The internal electric field accelerated the accumulation of electrons and holes in the conduction band of ZnFe2O4 and valence band of PCN, thus photocatalytic activity is greatly enhanced. The electron-hole separation is also improved and the transport of photo-generated electrons is facilitated by the special structure of the heterojunction and the unique morphology of PCN. In addition, the used catalyst can be recovered through magnetic fields, and this magnetic catalytic system has great application prospects in the fields of photocatalytic hydrogen production and pollutant degradation.

Preparation of porous carbon fibres : A review

Porous carbon fibres(PCF) was extensively applied to energy storage, environment pollution control and healthcare due to their superior electrical conductivity, diverse aperture,high specific surface area and super electrochemical stability.This paper reviewed the methods of preparing porous carbon fibres.The preparing PCF technology mainly included template methods( hard templates,soft templates, dual-templates), electrospinning technology and polymer blend technology. The working principles of different pore-forming techniques were summarized.The contributions of different preparation techniques to improve material properties such as electrochemical properties,adsorption performance,drug sustained-release materials and catalitic activity in practical applications were described.The different preparation methods had their superiorities and places needed improving.It was proposed that develop more advanced template methods to prepare PCF with reasonable cost, zero environmental pollution, high efficiency and easy removal.

High potential in synergizing the reduction of dissolved organic carbon concentration and carbon dioxide emissions for submerged-vegetation-covered river networks

Various technologies and projects have been explored and developed for the synergetic control of environmental pollution and carbon emissions in aquatic ecosystems. Planting submerged vegetation in shallow waters was also expected to achieve this purpose. However, the magnitude and mechanism of carbon dioxide (CO2) emission affected by submerged vegetation is not clear enough in complex aquatic ecosystems. This study investigated the influences of submerged plants on CO2 emission, ecosystem metabolism features, and microbial community traits based on observations in river networks on the Changjiang River Delta. The results showed that CO2 emission from planted waters accounted for 73% of unplanted waters. Meanwhile, planted waters had higher dissolved organic carbon removal capacity in overlying water and higher potential of carbon sequestration in sediment at the same time. These distinctions between the two habitats were attributed to (1) improved CO2 and bicarbonate consumption in water columns via enhancing photosynthesis and (2) inhibited CO2 production by reconstructing the benthic microbial community. Additional eco-advantages were found in planted sediments, such as a high potential of methane oxidation and xenobiotics biodegradation and a low risk of becoming black and odorous. In brief, submerged vegetation is beneficial in promoting pollution removal and carbon retention synchronously. This study advances our understanding of the feedback between aquatic metabolism and CO2 emission.

Environmental Policy Overlays and Urban Pollution and Carbon Reduction—Evidence from China

The in-depth promotion of environmental pollution prevention and control is a must for China to move towards green development, and the effectiveness of urban environmental pollution control largely depends on the selection of these environmental policies and the synergistic application of these policies. This paper empirically tests three environmental policies’ mixed and synergistic effects using Chinese urban data from 2000 to 2017. This study found that (1) the three environmental policies significantly curb urban environmental pollution and show synergistic effects. (2) The three types of environmental policies can have a superimposing effect by strengthening financial inputs and increasing environmental concern, as well as a complementary effect by improving the efficiency of environmental protection enforcement and the institutional environment. The synergy between the central environmental protection inspection policy and the environmental information disclosure policy is more of a superposition effect than a complementary effect due to the similarity of the policy objectives. (3) The synergistic effect of environmental policies is affected by factors such as the age of the principal officials and financial pressure. The younger the age of the principal officials and the cities with less financial pressure are more capable of utilizing the synergistic effect of environmental policies to form a situation where the market, the government, the public, and the enterprises work together to govern the city. This paper provides new ideas for exploring the synergies and mechanisms of environmental policies and theoretical references for the design, implementation, and effects of environmental policy portfolios in the 14th Five-Year Plan period.

Nonlinear Regression Approach as a Correction Factor of Measurements of Low-Cost Electrochemical Air Quality Sensors

Air quality directly affects the health of humans. The health implications of poor air quality are recognized by professionals and the public alike and these concerns have driven both the proliferation of formal sensor networks, but also low-cost sensors which can be used in the home. The advancement of technology in recent years has also led to the rapid development of low-cost sensors. Given that citizens are concerned about the air quality of the environment in which they live, they are turning to the supply of low-cost sensors, as they are affordable. The question of the reliability of measurements from low-cost sensors remains an area of research. In this research work, the optimization of ozone (O3) and nitrogen dioxide (NO2) measurements of low-cost electrochemical air quality sensors is investigated by applying nonlinear regression, using a second-order polynomial equation as a correction factor. The proposed correction method is implementable in IoT devices, as it does not require high computational resources. The results show that the measurements are susceptible to correction, with the effect that the corrected values are close to the actual values obtained by the reference instruments of the Department of Environmental Pollution Control Project of Athens (PERPA), a service of the Greek Ministry of the Environment and Energy.

Criminal Protection against Environmental Pollution in Omani and UAE Legislation

The article analyses the role of the criminal legislator in the field of environmental protection guaranteed by both Omani and UAE legislators. The problem of the study was the extent to which the Omani and UAE legislators contributed to the criminal protection of the environment. The study aimed to indicate and determine the content, elements, and penalties imposed by the Omani and UAE legislators for environmental offences. The study found several conclusions and recommendations, the most important of which being that the Omani and UAE legislature has ensured the criminal protection of the environment by criminalizing acts that pose a serious threat to one or more elements of the environment either by an explicit provision in the Penal Code or by special laws relating to the protection of the environment or within the special law on environmental protection and pollution control. The penalties prescribed for the offence of environmental pollution must be reviewed by establishing penalties for deprivation of liberty and not only a fine.

Study on the thermal behaviour of spontaneous combustion of open-pit minerals

To study thermal behaviour during spontaneous combustion of an open-pit coal mine, mixed slag (coal, oil shale, and coal gangue) was taken as the research object. Laser thermal conductivity analyser and differential scanning calorimetry were used to test thermophysical parameters and heat release characteristics of the minerals. The parameters can be employed to calculate the apparent activation energy using the Arrhenius equation and evaluate the thermal behaviour of open-pit mixed slag. The results indicate that thermophysical parameters have stage characteristics. Thermal diffusivity and thermal conductivity of minerals, especially mixed slag, have a strong correlation with temperature. Heat flow of minerals exhibits five characteristic stages, and heat flow of the samples is consistent with the change in heating rate. During the heating process, thermal diffusivity and heat flow of the mixed slag are between those of a single mineral. Except for the mixed slag at 15 and 20 °C/min, the initial exothermic temperature of the other samples is mainly concentrated at 50–80 °C. Thermal energy release of the sample is mainly concentrated in the accelerated exothermic stage and rapid exothermic stage. Thermal energy release of mixed slag in rapid exothermic stage is always greater than that in accelerated exothermic stage, and the proportion of thermal energy release in these two stages exceeds 98 %. The apparent activation energy during the accelerated exothermic stage is lower, making it easier to release heat, and rapid exothermic stage is relatively high, which can readily lead to heat accumulation. Thermal analysis reveals that the thermal behaviour of mixed slag is significantly different from that of a single mineral. Its unique exothermic characteristics can provide a more accurate theoretical basis for the prevention and control of environmental pollution caused by slag spontaneous combustion.

The treatment of acid mine drainage using a combination of selective precipitation and bio-sorption techniques: A hybrid and step-wise approach for AMD valorization and environmental pollution control

In this study, selective precipitation using magnesium oxide (MgO) and bio-sorption with banana peels (BPs) were explored for the treatment and valorization of acid mine drainage (AMD). The treatment chain comprised two distinct stages of which selective precipitation of chemical species using MgO (step1) and polishing of pre-treated AMD using BPs (step 2). In stage 1, 2.0 L of AMD from coal mine were used for selective precipitation and recovery of chemical species using MgO. The results revealed that chemical species of concern were precipitated and recovered at different pH gradients with Fe(III) precipitated at pH ≤ 4, Al at pH ≥ 4-5, Fe(II), Mn and Zn at pH ≥ 8 while Ca and SO42─ were precipitated throughout the pH range. In stage 2, the pre-treated AMD water was polished using BPs. The results revealed an overall increase of pH from 1.7 to 10, and substantial removal of chemical species in the following removal efficiency: Al, Cu and Zn (100% each), ≥ Fe and Mn (99.99% each), ≥ Ni (99.93%), and ≥ SO42─ (90%). The chemical treatment step removed pollutants partially, whereas the bio-sorption step acted as a polishing stage by removing residual pollutants.

SnO2-modified CuMnOx catalysts for humid CO oxidation at low temperature

Low-temperature CO oxidation has been widely applied in environmental pollution control, but challenges remain in CO purification in high-humidity environments. In this study, the CuMnSn8 catalyst exhibited excellent low-temperature CO oxidation performance, achieving complete CO oxidation at temperatures below 55 °C in 85 % relative humidity. A series of characterizations indicated that an appropriate amount of SnO2 doping could promote the formation of more amorphous oxides, increase the oxygen species content, and facilitate the dispersion of Cu and Mn elements. The catalytic active sites for CO oxidation and the influence of SnO2 doping on the CO oxidation mechanism were investigated through in-situ DRIFTS experiments. The results indicated that Sn enhanced the synergistic effect between Cu and Mn, altered the pathway of CO oxidation reaction, generated more easily decomposable bidentate carbonate intermediates. This work provides insight into the design of CO oxidation catalysts with high activity in high humidity.

Synergistic regulation of nanocomposite interlayered forward osmosis membranes with 1D/2D nanostructures for enhanced heavy metal retention

The treatment of heavy metal wastewater poses a significant challenge due to its adverse environmental consequences and potential hazards to human well-being, necessitating effective and sustainable solutions. Forward osmosis (FO) is an efficient and low-energy separation technology that serves as an effective strategy to address this issue. However, it still faces the trade-off between water permeability and selectivity, which directly impacts the solute separation efficiency and retention characteristics. In this study, a covalent organic framework (COF) interlayer was introduced via in-situ growth, and the surface properties of polyamide (PA) were synergistically regulated by amine-functionalized multi-wall carbon nanotubes (MWCNT-NH2), resulting in a 1D/2D nanocomposite interlayered FO membrane with a high crosslinking density, improved hydrophilicity, excellent stability, and antifouling properties. The synergistic effect of COF and MWCNT-NH2 led to an increase in the concentration of MPD participating in interfacial polymerization (IP) and a decrease in MPD diffusion rate. These improvements led to enhanced water permeability and selectivity, as well as outstanding retention efficiencies for heavy metal ions (Cr3+, Ni2+), exceeding 99.2 %. Therefore, this study holds significant implications for targeted application development of high-efficiency FO membranes in the future, demonstrating practical value in the treatment of heavy metal wastewater and environmental pollution control.

Improved convolutional neural network-assisted laser-induced breakdown spectroscopy for identification of soil contamination types

Identification of soil contamination types is of great scientific significance for soil remediation and environmental pollution control. However, traditional identification methods for soil determination are time-consuming, laborious, and complicated. Here, we proposed an accurate method for identifying soil contamination types based on laser-induced breakdown spectroscopy (LIBS) and an improved convolutional neural network (CNN) model. The spectral feature extraction-based multiple attention residual network (SFEMARNet) model was constructed to extract detailed features by spectral feature extraction (SFE) modules, and highlight useful features by multiple attention residual (MAR) modules in LIBS spectral data. In addition, deep learning models and machine learning models were used to identify the data. The results showed that the SFEMARNet model achieved an accuracy of 98.75% on the test set. The recall, precision, and F1-score of the models reached 98.78%, 98.75%, and 98.76%, respectively, which were significantly better than the three deep learning models and of four machine learning models. It seems that the SFEMARNet model combined with LIBS technology may be a potential method for the accurate identification of soil contamination types.

Development and characterization of a bacterial enzyme cascade reaction system for efficient and stable PET degradation

The widespread use of polyethylene terephthalate (PET) in various industries has led to a surge in microplastics (MPs) pollution, posing a significant threat to ecosystems and human health. To address this, we have developed a bacterial enzyme cascade reaction system (BECRS) that focuses on the efficient degradation of PET. This system harnesses the Escherichia coli (E. coli) surface to display CsgA protein, which forms curli fibers, along with the carbohydrate-binding module 3 (CBM3) and PETases, to enhance the adsorption and degradation of PET. The study demonstrated that the BECRS achieved a notable PET film degradation rate of 3437 ± 148μg/(d*cm²), with a degradation efficiency of 21.40% for crystalline PET MPs, and the degradation products were all converted to TPA. The stability of the system was evidenced by retaining over 80% of its original activity after multiple uses and during one month of storage. Molecular dynamics simulations confirmed that the presence of CsgA did not interfere with the enzymatic activity of PETases. This BECRS represents a significant step forward in the biodegradation of PET, particularly microplastics, offering a practical and sustainable solution for environmental pollution control. Environmental ImplicationPolyethylene terephthalate (PET) is a commonly utilized material in food packaging and various industries. Nevertheless, its disposal can have detrimental effects on the environment and human health as it transforms into microplastics in terrestrial and aquatic ecosystems. In response to the pressing global concern of PET pollution, we have introduced a novel whole-cell degradation system designed to effectively break down PET and its microplastics. This system involves the utilization of Escherichia coli that co-display binding and degradation modules on their surface while expressing a hydrolysis module internally. The strategy exhibits the robust repeatability and long-term storage stability of PET hydrolases.

Utilization of CRISPR-Cas genome editing technology in filamentous fungi: function and advancement potentiality.

Filamentous fungi play a crucial role in environmental pollution control, protein secretion, and the production of active secondary metabolites. The evolution of gene editing technology has significantly improved the study of filamentous fungi, which in the past was laborious and time-consuming. But recently, CRISPR-Cas systems, which utilize small guide RNA (sgRNA) to mediate clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated proteins (Cas), have demonstrated considerable promise in research and application for filamentous fungi. The principle, function, and classification of CRISPR-Cas, along with its application strategies and research progress in filamentous fungi, will all be covered in the review. Additionally, we will go over general matters to take into account when editing a genome with the CRISPR-Cas system, including the creation of vectors, different transformation methodologies, multiple editing approaches, CRISPR-mediated transcriptional activation (CRISPRa) or interference (CRISPRi), base editors (BEs), and Prime editors (PEs).

Analysis of Dynamic Evolution and Driving Factors of Low-Carbon Utilization Efficiency of Cultivated Land in China

In order to cope with global climate warming, measurement of the low-carbon utilization efficiency (LCUE) of cultivated land, considering carbon sink and carbon emission effects, is proposed. To address this, based on the data of 30 provinces in China, this study conducts a LCUE evaluation system by the MinDS-U-M productivity index model in order to analyze the spatiotemporal patterns and driving factors of LCUE with the geographic detector model and GTWR model. The results show the following: (1) Over the past 20 years, the average LCUE value exhibits a slow increasing trend from 2001 to 2021, which ranges from 0.9864 to 1.0272. Provinces with mid-level LCUE ranging from 1.0000 to 1.0990 account for the highest proportion in each period. (2) The annual growth rate of LCUE in the central region is the highest, where the promotion of green technology and farmland protection policies have played important roles. (3) According to the Geodetector analysis, urbanization rate (UR), irrigation index (IR), grain output value (GOV), precipitation (PR), arable land area (ALA), and environmental pollution control (EPC) are important drivers of the spatial difference of LCUE. (4) The GTWR model shows that the positive effects of ALA and SRT have always been concentrated in the main grain-producing areas over time. UR and PR have strong explanatory power for the space/time differentiation of LCUE, especially in eastern coastal regions. IR has an increasing effect on LCUE in the Western region, and the positive effect of EPC on the LCUE is concentrated in the central region. In order to coordinate regional LCUE contradictions, it is suggested to be wary of land resource damage caused by economic development, warn about the impacts of climate change, and strengthen the supervision of land remediation projects in order to achieve sustainable land management.

AIoT-driven multi-source sensor emission monitoring and forecasting using multi-source sensor integration with reduced noise series decomposition

The integration of multi-source sensors based AIoT (Artificial Intelligence of Things) technologies into air quality measurement and forecasting is becoming increasingly critical in the fields of sustainable and smart environmental design, urban development, and pollution control. This study focuses on enhancing the prediction of emission, with a special emphasis on pollutants, utilizing advanced deep learning (DL) techniques. Recurrent neural networks (RNNs) and long short-term memory (LSTM) neural networks have shown promise in predicting air quality trends in time series data. However, challenges persist due to the unpredictability of air quality data and the scarcity of long-term historical data for training. To address these challenges, this study introduces the AIoT-enhanced EEMD-CEEMDAN-GCN model. This innovative approach involves decomposing the input signal using EEMD (Ensemble Empirical Mode Decomposition) and CEEMDAN (Complete Ensemble Empirical Mode Decomposition with Adaptive Noise) to extract intrinsic mode functions. These functions are then processed through a GCN (Graph Convolutional Network) model, enabling precise prediction of air quality trends. The model’s effectiveness is validated using air pollution datasets from four provinces in China, demonstrating its superiority over various deep learning models (GCN, EMD-GCN) and series decomposition models (EEMD-GCN, CEEMDAN-GCN). It achieves higher accuracy and better data fitting, outperforming other models in key metrics such as MAE (Mean Absolute Error), MSE (Mean Squared Error), MAPE (Mean Absolute Percentage Error), and R2 (Coefficient of Determination). The implementation of this AIoT-enhanced model in air pollution prediction allows decision-makers to more accurately anticipate changes in air quality, particularly concerning carbon emissions. This facilitates more effective planning of mitigation measures, improvement of public health, and optimization of resource allocation. Moreover, the model adeptly addresses the complexities of air quality data, contributing significantly to enhanced monitoring and management strategies in the context of sustainable urban development and environmental conservation.

Spatial-temporal differentiation of urban eco-efficiency and its driving factors: A comparison of five major urban agglomerations in China.

This paper utilizes an improved undesirable output DEA model to measure the eco-efficiency of cities in five major urban agglomerations in China during 2006-2020. It employs the Theil Index and Geodetector to investigate the spatial-temporal distribution differentiation characteristics and driving factors of urban eco-efficiency. The main findings are as follows. Firstly, the eco-efficiency of all urban agglomerations showed a fluctuating upward trend, but the eco-efficiency performance of different urban agglomerations in China shows a stratification characteristic. Specifically, the Pearl River Delta urban agglomeration consistently ranks first in China, while the mean values of the Yangtze River Delta urban agglomeration, Beijing-Tianjin-Hebei urban agglomeration, and Chengdu-Chongqing urban agglomeration are lower than the national average. Secondly, the overall differences in the urban eco-efficiency of all sample cities show a consistently fluctuating downward trend. The factor that affects the level differences of eco-efficiency in different cities is the intra-regional differences. Last but not least, the top three factors affecting the spatial distribution difference of urban eco-efficiency in the whole sample are environmental pollution control investments, innovation level, and environmental infrastructure investments. In the end, this paper proposes that reducing the intra-regional differences is the primary task to achieve the coordinated improvement of urban eco-efficiency in urban agglomerations, and then puts forward some policy suggestions to improve eco-efficiency for the five major urban agglomerations.

Biosynthesis of PbO nanoparticles via Adhatoda vesica (Justicia adhatoda) leaves extract for antimicrobial and photocatalytic applications

Research applications in biology and the environment can benefit greatly from nanoscience and nanotechnology. Aqueous leaf extract of Adhatoda vesica (AV) mediated the formation of lead oxide (PbO) nanoparticles in this study. A XRD analysis confirmed that the lead oxide nanoparticles (PbO NPs) synthesized from leaves extract have a crystalline structure. UV–vis spectroscopy study of colloidal PbO nanoparticles absorption revealed the greatest absorption bands, and the photoluminescence (PL) emission spectrum revealed a broad nature of visible emission peaks with high surface defects. By analyzing PbO nanoparticles using the fourier transform infrared method (FTIR), the leaf extract demonstrated the presence of functional peaks. It was evident from the SEM images that most of the PbO NPs had a spherical, irregular sponge-like shape. Additionally, the PbO nanostructures were tested for their antibacterial activity against Escherichia Coli, and a high level of antibacterial activity was observed, indicating their suitability for antimicrobial applications. PbO NPs have been evaluated for photocatalytic degradation of methylene blue dye (MB) under UV irradiation and have produced indications that the synthesized material is suitable for photocatalytic degradation. The Adhatoda vesica is used as medicine and enhances lead oxide nanomaterials' antibacterial properties. The research is focused on focusing on environmental pollution control and treatment of different diseases such as asthma, bronchitis, tuberculosis, and other diseases through applications of Ayurveda, Siddha, Homeopathy, and Unani. A study based on these findings revealed that Adhatoda vesica (Justicia adhatoda) leaves extract can be utilized as a cost-effective and environmentally friendly alternative to producing lead oxide nanoparticles.

Natural pyrite-stimulative periodate activation: efficiency and mechanism study.

Natural pyrite (NP) is an alternative catalyst for wastewater purification via advanced oxidation processes (AOPs). However, the activation performance and mechanism of periodate (PI) by NP have not yet been revealed. Herein, this work examines the activation performance of NP towards PI and its application in the degradation of antibiotic wastewater. Interestingly, 95.69% of chlortetracycline (CTC) was degraded by NP within 20min via PI activation. Besides, NP shows effective degradation of various pollutants such as rhodamine B (65.81%), sulfamethoxazole (89.04%), and sodium butylxanthate (99.77%) within 20min. The active species quenching experiment suggested that the active species , , 1O2 and the active complex of PI bonded with NP surface participated in CTC degradation. In addition, Fe(II) on NP surface is the main active site for PI activation, while Sn2- species accelerates the reduction of Fe(III) to Fe(II) and promotes sustained PI activation. This work provides new ideas for the application of NP in environmental pollution control.