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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>2026-08-21T21:38:47.866+00:00</pubDate>
        <ttl>60</ttl>
        <item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1898743</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1898743</link>
        <title><![CDATA[Task-based AI exposure and industrial carbon emissions: evidence from China]]></title>
        <pubdate>2026-08-21T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Peng Xiao</author><author>Yuhang He</author><author>Keping Huang</author><author>Baoxi Li</author>
        <description><![CDATA[Artificial intelligence (AI) exposure, defined as the extent to which occupational tasks can be performed, substituted, or augmented by AI, provides a task-based way to study the environmental consequences of technological change. We construct total, substitution-oriented, and empowerment-oriented AI exposure measures and examine their relationship with industrial carbon emissions using an unbalanced, listed-firm-based province-industry-year panel covering 29 Chinese provinces, 52 industries, and 2016–2023. Baseline fixed-effects estimates show negative associations between AI task exposure and listed-firm carbon emissions, but these estimates are interpreted as conditional associations rather than definitive causal effects. Additional tests using fixed 2016 occupational recruitment weights, province-by-year and industry-by-year fixed effects, and continuous-firm carbon outcomes show that the negative association is most robust for the common intensity of AI task exposure. The mechanism evidence is strongest for industrial upgrading, supportive but less precise for green innovation, and suggestive for energy intensity. The findings support a cautious task-exposure interpretation of AI-related decarbonization: common AI exposure intensity is robustly associated with lower emissions, whereas the substitution-versus-empowerment composition margin is informative but less precisely identified.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1856508</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1856508</link>
        <title><![CDATA[Response of NDVI spatiotemporal variation to meteorological factors in arid areas]]></title>
        <pubdate>2026-08-21T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Ben Wang</author><author>Huixia Li</author><author>Wenhao Xia</author><author>Jiaqiang Wang</author><author>Chongfa Cai</author><author>Jing Chen</author>
        <description><![CDATA[This study investigated the spatiotemporal variation characteristics of vegetation coverage (NDVI) in the Kekeya project area and its response to meteorological factors over the past 3 decades. On the basis of Landsat remote sensing data from 1993 to 2023 and meteorological variables including air temperature, precipitation, relative humidity, and wind speed, this research aimed to reveal the spatial–temporal evolution patterns of vegetation and identify the dominant driving mechanisms underlying ecological change in this arid region. From 1993 to 2023, the NDVI showed an overall fluctuating upward trend, with the highest value in 2020 and the lowest in 2001. The Mann–Kendall test revealed an increasing abrupt change in 2013, reflecting the combined effects of climate variability and greening projects. Vegetation cover decreased from north to south, with high NDVI values concentrated in low-elevation zones (1065–1200 m). The proportion of extremely low coverage area declined from 70.28% to 14.33%, whereas the areas with high and very high coverage expanded notably, indicating significant ecological restoration. Between 2001 and 2021, the standardized precipitation evapotranspiration index (SPEI) showed an overall mild wetting trend with periodic drought fluctuations, while the NDVI continued to increase; however, their weak correlation (r = 0.2313, P > 0.05) suggested that vegetation recovery was driven mainly by anthropogenic activities, particularly ecological engineering and water management. The NDVI was significantly positively correlated with relative humidityand precipitation, whereas temperature exhibited a bidirectional effect and wind speed had a predominantly negative correlation. Residual trend analysis further supported that human-dominated areas occupied the largest proportion of the study area, with strong human dominance concentrated in the central-southern core zone spatially coinciding with the key implementation areas of the Kekeya Greening Project. Greening projects also reduced near-surface wind speeds, enhancing ecosystem stability. Overall, vegetation coverage in the Kekeya project area has significantly improved over the past 3 decades, reflecting the combined impacts of ecological restoration initiatives and climate variability, while human interventions—particularly large-scale greening projects and water management—play a crucial role in promoting ecosystem recovery. These findings provide valuable insights for ecological management, climate adaptation, and sustainable restoration planning in arid and semiarid regions.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1797598</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1797598</link>
        <title><![CDATA[Pond diversity in the hands of the community: eDNA metabarcoding meets participatory science in the GenePools project]]></title>
        <pubdate>2026-08-21T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Georgia M. Ward</author><author>Nicola M. Coyle</author><author>Giuliana Sinclair</author><author>Jessica Wardlaw</author><author>Stephen Juggins</author><author>Nicholas Dunn</author><author>Tom L. Jenkins</author><author>Harriet Knafler</author><author>Lauren S. J. Cook</author><author>Jeremy Biggs</author><author>Katie Clark</author><author>Matilda Dixon</author><author>Andrew Jefferies</author><author>Max John</author><author>Poppy Lakeman Fraser</author><author>Amy Pilsbury</author><author>Katy Potts</author><author>Emma J. Long</author><author>Bryony A. P. Williams</author><author>Paul Woodcock</author><author>David Bass</author>
        <description><![CDATA[Ponds in urban green spaces, including those in private gardens and public areas, are important biodiversity refuges in otherwise ecologically constrained landscapes, and are significant nodes in the UK’s freshwater biome network. These ponds also represent diverse instances of complex ecosystems created and managed by people who have decisive roles in their construction and maintenance. The GenePools project was a multi-year community science project, initiated by the Defra DNA Centre of Excellence and subsequently led by Natural England as part of the Natural Capital and Ecosystem Assessment (NCEA), which sought to directly involve community scientists in molecular genetic biodiversity assessment, engaging community scientists in each stage of the experimental process, from pond sampling through to multiple, iterative presentations and interpretations of results. Metabarcoding and taxonomic annotation of genetic marker regions targeting multiple taxonomic groups (vertebrates, invertebrates, microbial eukaryotes, plants, green algae and fungi, and prokaryotes) revealed extensive diversity associated with sampled ponds, including representatives of nearly all major branches of the eukaryote tree of life. The species lists generated were presented to community scientists via a specifically developed interactive dashboard in multiple formats, including sequence tables and interactive plots. Here we report on the findings of the final iteration of the project, conducted between April 2024 and March 2025, including community scientist-facing results, and a selection of further analyses demonstrating the strength of the generated dataset for exploring urban pond diversity and community composition.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1897986</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1897986</link>
        <title><![CDATA[Carbon-management decision support for prefabricated component production and delivery under dynamic energy–carbon signals]]></title>
        <pubdate>2026-08-21T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Yang Lu</author><author>Joston Gary</author>
        <description><![CDATA[IntroductionOperational decarbonization in prefabricated construction requires decision support that links factory production, transport logistics, energy prices, grid carbon intensity, and carbon-trading rules. This study develops an environmental systems engineering framework for carbon-management decision support in prefabricated component production and delivery.MethodsThe framework represents the supply chain as a coupled production–transport system in which steam-curing intensity, time-of-use electricity pricing, time-varying grid carbon factors, diesel transportation emissions, and stepped carbon trading jointly shape operational choices. A tri-objective model is formulated to minimize project completion time, energy and fuel costs, and net carbon-trading costs. The model is solved using the Bi-layer Cooperative Evolutionary Algorithm with Q-Learning (BCEA-QL), which jointly searches production and delivery decisions.ResultsComputational tests on nine synthetic test instances, including a recent reinforcement-learning-assisted baseline, show that BCEA-QL achieves the highest HV on all nine instances, with up to 6.88% higher hypervolume on large-scale instances. A 25-group metropolitan metro precast case further shows that, relative to a time-oriented schedule, a carbon-oriented schedule reduces energy and fuel costs by approximately 23% and yields only a small carbon-trading credit. A post-processing delay-cost analysis identifies manager-dependent switching thresholds near 57 and 212 CNY/h.DiscussionThe results indicate that coordinated production and delivery scheduling can help environmental managers interpret operational carbon-management trade-offs under asynchronous price–carbon signals, without implying universal carbon reduction or full field validation.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1863860</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1863860</link>
        <title><![CDATA[Transforming waste to agricultural resource: assessing the chemical and microbial quality of treated wastewater and its effects on selected soil chemical properties and microbial communities under tomato cultivation]]></title>
        <pubdate>2026-08-21T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>B. Hlophe</author><author>P. M. Kgopa</author><author>M. R. Masevhe</author><author>M. M. Mphahlele-Makgwane</author>
        <description><![CDATA[Treated wastewater (TWW) is increasingly used as an alternative irrigation source to alleviate water scarcity in agriculture; however, its effects on soil microbial communities and potential microbial contamination remain a concern. This study evaluated the chemical and microbial quality of TWW for irrigation and its effects on selected soil chemical properties and microbial communities using tomato (Solanum lycopersicum) as a test crop. A 90-day greenhouse pot experiment was conducted using two tomato cultivars (Roma and Rodade), irrigated with TWW from four wastewater treatment plants (Bochum, Polokwane, Mankweng, and Lebowakgomo), with tap water serving as the control. Soil samples collected at crop maturity were analysed for pH (water and potassium chloride), electrical conductivity (EC), beneficial microorganisms (Actinomycetes, Pseudomonas putida, and phosphate-solubilising bacteria), pathogenic bacteria (Escherichia coli, Salmonella, Staphylococcus, Shigella, Vibrio cholerae, Enteric bacteria, and Pseudomonas aeruginosa), and total bacterial and fungal counts. Irrigation water source was the main factor influencing soil chemical and biological properties, while tomato cultivar effects were negligible. Compared with the pre-irrigation soil, TWW irrigation increased soil EC by 109%–528% and soil pH by 24.5%–41.6%, whereas tap water reduced EC by 68.9%. Beneficial microbial populations increased under TWW irrigation, with Actinomycetes, P. putida, and phosphate-solubilising bacteria increasing by 131%–136%, 117%–124%, and 88%–96%, respectively. Total fungal and bacterial populations increased by up to 195.5% and 131.7%, respectively. However, TWW irrigation also elevated populations of several pathogenic bacteria, with E. coli, enteric bacteria, Salmonella, and Staphylococcus increasing by up to 72%, 141%, 73%, and 75%, respectively. In irrigation water, pathogen concentrations frequently exceeded the FAO and WHO guideline of 1,000 CFU/100 mL for unrestricted irrigation. Overall, TWW enhanced soil microbial activity and beneficial microorganisms, demonstrating its potential as a sustainable irrigation source in water-scarce regions. Nevertheless, routine monitoring and improved wastewater treatment are required to minimise pathogen transfer and support safe agricultural reuse practices.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1896442</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1896442</link>
        <title><![CDATA[Analysis of microplastics risk assessment research worldwide in the soil ecosystem: a scientometric review]]></title>
        <pubdate>2026-08-21T00:00:00Z</pubdate>
        <category>Systematic Review</category>
        <author>Juan Saldivar-Villarroel</author><author>Raymunda Veronica Cruz-Martinez</author><author>Luis Bendezu-Díaz</author><author>Jorge Magallanes-Magallanes</author><author>Juan Leonardo Tejada-Hinojoza</author><author>Paul Virú-Díaz</author><author>Alejandrina Sotelo-Méndez</author><author>Cecilia Alegría-Arnedo</author><author>Zoraida Gomez Lucana</author><author>Jose Luis Donayre Pasache</author><author>Orlando Rubén Balbin-Cardenas</author><author>Paul Virú-Vásquez</author>
        <description><![CDATA[Microplastic pollution has emerged as a critical environmental issue, extending beyond aquatic systems to significantly impact soil ecosystems and pose potential risks to human health. This research aims to analyze the global evolution of microplastic risk assessment research through a scientometric approach. Data was collected from the Scopus database using a structured search strategy, and analyzed using VOSviewer, Bibliometrix, and CiteSpace to identify publication trends, keyword co-occurrence networks, and thematic evolution. The results reveal a marked increase in research output since 2020, with a transition from early descriptive studies on microplastic occurrence (2013–2016) toward mechanistic and integrated risk assessment frameworks (2021–2025). Key research clusters include physicochemical processes such as adsorption and transport in porous media, soil accumulation and land-use impacts, microbial interactions analyzed through metagenomics, plant–microplastic interactions affecting crop productivity, and emerging concerns related to human health exposure. Furthermore, widely used indices such as Pollution Load Index Polymer Hazard Index and Potential Ecological Risk Index demonstrate variability in risk estimation, highlighting the lack of methodological standardization. Overall, the research concludes that microplastic risk assessment has evolved into a multidisciplinary and increasingly complex field, requiring the development of standardized, multi-compartment, and predictive frameworks to support environmental management and sustainability-oriented decision-making.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1861098</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1861098</link>
        <title><![CDATA[Mitigating the resource curse of fossil fuel rent dependence: the role of artificial intelligence]]></title>
        <pubdate>2026-08-21T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Jingyu Qu</author><author>Wooyoung Jeon</author>
        <description><![CDATA[IntroductionDependence on fossil fuel rents can impede economic performance by hindering diversification, diminishing innovation incentives, and entrenching rent-seeking distortions. Conversely, artificial intelligence (AI) possesses the potential to alleviate some of these constraints through enhanced productivity and improved production coordination.MethodsThis study employs an unbalanced panel dataset encompassing 72 countries from 2000 to 2022. We utilize fixed-effects, feasible generalized least squares (FGLS), and system generalized method of moments (GMM) models to investigate whether AI mitigates the adverse effects of fossil fuel rents on economic performance.ResultsOur findings reveal a negative association between fossil fuel rents and economic performance, alongside a positive association between AI and economic performance. Crucially, the interaction term between fossil fuel rents and AI is positive, indicating that AI ameliorates the detrimental impacts linked to fossil fuel dependence. This moderating effect is particularly salient in non-OECD economies, middle-income countries, and nations characterized by intermediate institutional quality. Further periodic analysis and rolling-window estimates demonstrate that this moderating effect predominantly manifests in later years. Robustness checks confirm the primary findings across alternative dependent variables, various measures of fossil fuel dependence, and additional control variables. However, the observed effect diminishes when AI is replaced with a broader information and communication technology (ICT) indicator.DiscussionThese findings suggest that AI offers the most substantial benefits in contexts where resource dependence obstructs diversification, productivity enhancement, and structural development, contingent upon the existence of requisite conditions for technological adoption. Therefore, while AI does not eliminate the inherent constraints associated with fossil fuel dependence, the evidence indicates its capacity to mitigate their impact when effectively implemented.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1915601</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1915601</link>
        <title><![CDATA[Hydrological controls on dissolved carbon export from permafrost peatland catchments of northeastern China]]></title>
        <pubdate>2026-08-20T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Shujie Wang</author><author>Yuedong Guo</author><author>Hao Zhang</author><author>Yaqin Miao</author>
        <description><![CDATA[Peatlands in Eurasian permafrost regions are among the world’s most important soil carbon reservoirs and may strongly influence future climate through carbon release. Runoff-mediated dissolved carbon export represents a critical carbon-loss pathway in permafrost peatlands, yet observations from the southern margin of Eurasian permafrost remain scarce. Here, we investigated dissolved carbon export from two differently sized permafrost peatland catchments in the Greater Khingan Mountains, northeastern China. We estimated dissolved organic carbon (DOC) and dissolved inorganic carbon (DIC) export fluxes and evaluated hydrological controls on dissolved carbon dynamics using three fluorescence indices. DOC and DIC concentrations were closely coupled with discharge during seasonal hydrological fluctuations, indicating that runoff dynamics were the primary driver of dissolved carbon export. During the growing season, the Fukuqi River exported 703.84 t total dissolved carbon, equivalent to approximately 20% of peatland net ecosystem exchange. Hydrological processes regulated not only dissolved carbon fluxes and the relative contributions of DOC and DIC, but also DOC chemical characteristics. Flood-peak flows promoted the export of more humified DOC, characterized by higher humification index and lower fluorescence index and freshness index, whereas baseflow showed the opposite pattern. The vertical organic–mineral stratification of peatland soils, with contrasting hydraulic transmissivity and dissolved-carbon production potential, directly governed temporal variations in discharge and dissolved carbon concentrations. Active-layer deepening may increase runoff contributions from deeper mineral soils, thereby increasing the DIC fraction while reducing DOC concentration and the degree of humification. Fluorescence indices were consistently correlated with discharge across both catchments, suggesting their potential as robust indicators of hydrological processes. Overall, these findings highlight runoff-mediated dissolved carbon export as an underrepresented carbon-loss pathway and suggest that permafrost degradation will reshape both the magnitude and chemical composition of dissolved carbon exports under future warming.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1900482</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1900482</link>
        <title><![CDATA[Leaf mould as a potential peat substitute in leafy vegetable seedling production — a citizen science study]]></title>
        <pubdate>2026-08-20T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Emese Gyöngyösi</author><author>Nuri Nurlaila Setiawan</author><author>László Csambalik</author><author>Ferenc Tóth</author><author>Anna Divéky-Ertsey</author><author>Dóra Drexler</author>
        <description><![CDATA[Peat extraction contributes to habitat loss, lowers water tables in peatlands, and releases stored carbon into the atmosphere. Rising awareness about the unsustainable use of peat as a growing medium has led to the search for more environmentally friendly alternatives. Leaf mould (also known as leaf compost), derived from deciduous leaves and characterised by a soft, porous structure, represents a potentially renewable peat-free substrate for seedling production. This study evaluated the suitability of mature leaf mould for vegetable seedling production using a citizen science approach. Hobby and market gardeners from Hungary cultivated lettuce (Lactuca sativa L.), kale (Brassica oleracea var. sabellica L.), kohlrabi (Brassica oleracea var. gongylodes L.), and pak choi (Brassica rapa subsp. chinensis (L.) Hanelt) in leaf mould and in commercially available or homemade control substrates. Seed emergence and seedling development were monitored for up to six weeks. Data collected included seed emergence, visual seedling appearance, and the number of true leaves, supported by photographic records. Overall, leaf mould supported seed germination to a similar extent as the control substrates. Seedling appearance was significantly improved in leaf mould compared with the control media for kale (p = 0.016) and pak choi (p = 0.007). Of the four crops, only pak choi developed significantly fewer true leaves in leaf mould than in the control substrates. The comparable performance of seedlings grown in leaf mould and control substrates, together with the observed improvements in seedling appearance for some crops, indicates that mature leaf mould can effectively support the early development of the tested vegetable seedlings. It may therefore represent a viable peat-free substrate for seedling production. The findings also demonstrate the potential of citizen science for evaluating horticultural growing media under practical cultivation conditions.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1810630</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1810630</link>
        <title><![CDATA[The impact of environmental performance industry gap on corporate green collaborative innovation]]></title>
        <pubdate>2026-08-20T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Xiaoping Hu</author><author>Xiajing Xu</author>
        <description><![CDATA[IntroductionTighter environmental regulations and stiffer competition are subjecting an increasing number of firms to environmental performance pressure.MethodsThis study draws on the Theory of Firm Behavior, Upper Echelons Theory, and the Red Queen Effect to examine how environmental performance industry gap affects corporate green collaborative innovation, using panel data from Chinese listed firms covering 2010–2023. It further examines the moderating roles of managerial risk preference and green strategic orientation, as well as the heterogeneity across industry attributes.ResultsThe findings reveal that environmental performance industry gap significantly promotes corporate green collaborative innovation. Managerial risk preference negatively moderates this relationship, whereas green strategic orientation exerts a positive moderating effect. In addition, heterogeneity analysis demonstrates that this driving effect is significant in low-carbon industries but not in high-carbon ones.DiscussionThe conclusions provide an integrated perspective for understanding the driving mechanisms of corporate green collaborative innovation and offer meaningful implications for promoting corporate green transformation and for governments to formulate differentiated environmental policies.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1916729</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1916729</link>
        <title><![CDATA[Event-driven atmospheric forcing and meltwater lake response in maritime antarctic]]></title>
        <pubdate>2026-08-20T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Shoukat Ali Shah</author><author>Mingliang Liu</author><author>Songtao Ai</author><author>Huanfeng Shen</author>
        <description><![CDATA[IntroductionMaritime Antarctic meltwater lakes are highly sensitive to atmospheric variability, yet their short-term hydrothermal responses remain poorly understood because most studies rely on seasonal or daily observations that cannot resolve sub-daily atmosphere–lake interactions.MethodsThis study investigated Yanou Lake, a shallow maritime Antarctic meltwater lake, using continuous 5‐min meteorological and hydrological observations collected over 66 days during the 2025–2026 austral summer. Wind speed, air temperature, atmospheric pressure, water temperature, and lake depth were analyzed using an integrated framework combining event‐based atmospheric forcing detection, lagged correlation, wavelet coherence, change‐point detection, and statistically validated threshold analysis.ResultsA total of 916 five‐min event observations (4.84% of the record) were grouped into 12 independent compound atmospheric forcing events. Cross‐correlation analysis identified weak but measurable delayed atmosphere–lake associations, while autocorrelation indicated persistence in water temperature (75.6 h) and lake depth (165.9 h). Wavelet coherence showed that atmosphere–lake coupling was intermittent and scale dependent, strengthening only during discrete atmospheric events. Event‐level analyses indicated that average lake responses were small and varied among individual events. Change‐point analysis identified repeated thermal and hydrological reorganizations, whereas statistically supported thresholds of 6.22 m s -1 (wind speed) and 2.41 °C (air temperature) were associated with changes in lake behaviour.DiscussionThese findings demonstrate that atmosphere–lake interactions in Yanou Lake are governed by delayed, episodic, and nonlinear processes rather than persistent atmospheric control. The proposed high‐frequency analytical framework provides a transferable approach for investigating short‐term hydroclimatic dynamics in Antarctic meltwater lakes and improves understanding of cryosphere–hydrology interactions under ongoing polar climate change.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1896671</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1896671</link>
        <title><![CDATA[Spatiotemporal patterns, propagation mechanisms, and driving factors of agricultural and groundwater droughts across major agricultural regions of Northeast China]]></title>
        <pubdate>2026-08-20T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Yong Huang</author><author>Zhaoqiang Zhou</author><author>Renjie Hou</author><author>Qinglin Li</author><author>Yibo Ding</author><author>Tian Wang</author><author>Peng Chen</author><author>Xiaowen Wang</author>
        <description><![CDATA[IntroductionCold region agriculture is an important component of the global food security system. In recent years, cold regions have experienced significant warming and increasingly frequent extreme events. However, the propagation characteristics and driving mechanisms of different drought types across agricultural regions in cold regions remain insufficiently understood. Therefore, this study focused on Northeast China, a major grain-producing region located in the high-latitude cold zone.MethodsMeteorological drought (MD), agricultural drought (AD), and groundwater drought (GD) were characterized across different agricultural regions. Drought response time and propagation time were analyzed to quantify the temporal relationships among different drought types. A drought propagation model was constructed to identify propagation thresholds and evaluate the drought resistance capacities of different agricultural regions. Furthermore, an XGBoost model combined with SHAP analysis was used to identify the main factors influencing AD and GD.Results(1) MD was more severe in the western and northern parts of the study area, AD was more severe in the southwestern and southeastern parts, and GD was more severe in the northern, western, and southwestern parts. (2) The propagation times between different drought types were generally longer in winter than during the growing season. (3) The soil water systems in the western, central, and southwestern parts of the study area exhibited relatively high resistance to MD, whereas groundwater systems in parts of the central and eastern regions showed relatively high resistance to AD. (4) Shallow soil temperature was one of the most important factors influencing AD in Northeast China, while the dominant factors influencing GD varied among agricultural regions.DiscussionThese findings improve the understanding of drought propagation processes and regional differences in drought resistance in cold regions under climate change and provide a scientific basis for region-specific drought monitoring and risk prevention.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1803763</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1803763</link>
        <title><![CDATA[Prioritizing public investments for low-carbon rural e-commerce in China: an AHP–TOPSIS framework linking income growth and environmental performance]]></title>
        <pubdate>2026-08-19T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Peng Zhang</author>
        <description><![CDATA[IntroductionRural e commerce is widely promoted in China to expand market access and increase rural incomes. However, its rapid development also creates environmental pressures through logistics related emissions and packaging waste. This study aims to identify and prioritize public investment packages that can support rural income growth while promoting low carbon development.MethodsAn integrated Analytic Hierarchy Process and Technique for Order Preference by Similarity to Ideal Solution (AHP TOPSIS) framework is developed to evaluate and rank public investment options for rural e commerce development. Pairwise comparison questionnaires from 60 experts are aggregated using the geometric mean to derive criterion weights. Six main criteria and 20 indicators are considered, covering digital infrastructure, logistics capability, human capital, market linkage, inclusive economic impact, and environmental outcomes. Five alternative public investment packages are evaluated using TOPSIS based on their distances from the positive and negative ideal solutions. Sensitivity analysis with ±30% weight perturbations and scenario analysis under inclusion, growth, and environmental priorities are also conducted to assess ranking robustness.ResultsThe baseline TOPSIS results show that A4 ranks first with a closeness coefficient of 0.630, followed by A2 with 0.593. A5 and A1 form a middle tier with coefficients of 0.556 and 0.534, respectively, whereas A3 ranks last with 0.489. The sensitivity analysis shows limited rank reversals, mainly among the middle ranked alternatives. Across the inclusion, growth, and environmental scenarios, A4 and A2 consistently remain the two highest ranked alternatives.DiscussionThe results indicate that skills and entrepreneurship support (A4) and low carbon logistics investment (A2) provide the most robust performance across different policy priorities. These findings suggest that rural development policies should combine human capital development with low carbon logistics infrastructure rather than focus on income growth alone. The proposed AHP-TOPSIS framework provides a transparent and robust decision support tool for prioritizing rural e commerce investments under multiple economic, social, logistical, and environmental objectives.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1920143</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1920143</link>
        <title><![CDATA[Ethical tensions in renewable energy transitions: a philosophical examination of innovation cycles, intergenerational justice, and the moral imperative of responsible decommissioning]]></title>
        <pubdate>2026-08-19T00:00:00Z</pubdate>
        <category>Conceptual Analysis</category>
        <author>Qunchao Huang</author>
        <description><![CDATA[Accelerated innovation in renewable energy technologies drives the energy transition, but it can also intensify end-of-life material risks and expose the transition to a form of systemic fragility. This conceptual paper examines those ethical tensions across photovoltaic modules, wind-turbine blades, and lithium-ion batteries. It advances a normative argument grounded in Hans Jonas’s imperative of responsibility, Rawls’s just savings principle, Gardiner’s “perfect moral storm,” and Science and Technology Studies critiques of technological determinism. It further conceptualizes resilience as the capacity of the renewable-energy material–institutional system to anticipate, absorb, adapt to, and transform in response to technology turnover, resource constraints, and decommissioning pressures without shifting uncompensated ecological burdens to future generations or marginalized communities. The paper therefore connects responsible decommissioning to the 2030 Agenda’s integrated Sustainable Development Goals (SDGs), especially SDGs 7, 9, 12, 13, and 17, and reframes governance as a multi-actor sustainability transition rather than a voluntary manufacturer response. It concludes that bounded acceleration—linking deployment, design, repairability, take-back, recycling, public information, and accountability across the life cycle—is a moral and institutional condition of a just and resilient energy transition.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1915548</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1915548</link>
        <title><![CDATA[Financial incentives or fiscal support? the differential impacts of green credit and green subsidies on corporate carbon intensity]]></title>
        <pubdate>2026-08-19T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Bo Wen</author><author>Dayi He</author><author>Ping Lei</author>
        <description><![CDATA[Green credit is a market-oriented financial instrument. Green subsidies are government-led fiscal instruments. Both are important policy instruments for directing resources toward green sectors. However, existing studies have generally examined the two instruments separately, with few comparing their target recipients and low-carbon resource allocation characteristics within a unified framework. This study develops a theoretical model incorporating firms, banks, and the government and compares the allocation of capital and output to low-carbon firms relative to high-carbon firms under alternative policy scenarios. Building on this framework, this study conducts an empirical analysis using data on China’s A-share listed firms. The results show that corporate carbon emission intensity is significantly negatively associated with the probability of obtaining both green credit and green subsidies, indicating that both types of policy resources are generally allocated preferentially to low-carbon firms. Compared with green subsidies, green credit exhibits stronger screening of low-carbon firms. This study reveals differences between green credit and green subsidies in low-carbon resource allocation and provides guidance for improving both policy instruments.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1854489</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1854489</link>
        <title><![CDATA[Smart economies and climate outcomes: assessing the impact of digital transformation, economic resilience, and renewable energy on CO2 emissions]]></title>
        <pubdate>2026-08-19T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Sobia Naseem</author>
        <description><![CDATA[In recent years, the rapid evolution of information and communication technology (ICT) has profoundly influenced various sectors of the economy. Nevertheless, it is crucial to underscore the environmental ramifications of the rapid expansion of information and communication technology. This research aims to examine the asymmetric effects of information and communication technology, renewable energy consumption, foreign direct investment, and economic growth on CO2 emissions in G-20 countries from 2000 to 2022. The study used Dynamic Ordinary Least Squares (DOLS) and Pooled Mean Group Autoregressive Distributed Lag (PMG-ARDL) techniques. The preliminary step was to determine the normality of the data series using the second-generation unit-root tests (CIPS and CADF), which are known for their high efficiency and accuracy compared to the first-generation tests. The Pedroni and Westerlund cointegration test confirms a long-run relationship among foreign direct investment (FDI), economic growth (EG), information and communication technology (ICT), renewable energy (RE), and CO2 emissions, as supported by the error correction term. The PMG-ARDL and DOLS analytical techniques confirm a positive contribution of FDI, EG, and ICT to CO2 emissions, and declare that the G-20 countries face environmental sustainability challenges, even though they account for the largest share of global GDP and international trade. The appropriate policy implications and keenly observed practices of these sectors can help achieve a zero-carbon-emission environment without compromising economic growth, international trade, and global technological competition.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1829377</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1829377</link>
        <title><![CDATA[Donor-recipient interactions and the governance of the Water-Energy-Food-Health (WEFH) nexus in Uganda]]></title>
        <pubdate>2026-08-18T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Aisha Nalugya</author><author>Tonny Ssekamatte</author><author>Richard K. Mugambe</author><author>Bas J. M. Van Vliet</author>
        <description><![CDATA[IntroductionThe Water-Energy-Food and Health (WEFH) nexus has gained prominence as an approach for improving policy coherence across interconnected sectors. In low- and middle-income countries, donor agencies play a central role in shaping WEFH policies and interventions. However, the influence of donor-recipient interactions on local-level WEFH governance remains underexplored, despite implications for priority-setting, resource allocation, and sustainability across sectors.MethodsWe conducted 20 key informant interviews with stakeholders from government ministries, development agencies, and civil society, purposively sampled to capture diverse positions across the WEFH governance landscape. Document reviews were used to corroborate and validate interview findings. Data were analyzed using thematic analysis, with NVivo software supporting coding and data organization.ResultsThe findings show that donor agencies significantly shaped WEFH governance across six action situations: policy formulation, program design, resource allocation, inter-ministerial coordination, monitoring, and international policy alignment. While ministries maintained formal authority, donor funding and technical assistance influenced policy priorities, where programs were implemented, and resource distribution. Rules-in-use, particularly boundary, choice, and payoff rules, were redefined through donor conditions. Participation also remained asymmetric, with local governments and non-core ministries excluded from upstream decision-making. These interactions led to varying governance outcomes: improved coordination efficiency, enhanced attention to equity and inclusion, strengthened institutional capacity and policy alignment with frameworks. However, they also reinforced fragmentation, spatial inequities, accountability tensions, and sustainability challenges beyond donor project cycles.DiscussionThese findings show that donor-recipient interactions are not merely financing relationships, but governance mechanisms that shape decision-making, participation, resource allocation, reporting, and accountability in WEFH systems. Externally funded governance can create hybrid action situations in which formal state authority and donor practical leverage diverge. Strengthening WEFH governance therefore requires earlier inclusion of subnational actors in upstream decision-making, harmonized reporting systems across donors and ministries, equitable financing arrangements, and stronger alignment of donor support with national priorities and local realities.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1865597</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1865597</link>
        <title><![CDATA[UWMR-net: uncertainty-aware and wind-guided remote-sensing fusion for urban PM2.5 and ozone forecasting]]></title>
        <pubdate>2026-08-18T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Shaoru Feng</author>
        <description><![CDATA[Accurately characterizing the spatio-temporal evolution of urban air pollution and its meteorological response remains challenging because public multi-source observations are often asynchronous, incomplete, and heterogeneous. To address this issue, this study proposes UWMR-Net, an uncertainty-aware and wind-guided spatio-temporal framework that integrates public remote-sensing products, meteorological reanalysis, static land-surface attributes, and activity-related proxies for joint pollutant forecasting and meteorological-response diagnosis. The model combines an uncertainty-aware fusion module for quality-, lag-, and missingness-sensitive multi-modal integration, a wind-guided dynamic propagation backbone for directional transport modeling, and a counterfactual response branch for separating atmospheric response from background emission-related signals. Experiments on two public study domains, Los Angeles and the Po Valley, show that UWMR-Net achieves the best performance with five-seed mean ± SD reporting across PM2.5 and O3 1-day-ahead and 7-day-ahead forecasting tasks. The UWMR-Net entries are calculated from cleaned row-level test predictions over five independent random seeds. Rolling-origin backtests, macro-area diagnostics, extreme-event analyses, and split-conformal prediction intervals further characterize temporal stability, spatial heterogeneity, and calibrated forecast uncertainty. Counterfactual case studies additionally reveal spatially coherent meteorological enhancement and mitigation patterns during representative particulate and ozone episodes. These results demonstrate that uncertainty-aware fusion and wind-guided response modeling provide an effective and interpretable framework for urban air-pollution forecasting and meteorological-response analysis from public multi-source data.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1848445</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1848445</link>
        <title><![CDATA[New-quality productivity and rating-based ESG outcomes: the roles of green innovation and intelligent technology]]></title>
        <pubdate>2026-08-17T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Pengfei Hu</author><author>Fang Wang</author>
        <description><![CDATA[Regarding the synergetic progression of high-quality development and China’s “dual carbon” objectives, the relationship between new-quality productivity (Npro) and firms’ environmental, social, and governance (ESG) ratings has become an important issue in corporate sustainability research. A key practical concern is that firms’ technology investment may not necessarily translate into improved ESG rating performance. Using data from Shanghai and Shenzhen A-share listed companies from 2011 to 2022, this study develops an integrated framework linking Npro, green innovation (GI), intelligent technology, and rating-based ESG outcomes. Specifically, it examines the parallel mediating roles of green technological innovation (Gt) and green management innovation (Gm), the moderating roles of digital transformation (Dig) and artificial intelligence (AI), and regional heterogeneity across eastern, central, and western China. The findings show that Npro is positively associated with firms’ rating-based ESG outcomes, and this association remains stable across lagged-variable tests, IV-based sensitivity analysis, and multidimensional robustness checks. The results further indicate that Gt and Gm partially mediate the Npro–ESG rating relationship in parallel, with Gm accounting for 85.1% of the total indirect effect. The evidence on intelligent technology suggests that Dig and AI condition parts of the Npro–GI–ESG rating pathway, although their moderating effects are heterogeneous across mechanisms and regions. Regional heterogeneity analysis shows that the association between Npro and ESG ratings follows the order Central > Eastern > Western China. The moderating role of Dig is mainly observed in the Central region, whereas that of AI is mainly observed in the Eastern region. This study contributes to the literature by examining whether firm-level Npro is associated with higher ESG ratings through green technological and green management innovation. It also refines the integrated framework of dual-path green innovation and technology-related boundary conditions. The findings provide practical implications for firms seeking to improve ESG-rating performance through technological upgrading and green management practices, and for governments designing region-specific policies to strengthen the rating-based governance and disclosure channels that support high-quality development and the “dual carbon” agenda.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1885945</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1885945</link>
        <title><![CDATA[Diversified legume-based crop rotations enhance nutrient cycling and long-term productivity in tropical no-tillage systems]]></title>
        <pubdate>2026-08-17T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Telmo Jorge Carneiro Amado</author><author>Jackson Ernani Fiorin</author><author>William Ramos da Silva</author><author>Thiago Massao Inagaki</author><author>Ulfried Arns</author><author>Tiago Wyzykowski</author><author>Felipe José Cury Fracetto</author><author>Ademir de Oliveira Ferreira</author>
        <description><![CDATA[Diversified no-tillage crop successions are key strategies for improving soil health, productivity, and sustainability in tropical environments. However, adoption of diversified cropping systems remains limited due to economic, cultural, and technical constraints. This study aimed to evaluate how long-term diversified crop rotations, differing in legume inclusion and mineral phosphorus (P) and potassium (K) fertilization, influence system nitrogen (N), P, and K budgets, biomass production, and crop productivity in mature tropical no-tillage systems (NTS). Using a 10-year field experiment established on a tropical Ferralsol in southern Brazil, we evaluated six long-term crop rotations that differed in crop diversification, inclusion of Fabaceae cover crops, and phosphorus and potassium mineral fertilization. Total system N, P, and K budgets were quantified by integrating nutrient inputs, crop uptake, grain nutrient export, biomass nutrient cycling, and net soil nutrient balances. Intensive legume-based rotations increased crop productivity compared with low-diversity, non-legume rotations (specifically, the two-crop black oat/common bean succession). Vetch-based rotations under optimal or suboptimal mineral fertilization, as well as unfertilized vetch rotations, produced the highest cumulative grain yields (∼52,000 kg ha-1), representing a 38% increase (a 1.38-fold increase) over the black oat/common bean rotation (∼38,000 kg ha-1). This response was associated with a 40% increase in aboveground biomass and grain yield when maize followed hairy vetch rather than black oat. Legume-intensive rotations under optimal mineral fertilization or without fertilization maintained a strongly positive N budget (+559 kg ha-1), whereas the low-diversity black oat/common bean rotation showed a net N deficit. Conversely, all unfertilized systems, including the highly productive unfertilized hairy vetch-based rotations, exhibited strongly negative P and K budgets, indicating a progressive risk of soil fertility depletion. Only suboptimal mineral-fertilized vetch rotations partially offset these nutrient deficits in highly crop-productive systems. The study highlights the role of legume-based crop rotations as a key strategy to sustain a positive N budget, thereby supporting nutrient cycling and crop productivity under tropical NTS. Maintaining nutrient balance remained dependent on coupling biological N fixation with balanced mineral P and K fertilization to offset nutrient export deficits in high-yield systems and to reduce the risk of long-term soil fertility depletion.]]></description>
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