Hasil untuk "Environmental Science"

C. Gibson, E. Ostrom, T. Ahn

Abstract Issues related to the scale of ecological phenomena are of fundamental importance to their study. The causes and consequences of environmental change can, of course, be measured at different levels and along multiple scales. While the natural sciences have long understood the importance of scale, research regarding scale in the social sciences has been less explicit, less precise, and more variable. The growing need for interdisciplinary work across the natural/social science divide, however, demands that each achieve some common understandings about scaling issues. This survey seeks to facilitate the dialogue between natural and social scientists by reviewing some of the more important aspects of the concept of scale employed in the social sciences, especially as they relate to the human dimensions of global environmental change. The survey presents the fundamentals of scale, examines four general scaling issues typical of social science, and explores how different social science disciplines have used scale in their research.

Liuwei Wang, David O’Connor, J. Rinklebe et al.

Biochar has triggered a black gold rush in environmental studies as a carbon-rich material with well-developed porous structure and tunable functionality. While much attention has been placed on its apparent ability to store carbon in the ground, immobilize soil pollutants, and improve soil fertility, its temporally evolving in situ performance in these roles must not be overlooked. After field application, various environmental factors, such as temperature variations, precipitation events and microbial activities, can lead to its fragmentation, dissolution, and oxidation, thus causing drastic changes to the physicochemical properties. Direct monitoring of biochar-amended soils can provide good evidence of its temporal evolution, but this requires long-term field trials. Various artificial aging methods, such as chemical oxidation, wet-dry cycling and mineral modification, have therefore been designed to mimic natural aging mechanisms. Here we evaluate the science of biochar aging, critically summarize aging-induced changes to biochar properties, and offer a state-of-the-art for artificial aging simulation approaches. In addition, the implications of biochar aging are also considered regarding its potential development and deployment as a soil amendment. We suggest that for improved simulation and prediction, artificial aging methods must shift from qualitative to quantitative approaches. Furthermore, artificial preaging may serve to synthesize engineered biochars for green and sustainable environmental applications.

Adam B. Jaffe, Richard G. Newell, Robert N. Stavins

B. Gatersleben, L. Steg, C. Vlek

S. Jasanoff

F. L. Matthews, R. Rawlings

K. Chan, Rachelle K. Gould, U. Pascual

Abstract Relational values—as preferences, principles and virtues about human-nature relationships—have attracted a great deal of attention in recent years. The term has been used to include concepts and knowledge from a wide range of social sciences and humanities, e.g., importantly making space for qualitative approaches often neglected within environmental management and science. Meanwhile, crucial questions have emerged. What counts as a relational value, and what does not? How do relational values (RVs) compare with other value categories and terms, including held, assigned, instrumental, moral, shared, social, and non-material values (e.g., associated with cultural ecosystem services)? In this article, we address these issues, partly by providing context about how the RV term originated and how it has evolved to date. Most importantly, because of their somewhat unique combination of groundedness and moral relevance, positive relational values may offer important opportunities for the evolution of values that may be necessary for transformative change towards sustainability. The special issue includes contributions that contemplate particular concepts (e.g., care, stewardship, eudaimonia—human flourishing), applications (e.g., environmental assessment, environmental policy design), and the history of relevant scholarship in various intellectual traditions (e.g., ecological economics, human ecology, environmental education). Together with this suite of thought-provoking papers, we hope that the clarification we provide here facilitates a broad and productive interdisciplinary exchange to create and refine a reflective but powerful tool for sustainability and justice.

Robert B. Jackson, M. Saunois, Philippe Bousquet et al.

R B Jackson, M Saunois, P Bousquet, J G Canadell, B Poulter, A R Stavert, P Bergamaschi, Y Niwa, A Segers and A Tsuruta 1 Department of Earth System Science, Woods Institute for the Environment, and Precourt Institute for Energy, , Stanford University, Stanford, CA 94305-2210, United States of America 2 Laboratoire des Sciences du Climat et de l’Environnement, LSCE-IPSL (CEA-CNRS-UVSQ), Universit́e Paris-Saclay, 91191 Gif-sur-Yvette, France 3 Global Carbon Project, CSIRO Oceans and Atmosphere, Canberra, ACT 2601, Australia 4 NASA Goddard Space Flight Center, Biospheric Sciences Laboratory, Greenbelt, MD 20771, United States of America 5 Global Carbon Project, CSIRO Oceans and Atmosphere, Aspendale, VIC 3195, Australia 6 European Commission Joint Research Centre, 21027 Ispra (Va), Italy 7 Center for Global Environmental Research, National Institute for Environmental Studies, Tsukuba, Ibaraki 305-8506, Japan 8 Meteorological Research Institute, Tsukuba, Ibaraki 305-0052, Japan 9 TNO, Dept. of Climate Air & Sustainability, NL-3508-TA Utrecht, The Netherlands 10 Finnish Meteorological Institute, FI-00101 Helsinki, Finland

T. Gneiting

R. Tice, C. Austin, R. Kavlock et al.

Background: In 2008, the National Institute of Environmental Health Sciences/National Toxicology Program, the U.S. Environmental Protection Agency’s National Center for Computational Toxicology, and the National Human Genome Research Institute/National Institutes of Health Chemical Genomics Center entered into an agreement on “high throughput screening, toxicity pathway profiling, and biological interpretation of findings.” In 2010, the U.S. Food and Drug Administration (FDA) joined the collaboration, known informally as Tox21. Objectives: The Tox21 partners agreed to develop a vision and devise an implementation strategy to shift the assessment of chemical hazards away from traditional experimental animal toxicology studies to one based on target-specific, mechanism-based, biological observations largely obtained using in vitro assays. Discussion: Here we outline the efforts of the Tox21 partners up to the time the FDA joined the collaboration, describe the approaches taken to develop the science and technologies that are currently being used, assess the current status, and identify problems that could impede further progress as well as suggest approaches to address those problems. Conclusion: Tox21 faces some very difficult issues. However, we are making progress in integrating data from diverse technologies and end points into what is effectively a systems-biology approach to toxicology. This can be accomplished only when comprehensive knowledge is obtained with broad coverage of chemical and biological/toxicological space. The efforts thus far reflect the initial stage of an exceedingly complicated program, one that will likely take decades to fully achieve its goals. However, even at this stage, the information obtained has attracted the attention of the international scientific community, and we believe these efforts foretell the future of toxicology.

Erica G. Hepper, C. Hart, A. Gregg et al.

S. Collins, S. Carpenter, S. Swinton et al.

W. Michener, Matthew B. Jones

Ecology is evolving rapidly and increasingly changing into a more open, accountable, interdisciplinary, collaborative and data-intensive science. Discovering, integrating and analyzing massive amounts of heterogeneous data are central to ecology as researchers address complex questions at scales from the gene to the biosphere. Ecoinformatics offers tools and approaches for managing ecological data and transforming the data into information and knowledge. Here, we review the state-of-the-art and recent advances in ecoinformatics that can benefit ecologists and environmental scientists as they tackle increasingly challenging questions that require voluminous amounts of data across disciplines and scales of space and time. We also highlight the challenges and opportunities that remain.

Yener Ulus, Yener Ulus, Shaoyi Wang et al.

Wildfires are an integral component of Mediterranean ecosystems. The forest management practices implemented following such forest fires can significantly influence soil chemistry and metal dynamics. This study investigates the effects of different forest management strategies, including natural regeneration, grading (e.g., gradoni terrace making), and subsoiling with ripper on soil levels of major, trace, and heavy metals in a fire-affected forest in the southwestern part of Türkiye. Soil samples were collected 2.5 years after the containment of the wildfire and analyzed for selected metals (Fe, Ca, Al, Mn, Cr, Ni, Zn, Cu, Pb, Co, As, and Hg) concentrations. The findings indicated that subsoiling with a ripper resulted in elevated levels of multiple potentially toxic metals, including Cr (223.22 ± 60.47 mg/kg), Ni (150.54 ± 27.33 mg/kg), Zn (156.18 ± 66.14 mg/kg), and As (6.72 ± 1.30 mg/kg), compared to other treatments. These findings demonstrate that management interventions such as subsoiling with a ripper can significantly alter the distribution and concentration of trace metals. Future research integrating topographic variation and earlier sampling would further strengthen our understanding of post-fire metal dynamics.

Chuanbao Jing, Weiqi Zhou, Yan Lin et al.

Accurate and high-resolution urban activity information is essential for quantitatively estimating Sustainable Development Goal 11, but is unavailable. We examined the capacity and limitation of the Sustainable Development Science Satellite−1 nighttime light (SDGSAT−1 GLI NTL) data in capturing the spatial extent and intensity of human activity in two Chinese megacities using mobile phone data. Key findings: (1) Lit areas highly overlap with human activity areas but are smaller. Over 92.62% of lit areas are occupied by humans. Only a minor population (<2.15%) lived in unlit areas, despite these areas accounting for over 20.01% of human activity areas, as revealed by the panchromatic band. Additionally, the NTL better identifies activity areas related to young and middle-aged adults and working and residential populations than those related to older adults and tourists. (2) The intensity relationships between NTL data and population are highly spatially heterogeneous, with weak global but strong local correlations. When accounting for land use, correlation remarkably improved, with an R2 value of even 0.85. (3) Notably, the correlation increased from fine to coarse resolution. In summary, NTL data effectively capture the spatial extent and intensity of urban human activity, especially when considering land use, but its limitations should be noted.

Edoardo Zelli, Océane Legatelois, Laura Calvet-Mir et al.

The escalating human-driven pressures, such as coastal development, climate change, and overfishing, have led to habitat degradation and declines in marine resource abundance. These impacts pose significant threats to the livelihoods of coastal communities, particularly in the Mediterranean Sea. In situations where stock assessment data is scarce, fishers’ ecological knowledge (FEK) has proven valuable for understanding the ecological status of marine resources and their historical transformations. However, FEK can be affected by memory bias, reducing its reliability, a phenomenon known as the "shifting baseline syndrome” (SBS). This study investigates the presence of SBS within Barcelona’s fishing community by comparing fishers’ perceptions of abundance changes in six commercially significant marine species in Catalonia with data from scientific stock assessments. A mixed-methods approach was employed, incorporating semi-structured interviews and the analysis of fishery-independent biological data. The findings reveal no significant discrepancies between scientific assessments and fishers’ perceptions, suggesting that SBS is not present in this fishery. However, variations in how fishers perceive these changes were identified, pointing to potential future challenges. This research provides novel evidence of fishers’ ability to offer consistent quantitative insights into the status of commercial marine species within Barcelona’s fishing sector.

Xi Chen, Aiwen Wang, Yang Cao et al.

Abstract Activating ground-state molecular oxygen (O2) without added oxidants or external energy is a central challenge in aerobic catalysis because triplet O2 imposes spin and electron-transfer constraints. Herein, we report a high-rate, energy-neutral O2 activation platform that converts ambient air O2 directly to singlet oxygen (1O2) under room-temperature, bias-free conditions. By engineering atomically adjacent Co-Mo dual sites, Co-Mo d-d coupling and electron delocalization create a short-range electron transfer pathway that strengthens O2 adsorption, weaken the O-O bond via π* orbital population, and limit solvent-induced dissipation, thereby favoring selective 1O2 formation. These features enable the catalyst 1O2 productivity and pollutant degradation rates up to three orders of magnitude higher than previously reported air-fed O2 heterogeneous catalysts and comparable to oxidant-driven processes, yet without chemical inputs or energy bias. The catalyst is robust and versatile across diverse applications, including the degradation of organic contaminants, transformation of inorganic ions and antibacterial applications. This work establishes a new approach for sustainable O2 activation, pointing toward next-generation energy-neutral catalytic technologies.

Jian Ao, Lingjun Bu, Yangtao Wu et al.

Selective perchlorate (ClO4−) removal from surface water is a pressing need due to the stringent perchlorate drinking water limits around the world. Herein, we anchored N+–C–H hydrogen bond donors in hydrophobic cavities via interactions of cationic surfactants with montmorillonite to prioritize perchlorate bonding. The prepared adsorbent exhibited high selectivity over commonly occurring competing anions, including SO42−, NO3−, PO43−, HCO3−, and halide anions. High adsorption capacity, fast adsorption kinetics, and excellent regeneration ability (removal efficiency ≥ 80% after 20 cycles) were confirmed via batch experiments. Unconventional CH···O hydrogen bonding was verified as the primary driving force for perchlorate adsorption, which relies on the higher bond energy (∼80 kcal·mol−1) than conventional bonding. The removal efficiency of anions followed the order of the Hofmeister Series, demonstrating the importance of hydrophobic cavities formed by the tail groups of cationic surfactants. The hydrophobic cavities sheltered the C–H bonds from interacting with anions of low hydration energy (e.g., perchlorate). Furthermore, a fixed-bed column test demonstrated that about 2900 bed volumes of the feeding streams (∼500 μg·L−1) can be treated to ≤ 70 μg·L−1, with an enrichment factor of 10.3. Overall, on the basis of the hydrophobicity-induced hydrogen bonding mechanism, a series of low-cost adsorbents can be synthesized and applied for specific perchlorate removal.

Muhammad Afaq Hussain, Zhanlong Chen, Biswajeet Pradhan et al.

Study region: The National Highways 85 and 50, key routes of the China–Pakistan Economic Corridor (CPEC) in Balochistan, Pakistan. Study focus: Flooding is a natural disaster that is becoming increasingly frequent and severe. The National Highways 85 and 50 are vulnerable, necessitating accurate flood susceptibility mapping (FSM). Current machine learning (ML) models for FSM often suffer from low efficiency and overfitting. This study introduces an innovative hybrid FSM approach using four heterogeneous ensemble learning (HEL) techniques combined with three ML models: Random Forest (RF), Support Vector Machine (SVM), and Light Gradient Boosting Machine (LGBM). The proposed method was tested using satellite data from Sentinel-1, Sentinel-2, and Landsat-8, analyzing 1371 flood locations and 12 contributing variables. RF, variable importance factors (VIF), and information gain ratio (IGR) were applied to assess multicollinearity. The dataset was split (70:30) for model training and testing, with HEL-based models achieving superior performance over single ML models. New hydrological insights for the region: The stacking model yielded the highest AUROC (0.98), Kappa (0.82), accuracy (0.927), precision (0.963), Matthew’s correlation coefficient (0.820), and F1-score (0.950). HEL-based models proved more stable and resistant to overfitting. IGR analysis identified slope and distance from streams as key factors in FSM. The resulting flood-prone maps provide insights for disaster management adaptation strategies, demonstrating the broader applicability of the developed approach to enhance FSM accuracy and reliability.

Márkus Keller