Hasil untuk "Environmental law"

H. Mansour, Sayed A. Ahmed, Hossam F. Nassar et al.

Abstract Background To maintain the synthesis simplicity and economic feasibility along with the environmental quality, adsorbents based on naturally occurring Egyptian and economic materials differ in their mineralogical composition will be prepared and used in the ongoing study to clean up environmental pollution. The study is aiming to focus on the preparation and the property change of zeolite and diatomite materials (functional groups and surface area) after modification even organically or biologically. Zeolite, diatomite and their modifiers with citric acid and Pseudomonas fluorescens bacteria were tested as adsorbent materials for heavy metal cations removal of El-Batts drain wastewater, Fayoum, Egypt, through the kinetic study. These (raw, organic and biological) modifiers were comparatively investigated regarding crystallinity (XRD), surface properties (SEM) and surface chemistry (EDX, FTIR). Batch experiments were conducted in response to pH, adsorbent type and contact time. Also, greenhouse experiments were accomplished using treated water to grow radish plants in polluted soils compiled from the site adjacent to El-Batts drain, to ensure the safety of crops grown with treated water. Results According to the optimum condition study, organic diatomite was most efficient compared to other modified materials prepared. Results of Zn. Equivalent (pollution index), heavy metals distribution, heavy metals concentricity in radish (roots/shoots) and the biological properties (enzymatic activities/pathogenic bacteria) in the soil receiving treated water, indicating soil health, and thus health of the plants produced, and their edibility, compared to soil receiving un treated water. Conclusions The results elucidated that the proposed natural and modified zeolite as well as diatomite materials have potential to expel heavy metals from low quality water in various circumstances and the successful adsorption abilities among the metal ions enhance the economic aspect of using it as cost effective adsorbents. Especially, organically diatomite treated with 0.2 molar citric acid which proved an exceptional adsorption capacity in treating El-Batts drain contaminated water at varying pH and contact time values.

Alex McBratney, Budiman Minasny, Amin Sharififar et al.

The concept of peak soil, the hypothetical point at which global soil productivity enters a sustained decline, has emerged as a metaphor for soil degradation. However, there is currently no globally accepted framework for assessing and communicating the status of soil degradation. In addition, the peak soil concept has not been critically analysed. This paper addresses this gap by critically evaluating the conceptual and scientific robustness of the peak soil metaphor, particularly in relation to soil capacity, condition, and socio-economic management. We contrast this metaphor with the soil security framework, which integrates five dimensions: capacity, condition, capital, connectivity, and codification. Drawing on a review of scientific literature and case studies, we argue that while peak soil serves as a powerful tool for raising public and policy awareness, it lacks scientific precision, particularly in assessing soil condition and capacity. The concept is ambiguous and overlooks the regenerative nature of soil systems. In contrast, the soil security assessment framework offers analytical rigour, enabling scientific evaluation while incorporating socio-economic and governance factors critical for sustainable soil management. We conclude by recommending enhancements to the peak soil concept, including suggestions for the development of clear, regionally adapted metrics. Furthermore, we propose integrating its communicative strengths with the multidimensional soil security concept to better inform policy and guide effective action.

Iryna Drobush, Liudmila Kornuta, Mykola Ukrainets

The establishment of an effective system of law and order, peace and security constitutes a fundamental responsibility of the international community. A fundamental element of this process pertains to the matter of sovereignty, which is a prerequisite for a state's participation as an equal participant in international relations. However, the equality of states in international communication gives rise to a variety of approaches to interpreting the meaning of this category, which complicates the task of regulating international law and order. In modern conditions, an effective way to ensure state sovereignty is to develop an economic security strategy, which plays a key role in ensuring the national security of such large states as the United States and China, as well as integration associations (the European Union), since the effectiveness of all other components of national security, in particular military security, largely depends on its state. The purpose of this study is to clarify the conceptual foundations of the mechanism for ensuring state sovereignty, the interconnection of key elements with economic development policy, European integration and public authority as a guarantee of the country's economic development. Methodology. The structural restructuring of the domestic economy and national security system during the formation of Ukrainian statehood, and eventually Ukraine's integration into European and Euro-Atlantic structures, is dynamic in nature and requires constant methodological reflection. The study was conducted on the principles of dialectical logic. The multifaceted, multifactorial and multifunctional nature of the phenomena of state sovereignty and economic security necessitates the use of a systematic, structural-functional and situational approach to their study. The work also employed methods of systematic, logical, institutional and retrospective analysis, as well as forecasting. The provisions and conclusions were developed using comparative analysis, conflict studies, rational choice theory, neo-institutionalism, geopolitics and geoeconomics. In international law, state sovereignty is not only a judgement on the aesthetics of the legal space, but also an arena in which there is a constant struggle between the ideals of justice and geopolitical realities. Ensuring Ukraine's state sovereignty as an independent, democratic, social and legal state is a complex, multifaceted and multi-level process that includes such key areas of activity as: guaranteeing the stability of the Ukrainian state; developing all elements of Ukraine's legal system; improving the efficiency of the organisation and functioning of the entire system of state power, not just individual branches and/or bodies of state power; strengthening the economic, cultural, social, political, environmental and security potential of the state; positioning Ukraine on the international and domestic arena as an active player capable of solving complex problems at the national and global levels and capable of predictable and reliable international co-operation; strengthening the democratic nature of the Ukrainian state and guaranteeing the foundations of Ukraine's constitutional order. National security is a prerequisite for economic development, while economic development contributes significantly to the protection of national security. A thorough examination of GDP dynamics reveals encouraging indications of recovery in the aftermath of the war-induced decline, underscoring the resilience of economic and public governance mechanisms. In order to ensure economic security, and thus national security and state sovereignty, it is vital that the state focuses on protecting against all types of significant threats, risks and challenges. It is imperative for Ukraine to exercise vigilance not only in regard to incidents that surpass expectations and bear grave consequences, but also in the prevention of threats associated with potential concealed conflicts. In the process of involving other states in ensuring its economic security, Ukraine should not focus on forcing its allies to adhere to its policy objectives. Sanctions imposed by the EU and individual states against Russia should focus on issues of international and regional security. The sustainability and effectiveness of sanctions will depend on their perceived legitimacy and awareness of the risk to international and regional law and order.

Shiyuan Luo, Chonghao Qiu, Runlong Yu et al.

Environmental modeling faces critical challenges in predicting ecosystem dynamics across unmonitored regions due to limited and geographically imbalanced observation data. This challenge is compounded by spatial heterogeneity, causing models to learn spurious patterns that fit only local data. Unlike conventional domain generalization, environmental modeling must preserve invariant physical relationships and temporal coherence during augmentation. In this paper, we introduce Generalizable Representation Enhancement via Auxiliary Transformations (GREAT), a framework that effectively augments available datasets to improve predictions in completely unseen regions. GREAT guides the augmentation process to ensure that the original governing processes can be recovered from the augmented data, and the inclusion of the augmented data leads to improved model generalization. Specifically, GREAT learns transformation functions at multiple layers of neural networks to augment both raw environmental features and temporal influence. They are refined through a novel bi-level training process that constrains augmented data to preserve key patterns of the original source data. We demonstrate GREAT's effectiveness on stream temperature prediction across six ecologically diverse watersheds in the eastern U.S., each containing multiple stream segments. Experimental results show that GREAT significantly outperforms existing methods in zero-shot scenarios. This work provides a practical solution for environmental applications where comprehensive monitoring is infeasible.

Han Yin, Yang Xiao, Rohan Kumar Das et al.

Audio generation systems now create very realistic soundscapes that can enhance media production, but also pose potential risks. Several studies have examined deepfakes in speech or singing voice. However, environmental sounds have different characteristics, which may make methods for detecting speech and singing deepfakes less effective for real-world sounds. In addition, existing datasets for environmental sound deepfake detection are limited in scale and audio types. To address this gap, we introduce EnvSDD, the first large-scale curated dataset designed for this task, consisting of 45.25 hours of real and 316.74 hours of fake audio. The test set includes diverse conditions to evaluate the generalizability, such as unseen generation models and unseen datasets. We also propose an audio deepfake detection system, based on a pre-trained audio foundation model. Results on EnvSDD show that our proposed system outperforms the state-of-the-art systems from speech and singing domains.

Nikolaos Papanikolaou, Doha Touhafi, Jurgen Vandendriessche et al.

Printed sensors represent a transformative advancement in sensor technology, utilizing innovative printing techniques to create flexible, cost-effective, and highly customizable sensing devices. Their versatility allows integration into numerous applications across diverse fields such as monitoring a wide range of environmental factors e.g. air and water quality, soil conditions, and atmospheric changes among others. These sensors demonstrate high sensitivity and accuracy in detecting pollutants, temperature variations, humidity levels, and other critical parameters essential for environmental assessment and protection.

Sasha Luccioni, Boris Gamazaychikov, Theo Alves da Costa et al.

In recent years, Artificial Intelligence (AI) models have grown in size and complexity, driving greater demand for computational power and natural resources. In parallel to this trend, transparency around the costs and impacts of these models has decreased, meaning that the users of these technologies have little to no information about their resource demands and subsequent impacts on the environment. Despite this dearth of adequate data, escalating demand for figures quantifying AI's environmental impacts has led to numerous instances of misinformation evolving from inaccurate or de-contextualized best-effort estimates of greenhouse gas emissions. In this article, we explore pervasive myths and misconceptions shaping public understanding of AI's environmental impacts, tracing their origins and their spread in both the media and scientific publications. We discuss the importance of data transparency in clarifying misconceptions and mitigating these harms, and conclude with a set of recommendations for how AI developers and policymakers can leverage this information to mitigate negative impacts in the future.

Peter J. Davies, Carl Tippler

The community value and resonate with some species and ecological systems more than others and therefore can be used to engender broader public support for nature positive outcomes. Yet many of these are not the scientifically-derived indicator species or ecological communities used by conservation scientists to determine and report on the pressures or condition of the environment nor by those implementing programs or actions needed to reverse biodiversity loss. Urban environments represent the intersection of two complex systems, human and natural, and yet this socio-ecological or coupled human-natural system nexus remains elusive within conservation law and policy and the dominant paradigm of grey infrastructure in cities. New approaches are needed to tether environmental policies and practices, such as nature based solutions, to the values and interests of individuals and their place. This article offers a novel framework through which nature-based solutions may achieve policy traction when tied to iconic species that the community value. The iconic species framework is founded on validity theory and the relevance of community-selected species in supporting nature positive outcomes. In parallel, the framework satisfies the data driven outcomes on which science and conservation policy relies upon and the use controls that direct nature-based rather than conventional engineering approaches. The iconic species framework is situated between the indicator species framework, whereby taxa are selected on the basis of their ecological sensitivity, and flagship species, that are largely emblematic. It links numerous ecological and environmental requirements of the species that are preferred by the community to develop nature-positive policy and practice outcomes.

Domenico Rossi, Antonio Pascale, Aurora Mascolo et al.

Road traffic noise is a severe environmental hazard, to which a growing number of dwellers are exposed in urban areas. The possibility to accurately assess traffic noise levels in a given area is thus, nowadays, quite important and, on many occasions, compelled by law. Such a procedure can be performed by measurements or by applying predictive Road Traffic Noise Models (RTNMs). Although the first approach is generally preferred, on-field measurement cannot always be easily conducted. RTNMs, on the contrary, use input information (amount of passing vehicles, category, speed, among others), usually collected by sensors, to provide an estimation of noise levels in a specific area. Several RTNMs have been implemented by different national institutions, adapting them to the local traffic conditions. However, the employment of RTNMs proves challenging due to both the lack of input data and the inherent complexity of the models (often composed of a Noise Emission Model–NEM and a sound propagation model). Therefore, this work aims to propose a methodology that allows an easy application of RTNMs, despite the availability of measured data for calibration. Four different NEMs were coupled with a sound propagation model, allowing the computation of equivalent continuous sound pressure levels on a dataset (composed of traffic flows, speeds, and source–receiver distance) randomly generated. Then, a Multilinear Regressive technique was applied to obtain manageable formulas for the models’ application. The goodness of the procedure was evaluated on a set of long-term traffic and noise data collected in a French site through several sensors, such as sound level meters, car counters, and speed detectors. Results show that the estimations provided by formulas coming from the Multilinear Regressions are quite close to field measurements (MAE between 1.60 and 2.64 dB(A)), confirming that the resulting models could be employed to forecast noise levels by integrating them into a network of traffic sensors.

Priya, Sharma Kavita

Environmental, Social, and Governance, or ESG, is a crucial intangible assessing element for investorswho are socially conscious and responsible. They are taking into account a company’s contributions tothe environment, society, and law compliance in addition to traditional financial considerations including returns, risk, cash flow, and profitability. As an option for ESG investment, mutual funds offered with an ESG focus serves as the best alternative. This current study attempts to examine the growth of Indian ESG mutual funds relative to selective developed, developing, and underdeveloped economies all around the globe. This Study finds the Indian Mutual fund industry has grown in the lastcouple of years, Yet the country is still in the infancy stage with respect to the number of ESG funds incomparison to developed countries. However, in terms of Returns Indian ESG mutual funds are performing admirably. Moreover, the research makes it abundantly clear that India has to do more to educate investors about the sustainability of their investments, as this will eventually encourage ESG investments.

Shijun Zhang, Qian Wu, M. Jahanzeb Butt et al.

Literature on integrated coastal zonal management (ICZM) for coastal sustainability from a legal perspective provided significant measures. Recently, sustainable development goals (SDGs) have become a focus in ICZM literature, which establishes coastal goals and connects these goals with other goals. Although integrating coastal goals into ICZM under international law challenges the existing models presented in the literature, the comprehensive literature review (CLR) methodology is appropriate for observing the current literature and provides a way-forward for coastal goals. Therefore, through this research, a CLR on ICZM literature is conducted to observe how far SDGs are integrated for coastal sustainability. The CLR identified that coastal city governance is a pertinent part of ICZM, and the coastal goals are devised in the form of environmental goals of SDG – 14 (life below water). This CLR examines the anthropogenic connections of waste, sanitation, and emissions management and urban planning with coastal ecosystems under the ICZM system. For such purposes, governance tools of science-policy integration under international law and policy for sustainable development are utilized to form an obligatory framework. The CLR further provided coordination, adaptivity, monitoring, and capacity-building tools, which were utilized thoroughly throughout the literature and can be incorporated with the SDGs in a multilevel governance framework of ICZM. Throughout the study, international law formulating SDGs is pivotal to be transplanted successfully into the ICZM governance processes.

Gabrielle dos Santos Ilha, Marianne Boix, Jürgen Knödlseder et al.

Astronomical observatories have been identified as substantial contributors to the carbon footprint of astrophysical research. Being part of the collaboration that currently develops the Medium-Sized Telescope (MST) of the Cherenkov Telescope Array, a ground-based observatory for very-high-energy gamma rays that will comprise 64 telescopes deployed on two sites, we assessed the environmental impacts of one MST on the Northern site by means of a Life Cycle Assessment. We identified resource use and climate change as the most significant impacts, being driven by telescope manufacturing and energy consumption during operations. We estimate life cycle greenhouse gas emissions of 2,660 +/- 274 tCO2 equivalent for the telescope, 44% of which arise from construction, 1% from on-site assembly and commissioning, and 55% from operations over 30 years. Environmental impacts can be reduced by using renewable energies during construction and operations, use of less electronic components and metal casting, and use of recycled materials. We propose complementing project requirements with environmental budgets as an effective measure for impact management and reductions.

Bohao Lu, Zhiqing Wei, Huici Wu et al.

Utilizing widely distributed communication nodes to achieve environmental reconstruction is one of the significant scenarios for Integrated Sensing and Communication (ISAC) and a crucial technology for 6G. To achieve this crucial functionality, we propose a deep learning based multi-node ISAC 4D environment reconstruction method with Uplink-Downlink (UL-DL) cooperation, which employs virtual aperture technology, Constant False Alarm Rate (CFAR) detection, and Mutiple Signal Classification (MUSIC) algorithm to maximize the sensing capabilities of single sensing nodes. Simultaneously, it introduces a cooperative environmental reconstruction scheme involving multi-node cooperation and Uplink-Downlink (UL-DL) cooperation to overcome the limitations of single-node sensing caused by occlusion and limited viewpoints. Furthermore, the deep learning models Attention Gate Gridding Residual Neural Network (AGGRNN) and Multi-View Sensing Fusion Network (MVSFNet) to enhance the density of sparsely reconstructed point clouds are proposed, aiming to restore as many original environmental details as possible while preserving the spatial structure of the point cloud. Additionally, we propose a multi-level fusion strategy incorporating both data-level and feature-level fusion to fully leverage the advantages of multi-node cooperation. Experimental results demonstrate that the environmental reconstruction performance of this method significantly outperforms other comparative method, enabling high-precision environmental reconstruction using ISAC system.

Matthew Speers, David Randell, Jonathan Angus Tawn et al.

Extreme value analysis (EVA) uses data to estimate long-term extreme environmental conditions for variables such as significant wave height and period, for the design of marine structures. Together with models for the short-term evolution of the ocean environment and for wave-structure interaction, EVA provides a basis for full probabilistic design analysis. Alternatively, environmental contours provide an approximate approach to estimating structural integrity, without requiring structural knowledge. These contour methods also exploit statistical models, including EVA, but avoid the need for structural modelling by making what are believed to be conservative assumptions about the shape of the structural failure boundary in the environment space. These assumptions, however, may not always be appropriate, or may lead to unnecessary wasted resources from over design. We demonstrate a methodology for efficient fully probabilistic analysis of structural failure. From this, we estimate the joint conditional probability density of the environment (CDE), given the occurrence of an extreme structural response. We use CDE as a diagnostic to highlight the deficiencies of environmental contour methods for design; none of the IFORM environmental contours considered characterise CDE well for three example structures.

Wei Jia, Roman Jandarov

This manuscript presents a novel Bayesian varying coefficient quantile regression (BVCQR) model designed to assess the longitudinal effects of chemical exposure mixtures on children's neurodevelopment. Recognizing the complexity and high-dimensionality of environmental exposures, the proposed approach addresses critical gaps in existing research by offering a method that can manage the sparsity of data and provide interpretable results. The proposed BVCQR model estimates the effects of mixtures on neurodevelopmental outcomes at specific ages, leveraging a horseshoe prior for sparsity and utilizing a Bayesian method for uncertainty quantification. Our simulations demonstrate the model's robustness and effectiveness in handling high-dimensional data, offering significant improvements over traditional models. The model's application to the Health Outcomes and Measures of the Environment (HOME) Study further illustrates its utility in identifying significant chemical exposures affecting children's growth and development. The findings underscore the potential of BVCQR in environmental health research, providing a sophisticated tool for analyzing the longitudinal impact of complex chemical mixtures, with implications for future studies aimed at understanding and mitigating environmental risks to child health.

Nicoletta D'Angelo, Alessandro Albano, Andrea Gilardi et al.

In 2023, Sicily faced an escalating issue of uncontrolled fires, necessitating a thorough investigation into their spatio-temporal dynamics. Our study addresses this concern through point process theory. Each wildfire is treated as a unique point in both space and time, allowing us to assess the influence of environmental and anthropogenic factors by fitting a spatio-temporal separable Poisson point process model, with a particular focus on the role of land usage. First, a spatial log-linear Poisson model is applied to investigate the influence of land use types on wildfire distribution, controlling for other environmental covariates. The results highlight the significant effect of human activities, altitude, and slope on spatial fire occurrence. Then, a Generalized Additive Model with Poisson-distributed response further explores the temporal dynamics of wildfire occurrences, confirming their dependence on various environmental variables, including the maximum daily temperature, wind speed, surface pressure, and total precipitation.

Eugenio Giannelli, Stacey Law

Let $p\ge 5$ be a prime and let $P$ be a Sylow $p$-subgroup of a finite symmetric group. To every irreducible character of $P$ we associate a collection of labelled, complete $p$-ary trees. The main results of this article describe Sylow branching coefficients for symmetric groups for all irreducible characters of $P$ in terms of some combinatorial properties of these trees, extending previous work on the linear characters of $P$.

Adriana Di Trana, Emilio Sabia, Ambra Rita Di Rosa et al.

Traditional agri-food products (TAPs) are closely linked to the peculiarities of the territory of origin and are strategic tools for preserving culture and traditions; nutritional and organoleptic peculiarities also differentiate these products on the market. One such product is Caciocavallo Podolico Lucano (CPL), a stretched curd cheese made exclusively from raw milk from Podolian cows, reared under extensive conditions. The objective of this study was to characterise CPL and evaluate the effects of ripening (6 vs. 12 months) on the quality and organoleptic properties, using the technological “artificial senses” platform, of CPL produced and sold in the region of Basilicata, Italy. Additionally, this study represents the first analysis of cheese-related digital communication and trends online. The study found no significant differences between 6-month- and 12-month-ripened cheese, except for a slight increase in cholesterol levels in the latter. CPL aged for 6 and 12 months is naturally lactose-free, rich in bioactive components, and high in vitamin A and antioxidants and has a low PUFA-n6/n3 ratio. The “artificial sensory profile” was able to discriminate the organoleptic fingerprints of 6-month- and 12-month-ripened cheese. The application of a socio-semiotic methodology enabled us to identify the best drivers to create effective communication for this product. The researchers recommend focusing on creating a certification mark linked to the territory for future protection.

Bogdana Rakova, Roel Dobbe

This paper reframes algorithmic systems as intimately connected to and part of social and ecological systems, and proposes a first-of-its-kind methodology for environmental justice-oriented algorithmic audits. How do we consider environmental and climate justice dimensions of the way algorithmic systems are designed, developed, and deployed? These impacts are inherently emergent and can only be understood and addressed at the level of relations between an algorithmic system and the social (including institutional) and ecological components of the broader ecosystem it operates in. As a result, we claim that in absence of an integral ontology for algorithmic systems, we cannot do justice to the emergent nature of broader environmental impacts of algorithmic systems and their underlying computational infrastructure. We propose to define algorithmic systems as ontologically indistinct from Social-Ecological-Technological Systems (SETS), framing emergent implications as couplings between social, ecological, and technical components of the broader fabric in which algorithms are integrated and operate. We draw upon prior work on SETS analysis as well as emerging themes in the literature and practices of Environmental Justice (EJ) to conceptualize and assess algorithmic impact. We then offer three policy recommendations to help establish a SETS-based EJ approach to algorithmic audits: (1) broaden the inputs and open-up the outputs of an audit, (2) enable meaningful access to redress, and (3) guarantee a place-based and relational approach to the process of evaluating impact. We operationalize these as a qualitative framework of questions for a spectrum of stakeholders. Doing so, this article aims to inspire stronger and more frequent interactions across policymakers, researchers, practitioners, civil society, and grassroots communities.

Rian Andrian Andrian, Aldi Yasin, Muhammad Raihan Ijlal Hanan et al.

Persons with disabilities have the same rights and responsibilities as citizens. Based on the 1945 Constitution Republic of Indonesia, article 31 paragraph 1 and Law Number 20 of 2003 concerning the National Education System, it can be concluded that the state provides full guarantees for Children with Special Needs to obtain quality education services. Many of the problems of inclusive learning that occurred during the Covid-19 pandemic, ranging from the unpreparedness of the school to various problems with environmental factors so that innovation was needed to overcome these problems. In this article, the author develops a prototype of a digital-based learning platform as a solution to facilitate inclusive learning for children with special needs.