Frontiers in Environmental Research (FER) is an international peer-reviewed, open access journal.
SPATIO TEMPORAL EVOLUTION AND INFLUENCING FACTORS OF WATER RESOURCE USE EFFICIENCY IN THE BEIJING–TIANJIN–HEBEI REGION: EVIDENCE FROM A SUPER EFFICIENCY SBM AND TOBIT MODEL
This study investigates the efficiency of water resource utilization in the Beijing–Tianjin–Hebei (BTH) region from 2013 to 2023. By employing a super-efficiency Slacks-Based Measure (SBM) model incorporating undesirable outputs, this research evaluated the spatial-temporal evolution of efficiency. Subsequently, a Tobit regression model was applied to analyze 13 determinants across natural, economic, social, and environmental dimensions. The results reveal that the region’s efficiency followed a fluctuating trajectory characterized by phases of stability, growth, decline, and leveling off, with a mean value of 0.870. Significant spatial heterogeneity was observed, with Beijing and Tianjin exhibiting higher efficiency levels than Hebei. The Tobit analysis identified positive correlations with per-capita water resources, annual precipitation, per-capita GDP, the share of the tertiary industry, and water intensity, reflecting the influence of resource endowment, economic structure, and management capacity. Conversely, factors such as per-capita water use, the share of the primary industry, and insufficient scientific and technological investment exerted negative impacts, suggesting constraints related to redundant consumption and structural imbalances. Based on these findings, we recommend implementing differentiated regional management strategies, establishing a market-oriented agricultural water rights trading system, and creating an integrated BTH platform for the collaborative innovation and diffusion of water-saving technologies. These measures aim to foster sustainable resource utilization and high-quality regional development.
Copyright (c) 2025 YuYang Liu https://creativecommons.org/licenses/by/4.0
THE EFFECT OF OSPHF1 ON THE COMPOSITION AND STRUCTURE OF RHIZOSPHERE SOIL MICROORGANISMS IN RICE
Plant-microbe interactions represent a pivotal strategy for optimizing crop growth, and phosphorus (P) nutrition-related genes can mediate this process by regulating the composition of the rhizosphere microbial community. To investigate the effects of OsPHF1 ( Phosphate Transporter Traffic Facilitator 1 ) on the rhizosphere microbiota, we analyzed the differences in rhizobacterial community structures between OsPHF1 functional loss mutants ( Osphf1 ) and wild-type (WT) rice plants. High-throughput sequencing of 16S rRNA gene amplicons was performed to characterize the composition of the rhizosphere microbial community. The colonization abundances of Bacillus and Paenibacillus were quantified using the plate counting method, and pot experiments were conducted to verify the growth-promoting effects of Bacillus subtilis . The results show that the rhizobacterial community structure of Osphf1 mutants undergoes significant alterations, with distinct enrichment of taxa such as the phyla Pseudomonadota, Bacillota, Bacteroidota and Verrucomicrobiota. Within the phylum Bacillota, the abundances of the genera Bacillus and Paenibacillus in the rhizosphere of Osphf1 mutants are significantly higher than those in the rhizosphere of WT plants. The colonization amounts of Bacillus subtilis , Paenibacillus mucilaginosus and Paenibacillus polymyxa in the rhizosphere of Osphf1 mutants are all significantly increased. Inoculation with Bacillus subtilis significantly improves the aboveground fresh weight of rice plants, with an increase of 22.7% in WT plants and a more prominent increase of 31.6% in Osphf1 mutants. In conclusion, the OsPHF1 gene is involved in regulating the rhizosphere microbial community structure of rice, and specifically affects the rhizosphere enrichment and colonization of Bacillus species. These findings provide novel insights into the interaction mechanisms among plant nutrient-related genes, the microbiome and plant growth.
Copyright (c) 2026 Huang Wang; JinYu Zheng; Zhuang Xu; Lei Xu https://creativecommons.org/licenses/by/4.0
SPATIOTEMPORAL EVOLUTION OF CULTIVATED LAND PATTERN AND MULTIDIMENSIONAL DRIVING FORCE MECHANISM IN HEILONGJIANG PROVINCE
To deeply explore the dynamics of cultivated land use and its driving mechanism in Heilongjiang Province, a major grain-producing area in China, this study systematically reveals the spatiotemporal evolution characteristics of the cultivated land pattern in the study area over the past 20 years based on three phases of remote sensing of land use monitoring data (2000, 2010, and 2020) using methods such as land use transfer matrix and spatial analysis. On this basis, a driving force index system including natural factors (elevation, slope, precipitation, farmland production potential) and socioeconomic factors (population density, night-time light) was constructed. The Geographical Detector model was used to quantitatively examine explanatory capacity and interactive effects of each driving driver affecting the spatial heterogeneity of cultivated land changes in two time cross-sections (2000 and 2020). The research aims to clarify the evolution path of the cultivated land utilization pattern and its multidimensional driving force mechanism in Heilongjiang Province, providing a scientific basis for cultivated land protection, regional territorial space optimization, and the implementation of the national food security strategy.
Copyright (c) 2025 YiHui Chen; BoRui Li; XuSheng Zhao; BingYu Sun https://creativecommons.org/licenses/by/4.0
ENVIRONMENTAL RISKS AND ECOTOXICOLOGY OF ANTIBIOTIC POLLUTION IN WATER ENVIRONMENTS AND COMPREHENSIVE PREVENTION AND CONTROL STRATEGIES
The widespread detection of antibiotics in aquatic environments has become a global environmental issue, posing huge potential threats to ecosystems and human health. This paper systematically reviews research progress on antibiotic pollution in aquatic environments, focusing on its environmental behavior, ecotoxicological effects, and comprehensive prevention and control strategies. Firstly, an overview of the global and Chinese pollution status, major sources, and occurrence characteristics of antibiotics in aquatic environments is provided. Secondly, the migration and transformation laws, environmental fate, and ecological risk assessment methods of antibiotics in aquatic environments are explored in depth. Then, the ecotoxicological effects of antibiotics on aquatic organisms are elaborated in detail, including impacts on microbial community structures, the generation and spread of antibiotic resistance genes (ARGs), toxic effects on aquatic animals and plants, and potential risks to human health. Finally, comprehensive prevention and control strategies are proposed from four levels: source control, process interception, end-of-pipe treatment, and system management. Future research directions are also outlined to provide a scientific basis for the risk management of antibiotic pollution in aquatic environments.
Copyright (c) 2025 ZhiJiang Nan https://creativecommons.org/licenses/by/4.0
RAINFALL PREDICTION FOR QINGMING FESTIVAL BASED ON ARIMA-LSTM MODEL
Requent rainfall during the Qingming Festival period has impacted public travel, cultural and tourism activities, as well as urban management. Based on nearly 20 years of meteorological data, this study develops an ARIMA-LSTM hybrid model to model and predict rainfall patterns in five representative cities: Xi’an, Turpan, Wuyuan, Hangzhou, and Wuhan. The results indicate that the model demonstrates strong fitting accuracy and stability, with an average R2 of 0.84196 and a prediction accuracy of 89.9%. After incorporating a real-time correction mechanism, the model’s responsiveness to abrupt weather changes improved, with error control enhanced by over 15%. This study provides data support and methodological reference for short-term meteorological services and public travel during the Qingming Festival.
Copyright (c) 2025 XinYing Song; YuXuan Zhao; SiYu Yang; Chao Luo; ZhenCheng Fu https://creativecommons.org/licenses/by/4.0
ECOSYSTEM SERVICES SUPPLY–DEMAND DYNAMICS AND MULTIDIMENSIONAL RELATIONSHIPS IN THE SHIYANG RIVER BASIN
Arid inland river basins are highly sensitive to climate change and anthropogenic disturbances, and persistent imbalances between the supply and demand of ecosystem services have become a critical constraint on regional sustainable development. Taking the Shiyang River Basin, a typical arid inland river basin in northwestern China, as the study area, this research selected four categories of ecosystem services—food provision, water yield, carbon storage, and windbreak and sand fixation. Using a parameter-calibrated InVEST model and GIS-based spatial analysis, we quantified ecosystem services supply and demand from 2000 to 2020, and evaluated supply–demand relationships across three dimensions: quantity matching, spatial matching, and trade-off/synergy assessment. The results show that: (1) From 2000 to 2020, the average supply of food provision and water yield exhibited an increasing trend, whereas carbon storage and windbreak and sand fixation showed fluctuating changes. High food supply was mainly concentrated in oasis areas, while the supply of water yield, carbon storage, and windbreak and sand fixation decreased from the southwest to the northeast; (2) During 2000–2020, the average demand for food provision and carbon storage continued to increase, while the average demand for water yield and windbreak and sand fixation gradually declined. High-demand areas for food provision, water yield, and carbon storage were primarily located in the main urban areas of the oasis, whereas demand for windbreak and sand fixation was mainly distributed in oasis–desert transition zones and desert regions; (3) In terms of quantity matching, food provision and carbon storage were predominantly surplus-oriented, water yield exhibited comparable proportions of surplus and deficit areas, and windbreak and sand fixation were dominated by deficit conditions. For all ecosystem services, low-low spatial matching and synergistic relationships were dominant, with synergy zones accounting for more than 50% of the basin.
Multidimensional supply–demand relationships
Copyright (c) 2025 ZeTao Chen https://creativecommons.org/licenses/by/4.0
THE ROLE OF MICROORGANISMS IN SOIL SALINIZATION REMEDIATION
Saline soil is one of the main forms of soil degradation, covering approximately 1 billion hectares globally. It is mainly found in Russia, the United States and China. Climate warming and improper irrigation practices have accelerated the salinization of the soil, posing a threat to crop productivity. In recent years, microorganisms, as an important part of the natural cycle, have been playing an increasingly significant role in the restoration of soil salinization. However, a comprehensive bibliometric analysis of this field has not yet been performed. Here CiteSpace, VOSviewer and the Bibliometrix R package were used to predict future trends in this field. The results showed numbers of published papers on the role of microorganisms in soil salinization remediation is increasing year by year. Functional microorganisms play a crucial role in restoring saline-alkali wetlands by regulating the expression of plant salt-tolerance genes and improving the soil microenvironment. Future research will focus on designing synthetic microbial communities, analyzing multi-omics interaction networks, and jointly enhancing the efficacy of ecological restoration and carbon sequestration, providing innovative solutions for the sustainable management of saline-alkali wetlands.
Copyright (c) 2025 XinRui Fan; DongXue Chen; Tong Gou; GanChenXi Chen; XuYue Zhang; HaiYan Xi; Jie Wei https://creativecommons.org/licenses/by/4.0
COMPARATIVE STUDY OF DIFFERENT WAVELET TRANSFORM METHODS FOR GNSS COORDINATE TIME SERIES ON THE QINGHAI–TIBET PLATEAU
This study analyzes 1,611 days of GNSS data from the LHAZ IGS station on the Qinghai–Tibet Plateau (2018–2022). Daily coordinate time series were derived using GAMIT, followed by outlier removal and spline interpolation. Multi-resolution denoising was performed with DWT, CWT, and MODWT. Results show westward X displacement, minor Y fluctuations, and ~3 mm/year Z uplift with periodic variations. MODWT achieved the best denoising, outperforming DWT and CWT. MODWT is recommended for full 3D time series, while DWT suffices for horizontal-only applications. This study provides robust technical support for GNSS time series analysis on the Qinghai–Tibet Plateau.
Copyright (c) 2025 Wei Wu; JiWei Ma https://creativecommons.org/licenses/by/4.0
SURFACE DEFORMATION MONITORING AND ANALYSIS IN XINJING MINING AREA BASED ON SBAS-INSAR TECHNOLOGY
Large-scale mining activities in mining areas can induce surface deformation phenomena, threatening the stability of peripheral production systems and residential environmental safety. Consequently, implementing high-precision surface deformation monitoring has become a critical component of mine safety assessment systems and ecological restoration projects. This study takes the Xinjing Mining Area in Alxa League, as a case study. Utilizing 20 scenes of Sentinel-1 ascending orbit images acquired from January 2022 to December 2023, this study applied the SBAS-InSAR technique for deformation monitoring and analysis. The results demonstrated complex deformation patterns in the Xinjing Mining Area during the study period, primarily characterized by subsidence. The deformation rate across the study area ranged from -125.8 mm/a to +36.3 mm/a, with cumulative deformation magnitudes ranging from -213.3 mm to +76.7 mm. The deformation process evolved through three distinct phases: an accelerated deformation phase, a moderate deformation phase, and a stabilization phase. This study provides essential data support and a scientific basis for preventing mining-induced subsidence caused by engineering activities in mining areas.
Copyright (c) 2025 FangZhou Fu https://creativecommons.org/licenses/by/4.0
AN ECOSYSTEM-SERVICE EVALUATION METHOD OF A RIVER BASIN WITH RAPID CHANGES IN LAND USE WITHIN A SHORT TERM
In 2015, Zhangjiakou City was selected as the co-host city for the 2022 Winter Olympics. In order to improve ecosystem service functions, land use types in the region were changed greatly within the short term. Therefore, existing evaluation methods of the ecosystem service value (ESV) are not applicable to such an underdeveloped region. With the year of 2015 as the key time node, a dynamic process evaluation method of ESV was established for Zhangjiakou City based on classic equivalent factors in this study. The five economic coefficients of net primary productivity (NPP) coefficient, precipitation adjustment coefficient, soil conservation adjustment coefficient, habitat adjustment coefficient and accessibility adjustment coefficient were introduced into the classic method to correct the commonly Chinese equivalent factors to obtain the actual ESV. Firstly, the results obtained from the dynamic process evaluation method could clearly distinguish the changing trend of ecosystem service value (ESV) after the change of land use type. Secondly, the ESV increment calculated with the dynamic process evaluation method was more sensitive to land use change. The change in the forest area proportion was the most significant and reached 6.8%, and corresponding ESV increment was 14.89%. Thirdly, from the perspectives of 11 sub-categories of ecosystem services, the ESV of hydrological regulation was the largest and reached 30%. The ESVs of food production, raw material production, maintenance of nutrient cycle, water supply and aesthetic value supply were relatively small. From the sub-categories of enhancing ecosystem services, the ESV of each sub-category increased after changing land use type. Fourthly, after the introduction of five economic adjustment coefficients, the ESVs of the other four categories of ecosystem services, except the ESV of biodiversity, increased significantly after the change in the land use types. The results indicated that the dynamic evaluation method could better identify the sensitive factors affecting the value of regional ecosystem services.
Copyright (c) 2025 HeSheng Zhang; MengHao Li; ZiYao Xing; YuLing Zhang; Xin Zan; XiaoYu Jia https://creativecommons.org/licenses/by/4.0
OPTIMIZATION OF RIPARIAN PLANT COMMUNITIES IN MOUNTAINOUS URBAN PARKS BASED ON THE CONCEPT OF REWILDING — A CASE STUDY OF CHONGQING URBAN AREA
This study examines the riparian zones of seven representative urban parks in Chongqing, exploring strategies for optimizing plant communities based on the concept of "rewilding." The findings indicate several issues in the current riparian vegetation, including a dominance of cultivated species (accounting for 80.57%), a simplistic community structure (with "tree + herb" combinations comprising 57.94%), and a scarcity of wild species (only 55 species, or 19.43%). These factors result in low biodiversity (average Shannon-Wiener index of 1.52), weak soil and water conservation capacity (soil erosion modulus of 312 t/(km2·a) in areas with a single structure), and landscape homogenization, all of which limit the ecological service functions of these areas. Rewilding refers to enhancing ecosystem self-regulation by reducing human intervention and actively introducing native species. Constraints to rewilding include excessive human interference, habitat fragmentation, invasive plant species, and outdated management practices.Based on this, a series of optimization strategies are proposed, including the selection of native wild plants, the development of multilayered plant communities, the implementation of tiered management and targeted control of invasive species, and the encouragement of public participation, aiming to provide scientific support and practical guidance for the ecological restoration of riparian zones in mountainous cities.
Copyright (c) 2025 KaiWei Du; ChengJi Shu; YuSong Li; ZiYi Jiang; YunDuo Kang https://creativecommons.org/licenses/by/4.0
INTELLIGENT PREDICTION OF WATER QUALITY PARAMETERS BASED ON IMPROVED PARTICLE SWARM OPTIMIZATION COUPLED WITH RANDOM FOREST MODEL
In recent years, the problem of water pollution has become increasingly serious, and traditional water quality monitoring methods are difficult to meet the demand for high precision. Constructing an efficient and reliable water quality prediction model is of great significance for governance decisions. To this end, this paper proposes a random forest (IPSO-RF) water quality prediction model optimized based on the improved particle swarm algorithm. Firstly, for the problems of traditional particle swarm algorithm (PSO), such as easy premature convergence and insufficient global search ability, an improved particle swarm algorithm (IPSO) with nonlinear iteration incorporating inertia weights is proposed, and its optimization performance is verified based on typical test functions. Secondly, the IPSO algorithm is combined with random forest (RF) to optimize the key hyperparameters of RF (e.g., the number of decision trees, the minimum number of samples for node splitting, etc.) in order to improve the prediction accuracy and generalization ability of the model. Simulation experiments were carried out based on the water quality monitoring data of a watershed, and the results showed that compared with RF and standard PSO-RF and other models, the IPSO-RF model showed lower MSE in the prediction of key indicators such as dissolved oxygen, phosphorus content of water body and ammonia nitrogen amount of water body, which verified its superiority in the prediction of water quality. This study not only provides new ideas for the application of intelligent optimization algorithms in the field of water environment, but also provides more accurate technical support for water quality monitoring and pollution prevention and control of environmental protection departments.
Copyright (c) 2025 JinYi Luo https://creativecommons.org/licenses/by/4.0
SUITABILITY EVALUATION OF WATER INDEX UNDER EXTRACTION OF COMPLEX ENVIRONMENTAL WATER BODIES
With the development of remote sensing technology, remote sensing images are more and more widely used in water monitoring. This paper uses Landsat 8 remote sensing images as the data source, selects Poyang Lake, Taihu Lake and Dingnan County as the study area, and combines NDWI, MNDWI, EWI, SWI, TCW, MBWI, WI2015, AWEInsh and AWEIsh to extract water bodies and evaluate the accuracy of the study area. The results are as follows: 1. The overall extraction accuracy of TCW and MBWI is the highest. 2. For mountain shadow areas, AWEInsh and TCW have the best extraction effect. For shallow water area, TCW and MBWI have the b est extraction effect, and the spectral distinction between water and non water is greatly increased. For the eutrophication area of water body, the ten methods have high accuracy, and can distinguish the spectral characteristics of chlorophyll and non water body.
Copyright (c) 2025 ZhiHua Liu https://creativecommons.org/licenses/by/4.0
REVEALING HETEROGENEITY OF N2O CONCENTRATION IN SELECTIVE CATALYTIC REDUCTION DENITRIFICATION: A MULTI-POINT SAMPLING STUDY IN COAL-FIRED POWER PLANT
Selective catalytic reduction (SCR) plays a critical role in achieving ultra-low emissions from coal-fired power plants by enabling highly efficient removal of nitrogen oxides (NOx). However, the denitrification process may concurrently generate nitrous oxide (N 2 O), a potent greenhouse gas often overlooked in emission control strategies. Crucially, conventional continuous emission monitoring systems (CEMS) focus solely on NOx reduction efficiency without tracking byproduct formation, creating a potential blind spot for N 2 O emissions when reduction reactions are incomplete. To address this gap, this study conducted multi-point on-site sampling monitoring within SCR system of ultra-low emission units at a 693 MW coal-fired power plant and a separate 2× 300 MW plant. A pivotal question was investigated: Are N 2 O emissions inevitably elevated by SCR operation? Our findings reveal significant spatial heterogeneity in N 2 O distribution: while concentrations increased at certain locations (e.g., upstream catalyst layers), they unexpectedly decreased at others (e.g., optimized mid-reactor zones), demonstrating position-dependent synergistic reduction of NOx and N 2 O under specific operational conditions. This work highlights the necessity of multi-dimensional emission assessment beyond standard CEMS protocols and provides actionable insights for co-controlling air pollutants and greenhouse gases in industrial air pollution control systems.
Copyright (c) 2025 ZePeng Li; Yasser M. A. Mohamed; YingHui Han https://creativecommons.org/licenses/by/4.0
SPATIOTEMPORAL VARIABILITY OF YELLOW RIVER WATER-SEDIMENT FLUXES: A HYBRID APPROACH USING CUBIC SPLINE INTERPOLATION AND MANN-KENDALL TEST
Studying the variation law of water and sediment fluxes in the Yellow River is of great significance for environmental protection, adaptation to climate change and improvement of the quality of life of residents in the Yellow River Basin. this paper established a cubic spline interpolation model to supplement the missing sediment content data. By using the known data and interpolation data for plotting, it was found that the interpolation effect was good. Subsequently, the total drainage volume and total sediment discharge volume from 2016 to 2021 were calculated respectively using the interpolation data. In order to further study the variability of water and sediment content, this paper adopts the Mann-Kendall non-parametric test method to analyze the variability of water and sediment flux, revealing its inherent law. Through specific data analysis, the important role of sand regulation and water control in ensuring the ecological health of the Yellow River has been further demonstrated.
Copyright (c) 2025 Yun Xiao https://creativecommons.org/licenses/by/4.0
RECONSTRUCTION OF SEVERAL LANDSLIDE DAMMED LAKES IN THE UPPER REACHES OF JINSHA RIVER AND ITS INFLUENCE ON RIVER PROFILE EASTERN TIBETAN PLATEAU
The damming phenomenon caused by landslides is a significant disturbance factor in the evolution of mountainous rivers, influencing river morphology across multiple timescales. The temporal characteristics of this phenomenon are often analyzed by examining the relationship between dam locations and the river longitudinal profile within a specific area. In the Batang section of the upper Jinsha River, located within the Jinsha river suture zone, intense tectonic activity makes the region highly susceptible to geological hazards such as landslides. Through data collection, remote sensing interpretation, and field investigations, we identified nine landslide dams in this area. Systematic studies of these dams were conducted, including preliminary measurements of dam heights and volumes. By reconstructing dam elevations, we calculated the areas, volumes, and peak discharge flows of the associated dammed lakes. A detailed analysis of the Wangdalong landslide dam revealed that its maximum lake surface area reached 106.70 million m 2 , with a maximum volume of 14.57 billion m 3 . The peak discharge flow was calculated at 31.98×104 m 3 /s, and the dammed lake existed for a duration of approximately 1.09-1.76 ka. Additionally, a comparison of river geomorphological parameters indicated that the impact of a single dammed lake on the river's longitudinal profile is limited when its duration is relatively short. However, clusters of dammed barriers significantly affect the river steepness index, increasing the likelihood of forming knickpoints. These findings provide valuable insights into the role of landslide dams in shaping the geomorphological evolution of mountainous river systems.
Copyright (c) 2025 LiQin Zhou; Lu Cong https://creativecommons.org/licenses/by/4.0
QUANTITATIVE STUDY ON METHANE EMISSION IN LIAONING PROVINCE BASED ON GAUSSIAN PLUME MODEL
Methane, a critical greenhouse gas, significantly contributes to climate warming. This study quantifies methane emissions in Liaoning Province, China—a major industrial region—using TROPOMI satellite data and the Gaussian plume model. Filtered satellite observations and ERA5 meteorological parameters were integrated to retrieve emission rates and spatial patterns. Results indicate annual methane emissions of (720 ± 150) Gg yr -1 , with coal mining accounting for more than 60%. Seasonal analysis highlights elevated winter emissions linked to heating-related coal use. Satellite-derived emissions exceed EDGARv6.0 estimates by approximately 35%, suggesting underreported industrial sources, particularly mine ventilation leaks. The study demonstrates the effectiveness of combining remote sensing and dispersion modeling for regional methane monitoring. Key recommendations include enhancing emission inventories through high-resolution models and promoting methane recovery technologies in coal and steel sectors. These findings emphasize the need for targeted industrial emission controls to address climate and air quality challenges.
Copyright (c) 2025 YuChao Zhang https://creativecommons.org/licenses/by/4.0
GROUNDWATER LEVEL FITTING OF MONITORING WELLS IN THE BAODING REGION BASED ON LONG SHORT-TERM MEMORY (LSTM) NEURAL NETWORKS
This study applies a Long Short-Term Memory (LSTM) neural network to model daily groundwater level variations at four monitoring wells in the piedmont plain of Baoding City, Hebei Province, China. Using daily data from January 1, 2018 to August 31, 2019, the LSTM model is trained and tested under a one-step rolling prediction framework. The results demonstrate that the LSTM model accurately fits groundwater time series across various hydrogeological conditions, with testing-phase RMSE values ranging from 0.08 to 0.45 meters and R2 values exceeding 0.90. The model performs exceptionally well for both stable and fluctuating groundwater level conditions, capturing seasonal decline and recovery patterns without requiring explicit seasonal indicators. It also reveals the model’s ability to learn long-term trends and nonlinear dynamics inherent in groundwater systems. Despite its high short-term prediction accuracy, challenges remain regarding multi-step forecasting and responses to extreme events outside the training data. The study concludes that LSTM offers strong potential for groundwater simulation in data-limited environments and recommends further integration of hydro-meteorological variables for enhanced model robustness.
Copyright (c) 2025 Wei Guo https://creativecommons.org/licenses/by/4.0
CO-PYROLYSIS OF BIOMASS-BASED FURAN AND METHANOL TO LIGHT AROMATICS OVER MODIFIED HIERARCHICAL ZEOLITES
Light aromatics, including benzene, toluene, and xylene, are essential chemical feedstocks, traditionally produced via catalytic reforming of petroleum fractions. Due to the depletion of fossil resources, lignocellulose has attracted considerable interest as a renewable carbon source. Furans as key platform molecules can be catalyzed into aromatics over zeolites; however, their application is often limited by low selectivity and catalyst deactivation from coke. In this work, a co-pyrolysis approach using 2-methylfuran and methanol was developed to enhance aromatic production. Methanol served both as a heat-releasing agent during the aromatization process and as a hydrogen donor due to its high effective hydrogen-to-carbon ratio, promoting a synergistic effect with furan compounds, enhancing aromatization efficiency. Hierarchical HZSM-5 modified with Ga, Zn, Mo, and W were synthesized and characterized using various characterization techniques to correlate pore structure and acidity with product distribution. It is found that W-modified HZSM-5 can further improve the carbon yield of aromatics (70.62%), while other metal modifications resulted in decreased performance due to reduced acidity and pore blockage, accompanied by increased coke formation. This strategy provides new insight into the efficient catalytic conversion of biomass-derived platform molecules into high-value aromatics.
Copyright (c) 2025 Qing Xu; JunMing Liang; DongYan Zhang; ShengPeng Xia; AnQing Zheng; Kun Zhao; ZengLi Zhao https://creativecommons.org/licenses/by/4.0
CAN OPEN WEB DATA ASSESS URBAN FLOOD RISK? EVIDENCE FROM ZHENGZHOU
Under extreme rainfall scenarios, urban stormwater pipe networks are prone to saturation and failure, rendering flood risk assessment under such conditions of critical importance. This study established a flood risk assessment framework using GIS technology and open web data to evaluate 270 catchment subunits in Zhengzhou's main urban area. Results reveal an overall stepped spatial pattern of flood risks, characterized by lower risks in the southwest and higher risks in the northeast, with contiguous high-risk clusters identified in the city center. Spatial autocorrelation analysis confirms strong spatial dependence of flood risks: High-High clusters concentrate in the urban core and northeastern districts, while Low-Low clusters are distributed across the higher-elevation southwestern region. The study further conducts bivariate correlation analysis between zonal flood risks and influencing factors, culminating in the proposal of targeted mitigation strategies.
Copyright (c) 2025 Da Mao; Yan Xie; ZhiYu Yuan https://creativecommons.org/licenses/by/4.0
PREPARATION OF HIGH-TOUGHNESS THERMOPLASTIC STARCH FILMS VIA ENZYMATIC HYDROLYSIS AND CROSS-LINKING MODIFICATION
Unlike traditional petroleum-based thermoplastic films, starch-based films rely on solvent systems and cannot be processed thermally, resulting in low production efficiency and hindering large-scale industrial applications. This study developed a dual-modification method combining enzymatic hydrolysis, dual cross-linking, and plasticizers to prepare enzyme-crosslinked thermoplastic starch (ECSS). High-toughness and transparent films were fabricated via hot-pressing technology. Enzymatic hydrolysis reduced starch crystallinity and molecular chain entanglement, facilitating subsequent cross-linking reactions. Citric acid (CA) and sodium trimetaphosphate (STMP) synergistically constructed a dense molecular cross-linked network through esterification and phosphorylation, respectively. With the assistance of plasticizers, the tensile strength of the film increased by 62.3%, and the elongation at break reached 348.7%. Thermogravimetric analysis (TGA) confirmed that dual cross-linking significantly enhanced thermal stability. Differential scanning calorimetry (DSC) revealed a reduced glass transition temperature (Tg), indicating improved thermoplasticity. X-ray diffraction (XRD) demonstrated that cross-linking effectively disrupted the crystalline structure of starch, forming a stable amorphous network.
Copyright (c) 2025 Hao Wang; ChuanWei Zhang https://creativecommons.org/licenses/by/4.0
CURRENT STATUS AND PROSPECTS OF ADVANCED COMPRESSED AIR ENERGY STORAGE IN CHINA
Under the "dual carbon" target, the intermittency and fluctuation of renewable energy generation pose challenges to grid stability, making energy storage technologies crucial for enhancing energy utilization efficiency and ensuring power system security. Among these, compressed air energy storage (CAES) has emerged as a key large-scale storage solution due to its advantages in scalability, longevity, and cost-effectiveness. This paper analyzes the fundamental principles, technological classifications, and application status of CAES in China. Studies indicate that China has successfully developed multiple hundred-megawatt-scale non-combustion CAES demonstration projects, with system efficiency reaching 65%–70%, and has achieved breakthroughs in salt cavern storage, supercritical compression, and phase-change thermal storage technologies. However, CAES in China still faces challenges such as geographical limitations, high investment costs, and an underdeveloped market mechanism. Future advancements can be driven by technological optimization, large-scale deployment, and policy incentives, ultimately establishing CAES as a core technology for renewable energy integration and grid peak shaving, thus contributing significantly to the realization of the "dual carbon" target.
Copyright (c) 2025 YanPeng Li; HaoRan Zhou; RiPeng Cong; TianChen Rao https://creativecommons.org/licenses/by/4.0
NEW DEVELOPMENT OF BIOLOGICAL NITROGEN AND PHOSPHORUS REMOVAL PROCESSES FOR MUNICIPAL WASTEWATER
In recent years, with the acceleration of urbanization,surface water eutrophication caused by excessive nitrogen and phosphorus content in sewage has become increasingly serious,and highly efficient nitrogen and phosphorus removal technology has become a key demand for urban wastewater treatment. In this paper, we systematically sorted out the traditional and emerging technologies of biological nitrogen and phosphorus removal, and compared and analyzed their advantages and disadvantages. Firstly, the basic principles of biological nitrogen removal and phosphorus removal are introduced respectively, and the A2/O process with nitrification-denitrification as the core is elaborated in detail. Secondly, for the emerging technologies, low energy consumption processes such as BCFs, SHARON-ANAMMOX combined process and Dephanox process were introduced. Finally, the advantages and disadvantages of traditional and novel processes are compared by observing the activity of microflora and other indicators. The results show that the traditional technology is mature and stable but less economical, while the new technology has significant potential for energy saving and consumption reduction, but needs to further solve the stability problem of engineering application. The multi-dimensional comparison framework and process optimization path proposed in this paper can provide theoretical references for the technological upgrading and process selection of urban wastewater treatment plants, and has positive significance in promoting the technological innovation and sustainable development of water environment treatment.
Biological nitrogen and phosphorus removal
Copyright (c) 2025 ZouTing Sun https://creativecommons.org/licenses/by/4.0
SUPPLY AND DEMAND EVALUATION OF URBAN RECREATIONAL GREEN SPACES IN ZHAOQING CITY FROM THE PERSPECTIVE OF SUPPLY AND DEMAND BALANCE
Urban recreational green spaces, as an important component of the urban ecosystem, are of significant value to study. This paper delves into the supply and demand conditions of urban recreational green spaces in Zhaoqing City. The study reveals that there are significant differences in the demand and satisfaction levels of recreational green spaces among different social groups. Moreover, the supply and demand conditions of urban recreational green spaces in Zhaoqing City exhibit a pronounced differentiation in spatial distribution, with the northern and southeastern areas being high-supply hotspots, while some regions experience insufficient supply. This imbalance between supply and demand, along with the spatial differentiation, not only exacerbates the unfairness in the allocation of green space resources but also affects the quality of life and happiness of urban residents. The findings of this study can provide practical references for the future optimization of urban recreational green space planning in Zhaoqing City, strengthening resource integration, and ensuring the equitable distribution of green space resources, with the aim of achieving a balance between supply and demand and sustainable development.
Three-step floating catchment area method
Copyright (c) 2025 HongJun Xie; SiRu Ye https://creativecommons.org/licenses/by/4.0
LOW-CARBON TRANSFORMATION OF CHINA’S COAL-FIRED POWER INDUSTRY: CURRENT SITUATION INSIGHTS AND TREND PROSPECTS
Considering the importance of global climate change mitigation, this paper focuses on the low-carbon transformation of China's coal-fired power industry. China's coal-fired power industry is large-scale. The geographical distribution of power plants is uneven, and the technical level shows an unbalanced pattern. The existing units are mainly those with capacities of 300-600MW and 600-1000MW, while most of the newly added units are advanced ones with high parameters. Although the proportion of coal-fired power installed capacity has decreased to 36.9% due to new energy, it still plays a crucial role in power supply. Clean coal technologies, such as ultra-supercritical units, have developed well, and technologies like green ammonia co-firing and CCUS have also made good progress. Coal-fired power is of vital importance in ensuring power security, system regulation, centralized heating, and reducing energy consumption costs. In terms of policies, the "1+N" system and local policies promote the low-carbon transformation.
Copyright (c) 2025 Rui Yang https://creativecommons.org/licenses/by/4.0
OPTIMIZATION AND MODELLING FOR WET BENEFICIATION OF KAOLIN BY SEDIMENTATION
Kaolinite is widely used in the paper, rubber, and paint industry. Global processing of kaolin is carried out by dry and wet processing. The dry processing provides lower yield and average product quality, than wet processing limiting their industrial applications. This study increases the kaolinite grade by developing a cheaper, simpler, and more efficient technique for utilization in the paper industry. The mineralogy of kaolin was analyzed by XRD, SEM, Size distribution, and XRF analysis. From these analyses, we found kaolin having kaolinite 59.6%, quartz 12% at 4.5% moisture content, was then beneficiated by dispersion and sedimentation. Kaolin was crushed, grounded, and screened through 325 mesh (44 um) then performed dispersion at different solid percentages and dispersant dosages using sodium tri-polyphosphate as dispersants. The dispersed solution was agitated at 800 rpm for 15 minutes and settled for 30 minutes in a measuring cylinder. The Central composite design was used to optimize parameters varying solid percentage (5-30) % and dispersant dosage percentage (0.1-0.3) % for kaolin recovery. Results showed that the maximum grade and recovery of kaolinite was 88.8% and 76.03% at a dispersant dosage of 0.3% and a solid percentage of 17.5%. Overall, the grade of kaolin was successfully increased from 59.6% to 88.8%. It is also recommended to use ball mill with rubber coated steel balls instead of pin mill for efficient grinding.
Copyright (c) 2025 Tayyaba Jamil https://creativecommons.org/licenses/by/4.0
ADVANCING ENVIRONMENTAL RESEARCH IN AFRICA: TOWARDS A SUSTAINABLE AND RESILIENT FUTURE
This research article examines the critical role of environmental research in Africa, emphasizing its significance in addressing the continent's unique ecological challenges. The study highlights the multifaceted environmental issues faced by African nations, including deforestation, desertification, biodiversity loss, and the impacts of climate change. These problems not only threaten the continent's natural resources but also jeopardize the livelihoods of millions of people who depend on these ecosystems. Key findings from this research indicate that while there has been a growing body of environmental studies in Africa, there remains a substantial gap in data and resources. The research underscores the need for enhanced collaboration among governments, local communities, and international organizations to develop comprehensive strategies aimed at mitigating environmental degradation. The study also identifies successful case studies where integrated approaches have led to improved conservation outcomes and community resilience. The implications of this research extend to policy and practice, suggesting that targeted investment in environmental research can lead to more informed decision-making. Policymakers are encouraged to prioritize funding for research initiatives that address local environmental issues while fostering sustainable development. Furthermore, the article advocates for the involvement of indigenous knowledge and local expertise in environmental management strategies to ensure that solutions are culturally relevant and effective. Ultimately, this research serves as a call to action for stakeholders across Africa and beyond to recognize the urgency of environmental issues and to commit to collaborative efforts that promote ecological sustainability and enhance the quality of life for all citizens. Through a concerted focus on environmental research, Africa can pave the way toward a more sustainable and resilient future.
Copyright (c) 2025 Okechukwu Chidoluo Vitus https://creativecommons.org/licenses/by/4.0
DEEP LEARNING APPROACHES FOR BUILDING ENERGY CONSUMPTION PREDICTION
Building energy consumption prediction has emerged as a critical component in the global effort to achieve energy efficiency and sustainability in the built environment. This systematic review comprehensively analyzes the application of deep learning approaches in building energy consumption prediction, synthesizing findings from recent research published between 2018 and 2024. Our methodology involved a systematic search across major scientific databases, including IEEE Xplore, Science Direct, and Web of Science, yielding 127 relevant studies that met our inclusion criteria. The review reveals significant advancements in prediction accuracy through various deep learning architectures, with particular success in hybrid models combining multiple neural network types. Key findings indicate that transformer-based models and attention mechanisms show superior performance for long-term predictions, while LSTM networks excel in capturing short-term consumption patterns. However, challenges persist in data quality, model interpretability, and real-world deployment. This review provides valuable insights for researchers and practitioners, highlighting promising research directions in transfer learning, explainable AI, and integration with building management systems.
Copyright (c) 2024 Lei Qiu https://creativecommons.org/licenses/by/4.0
THE CONVERGENCE RATE ANALYSIS OF CONJUGATE GRADIENT METHOD IN TYPHOON FORECASTING
During the process of typhoon forecasting, numerious symmetric positive definite linear systems are needed to be solved. They are often solved by conjugate gradient method with preconditioning technique. This paper focuses on the convergence rate analysis of conjugate gradient method. The properties of Chebyshev polynomial and Krylov subspace are utilized. The effect of the right-hand-side vector are considered. Several convergence rate estimations are given. Compared with the existing estimation results, the presented results are more exact. This enable us to construct more efficient preconditioners to forecast typhoon more quickly.
Copyright (c) 2024 HaiFeng Liu https://creativecommons.org/licenses/by/4.0
WASTEWATER MANAGEMENT IN THE PHILIPPINES: CHALLENGES, POLICIES, AND SUSTAINABLE SOLUTIONS
This study explores the current state of wastewater management in the Philippines, focusing on the challenges, policies, and sustainable solutions. A comprehensive literature review was conducted to examine key issues such as inadequate infrastructure, financial constraints, and gaps in the implementation of the Philippine Clean Water Act. The findings reveal that the country faces significant hurdles in managing wastewater, particularly in urban and rural areas where sewerage systems are limited or absent. Despite these challenges, several sustainable solutions have been identified, including decentralized wastewater treatment systems (DEWATS), green infrastructure, and community-based management programs. These innovations offer promising approaches for improving wastewater treatment while addressing environmental concerns and public health risks. The study emphasizes the importance of a multi-stakeholder approach that involves national and local governments, the private sector, and communities. Strengthening policy enforcement, securing funding, and enhancing public awareness are critical to advancing sustainable wastewater management in the Philippines. This research underscores the need for integrated and adaptive strategies to ensure long-term environmental sustainability and water resource management.
Decentralized wastewater treatment systems (DEWATS)
Copyright (c) 2024 Jan Christer M. Dela Rosa https://creativecommons.org/licenses/by/4.0