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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>2026-05-14T06:04:56.837+00:00</pubDate>
        <ttl>60</ttl>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1704560</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1704560</link>
        <title><![CDATA[Can market-based environmental regulation curb corporate greenwashing? Evidence from China’s carbon emissions trading scheme]]></title>
        <pubdate>2026-05-14T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Chen Ling</author><author>Yue Li</author><author>Fangyuan Xu</author>
        <description><![CDATA[Greenwashing refers to firms’ strategic responses that superficially comply with environmental and social responsibilities while substantially resisting them. In recent years, corporate greenwashing has attracted increasing attention, prompting calls for effective environmental regulations to curb such practices. Among various regulatory instruments, market-based mechanisms such as the carbon emissions trading scheme (ETS) have gained wide recognition. This study investigates the impact of China’s ETS implementation on corporate greenwashing behaviors, using a panel dataset of A-share listed firms from 2012 to 2022. The empirical results show that the implementation of the ETS significantly restrains greenwashing behaviors. Furthermore, the deterrent effect is more pronounced for firms with higher levels of green innovation and in regions experiencing more advanced industrial upgrading. These moderating effects highlight the importance of internal firm capabilities and external regional development in enhancing regulatory effectiveness. Robustness checks, including parallel trend tests and PSM-DID estimation, confirm the validity of our findings. This study enriches the understanding of China’s carbon trading system and provides empirical evidence for policymakers aiming to promote corporate environmental responsibility and improve the design of pilot carbon trading policies.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1826712</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1826712</link>
        <title><![CDATA[Integrated assessment of hydroclimatic, agricultural, and land-use dynamics under climate change in a semi-arid volcanic plateau: the case of Siverek, Türkiye]]></title>
        <pubdate>2026-05-14T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Hurşit Yetmen</author><author>Mehmet Bozkoyun</author><author>Betul İzol</author><author>Ahmet Şahap</author>
        <description><![CDATA[Hydroclimatic processes, land-use patterns, and agricultural activities are highly vulnerable to climate change, particularly in semi-arid regions where production systems depend strongly on local water resources. The Karacadağ Region (Siverek), located in northeastern Şanlıurfa, is a large rural area lacking large-scale irrigation infrastructure; therefore, local surface and groundwater resources are essential for agriculture, livestock, and domestic use. This study examines the transformation of hydroclimatic, hydrological, agricultural, and land-use dynamics in Siverek under climate change conditions. To achieve this integrated assessment, the study combined trend analysis, SPEI-based drought assessment, selected correlation analyses, remote-sensing-based reservoir mapping, and land-use change analysis. Long-term trends in precipitation, temperature, PET, streamflow, groundwater levels, well development, and crop area/yield series were evaluated using Mann–Kendall tests, Sen’s slope estimator, sequential Mann–Kendall analysis, and linear regression according to data structure. Hydroclimatic linkages were further assessed using Spearman rank correlations between precipitation and SPEI series and selected hydrological indicators, particularly streamflow and reservoir area. Landsat imagery was used to reconstruct temporal changes in reservoir surface area, while CORINE data were compared to quantify changes in non-irrigated agricultural land. The results indicate non-significant declines in annual precipitation but statistically significant increases in temperature and PET, accompanied by intensifying drought conditions. These changes were associated with declining streamflow, shrinking reservoir area, increasing groundwater dependence, and marked groundwater-level decline. In agriculture, barley cultivation expanded, whereas wheat and lentil cultivation areas contracted, while dryland agricultural land also decreased. Overall, the findings show that climatic stress is being transmitted through interconnected hydrological and agricultural pathways, reshaping both natural and human systems in this semi-arid region. These results highlight the need for more integrated and climate-compatible strategies in future water management, agricultural planning, and land-use policy.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1818116</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1818116</link>
        <title><![CDATA[Assessing knowledge and implementation gaps in soil health: an analysis from stakeholders]]></title>
        <pubdate>2026-05-14T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Giuliano Ferraro</author><author>Mohamed Houssemeddine Sellami</author><author>Carmen Vazquez Martin</author><author>Fabio Terribile</author>
        <description><![CDATA[Despite the European Union establishing an ambitious legislative framework—including the recent Soil Monitoring Law—and making significant scientific progress in understanding soil health, 60%–70% of EU soils remain unhealthy. This persistence of degradation highlights a potential disconnect between policy ambition and reality. This study–conducted within the EU “Benchmarks” project - investigates whether specific knowledge gaps are hindering the implementation of sustainable soil management (SSM) and the delivery of ecosystem services. We conducted a quantitative stakeholder perception analysis using a structured questionnaire based on the 13 action areas of the EU Soil Strategy for 2030. Data were collected from 79 experts across various sectors (Research, Government, NGOs, Education) using a purposive sampling strategy to identify soil knowledge gaps and prioritize intervention points based on the perceived urgency of knowledge and implementation failures. The analysis reveals a “Governance-Science Gap”. While stakeholders report high confidence in technical monitoring tools (e.g., LUCAS, Copernicus), they identify critical failures in integrating ecosystem services into political decision-making, defining actionable SSM practices and securing adequate funding. Disaggregated data show distinct perceptual disconnects; NGOs prioritize practical actions and funding, whereas researchers focus on theoretical gaps in climate and biodiversity. Comparing these findings with other EU initiatives (Soil Mission Support (SMS) and SOLO projects), we conclude that the primary barrier to soil health is not a lack of fundamental data, but a “Technical-Institutional Mismatch”. Future Research and Innovation (R&I) must therefore shift focus from data generation (Knowledge Development Gaps) to governance (e.g. research in developing approaches and tools to support informed decision), economic incentives, and educational frameworks (Knowledge Gaps) to translate science into effective stewardship. These exploratory findings warrant confirmation through larger-scale surveys but offer an evidence-based, stakeholder-driven diagnosis of priority areas for EU soil policy implementation.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1805203</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1805203</link>
        <title><![CDATA[The impact of energy-consuming right trading policy on urban ecological resilience: evidence from China]]></title>
        <pubdate>2026-05-14T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Pengchen Wang</author><author>Bingnan Guo</author>
        <description><![CDATA[The energy-consuming right trading policy is an important policy initiative by the government to use market mechanisms to curb energy consumption and improve energy efficiency, thereby exerts a profound impact on urban ecological resilience. Based on panel data of 243 cities from 2006 to 2019, this study employs the Propensity Score Matching-Difference-in-Differences (PSM-DID) method and a mediation effect model to assess the impact of the energy-consuming right trading policy on urban ecological resilience and its underlying mechanisms. The results reveal: ①The policy significantly enhances urban ecological resilience, and this finding is validated by a series of robustness checks, such as the parallel trend test. ② The energy-consuming right trading policy can enhance the ecological resilience by reducing coal consumption and driving green technology innovation. ③ The policy exhibits significant heterogeneous effects across cities with different characteristics: it exerts a significantly positive impact on urban ecological resilience in both high-income and low-income cities, with a more pronounced effect in low-income cities; it has a notably positive effect on cities with a high level of industrial structure but an insignificant effect on those with a low level of industrial structure; it also significantly promotes ecological resilience in both high-openness and low-openness cities, with a more prominent effect in low-openness cities. The results provide theoretical and empirical support for enhancing the energy-consuming right trading system and improving the execution of market-oriented environmental policies. At the same time, it gives clear instructions on how to make cities more ecologically resilient.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1874041</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1874041</link>
        <title><![CDATA[Editorial: Modeling for environmental pollution and change, volume II]]></title>
        <pubdate>2026-05-13T00:00:00Z</pubdate>
        <category>Editorial</category>
        <author>Chunlan Wei</author><author>Jian Zhai</author><author>Xiaoxiang Wang</author><author>Xuesheng Zhang</author><author>Pu Xia</author><author>Rui Zhang</author>
        <description></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1761204</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1761204</link>
        <title><![CDATA[Effects of new energy vehicle industry policies on manufacturing carbon emission efficiency: evidence from econometrics and doubly robust causal machine learning]]></title>
        <pubdate>2026-05-13T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Wenxin Liu</author><author>Tao Xie</author>
        <description><![CDATA[In light of global climate change and carbon-neutrality targets, carbon emissions from the manufacturing sector and the development of the new energy vehicle (NEV) industry have become central to policy agendas worldwide. NEV industry policies are a key instrument for enhancing manufacturing carbon-emission efficiency. Using provincial panel data from 30 Chinese provinces over 2010–2023, this study examines the effect of NEV industry policies on manufacturing carbon-emission efficiency. A hybrid analytical framework that combines traditional econometric methods with machine-learning techniques is employed for empirical analysis. The results indicate that a one–percentage-point increase in the policy index for the NEV industry is associated with a 0.0064 increase in manufacturing carbon-emission efficiency, significant at the 1% level. Regional heterogeneity is evident, with more pronounced policy effects in eastern and western China and in provinces with stronger fiscal support. Using a panel-consistent doubly robust causal machine-learning framework, we find that stronger NEV policy intensity improves manufacturing carbon emission efficiency. The analysis also highlights the importance of panel-aware estimation, overlap (common-support) diagnostics, and cluster-robust inference when evaluating policies using observational data. CATE-based heterogeneity analysis suggests that effect differences across covariate quantiles are generally modest, with the clearest separation observed for social consumption.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1806217</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1806217</link>
        <title><![CDATA[Environmental impact analysis of nano-level COVID-19 waste disposal using a comparative deep multi-layer perceptron algorithm]]></title>
        <pubdate>2026-05-13T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Yaser A. Nanehkaran</author><author>Zhu Licai</author><author>Youngseob Eum</author><author>Ahmed Cemiloglu</author><author>Zhandos Kudaibergenov</author><author>Elkhan Mahmud</author>
        <description><![CDATA[The improper disposal of COVID-19-related waste, such as masks, gloves, and personal protective equipment, has contributed to the release of nano-plastics, which degrade into nano-sized particles, posing severe environmental risks. Understanding the impacts of these nano-level particles is essential for mitigating long-term ecological harm. A comparative analysis was conducted to evaluate the effectiveness of the deep multi-layer perceptron (DMLP) algorithm in predicting the environmental impacts of pollution from nano-level plastic pollution from COVID-19 waste. The study focused on the degradation and dispersion of nano-plastics in Isfahan, Iran. The DMLP’s performance was benchmarked against multiple classifiers to assess its ability to capture intricate patterns and high-level feature representations unique to nano-plastic behavior. Hyperparameter optimization played a central role, fine-tuning learning rates, activation functions, and network configurations to enhance the DMLP’s predictive capabilities. The model’s performance was rigorously evaluated using metrics such as accuracy and the area under the receiver operating characteristic curve (AUC-ROC). The analysis specifically targeted nano-plastic dispersal patterns, identifying hot spots and ecological risks, to provide a comprehensive understanding of COVID-19 waste-related environmental impacts. The DMLP algorithm demonstrated exceptional performance in modeling and predicting the environmental dispersion of nano-plastics originating from COVID-19 waste in Isfahan, Iran. By leveraging its deep architecture, the DMLP effectively identified complex patterns in the degradation and movement of nano-plastics, outperforming other classifiers in accuracy and AUC-ROC metrics. Innovative visualization methods were employed to interpret the model’s decision boundaries, providing clear insights into high-risk zones and potential environmental impacts. The findings revealed critical nano-plastic accumulation hot spots, particularly in urban and water-sensitive areas, underscoring the vulnerability of these ecosystems to pollution from COVID-19 waste. This study demonstrates the capability of the DMLP to uncover intricate relationships within environmental datasets, particularly in analyzing the impacts of nano-level COVID-19 waste. The model’s ability to accurately predict the dispersion and accumulation of nano-plastics provides valuable insights into high-risk ecological zones, underscoring its potential to support environmental decision-making. These findings underscore the critical need for targeted waste management strategies to mitigate the long-term environmental impacts of nano-plastics and highlight the DMLP’s applicability in addressing complex pollution challenges in dynamic urban ecosystems.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1802874</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1802874</link>
        <title><![CDATA[Energy–economic transition and total factor productivity: empirical evidence from China]]></title>
        <pubdate>2026-05-13T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Han Cui</author><author>Baoshuai Yao</author>
        <description><![CDATA[Promoting energy economic transition is a critical pathway for achieving high-quality economic growth and improving total factor productivity (TFP), especially in the context of China’s carbon peaking and carbon neutrality goals. Based on panel data of Chinese prefecture-level cities, this study constructs a comprehensive index to measure the level of energy economic transition and empirically examines its impact on total factor productivity. Using a two-way fixed effects model and a threshold regression framework, we investigate both the nonlinear effects and regional heterogeneity of energy economic transition on productivity growth. The results indicate that energy economic transition significantly enhances total factor productivity, and this conclusion remains robust after a series of robustness checks. Further analysis reveals the existence of threshold effects associated with economic development level and environmental regulation intensity, under which the productivity-enhancing effect of energy economic transition becomes more pronounced. Regional heterogeneity analysis shows that the positive impact is stronger in eastern and economically developed regions than in central and western regions. Mechanism tests suggest that technological progress and industrial structure upgrading serve as important mediating channels through which energy economic transition improves total factor productivity. These findings provide empirical evidence for optimizing energy transition policies and promoting regionally coordinated green development in China.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1785661</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1785661</link>
        <title><![CDATA[Analysis and prediction of monthly runoff evolution characteristics in Linqi reservoir (China)]]></title>
        <pubdate>2026-05-13T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Dazhong Ma</author><author>Chaoqaing Yang</author><author>Qingqing Tian</author><author>Lei Guo</author>
        <description><![CDATA[Under the combined influences of climate change and human activities, the runoff processes in a watershed exhibit significant non-stationarity and multi-scale characteristics, posing challenges to water resource allocation and reservoir management. This study focuses on Linqi Reservoir, located in the former Yellow River course in Shangqiu City, Henan Province. Using monthly runoff data from 1980 to 2022 and climate factor data from 1980 to 2017, the study systematically analyzes the periodicity, abrupt changes, and climate-driven mechanisms of runoff through Extreme-point Symmetric Mode Decomposition (ESMD), Bayesian time series decomposition, and cross-wavelet analysis. Additionally, predictive models including Temporal Convolutional Network (TCN), Long Short-Term Memory (LSTM), LSTM-RF, and TCN-LSTM were developed. The results indicate that the monthly runoff is dominated by a quasi-7.28-month periodicity at the intra-annual scale and exhibits a quasi-12-month oscillation at the inter-annual scale. A significant seasonal abrupt change occurred in mid-1980, and long-term trend shifts were observed in 1985 and 2003. Analysis of climate factors reveals that El Niño-Southern Oscillation (ENSO), North Pacific Index (NPI), and Atlantic Multidecadal Oscillation (AMO) significantly influence runoff, with NPI showing the most pronounced positive correlation. Prediction results demonstrate that all four models achieve high accuracy, with NSE values exceeding 0.93. The TCN-LSTM hybrid model performs the best, achieving an NSE of 0.974, RMSE of 0.237 m3/s, and MAE of 0.182 m3/s, all optimal among the models and significantly outperforming individual models. This study reveals the multi-scale evolution patterns and climate-driven effects of runoff in LQ Reservoir along the former Yellow River course and validates the advantages of deep hybrid models in improving predictive accuracy, providing a scientific basis for water resource allocation, flood control, and sustainable management in the region.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1815865</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1815865</link>
        <title><![CDATA[Transformer encoder for one-step-ahead AQI forecasting using multivariate air-quality monitoring data]]></title>
        <pubdate>2026-05-13T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Kun-Chou Lee</author><author>Shi-Qi Chen</author>
        <description><![CDATA[Short-term forecasting of the Air Quality Index (AQI) can support public health risk management and real-time environmental decision-making. In this study, we propose a multivariate, one-step-ahead time-series forecasting approach based on a Transformer encoder. The model predicts the AQI at the next time point using an observation sequence within a fixed historical window (five time steps in this work), where the input features include AQI and other numerical variables. For data preprocessing, the observation time column is converted into a temporal index, missing values are handled using forward-fill, and Min–Max normalization is fitted on the training set and then applied to the test set to prevent data leakage. Supervised learning samples are constructed using a sliding-window scheme, and the dataset is split into training and test sets in chronological order. The proposed model stacks encoder blocks composed of multi-head self-attention and feed-forward networks, and a causal mask is applied in the attention mechanism to ensure that predictions rely only on historical information. The representation at the final time step is fed into a regression head to output the AQI forecast. To improve reproducibility, we fix random seeds and enable deterministic settings during training. Experimental results on the test set show that the proposed method achieves MSE = 19.84, RMSE = 4.45, and MAE = 3.57, demonstrating its ability to capture short-term temporal dependencies and provide stable AQI forecasting performance.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1803958</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1803958</link>
        <title><![CDATA[Assessment of air pollution disparities and allied climatic variability across the SAARC nations during the past quarter century]]></title>
        <pubdate>2026-05-13T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>R. Bhatla</author><author>Pradeep Kumar</author><author>Yajnaseni Dash</author><author>Needhish Bissessur</author><author>Abhishek Lodh</author><author>Vivek Singh</author><author>Amit Awasthi</author>
        <description><![CDATA[This study presents a comprehensive 25-year chronology of air pollution and climatic variable disparity across seven SAARC nations—Afghanistan, Bangladesh, Bhutan, India, Nepal, Pakistan, and Sri Lanka—emphasizing the region’s developing burdens of fine PM2.5 and SO2 from 2000 to 2024. MODIS and MERRA-2 data are used for a regional-scale analysis of seasonal, annual, and inter-annual variations in PM2.5 and SO2 concentrations. Spatially averaged metrics reveal marked disparities among SAARC countries, with Bangladesh, India, and Pakistan emerging as severe hot spots of PM2.5 pollution. Seasonal cycles demonstrate that winter months commonly experience peak pollutant accumulation, attributed to stable atmospheric boundary layers and reduced vertical mixing. Conversely, monsoon periods generally result in lower PM2.5 and SO2 concentrations due to enhanced wet scavenging and increased rainfall. PM2.5 values range as high as 100 µgm−3 in Bangladesh and often exceed 55 µgm−3 seasonally in India, while Sri Lanka and Bhutan maintain comparatively lower baseline levels, although with episodic cross-boundary pollution spikes. Simultaneously, climatic variables such as temperature, wind speed, precipitation, and planetary boundary level height were analyzed for air pollution. This study shows that policy interventions, although increasing, remain insufficiently robust to counteract the region’s escalating pollution problem as continued industrialization, population growth, and infrastructure expansion offset regulatory progress. The analysis provides an understanding of the spatio-temporal evolution of PM2.5 and SO2 in South Asia, highlighting the urgent need for regionally coordinated, multi-sector emission control strategies. Bangladesh stands out as the most severely impacted, followed by India. The overall air quality in the SAARC nations has been deteriorating, notably over the most recent 4-year period.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1813010</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1813010</link>
        <title><![CDATA[The mineralogy of dust and the solubility of phosphorus in dry particulate matter: ecosystem impacts to a large, shallow eutrophic lake]]></title>
        <pubdate>2026-05-13T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Kristen Smith</author><author>Yazhe Hu</author><author>Barry Bickmore</author><author>Joshua LeMonte</author><author>Gregory Carling</author><author>Kevin Rey</author><author>Theron Miller</author><author>Leland Meyers</author><author>Stephen Nelson</author>
        <description><![CDATA[Utah Lake is a large (380 km2) shallow (<4 m deep) eutrophic lake in the United States that experiences regular harmful algal blooms (HABs). West of the Mississippi River, only Flathead Lake, Montana and Lake Tahoe, Nevada/California have greater surface areas among fresh water lakes. Unlike these other lakes, it is adjacent to a large urban corridor and its water quality is of concern for aesthetics, recreation and irrigation diversions. HABs in Utah Lake can affect ecosystem health, including the production of cyanotoxins and profound anoxia. Active sampling of the Utah Lake airshed has shown that the mineralogy and phosphorus content and solubility of dust varies in time and space. Dust is comprised of varying proportions of quartz, calcite, dolomite, sodium feldspar, gypsum, halite, illite and kaolinite. The soluble phosphorus fraction of dust is bi-modally distributed with nodes at 10% and 50% releases to synthetic lake water. Active sampling also showed that there is little attenuation of >2 μm particles as air blows across the lake. Soluble phosphorus appeared to be associated with calcium-rich phases and especially areas with high gypsum content. As much as 1/3 of phosphorus is delivered to the lake during June through August. High phosphorus deposition during the summer months exacerbates the tendency for HABs to form in warm weather. Monte Carlo simulations suggest that phosphorus associated with atmospheric deposition alone is sufficient to maintain a eutrophic state in the lake. Dust has become a large, non-point source of phosphorus, with external fluxes to the lake that equal or exceed point sources like waste-water treatment plants. It is also largely anthropogenic as dust movement has increased 500% since European settlement. This suggests that active ecosystem management is needed to maintain and improve water quality and ecosystem function as non-point source phosphorus fluxes may overwhelm point-source controls.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1738158</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1738158</link>
        <title><![CDATA[Multidimensional linkages among carbon, energy, and industrial metals markets: evidence from spillover effects and co-movements]]></title>
        <pubdate>2026-05-13T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Shuifeng Hong</author><author>Yimin Luo</author><author>Jinhua Cheng</author>
        <description><![CDATA[This study investigates the spillover effects and co-movements among carbon, energy, and industrial metals markets using a multidimensional research framework encompassing the time, frequency, and time-frequency domains. The methodologies applied include the cointegration approach, a discrete wavelet-based Diebold-Yilmaz (DY) model, and wavelet coherence analysis. The findings are as follows: firstly, long-term cointegration relationships exist among these markets in the time domain. Secondly, the discrete wavelet-based DY model identifies the carbon and oil markets are the primary net spillover transmitters, while the gas, coal, and industrial metals markets are the major net spillover recipients. Finally, wavelet coherence analysis shows that co-movements are fragmented and time-varying in the time-frequency domain. Several occasions of high correlations among these markets are observed in the medium- and long-term, and these correlations have been intensified by crisis events. In addition, an increase in the carbon market price tends to drive up energy and industrial metals market returns, mainly exhibiting a positive correlation. These findings have significant implications for policymakers to formulate differentiated regulatory measures across different time horizons.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1812062</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1812062</link>
        <title><![CDATA[Waste management in developing countries: a systematic literature review of policy implementation]]></title>
        <pubdate>2026-05-13T00:00:00Z</pubdate>
        <category>Systematic Review</category>
        <author>I. Putu Dharmanu Yudartha</author><author>Teguh Yuwono</author><author>Sri Suwitri</author>
        <description><![CDATA[BackgroundWaste management in developing countries is a significant governance challenge that hinders progress toward the SDGs. Despite policy efforts and aid, implementation gaps persist, characterized by fragmented institutions, exclusionary formalization, and the marginalization of the informal recycling sector, which is essential to waste systems.ObjectiveThis review explores how policy integration and multi-stakeholder collaboration influence waste management in developing countries. It aims to: (1) categorize implementation models; (2) synthesize success factors and barriers; (3) analyze outcomes and trade-offs; and (4) propose future research and policy actions.MethodsFollowing PRISMA 2020 guidelines, we conducted a systematic search of Scopus and Web of Science for peer-reviewed articles published between 2014 and 2025. After screening 310 records, 25 articles met the inclusion criteria: empirical or conceptual studies examining waste management policy implementation in developing countries from social science, governance, or public policy perspectives.ResultsWe identify three implementation models and theorize the co-constitutive relationship between policy integration and collaboration. The hybrid model offers the greatest potential for inclusivity but risks power imbalances and co-optation. Successful cases such as Brazilian cooperatives and Indonesian Waste Banks demonstrate that formal legal recognition, reserved contracts, infrastructure, and social protections help integrate informal workers equitably.ConclusionWaste management transformation demands policy integration and stakeholder collaboration as co-constitutive governance. Governments should move beyond policy borrowing to context-sensitive adaptation; donors must reform financing biases and invest in knowledge infrastructure; and civil society must mobilize collective agency for inclusive formalization. The findings contribute to implementation theory, offering perspectives on distributive justice, democracy, and accountability.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1775245</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1775245</link>
        <title><![CDATA[Detection of phenological features of an evergreen broadleaved tree by analysis of fractal dimension]]></title>
        <pubdate>2026-05-12T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Nagai Shin</author><author>Yuji Tokumoto</author><author>Tomoaki Ichie</author><author>Paulus Meleng</author><author>Hiroshi Morimoto</author>
        <description><![CDATA[The development of phenological observations of evergreen broadleaved trees is required to deepen our understanding of ecosystem functions and services and of biodiversity under climate and societal changes. Toward that end, we examined the relationship between daily fractal dimension D values calculated from long-term timelapse canopy-surface images of Castanopsis sieboldii and the appearance and disappearance of plant organs and changes in their structure over time. The daily D values based on the size of outlines of plant organs (such as leaf buds, flowers, and new leaves) changed seasonally in accordance with developments such as leaf flush and flowering. The seasonal patterns of change differed between a year with many flowers and years with few to no flowers. Despite the need for further long-term daily timelapse images of various evergreen broadleaved trees to allow the extraction of outlines of smaller organs, our findings suggest that the analysis of daily D values is useful for detecting details of flowering and of leaf flush and senescence phenology, focusing on temporal changes in the structures of each organ.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1782320</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1782320</link>
        <title><![CDATA[Caribbean small island developing states and the climate change advisory opinions: engagement and potential use]]></title>
        <pubdate>2026-05-12T00:00:00Z</pubdate>
        <category>Review</category>
        <author>David S. Berry</author><author>James L. Fletcher</author><author>Zachary A. R. Phillips</author>
        <description><![CDATA[Facing an existential threat, Caribbean small island developing states have actively engaged in international legal processes aimed at combatting climate change. Caribbean states initiated the advisory opinion before the International Tribunal on the Law of the Sea and participated in two others, one before the Inter-American Court of Human Rights and the other before the International Court of Justice. The present article seeks to explore the reasoning and potential of the three advisory cases for strategic use by SIDS. To this end the article summarises key aspects of the advisory opinions for practical use by Caribbean Governments, with particular focus on the ICJ’s opinion. It identifies areas of divergence between Caribbean submissions and the positions adopted by the ICJ and assesses the accuracy of the climate science discussed in the opinion, especially in relation to Caribbean climate change challenges. The article offers concrete recommendations for Caribbean SIDS about how to strengthen and deploy regional climate science, and to use the advisory opinions, in their future legal and negotiating strategies.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1771178</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1771178</link>
        <title><![CDATA[Analysis of grassland phenology dynamics and response to seasonal scale climate, topography in China based on geodetector for the period 2001 to 2019]]></title>
        <pubdate>2026-05-12T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Zhiyuan Gong</author><author>Ye Tian</author><author>Chunlin Wang</author><author>Dandan Dong</author><author>Rui Zhang</author><author>Xi Zhang</author><author>Jinyan Sun</author>
        <description><![CDATA[IntroductionThere is limited research on the cumulative effects of seasonal climate factors and the combined impacts of climate and topography on grassland phenology. This gap hinders the understanding of the climate adaptability of China’s grasslands ecosystems.MethodsThis work used the GeoDetector method to examine how grassland phenology in China (CGP) responds to seasonal climate factors, elevation, slope, and aspect. First, we studied the spatiotemporal distribution characteristics of CGP through spatial analysis and trend analysis methods. Second, we examined the effects of different climatic factors on CGP at the seasonal scale through correlation analysis. Third, we classified the topography of the study area and investigated the influence of different terrains on CGP. Finally, GeoDetector was used to quantify the explanatory power of seasonal climate and topography on CGP, as well as the impact of climate-topography interactions on CGP.Results and DiscussionThe results showed that with increasing preseason length, the areas showing a negative correlation between temperature and the start of season (SOS) expanded. SOS was negatively correlated with precipitation and evapotranspiration, except precipitation of the previous year and evapotranspiration in winter. Temperature, precipitation, and evapotranspiration all showed positive correlations with the end of season (EOS). The responses of SOS to elevation and slope exhibited nonlinear trends. When elevation exceeded 4 km, the rate of SOS delay accelerated markedly. SOS also showed significant delays at slopes greater than 25°. Meanwhile, with increasing elevation and slope, EOS tended to advance. The interaction effects of climate and topography on EOS were weaker than those on SOS. SOS (EOS) is primarily influenced by the interaction between elevation and evapotranspiration (precipitation), highlighting the importance of the interaction between DEM and climatic factors in shaping grassland phenology in China. The findings in this work suggest that topographic heterogeneity should be incorporated into ecological management to better respond to environmental challenges under climate change.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1773535</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1773535</link>
        <title><![CDATA[Integration of tailored Co3O4@G with porous biochars for efficient degradation of tetracycline]]></title>
        <pubdate>2026-05-12T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Meiling Zhu</author><author>Yuejie Wang</author><author>Ruirui Li</author><author>Feng Liang</author>
        <description><![CDATA[Graphitic-carbon-coated metallic-catalyst-loaded porous carrier composites are widely used to degrade antibiotics by activating peroxymonosulfate (PMS). Integration of the defect sites within the graphitic shell, core–shell interface, and catalyst/carrier could enhance the “1 + 1 > 2” catalytic effect. In this work, graphitic-carbon-coated cobaltosic oxide (Co3O4@G) having a tailored nanostructure (23.3–29.7 nm for the core and 2.35–1.29 nm for the shell) was first synthesized by pulsed laser ablation. Then, porous Co3O4@G/biochars (Co3O4@G/Bs; 18.5–134.8 m2/g) were synthesized by crosslinking nitrogen-modified Co3O4@G with waste bamboo-pyrolyzed biochars. The degradation behaviors were evaluated as functions of the composite species, catalyst dosage, PMS concentration, tetracycline concentration, solution pH, and coexisting anions. The Co3O4@G/Bs presented high catalytic k values (0.159–0.449 min–1) that were 15.5–40.8 times higher than those of the individual biochars; furthermore, excellent recycling performance (92.5% remaining k value) and promising stability (8.31–2.77 μg/L of Co leakage) were observed after recycling 10 times. The favorable catalytic versatility of the Co3O4@G/Bs was verified by the efficient degradations of levofloxacin (88.6%), oxytetracycline (95.4%), and norfloxacin (92.5%). The degradation mechanism was governed by the radical-based degradation pathways involving •OH, SO4•–, and 1O2 via Co3+ and Co2+ recycling. The present study is expected to provide a valuable reference for degrading antibiotics by integrating tailored laser-ablated core/shell nanoparticles with biochars.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1751485</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1751485</link>
        <title><![CDATA[Environmental processes and ecosystem services of self-purifying mercury in constructed wetlands in industrial cities: a case study of the main urban area of Changchun, Yitong River]]></title>
        <pubdate>2026-05-11T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Rongyang Fan</author><author>Xuemei Li</author><author>Shijie Hao</author><author>Xiao Yuliang</author><author>Jing Zong</author><author>Yiran Gao</author><author>Yishan Sun</author><author>Zhaojun Wang</author><author>Gang Zhang</author>
        <description><![CDATA[With the rapid development of urbanization and the economy, the deterioration of water quality in urban aquatic ecosystems has become a global environmental problem. Currently, research on global and regional mercury cycling primarily focuses on vulnerable ecosystems such as polar regions, mining areas, and permafrost zones. While numerous studies have investigated mercury pollution in urban areas worldwide, research specifically addressing the role of constructed wetlands in mitigating mercury pollution in urban river systems in Northeast China remains limited. This study focuses on a typical constructed wetland in the urban section of the Yitong River in Changchun, systematically analyzing the temporal and spatial distribution characteristics of mercury in water, sediments, and plants, and assessing the removal efficiency of mercury pollution as well as the ecological service value of the urban river wetland system. The results show that the spatiotemporal distribution of mercury is jointly influenced by human activities, such as municipal sewage discharge, industrial emissions, and transportation, as well as natural processes like climate, hydrology, and organic matter degradation. In densely urbanized areas, mercury concentrations in water and sediments have significantly increased. The mineralization of organic matter in autumn and coal-burning activities in winter intensify mercury emissions, while high temperatures in summer promote the volatilization and recirculation of mercury. Furthermore, this study quantified the economic value of wetland ecosystem services and suggests that optimizing the spatial layout of wetlands, strengthening industrial source control, and developing multidimensional assessment models provide a scientific basis for enhancing regional ecological security and water environment governance.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fenvs.2026.1798633</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fenvs.2026.1798633</link>
        <title><![CDATA[The decoupling frontier: efficiency, inequality, and biocapacity in the global search for absolute sustainability]]></title>
        <pubdate>2026-05-11T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Mansoor Ahmed</author><author>Ghulam Shabbir</author><author>Ahsan Shafi</author>
        <description><![CDATA[IntroductionConventional approaches for decoupling economic growth from resources often emphasize regression-based evaluations while omitting structural heterogeneity and biophysical limits. The present study aimed to examine country-specific pathways for absolute decoupling of fossil material use within the planetary boundaries.MethodsUsing a panel dataset encompassing information from 85 countries over the period of 2002 to 2023, we approximated the material efficiency scores via stochastic frontier analysis (SFA) by assuming half-normal and exponential distributions.ResultsThe results show that the biocapacity overshoot varies irregularly and ranges between 9.5% and 19% of the national averages; this trend indicates the cyclic fragility of decoupling. Furthermore, the results indicate high material inequality (Gini = 0.55), including the fact that nearly two-thirds of the fossil-based material resources were consumed by approximately 20% of the global population. Rwanda, Myanmar, and Oman were found to be the most efficient countries, whereas high-income economies were faced with diminishing returns. Additionally, we proposed an efficiency-adjusted index above USD 650,000 per ton based on global climate investment at the forefront. We found that the richest or the most polluting countries did not provide the greatest marginal benefits; instead, countries with structurally inefficient economies could provide massive economic and ecological benefits through specific policy interventions.DiscussionThe present work expands on this frontier of knowledge by shifting the decoupling paradigm to ecological feasibility, which indicates that the highest marginal gains are available in structurally inefficient economies rather than polluting nations. By integrating SFA in this work, we identified the absolute minimum achievable fossil footprints by prioritizing equity sensitive climate finance.]]></description>
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