Hasil untuk "Environmental sciences"

M. Sivapalan, H. Savenije, G. Blöschl

J. Callow, M. Callow

K. Suding

M. Jamshidian, E. Tehrany, Muhammad Imran et al.

Jiahe Peng, Xingzhu Chen, Wee‐Jun Ong et al.

Summary In 2011, a new and growing family of two-dimensional (2D) transition-metal carbides, nitrides, and carbonitrides (MXenes) was discovered. Benefitting from intriguing electronic and structural properties, MXenes have received increasing attention and emerged as next-generation nanomaterials for the exploration of environmentally friendly energy resources for catalysis in energy and environmental technologies. In this review, we systematically highlight the expeditious advances and achievements in design strategies, physico-chemical properties, and catalytic applications of 2D layered MXenes and their nanocomposites in environmental science and renewable energy. In addition, we unravel the structural, optical, and electronic properties of MXenes to elucidate their key roles of ameliorating the niche areas of photo(electro)catalytic hydrogen evolution reaction, oxygen evolution reaction, oxygen reduction reaction, carabon dioxide reduction reaction, nitrogen reduction reaction, and pollutant degradation. This review concludes with invigorating perspectives, outlooks, and formidable challenges in the future development of MXene-based materials for sustainable applications.

M. Arias-Estévez, E. López-Perı́ago, E. Martínez-Carballo et al.

F. Bergaya, B. Theng, G. Lagaly

F. Fischer

W. Turner, S. Spector, N. Gardiner et al.

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.

J. Fergusson

D. Kriebel, J. Tickner, P. Epstein et al.

Environmental scientists play a key role in society's responses to environmental problems, and many of the studies they perform are intended ultimately to affect policy. The precautionary principle, proposed as a new guideline in environmental decision making, has four central components: taking preventive action in the face of uncertainty; shifting the burden of proof to the proponents of an activity; exploring a wide range of alternatives to possibly harmful actions; and increasing public participation in decision making. In this paper we examine the implications of the precautionary principle for environmental scientists, whose work often involves studying highly complex, poorly understood systems, while at the same time facing conflicting pressures from those who seek to balance economic growth and environmental protection. In this complicated and contested terrain, it is useful to examine the methodologies of science and to consider ways that, without compromising integrity and objectivity, research can be more or less helpful to those who would act with precaution. We argue that a shift to more precautionary policies creates opportunities and challenges for scientists to think differently about the ways they conduct studies and communicate results. There is a complicated feedback relation between the discoveries of science and the setting of policy. While maintaining their objectivity and focus on understanding the world, environmental scientists should be aware of the policy uses of their work and of their social responsibility to do science that protects human health and the environment. The precautionary principle highlights this tight, challenging linkage between science and policy.

T. M. Crisp, E. Clegg, R. Cooper et al.

This report is an overview of the current state of the science relative to environmental endocrine disruption in humans, laboratory testing, and wildlife species. Background information is presented on the field of endocrinology, the nature of hormones, and potential sites for endocrine disruption, with specific examples of chemicals affecting these sites. An attempt is made to present objectively the issue of endocrine disruption, consider working hypotheses, offer opposing viewpoints, analyze the available information, and provide a reasonable assessment of the problem. Emphasis is placed on disruption of central nervous system--pituitary integration of hormonal and sexual behavioral activity, female and male reproductive system development and function, and thyroid function. In addition, the potential role of environmental endocrine disruption in the induction of breast, testicular, and prostate cancers, as well as endometriosis, is evaluated. The interrelationship of the endocrine and immune system is documented. With respect to endocrine-related ecological effects, specific case examples from the peer-reviewed literature of marine invertebrates and representatives of the five classes of vertebrates are presented and discussed. The report identifies some data gaps in our understanding of the environmental endocrine disruption issue and recommends a few research needs. Finally, the report states the U.S. Environmental Protection Agency Science Policy Council's interim position on endocrine disruption and lists some of the ongoing activities to deal with this matter.

Joaquin Armijo, Lucas Da Costa

We study environment-dependent clustering using the marked correlation function applied to Hu-Sawicki $f(R)$ modified gravity simulations. This gravity theory enriches the structure formation by enhancing gravity in a scale-dependent form. By employing a multi-scale cosmic structure finder algorithm, we define the cosmic environments divided in: nodes, filaments, walls and voids. We find a stronger impact of modified gravity in nodes and filament, which together dominate the information content by more than a factor of four relative to other environments. Combining environmental information further enhances the expected signal-to-noise ratio for CMASS- and DESI-like mock samples, particularly in configurations including filaments. Overall, marked correlation functions that incorporate environmental structure increase the information content by about a factor of two compared to standard density-based marks applied to the full galaxy sample. These results demonstrate the importance of environmental information, especially from filaments, in improving the constraining power of galaxy clustering tests of modified gravity.

Markus Dertwinkel-Kalt, Max R. P. Grossmann

When environmental regulations are unpopular, policymakers often attribute resistance to information frictions and poor communication. We test this idea in the context of a major climate policy: Germany's Heating Law of 2023, which mandates the phase-out of fossil fuel heating. Through a survey experiment with property owners, we examine whether providing comprehensive information about the regulation's costs, requirements, and timeline affects adoption decisions and policy support. Despite successfully increasing factual knowledge, information provision has no significant effect on intended technology adoption, policy support, or incentivized measures of climate preferences. Instead, pre-existing environmental preferences and demographic characteristics emerge as the key predictors of responses to the regulation. A feeling that existing systems still work well and cost considerations dominate fossil fuel users' stated reasons for non-adoption, while independence from fossil fuels and perceived contributions to the common good drive adoption among switchers. Our findings suggest that opposition to climate policy stems from fundamental preference heterogeneity rather than information frictions. This has important implications for optimal policy design, highlighting potential limits of information provision in overcoming resistance to environmental regulation. The results also speak to broader questions in political economy about the relationship between knowledge, preferences, and support for policy reform.

Riccardo Gianluigi Serio, Diego Giuliani, Maria Michela Dickson et al.

This study investigates the relationship between environmental sustainability policies and tourism flows across Italian provinces using a Spatial Durbin Error Model (SDEM) within a gravity framework. By incorporating both public and corporate environmental initiatives, the analysis highlights the direct and spatial spillover effects of sustainability measures on tourism demand. The findings indicate that corporate-led initiatives, such as ecocertifications and green investments, exert a stronger direct influence on tourism flows compared to public measures, underscoring the visibility and immediate impact of private sector actions. However, both types of initiatives generate significant positive spatial spillovers, suggesting that sustainability efforts extend beyond local boundaries. These results demonstrate the interconnected nature of regional tourism systems and emphasize the critical role of coordinated sustainability policies in fostering tourism growth while promoting environmental protection. By addressing the spatial interdependencies of tourism flows and sustainability practices, this research provides valuable insights for policymakers and stakeholders seeking to improve sustainable tourism development at regional and national levels.

Christo Kurisummoottil Thomas, Omar Hashash, Kimia Ehsani et al.

Aligning with the global mandates pushing towards advanced technologies with reduced resource consumption and environmental impacts, the sustainability of wireless networks becomes a significant concern in 6G systems. To address this concern, a native integration of sustainability into the operations of next-generation networks through novel designs and metrics is necessary. Nevertheless, existing wireless sustainability efforts remain limited to energy-efficient network designs which fail to capture the environmental impact of such systems. In this paper, a novel sustainability metric is proposed that captures emissions per bit, providing a rigorous measure of the environmental footprint associated with energy consumption in 6G networks. This metric also captures how energy, computing, and communication resource parameters influence the reduction of emissions per bit. Then, the problem of allocating the energy, computing and communication resources is posed as a multi-objective (MO) optimization problem. To solve the resulting non-convex problem, our framework leverages MO reinforcement learning (MORL) to maximize the novel sustainability metric alongside minimizing energy consumption and average delays in successfully delivering the data, all while adhering to constraints on energy resource capacity. The proposed MORL methodology computes a global policy that achieves a Pareto-optimal tradeoff among multiple objectives, thereby balancing environmental sustainability with network performance. Simulation results show that the proposed approach reduces the average emissions per bit by around 26% compared to state-of-the-art methods that do not explicitly integrate carbon emissions into their control objectives.

Liam Kearns

The integration of AI tools into medical applications has aimed to improve the efficiency of diagnosis. The emergence of large language models (LLMs), such as ChatGPT and Claude, has expanded this integration even further despite a concern for their environmental impact. Because of LLM versatility and ease of use through APIs, these larger models are often utilised even though smaller, custom models can be used instead. In this paper, LLMs and small discriminative models are integrated into a Mendix application to detect Covid-19 in chest X-rays. These discriminative models are also used to provide knowledge bases for LLMs to improve accuracy. This provides a benchmark study of 14 different model configurations for comparison of diagnostic accuracy and environmental impact. The findings indicated that while smaller models reduced the carbon footprint of the application, the output was biased towards a positive diagnosis and the output probabilities were lacking confidence. Meanwhile, restricting LLMs to only give probabilistic output caused poor performance in both accuracy and carbon footprint, demonstrating the risk of using LLMs as a universal AI solution. While using the smaller LLM GPT-4.1-Nano reduced the carbon footprint by 94.2% compared to the larger models, this was still disproportionate to the discriminative models; the most efficient solution was the Covid-Net model. Although it had a larger carbon footprint than other small models, its carbon footprint was 99.9% less than when using GPT-4.5-Preview, whilst achieving an accuracy of 95.5%, the highest of all models examined. This paper contributes to knowledge by comparing generative and discriminative models in Covid-19 detection as well as highlighting the environmental risk of using generative tools for classification tasks.

Lina Li, Rui Xia, Ming Dou et al.

Abstract In remote sensing research, vegetation dynamics are often used as indicators of ecosystem conditions, especially in semi-arid areas. The Wei River Basin (WRB) is a semi-arid region in western China prone to climate change and sensitive to the environment. Driven by climate change and human activities, particularly the recent reforestation projects, the environment and landscape of this region have undergone significant changes. However, the quantitative contributions of the driving factors to vegetation dynamics have not yet been well established. Here, we use a first-difference multiple regression model to separate and quantify the impacts of climate change and human activities on normalized difference vegetation index (NDVI) from 1998 to 2023. The results indicate that: (1) the growing season NDVI has significantly increased (slope = 0.006, R2 = 0.85) during the previous 26 years. (2) The main factor limiting the improvement of NDVI is precipitation, accounting for 67.6% of the area (p < 0.05). (3) During 1998–2023, climate factors accounted for 27.5% of NDVI changes in the Wei River Basin (WRB), with precipitation contributing 63.2% of the climatic influence, making it the primary positive driver of vegetation growth. Meanwhile, anthropogenic factors contributed 72.5%, with ecological restoration projects promoting greening and urban expansion causing degradation. These findings provide a basis for future assessments of vegetation management strategies and ecological restoration policies under climate and anthropogenic pressures in semi-arid basins.

Mona Kaamoush, Mohi El-Sayeh, Mohamed Y. Omar

Abstract The COVID-19 pandemic has significantly affected global society, influencing public health, economies, and the environment. This study examines the environmental impact of the pandemic on Alexandria Port, a key maritime hub in Egypt. By analyzing Automatic Identification System (AIS) data from the port area and multi-temporal satellite imagery from the Sentinel-5 Precursor (Sentinel-5p) satellite, the study investigates the changes in shipping activities and pollution emissions from 2018 to 2022. The aim was to assess the effect of the COVID-19 preventive measures on air quality in the vicinity of Alexandria Port, using satellite data provided by the European Space Agency’s geospatial processing engine. The study focused on several air quality parameters, including carbon monoxide (CO), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), ozone (O₃), and aerosol properties such as Aerosol Optical Depth (AOD) and Absorbing Aerosol Index (AAI). The results revealed varying degrees of reduction in air pollutants during the COVID-19 lockdown, with each pollutant showing a distinct change in levels. Specifically, the AAI and AOD reached their lowest mean values in 2020, recording -1.2 and 214 mol/m2, respectively, which represents a significant reduction. Likewise, NO₂ and SO₂ concentrations dropped to their lowest mean values of 0.000048 and 0.000125 mol/m2 during the lockdown period, reflecting a decrease of approximately 30% compared to pre-lockdown levels in 2018–2019. Notably, CO and O₃ levels showed considerable reductions as well, with CO decreasing to 0.015 mol/m2 and O₃ reaching 0.125 mol/m2, both of which represented decreases of around 10% and 15%, respectively, compared to their 2019 levels. However, following the resumption of full-capacity maritime operations at Alexandria Port, pollution levels returned to pre-lockdown values, indicating that the environmental benefits of the lockdown were short-term. The study concludes that the COVID-19 lockdown had a positive short-term impact on air quality, particularly in reducing harmful pollutants like NO₂, SO₂, and aerosols. However, these improvements were transient, with pollution levels rebounding to pre-lockdown levels once maritime activities resumed. This highlights the importance of continuous monitoring and enforcement of environmental regulations to ensure long-term improvements in air quality. Effective pollution management strategies must be implemented to sustain the environmental gains observed during the pandemic lockdown.