Hasil untuk "Environmental sciences"

B. Davies, D. Baulcombe, I. Crute et al.

M. Meier, J. Metzger, U. Schubert

Shahid Naeem, J. Duffy, E. Zavaleta

P. Stern, Linda Kalof, Thomas Dietz et al.

H. Raiffa

E. Dockner, S. Jørgensen, N. Long et al.

E. Abt, J. Rodricks, J. Levy et al.

R. C. Patra, Devendra Swarup, R. Ranjan et al.

C. Makondo, D. Thomas

Abstract The implementation of climate change response programmes for adaptation and resilience is anchored on western scientific knowledge. However, this has led to a tendency to marginalise indigenous knowledge as it is considered unimportant in this process (Belfer et al., 2017; Lesperance, 2017; Whitfield et al., 2015 ). Yet, knowledge systems rarely develop in isolation as they normally tend to cross-fertilize and benefit from each other. In this regard, we think that indigenous knowledge is just as important as scientific knowledge and the two must be integrated through multiple evidence base approach for climate change adaptation and mitigation. In this paper, focussing on African traditional society, we combine oral history with the available literature to examine traditional knowledge and awareness of climate change and related environmental risks. Interesting themes emerge from the knowledge holders themselves and our analysis uncovers a wide range of adaptive coping strategies applied with mixed success. From spotting and reading the position and shape of the ‘new moon’ to the interpretative correctness of its symbolism in “applied traditional climatology,” and from rain-making rituals to conservation of wetlands and forests. Generally, findings seem to suggest that traditional African knowledge of environmental change may be as old as the society itself, with local knowledge transmitted from one generation to the next. Based on the perceived vulnerability of indigenous communities, many scholars tend to argue generically for the integration of indigenous knowledge into climate change policies and implementation (Ross, 2009; Maldonado et al., 2016 ; Etchart, 2017 ). In this paper however, we attempt to supplement these arguments by providing specific and contextualised evidence of indigenous knowledge linked to climate change adaptation. It is demonstrated that indigenous knowledge is neither singular nor universal, but rather, a voluminous, diverse and highly localised source of wisdom. We conclude that integration of such unique and specific indigenous knowledge systems into other evidence bases of knowledge, could be one of the best ways to the more effective and sustainable implementation of climate change adaptation strategies among target indigenous communities.

Xinwen Chen, Ruisi He, Mi Yang et al.

In urban environments, vehicle-to-everything (V2X) communications require accurate wireless channel characterization. This requirement is particularly critical at street-canyon intersections, where building blockage and rich multipath propagation can severely degrade link reliability. Due to its unique environmental layout, the channel characteristics in urban canyon are influenced by building distribution. However, this feature has not been well captured in existing channel models. In this paper, we propose an environment-related statistical channel model based on 5.8~GHz channel measurements. We construct a composite environmental factor to characterize environmental differences in intersections. Then, the factor is incorporated into 3GPP path-loss model and further linked to small-scale channel parameters. Finally, accuracy of the proposed model is validated using second-order channel statistics. The results show that the proposed model can effectively characterize propagation properties of urban street-canyon intersection channels with different building conditions. The proposed model provides a physically interpretable and statistically effective framework for channel simulation and performance evaluation in urban vehicular scenarios.

Yonatan Uziel, Natan Orlov, Loay Atamneh et al.

Chemical monitoring of pollutants and hazardous materials in water supply systems traditionally depends on centralized laboratories, advanced instrumentation, and trained personnel, limiting accessibility and preventing real-time, on-site analysis. This work presents an alternative cost-effective, field-deployable approach that uses genetically engineered bioluminescent bioreporters, encapsulated in self-sufficient alginate capsules and integrated with an optoelectronic detection circuit, to detect and quantify target materials in water. We have developed a scalable single-channel prototype featuring four sensing tracks—two for sample measurement, one for clean water, and one for a standard reference solution. The latter employs the standard ratio (SR) method to ensure robust quantification, compensating for batch variability and environmental effects. System characterization showed high uniformity across tracks. Validation with nalidixic acid (NA) demonstrated reliable quantitative performance, with a blind test estimation of 5.6 mg/L for a true concentration of 5 mg/L, well within the calibration error range. Additional sensitivity testing confirmed detection of mitomycin C (MMC) at concentrations as low as 50 µg/L. Overall, the results highlight the potential of bacterial chemical sensing as a practical and scalable tool for real-time, in situ water quality monitoring networks.

Yanran Wu, Inez Hua, Yi Ding

Large language models (LLMs) offer powerful capabilities but come with significant environmental impact, particularly in carbon emissions. Existing studies benchmark carbon emissions but lack a standardized basis for comparison across different model configurations. To address this, we introduce the concept of functional unit (FU) as a standardized basis and develop FUEL, the first FU-based framework for evaluating LLM serving's environmental impact. Through three case studies, we uncover key insights and trade-offs in reducing carbon emissions by optimizing model size, quantization strategy, and hardware choice, paving the way for more sustainable LLM serving. The code is available at https://github.com/jojacola/FUEL.

Manya Pandit, Triveni Magadum, Harshit Mittal et al.

The research examines the challenges revolving around young people's social movements, activism regarding sustainability, as well as the accompanying social media aspect, and how social media impacts environmental action. This study focuses on the environmental craze on social media platforms and its impact on young activists aged 16-25. With the advancement of social media, new avenues have opened for participation in sustainability issues, especially for the marginalized, as information moved through transnational networks at lightning speed. Along with specific Formative Visual Storytelling methods, the young leaders of the movement deploy hashtags and other online tools to capture the attention of their peers and decision makers. Challenges persist with "clicktivism" fatigue from the internet, and site limitations. This article contributes to insights on emerging forms of civic activism by explaining how digital natives adapt technology to reframe green activism. The research suggests that effective digital environmental movements integrate online and offline action, make it simple for individuals to get involved, and promote tolerance to algorithmic modifications and climate care among participants.

Chiyu Chen, Xinhao Song, Yunkai Chai et al.

Vision-Language Models (VLMs) are increasingly deployed as autonomous agents to navigate mobile graphical user interfaces (GUIs). Operating in dynamic on-device ecosystems, which include notifications, pop-ups, and inter-app interactions, exposes them to a unique and underexplored threat vector: environmental injection. Unlike prompt-based attacks that manipulate textual instructions, environmental injection corrupts an agent's visual perception by inserting adversarial UI elements (for example, deceptive overlays or spoofed notifications) directly into the GUI. This bypasses textual safeguards and can derail execution, causing privacy leakage, financial loss, or irreversible device compromise. To systematically evaluate this threat, we introduce GhostEI-Bench, the first benchmark for assessing mobile agents under environmental injection attacks within dynamic, executable environments. Moving beyond static image-based assessments, GhostEI-Bench injects adversarial events into realistic application workflows inside fully operational Android emulators and evaluates performance across critical risk scenarios. We further propose a judge-LLM protocol that conducts fine-grained failure analysis by reviewing the agent's action trajectory alongside the corresponding screenshot sequence, pinpointing failure in perception, recognition, or reasoning. Comprehensive experiments on state-of-the-art agents reveal pronounced vulnerability to deceptive environmental cues: current models systematically fail to perceive and reason about manipulated UIs. GhostEI-Bench provides a framework for quantifying and mitigating this emerging threat, paving the way toward more robust and secure embodied agents.

F. E. Kemgang Ghomsi, F. E. Kemgang Ghomsi, F. E. Kemgang Ghomsi et al.

This study provides an in-depth evaluation of sea level rise (SLR) and its varied effects across the coastal regions of southern Africa. Utilizing data collected between 1993 and 2022, we analyze SLR patterns alongside land subsidence phenomena, based on observations from 10 strategically located tide gauges and X-TRACK satellite altimetry datasets. To ensure greater accuracy, the Coastal Altimetry Approach was adopted to refine nearshore measurements. Findings indicate that in areas such as Cape Town, sea-level rise rates reach around 6.3 mm/year, which is nearly twice the current global average of 3.3 mm/year. The interaction between rapid sea-level rise and subsidence rates surpassing 2.2 mm/year presents significant threats to coastal communities, critical infrastructure, and natural ecosystems. Moreover, the study highlights how seismic activity contributes to coastal dynamics, illustrating the role of earthquake-induced subsidence in magnifying the impacts of SLR. By incorporating seismic factors into the analysis, a more comprehensive understanding of the interplay between natural and human-induced drivers of sea-level variability is achieved. Additionally, the study examines the broader effects of SLR on Africa’s culturally and historically important coastal heritage sites, emphasizing the urgent need for proactive coastal management and climate adaptation efforts.

Dongyu Cui, Yike Kang, Beidou Xi et al.

Organic pollutants remain a persistent threat to ecosystems and human health. In soils, humification gradually converts these compounds into stable humic substances and attenuates their toxicity, but the transformation can take decades—far too slow to match current pollution loads. In this Perspective, we argue that mature compost offers a pragmatic means to accelerate this process: it delivers partially humified intermediates that can “seed” soil humification and shorten its timescale from decades to seasons. Spectroscopic evidence shows that compost-derived humus is enriched in aromatic backbones and reactive functional groups (–COOH, –OH) that both catalyze further condensation of organic matter and immobilise pollutants through π–π stacking, hydrogen bonding and covalent coupling. By merging these catalytic and sorptive functions, compost amendments provide a scalable, low-cost route to the long-term stabilization of organic contaminants. We outline the key mechanistic questions that now need resolution—particularly the reactivity of specific intermediates in situ—to guide field trials and unlock the full potential of compost-driven accelerated humification as an environmental remediation platform.

Xinyue Hu, Haitao Han, Shanshan Wang et al.

Copper (Cu) is an essential trace element for plankton, but excessive amounts can be toxic and threaten the ecosystems and human health. However, the determination of low concentration labile Cu (CuLabile) in complex water environments remains a huge challenge. In this work, a gold microelectrode (μ-GE) with high sensitivity and anti-fouling capability was fabricated based on a double-layer membrane framework consisting of ion-exchange polymer (Nafion) and agarose gel (LGL). The Nafion stabilized on the surface of μ-GE not only enhanced the voltammetric response significantly through its specific cation-exchange ability with Cu2+, but also improved the chemical and mechanical stability. In addition, the LGL formed an another efficient anti-fouling membrane which could prevent the contamination of electrode by microorganisms, particulate matters, etc. Benefiting from the synergistic effects of the double-layer membrane framework, the so-designed LGL/Nafion functionalized μ-GE (LGL/Nafion/μ-GE) exhibited excellent detection performance for Cu, as well as anti-biofouling capability. Two linear ranges (0.5–10 nM and 10–1000 nM) were achieved for Cu2+, with a detection limit of 0.043 nM in NaCl solution with a salinity of 30 ‰. The LGL/Nafion/μ-GE was successfully applied for the determination of CuLabile in complex environmental water samples including natural seawater and artificial algae culture medium. Furthermore, the real-time changes of CuLabile in culture medium of Synechococcus sp.PCC 7002 was obtained successfully with the LGL/Nafion/μ-GE via in situ continuous monitoring.

Tiejun Xie, Hui Gao, Ting Ding et al.

Abstract It was found that the Central-eastern China’s summer extreme heat (CECSH) has a decadal variability with a cycle of about 70 years and is significantly positively correlated with the Atlantic Multidecadal Oscillation (AMO) core area sea surface temperature (SST; AMOCORE) and the tropical western Pacific SST (WPSST) in boreal summer. Diagnostic analyses such as synergistic diagnostic and linear baroclinic model (LBM) experiments show that the warm AMOCORE and WPSST in boreal summer can generate the localized heat dome (HD) over Mongolia to northeast China by exciting local convection and subsequent propagation, respectively, which in turn directly influences the CECSH decadal variability through compression of the atmosphere and temperature transport. The empirical models of the CECSH decadal variability were constructed based on the AMOCORE or the WPSST separately and synergistically considering both, and the empirical model considering the synergistic effects of the AMOCORE and the WPSST had better simulation capability.

Bence Lukács, Péter Molnár

Abstract The growing integration of Environmental, Social, and Governance (ESG) factors into corporate decision-making and investment strategies has heightened the need for reliable and comparable ESG ratings. However, substantial divergence across rating agencies—driven by inconsistent methodologies, weighting schemes, and disclosure practices—poses challenges for investors, firms, and regulators. Addressing a key gap in the literature, this study investigates how regulatory environments influence ESG rating divergence by comparing hard, soft, and unregulated frameworks across five major economies: the United States, China, Japan, Germany, and India. ESG ratings were collected from Sustainalytics, S&P Global, and Refinitiv for the top 50 publicly listed companies in each country. The divergence was measured using absolute score differences between agencies, and statistical tests and cluster analysis were conducted to evaluate the impact of regulation on rating consistency. The results indicate that countries with strong, mandatory ESG disclosure regimes—such as Germany's CSRD and India’s BRSR—exhibit significantly lower levels of rating divergence, while unregulated markets like the USA and China display the highest discrepancies. Notably, Japan’s soft-law approach achieves alignment levels comparable to those of hard-law environments, emphasizing the role of regulatory enforcement. These findings reinforce both signaling and agency theories by demonstrating how regulatory oversight and transparency reduce information asymmetry and promote stakeholder trust. The study highlights the importance of direct supervision of ESG rating agencies and supports global harmonization of ESG disclosure standards as a means to enhance market efficiency and comparability.

Kai Wang, Li Yu, Jianhua Zhang et al.

The stability and reliability of wireless data transmission in vehicular networks face significant challenges due to the high dynamics of path loss caused by the complexity of rapidly changing environments. This paper proposes a multi-modal environmental sensing-based path loss prediction architecture (MES-PLA) for V2I communications. First, we establish a multi-modal environment data and channel joint acquisition platform to generate a spatio-temporally synchronized and aligned dataset of environmental and channel data. Then we designed a multi-modal feature extraction and fusion network (MFEF-Net) for multi-modal environmental sensing data. MFEF-Net extracts features from RGB images, point cloud data, and GPS information, and integrates them with an attention mechanism to effectively leverage the strengths of each modality. The simulation results demonstrate that the Root Mean Square Error (RMSE) of MES-PLA is 2.20 dB, indicating a notable improvement in prediction accuracy compared to single-modal sensing data input. Moreover, MES-PLA exhibits enhanced stability under varying illumination conditions compared to single-modal methods.