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        <title>Frontiers in Environmental Science | New and Recent Articles</title>
        <link>https://www.frontiersin.org/journals/environmental-science</link>
        <description>RSS Feed for Frontiers in Environmental Science | New and Recent Articles</description>
        <language>en-us</language>
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        <pubDate>2026-05-09T13:01:49.456+00:00</pubDate>
        <ttl>60</ttl>
        <item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1815592</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1815592</link>
        <title><![CDATA[Regulation of pyrolysis temperature on the structural evolution of maize stover biochar and its mechanism of Cd2+ adsorption]]></title>
        <pubdate>2026-05-08T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Lin Zhao</author><author>Yan Zha</author><author>Wang Miao</author><author>Bin Wang</author><author>Yalin Han</author><author>Jie Tang</author>
        <description><![CDATA[Cadmium (Cd) pollution has emerged as a grave global environmental concern, rendering it imperative to develop cost - effective, environmentally friendly, and highly efficient adsorbents for the remediation of Cd2+. Biochar derived from agricultural waste is recognized as a promising material for heavy metal removal. However, the regulatory effect and internal mechanism of pyrolysis temperature on Cd2+ adsorption remain ambiguous. In this study, maize stover was chosen as the raw material to prepare biochar under three typical pyrolysis temperatures (300 °C, 500 °C, and 700 °C). A comprehensive exploration was conducted on the disparities in pore microstructure, surface chemical characteristics, mineral composition, and Cd2+ adsorption capacity of biochar at different temperatures. The findings indicated that an increase in pyrolysis temperature significantly enhanced the specific surface area, total pore volume, and average pore size of biochar. Among them, RSB700 exhibited the optimal pore structure. High - temperature pyrolysis led to a reduction in surface oxygen content, an increase in carbon content, and the retention of abundant mineral elements (Mg, Si, Ca, K), which could promote Cd2+ immobilization through ion exchange and complexation. XRD analysis confirmed that high - temperature treatment induced the formation of Fe2O3 and turbostratic graphitic carbon crystals. FTIR results corroborated that high temperature caused the decomposition of oxygen - containing functional groups (−OH, −COOH) and strengthened the aromatic structure of biochar. The adsorption process conformed to the pseudo - second - order kinetic model and Langmuir isotherm model, suggesting that monolayer chemical adsorption played a dominant role in Cd2+ fixation. RSB500 demonstrated the fastest adsorption rate, while RSB700 achieved a maximum adsorption capacity of 40.68 mg g−1 at 25 °C. In summary, pyrolysis temperature serves as a crucial regulatory factor that can reshape the pore structure, surface functional groups, and crystalline phase composition of biochar, thereby significantly mediating its Cd2+ adsorption behavior and underlying mechanism.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1863446</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1863446</link>
        <title><![CDATA[Editorial: Advances in soil pollution research: risk assessment and ecosystems management]]></title>
        <pubdate>2026-05-08T00:00:00Z</pubdate>
        <category>Editorial</category>
        <author>Oliver Wiche</author><author>Lyudmyla Symochko</author><author>Pavol Midula</author><author>Zahra Kalantari</author><author>Carla Sofia Santos Ferreira</author>
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1809214</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1809214</link>
        <title><![CDATA[The effect of social trust on rural residents’ willingness to participate in waste management: evidence from Guangxi, China]]></title>
        <pubdate>2026-05-08T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Yiqing Su</author><author>Yaying Zhu</author>
        <description><![CDATA[Rural waste management is a critical measure to improve the living environment in underdeveloped regions. Existing studies have mostly analyzed social trust from an overall perspective, lacking investigations into the micro mechanisms and mediating pathways of its subdivided dimensions, and there is scarce empirical support from underdeveloped western areas of China. Based on Collective Action Theory and the Norm Activation Model, this paper constructs an IAD-NAM analytical framework. Using 585 household survey data from rural areas of Guangxi in 2023 as the sample, this study empirically examines the impact mechanisms of social trust and its two specific dimensions of institutional trust and interpersonal trust on rural residents’ willingness to participate in waste management, by applying OLS regression, mediation effect models, the instrumental variable method, and robustness tests. The findings are as follows:(1) Social trust has a significant positive effect on rural residents’ willingness to participate in waste management.(2) Both institutional trust and interpersonal trust significantly promote rural residents’ willingness to participate in waste management, and both function through mediating pathways. Specifically, institutional trust influences rural residents’ willingness to participate in waste management through the mediating role of willingness to engage in collective environmental sanitation cooperation, while interpersonal trust exerts its impact via the mediating effect of perceived compliance with village rules and regulations. (3) Party membership, the adaptability of village rules and regulations, and behaviors of supervising other villagers to abide by village rules and regulations positively affect rural residents’ willingness to participate in waste management, whereas age has a significant negative effect.This study refines the social trust analysis framework for rural waste management, extends the micro explanatory power of Collective Action Theory, and provides theoretical basis and practical implications for enhancing participation in rural waste management in Guangxi and similar underdeveloped regions.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1821521</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1821521</link>
        <title><![CDATA[Decoupling climate and local hydrology in Central Botswana: new insights from carbonate δ13C, δ18O isotopes, and elemental geochemistry]]></title>
        <pubdate>2026-05-08T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Ferdinand J. Dina Ebouel</author><author>Thierry Bineli Betsi</author><author>Elisabeth Eiche</author><author>Stefan Norra</author><author>Peter N. Eze</author>
        <description><![CDATA[Pedogenic carbonates provide valuable archives of past environmental conditions through their elemental and isotopic compositions. This study integrates stable carbon (δ13C) and oxygen (δ18O) isotopes, obtained from carbonate features alongside manganese (Mn) and iron (Fe) concentrations in carbonate features and soil horizons across four pedosedimentary sections (SC01–SC04), to reconstruct vegetation dynamics, climatic stability, and local hydrological variability. Elemental concentrations of Mn and Fe are reported in molar percent (mol%). Soil profiles exhibit low Mn content (0.04%–0.11%), in contrast to higher Fe concentrations (2.68%–7.47%). Carbonate features are systematically depleted in Fe relative to their host matrices (0.42%–3.13%), while Mn is selectively enriched in several nodules, reaching up to 0.22% (Nd07, SC02). Stable isotope data reveal tightly clustered values within each section. δ13C values range from −3.17‰ to −0.24‰ for nodules, which is consistent with a C4-dominated savannah ecosystem. However, deep-seated pseudomycelia exhibit a distinct δ13C signature of −6.85‰, interpreted as a biogenic signal from C3 shrub roots in a closed, riparian sub-surface environment rather than a vegetation shift. δ18O values display a narrow range of −5.52‰ to −3.39‰ across all sections, indicating limited variability in meteoric water composition and evaporative conditions. High Mn/Fe ratios correlate with depleted δ18O values (≤−5‰), marking periods of increased freshwater input and seasonal waterlogging. Crucially, the decoupling of redox signals in some nodules, characterised by a combined high Mn/Fe ratio with δ18O enrichment, highlights the occurrence of episodic fluvial pulses and overbank flooding superimposed on a generally semi-arid background. These findings demonstrate that while the regional macro-climate remained stable, local hydrology was highly dynamic, driven by high-frequency fluctuations in river-water influence.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1805593</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1805593</link>
        <title><![CDATA[Comprehensive risk assessment of cadmium and arsenic contamination in karst soils from high geological background areas]]></title>
        <pubdate>2026-05-08T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Jinfeng Wang</author><author>Fang Liu</author><author>Fei Xie</author><author>Zaichao Yang</author><author>Jia Jun Mo</author><author>An Le Liu</author><author>Shibin Ma</author>
        <description><![CDATA[The study provides an in-depth assessment of the pollution risks stemming from cadmium (Cd) and arsenic (As) in the soils of the Guizhou Karst region. The aim is to offer critical insights for effective land management in these distinct geological settings.This study is based on 235 soil samples collected from woodlands and other areas in high geological background areas, and employed an enhanced fuzzy comprehensive evaluation method. This approach integrates four analytical models: the Pollution Index Method, Pollution Load Index, Potential Ecological Risk Assessment, and Human Health Risk Assessment, to quantitatively examine the ecological and environmental risks of Cd and As contamination. Findings indicate that Cd and As concentrations in the region markedly exceed national averages, highlighting a significant enrichment of these elements.Based on the Nemerow Pollution Index, 20.43% of the samples are classified as unpolluted, 45.96% as slightly polluted, 12.34% as moderately polluted, and 21.28% as heavily polluted.From the Pollution Load Index, the predominant category is slightly polluted, representing 43.83% of samples, with 21.28% classified under strong pollution contribution.The Potential Ecological Risk Assessment predominantly identifies slight ecological risks, encompassing 78.30% of the samples. Regarding human health risks, cadmium poses negligible non-carcinogenic threats to adults, whereas arsenic presents a higher non-carcinogenic risk to children.Although carcinogenic risks remain within acceptable limits for both demographics, the risk from arsenic exposure for children approaches levels of expert concern.By coupling the four evaluation models using fuzzy mathematics, the researchers categorize the soil environmental quality into four risk levels. These classifications guide the proposal of targeted land-use strategies, offering scientific recommendations for the adaptation of agricultural practices to local conditions in the Karst region.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1817685</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1817685</link>
        <title><![CDATA[Effects of the polycyclic aromatic hydrocarbon anthracene on the survival of the semi-aquatic grasshopper Cornops aquaticum (Bruner, 1906): an experimental toxicological study]]></title>
        <pubdate>2026-05-08T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Wilson F. De Lima</author><author>Mônica Regina C. M. Calderari</author><author>Ana Lúcia N. Gutjahr</author><author>Matheus C. Batista</author><author>Vinícius C. Santana</author><author>Carlos Elias S. Braga</author>
        <description><![CDATA[IntroductionEnvironmental contamination by polycyclic aromatic hydrocarbons (PAHs) has increased in recent decades, intensifying the exposure of organisms in wetland ecosystems. Anthracene, due to its chemical stability and persistence, represents a potential risk to herbivorous insects associated with aquatic vegetation.MethodsThe toxicity of anthracene to the semi-aquatic grasshopper Cornops aquaticum (Bruner, 1906) was experimentally evaluated under controlled laboratory conditions using Eichhornia crassipes leaf fragments (49 cm2) contaminated with increasing amounts (0.05, 0.10, and 0.20 g). Mortality, survival time, and bioaccumulation parameters, including daily uptake rate, were assessed.Results Anthracene exposure significantly reduced survival, confirming a dose-dependent toxic effect. A non-linear response was observed, with the 0.10 g treatment showing the most pronounced effect, resulting in only 10% survival at the end of the experiment. This pattern may be associated with reduced feeding or avoidance behavior at higher contamination levels. Sex-dependent differences were also identified: females exhibited greater tolerance at lower doses, whereas males showed higher survival at elevated concentrations. Body concentrations ranged from 0 to 4,022 μg g−1, confirming effective uptake. Survival was more strongly associated with daily exposure rate than with total accumulated concentration, indicating a critical threshold between 450 and 550 μg g−1 day−1.DiscussionThese findings demonstrate that exposure dynamics play a key role in anthracene toxicity and highlight Cornops aquaticum as highly sensitive to PAHs. The species shows strong potential as a bioindicator of organic contamination in wetland ecosystems, contributing to improved ecological risk assessment of persistent pollutants.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1806129</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1806129</link>
        <title><![CDATA[Configurational driving mechanisms of local environmental governance under the institutional pressure-organizational capacity framework: evidence from China]]></title>
        <pubdate>2026-05-08T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Ning Kang</author><author>Tao Hong</author>
        <description><![CDATA[IntroductionUnder the background of advancing global climate governance and deepening green and low-carbon transition, the Chinese central government has imposed the hard constraints of carbon peaking and carbon neutrality and strengthened supervision of local implementation through the Central Environmental Protection Inspection (CEPI) system. However, some local governments may resort to symbolic and performative governance under strong central regulatory pressure, thereby undermining the effectiveness of environmental policy. This paper focuses on local governments’ environmental governance behavior in implementing policies for coordinated pollution control and carbon reduction and explores the drivers of divergent outcomes.MethodsIt proposes an integrated institutional pressure–organizational capacity analytical framework and employs fuzzy-set Qualitative Comparative Analysis (fsQCA) and Necessary Condition Analysis (NCA) to analyze 42 CEPI cases from 2018 to 2022, which identifies multiple configurational pathways that lead to either substantive or symbolic governance.ResultsThe findings demonstrate that effective local environmental governance arises from specific configurations of institutional pressures and organizational capacities instead of any single factor. Pollution control and carbon reduction are more likely when regulatory pressure is aligned with local capacity, whereas misalignment tends to produce symbolic compliance, thereby limiting the effectiveness of high-pressure environmental regulation. Notably, even in regions with significant industrial structural constraints, substantial progress in pollution control and carbon reduction can still be achieved through green technology innovation, low-carbon industrial restructuring, and enhanced cross-sector collaborative governance.DiscussionThis study reveals the mechanisms underlying both the success and failure of pollution control and carbon reduction policy implementation from the perspective of local governance behavior, extends institutional and organizational theory to the domain of carbon governance, and provides actionable policy insights for advancing integrated carbon reduction and pollution control strategies.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1833310</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1833310</link>
        <title><![CDATA[Feasibility of microbially-solidified coal gangue particles as vegetation substrate for vegetation restoration]]></title>
        <pubdate>2026-05-07T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Erxing Peng</author><author>Xiaoying Hu</author><author>Zuojun Ning</author><author>Fansheng Zhou</author><author>Yaling Chou</author><author>Kaichun Zhou</author><author>Qifan Yang</author>
        <description><![CDATA[The feasibility of coal gangue particles solidified with microbially-induced carbonate precipitation technology (MICP) as vegetation substrate for vegetation restoration is studied by solidification tests, microscopic tests, and pot tests. Test results show that the strength, water retention, and anti-wind ability of coal gangue particles can be improved by MICP. The main products of MICP solidifying coal gangue particles are calcite and vaterite. Under low solidification degrees, the shape of CaCO3 is an irregular granule. With an increase in the solidification degree, CaCO3 becomes a uniform sphere. Ryegrass can grow in solidified coal gangue particles. When cementation solution concentration and cementation cycles are low, the germination and growth of ryegrass can be improved. With a surge in the solidification degree and ion concentration, salt stress becomes more obvious, and its germination and growth are inhibited. The combined use of coal gangue, MICP treatment, and ryegrass cultivation can provide a potential approach for environmental restoration.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1800122</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1800122</link>
        <title><![CDATA[The impact of transverse grass strip distribution patterns on slope erosion and hydrodynamic mechanisms]]></title>
        <pubdate>2026-05-07T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Yiwen Liang</author><author>Sijia Feng</author><author>Ke Li</author>
        <description><![CDATA[Vegetation distribution patterns are key drivers of surface runoff and soil erosion in arid and semi-arid regions. However, quantitative studies on the parameterization of Transverse Grass Strip Combinations (TGSC) patterns are still scarce. Through controlled movable-bed erosion experiments conducted under a fixed 50% vegetation cover, we quantified the effects of different TGSC patterns on slope hydrodynamic characteristics and erosion rates under various slopes and flow conditions. Results show hydrodynamic parameters and slope erosion rate increase with the increase of slope and flow rate. In addition, the TGSC significantly reduced slope erosion, and there was a significant power-law relationship between erosion rates and hydrodynamic parameters (with flow rate exponent being the best indicator). We further parameterized TGSC patterns based on the Path Connectivity Index (PCI), developed and validated a high-performance erosion prediction model, and identified a critical grass strip width threshold of 0.3 m to achieve optimal erosion control. This study provides theoretical support for vegetation-based soil and water conservation in arid and semi-arid regions.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1798930</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1798930</link>
        <title><![CDATA[Integrating InSAR-derived deformation into landslide susceptibility mapping in the Ninglang–Yongsheng expressway region, Yunnan, China]]></title>
        <pubdate>2026-05-07T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Shi Xu</author><author>Fei Wang</author><author>Jiayu Wang</author>
        <description><![CDATA[A Landslide susceptibility mapping along mountain highways is often based on static predisposing factors and historical inventories, which may fail to identify slopes currently destabilized by recent engineering activities. This study adapts and extends a deformation enhanced landslide susceptibility framework for the Ninglang to Yongsheng Expressway corridor in Yunnan Province, Southwest China. A landslide inventory comprising 256 mapped events was established from historical records and high resolution optical imagery. Susceptibility models were developed using Random Forest and XGBoost classifiers based on a suite of static conditioning factors describing topography, land cover, geology, hydrology, and human activity. To account for ongoing slope processes, multi temporal InSAR derived deformation information was integrated into the modeling framework to represent present day slope instability. The inclusion of deformation features leads to a clear improvement in predictive performance, with ROC AUC increasing from 0.764 to 0.826 for the Random Forest model and from 0.758 to 0.820 for the XGBoost model, while PR AUC reaches approximately 0.876–0.878 for the deformation enhanced models. Crucially, a multi-phase SHAP evaluation across the engineering lifecycle revealed that the predictive importance of InSAR deformation surged during active excavation, confirming that the models captured actual physical kinematics rather than statistical artifacts. SHAP based interpretation indicates that distance to road and elevation are the most influential predictors, while deformation information provides complementary dynamic evidence of active slope instability. The adapted framework enhances the operational value of landslide susceptibility mapping for inspection prioritization and geohazard management along newly constructed mountain highways.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1798412</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1798412</link>
        <title><![CDATA[Research trends and conservation implications of ecological water levels in Poyang Lake]]></title>
        <pubdate>2026-05-07T00:00:00Z</pubdate>
        <category>Systematic Review</category>
        <author>Yanhui Zhang</author><author>Ruoqi Xia</author><author>Jinhui Zhu</author><author>Jinliang Liu</author><author>Bing Li</author>
        <description><![CDATA[This study comprehensively reviews domestic and international research on the ecological water level (EWL) of Poyang Lake by integrating bibliometric analysis and quantitative synthesis. Using CiteSpace software for bibliometric mapping of publications from the CNKI and Web of Science Core Collection databases, we identified key research hotspots, trends, and characteristics. Concurrently, statistical methods were applied to analyze variations in EWLs, which were estimated using multiple methods across annual and monthly scales. Our bibliometric findings reveal three primary research clusters: (1) methodologies for EWL determination, (2) impacts of water level fluctuations on wetland ecosystems, and (3) mechanisms by which the Three Gorges Dam and climate change influence EWL. The field has evolved from initial hydrological analyses toward assessments of biological impacts. Methodologically, it has shifted from statistical approaches to model-based simulations. Furthermore, EWL findings are increasingly presented as interval-based thresholds rather than fixed values. First, data precision is insufficient; for instance, hydrological station data lack the spatial resolution to accurately characterize the hydrological regimes of critical micro-geomorphic units like sub-lakes and mudflats. Second, the link between water levels and biotic requirements remains weak, with few studies quantifying the needs of specific species during key life stages, such as migratory birds. Future research priorities should focus on enhancing data quality through remote sensing technologies and advancing practical applications in water resource management. Quantitatively, the annual minimum ecological water level (Min-EWL) was determined to be 9.71 ± 1.94 m, while the annual optimal ecological water level (O-EWL) was 12.53 ± 2.01 m, both exhibiting substantial inter-annual variability. At the monthly scale, ecological water level requirements peaked from July to August and reached their lowest in January. Although trends derived from different accounting methods were generally consistent, significant variations in the ranges of minimum and optimal EWL values were observed across different months.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1793022</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1793022</link>
        <title><![CDATA[Geomorphology-informed habitat quality dynamics and connectivity-based restoration prioritization in semi-arid coal-mining landscapes]]></title>
        <pubdate>2026-05-07T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Zhanrong Zhu</author><author>Yangyang He</author><author>Husheng Cao</author><author>Shiyue Fang</author><author>Kehua Li</author><author>Huadong Du</author><author>Congying Yu</author>
        <description><![CDATA[IntroductionHabitat degradation in semi-arid coal-mining landscapes is strongly conditioned by geomorphology, yet restoration planning often relies on habitat maps that insufficiently capture landform-specific constraints, shifting drivers, and connectivity bottlenecks.MethodsWe developed a geomorphology-informed, multi-source framework to assess habitat quality (HQ) dynamics and restoration priorities in the Yushenfu mining area from 1995 to 2023 by integrating InVEST-based HQ assessment, spatial autocorrelation and trend analysis, structural equation modeling, and connectivity modeling based on MSPA, graph indices, and circuit theory.ResultsHQ exhibited persistent geomorphology-dependent heterogeneity, with loess hilly-gully terrain maintaining comparatively cohesive high-quality habitat mosaics, whereas aeolian sandy terrain remained dominated by aggregated low-quality patches. Regionally, the area share of very low-quality habitats increased from 18.01% to 26.13%, while high-quality habitats declined from 60.34% to 54.59%. Driver analyses indicated a shift from vegetation-mediated regulation in earlier stages to stronger cumulative human modification and topographic control in later stages. Core habitat area contracted from 648.39 km2 to 349.01 km2, indicating progressive simplification of ecological network structure and increasing dependence on a limited set of sources, corridors, and bottlenecks.DiscussionRestoration should shift from patch-based intervention to landform-stratified, connectivity-oriented prioritization, emphasizing source protection and corridor consolidation in loess terrain and resistance reduction through substrate stabilization and disturbance mitigation in aeolian sandy terrain.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1868447</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1868447</link>
        <title><![CDATA[Correction: Large herbivores on permafrost – a pilot study of grazing impacts on permafrost soil carbon storage in northeastern siberia]]></title>
        <pubdate>2026-05-07T00:00:00Z</pubdate>
        <category>Correction</category>
        <author>Torben Windirsch</author><author>Guido Grosse</author><author>Mathias Ulrich</author><author>Bruce C. Forbes</author><author>Mathias Göckede</author><author>Juliane Wolter</author><author>Marc Macias-Fauria</author><author>Johan Olofsson</author><author>Nikita Zimov</author><author>Jens Strauss</author>
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1837937</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1837937</link>
        <title><![CDATA[Editorial: New artificial intelligence methods for remote sensing monitoring of coastal cities and environment]]></title>
        <pubdate>2026-05-06T00:00:00Z</pubdate>
        <category>Editorial</category>
        <author>Peng Liu</author><author>Fang Huang</author><author>Gary Zarillo</author>
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1782580</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1782580</link>
        <title><![CDATA[Multi-temporal remote sensing diagnosis of urban cooling networks: mechanisms and pathways of thermal degradation in Dongguan]]></title>
        <pubdate>2026-05-05T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Qi Wang</author><author>Qian He</author><author>Jing Qiu</author>
        <description><![CDATA[IntroductionUnder the double pressure of climate change and rapid urbanization, the degradation of the urban thermal environment has become a major obstacle to regional sustainable development. As a manufacturing-leading metropolis, Dongguan has undergone a drastic land use transformation and ecological space compression since 2000, potentially undermining its urban cooling system.MethodsIn this study, multi-temporal Landsat imagery was used to characterize the spatiotemporal evolution of land surface temperature (LST) and to examine the long-term dynamics of an urban cold island network from a source–corridor–matrix perspective. Cold island sources were identified using morphological spatial pattern analysis (MSPA), resistance surfaces were weighted using the CRITIC method, and potential cooling corridors were extracted using the minimum cumulative resistance (MCR) model.ResultsThe results show that from 2000 to 2025, LST increased markedly and the urban heat island expanded from fragmented hotspots to a more continuous pattern, forming multi-core high-temperature clusters along major urban corridors and industrial belts. Meanwhile, core cold sources progressively contracted and became increasingly concentrated, with remaining major cold sources retreating to the southern hilly areas and the western waterfront. The thermal resistance surface shifted from a dispersed low-resistance structure to a more connected high-resistance pattern. Correspondingly, the cold island corridor network simplified from a multi-level configuration to a more linear framework, indicating a degradation sequence characterized by core source degradation–corridor fragmentation–functional decline.DiscussionThese findings highlight that blue–green space fragmentation and the intensification of high-resistance surfaces are key factors associated with the weakening of urban cooling connectivity. Rebuilding low-resistance ventilation corridors and strengthening ecological links among cold sources, supported by nature-based solutions, are critical for restoring cooling network functions and enhancing urban climate resilience.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1757914</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1757914</link>
        <title><![CDATA[Forecasting the total carbon allowance cap under emission-reduction targets using a hybrid path analysis and supervised machine learning framework]]></title>
        <pubdate>2026-05-04T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Xin Wang</author><author>Wenxiu Hu</author><author>Li Bai</author><author>Wei Chang</author><author>Xinli Yu</author>
        <description><![CDATA[Carbon allowances constitute a foundational component of national carbon emission control frameworks, as they govern the equitable distribution of subsequent allocations and directly shape the overall effectiveness of greenhouse gas mitigation strategies. However, the temporal evolution of carbon allowances is inherently complex, high-dimensional, and nonlinear, thereby posing substantial challenges to the rigorous prediction of the aggregate allowance cap. Although artificial intelligence technologies have achieved substantial advances in environmental forecasting in recent years, existing predictive approaches often prioritize predictive accuracy while neglecting systematic variable selection and structured modeling procedures, thereby constraining their utility for policy-oriented decision support. To address this limitation, we propose a hybrid modeling framework that integrates path analysis with supervised machine learning to forecast China’s future carbon allowance cap. Path analysis was first applied to disentangle both direct and indirect relationships among the variables, thereby enabling the identification of structurally significant predictors with substantial explanatory power. Based on the selected indicators, a standardized dataset was constructed to train and systematically compare multiple supervised machine learning algorithms. Empirical results demonstrate that, under uniformly regularized data conditions, Gaussian Process Regression (GPR) consistently outperforms alternative supervised learning algorithms in terms of predictive accuracy and robustness. The integrated forecasting framework developed herein provides a robust analytical foundation for identifying the determinants of carbon allowance trajectories and illustrates how machine learning can be effectively integrated with environmental datasets to inform carbon governance, strengthen climate mitigation pathways, and advance data-driven environmental decision-making under realistic emission reduction targets.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1816065</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1816065</link>
        <title><![CDATA[Circular valorization of acid-hydrolyzed fishery wastewater: integrated remediation and enhanced C-phycocyanin production by Spirulina sp.]]></title>
        <pubdate>2026-05-04T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Charith Akalanka Dodangodage</author><author>Geethaka Nethsara Gamage</author><author>Ranoda Hasandee Halwatura</author><author>Jagath C. Kasturiarachchi</author><author>Thilini A. Perera</author><author>Sanjitha Dilan Rajapakshe</author><author>Sayuri S. Niyangoda</author><author>Rangika Umesh Halwatura</author>
        <description><![CDATA[The valorization of fishery-derived wastes through microalgal biotechnology provides a practical route to integrate wastewater remediation with high-value bioproduct generation. This study demonstrates an integrated process in which solid fish waste was converted into an algal growth medium via sulfuric acid hydrolysis (3% H2SO4; 1:8, w/v) combined with autoclave-assisted pretreatment (121 °C, 20 min), and subsequently utilized for the mixotrophic cultivation of Spirulina sp. in bench-scale photobioreactors. The resulting hydrolysate contained a chemical oxygen demand (COD) of 2,897 ± 28 mg L-1, NO3−–N of 284.89 ± 11.04 mg L-1, and PO43-–P of 130.23 ± 0.47 mg L-1 at an adjusted pH of 9.10 ± 0.05. Process optimization identified a 75% (v/v) hydrolysate concentration and an irradiance of 180 μmol photons m-2 s-1 as the most effective operating condition. Under this optimized regime, the culture reached a maximum biomass concentration of 2.10 ± 0.03 g L-1, representing an 11.1-fold increase relative to the autotrophic BG-11 control. Simultaneously, robust nutrient polishing was achieved, with NO3−–N and PO43-–P removal efficiencies of 96.6% and 93.2%, respectively. Concurrently, pigment synthesis was significantly enhanced, delivering an intracellular C-phycocyanin content of 66.00 ± 0.85 mg g-1 DW (a 14.7-fold increase over the control) and a volumetric productivity of 10.66 ± 0.20 mg L-1 d-1. Lipid accumulation also increased in the hydrolysate-grown biomass (12.25%) versus the control (5.87%). Overall, the proposed circular bioprocess confirms that acid-hydrolyzed fishery waste serves as a highly effective substrate for simultaneous bioremediation and high-yield C-phycocyanin production, establishing a scalable resource recovery strategy for the fishery industry.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1797545</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1797545</link>
        <title><![CDATA[Enhanced weather classification using xception with SENet and attention mechanisms]]></title>
        <pubdate>2026-05-04T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Gunjan Shandilya</author><author>Sheifali Gupta</author><author>Abdul Khader Jilani Saudagar</author><author>Sunnia Ikram</author><author>Ateeq Ur Rehman</author><author>Isabel De la Torre Díez</author><author>Heba G. Mohamed</author><author>Ramón Pali Casanova</author><author>Ángel Kuc Castilla</author><author>Upinder Kaur</author>
        <description><![CDATA[IntroductionWeather classification plays a crucial role in applications such as environmental monitoring, disaster management, and smart city infrastructure. Accurate and efficient classification of weather conditions from images remains a challenging task due to variations in illumination, texture, and atmospheric conditions.MethodsThis study proposes an efficient deep learning framework for multi-class weather classification by integrating the Xception architecture with Squeeze-and-Excitation (SE) blocks and a spatial attention mechanism. Transfer learning with pre-trained ImageNet weights was employed, and a comparative analysis was conducted using EfficientNet-B3, ResNet152V2, and Xception architectures. The proposed enhanced Xception model incorporates channel-wise recalibration and spatial feature refinement to improve representational capability. The model was trained and evaluated on the Multi-Class Weather Dataset (MWD), which consists of 1,125 images categorized into four classes: sunshine, cloudy, rain, and sunrise. To ensure robustness and generalization, 5-fold cross-validation, statistical significance testing, calibration analysis, and robustness evaluation under image perturbations were performed.ResultsThe proposed model achieved a classification accuracy of 99.06% on the test set. Additionally, it attained a macro precision of 98.3%, macro recall of 97.7%, and macro F1-score of 98.0%. The model demonstrated strong generalization capability and robustness under varying perturbation conditions, with only moderate computational overhead.DiscussionThe integration of SE blocks and spatial attention significantly enhances feature representation by emphasizing informative channels and spatial regions. Compared to baseline architectures, the proposed framework shows superior performance in terms of accuracy and robustness. These results indicate that the model is well-suited for real-world weather classification applications, particularly in intelligent environmental monitoring systems.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1799981</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1799981</link>
        <title><![CDATA[Policy-driven industrial transformation and associated agriculture–ecology–economy nexus shifts within social–ecological system: a case of the greenest coastal province of China]]></title>
        <pubdate>2026-05-01T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Chong Jiang</author><author>Mingrui Liao</author><author>Yunzhe Hu</author><author>Yixin Wang</author><author>Yutong Guan</author><author>Buqing Wang</author><author>Yuexin Xiao</author>
        <description><![CDATA[A rising human impact alters landscape patterns and determines the agriculture–ecology–economy nexus (AEEN), which further threatens the sustainability of social–ecological system (SES). However, the mechanisms through which policy interventions drive AEEN evolution and regime shifts are not sufficiently elucidated. We adopted the Fujian Province, which is undergoing intensive policy interventions, rapid socioeconomic development, and ecosystem restoration, as a case study to examine SES evolution and its responses to diverse interventions. Vegetation greening enhanced carbon sequestration and reduced soil loss, while built-up area expansion rapidly occupied croplands, and aquaculture development squeezed coastal zones. Macroeconomic policies and industrial structure upgrades necessarily promote economic growth, which results in employment structure adjustments and population redistribution. The unequal urban–rural developments led to rural population loss and urban–rural resident migration; thus, the dominant role of rural residents in the employment structure for primary sector was gradually substituted by urban employment population for second and tertiary sectors. Regarding agricultural production, the sown area declined, and planting structure adjustments since 1997 led to a substantial decline in grain crop productivity. Regime shifts in nexus sectors reversed the pairwise interactions from co-benefits in the agriculture- (1978–1997) and ecology- (2017–2022) dominated phases to tradeoffs in the economy-dominated (1998–2016) phase, which were driven by compound policy interventions and historical events. Our findings are expected to enrich the understanding of AEEN interplay, SES governance, and support strategy formulations for regionally coordinated development of agriculture, ecology, and economy in Fujian and beyond.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1769038</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1769038</link>
        <title><![CDATA[Carbon emission reduction under import competition: a green breakthrough or burdened endeavor?]]></title>
        <pubdate>2026-05-01T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Mingrong Wang</author><author>Longnan Ma</author>
        <description><![CDATA[In the dual context of trade liberalization and the low-carbon transition, understanding how import competition shapes corporate carbon emissions has become a critical question. This study introduces an innovative “dual-track competition” framework and uses panel data of Chinese listed companies from 2010 to 2023 to examine the impact of import competition on corporate carbon emissions, yielding four key findings: First, import competition significantly increases firms’ carbon emissions. Second, import competition promotes green innovation, which reduces carbon emissions and generates a “green breakthrough effect.” However, it simultaneously reduces corporate energy utilization efficiency and compresses cost-plus markups, generating a “heavy burden effect.” Third, the emission-increasing impact of import competition is primarily driven by the dominance of the “cost-survival race” over the “green innovation race.” Finally, the emission-increasing effect of import competition is weaker for firms engaging in green mergers and acquisitions, firms facing relatively mild financing constraints, and firms operating in clean and low-technology industries. These findings provide important insights into the dual nature of import competition on carbon emissions, thereby advancing the understanding of how trade liberalization interacts with corporate environmental performance.]]></description>
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