Hasil untuk "Environmental law"

A. Espert, F. Vilaplana, S. Karlsson

J. F. Medeiros, J. Ribeiro, M. Cortimiglia

J. Jensen, N. Berg

Xiaoyan Meng, Xianchun Tan, Yi Wang et al.

Abstract Residents’ participation in classification and recycling of urban household solid waste (HSW) is a critical factor for the success of municipal solid waste management. The aim of this study is to investigate the decision-making mechanism of residents’ HSW disposal behaviors by merging the theory of planned behavior and the Attitude-Behavior-Condition theory. In this study, based on the survey data of 709 residents in Suzhou, China and structural equation modeling method, the main factors that affect residents’ HSW disposal behaviors and their degree of influence were analyzed, followed by discussion on decision-making mechanisms. The findings show that residents’ behavioral selection has been significantly related to four intrinsic subjective factors and seven external objective factors, and the combined effect of the latter ones is nearly twice of that of the former ones. Moreover, the convenient of environmental facilities and services are most effective at promoting residents’ participation in HSW classification and recycling. Specifically, the observed variables of publicity and education, accessibility to recycling facilities, accessibility to classification facilities, willingness to participation of classification and residents' environmental awareness are the five most significant factors. The impact of laws and regulations is not significant; however, this may be because that there was no mandatory laws, regulations and incentive mechanisms on HSW classification and recycling in Suzhou in this period, and there is still a big gap and room for improvement in this aspect in mainland China. Finally, the study put forward relevant policy recommendations for the comprehensive management of urban HSW classification and recycling.

A. Perrucci, A. Perrucci, A. Magri et al.

Inadequately cleaned transport vehicles can act as reservoirs for pathogens jeopardizing pigs’ health status. Although effective cleaning and disinfection (C&D) of live-pig transport trucks is required by law, there is still no universally accepted protocol for C&D of trucks. This study aimed to evaluate the effectiveness of a standardized hygiene protocol under field conditions and to provide practical guidance, thereby fostering harmonized hygiene procedures. Starting from current legislation for barn C&D, and refining it through available literature, a detailed standardized protocol for truck hygiene was developed. Each vehicle was divided into three functional sections: transport unit, boot-storage compartment, and driver’s cabin. The protocol was applied to 15 trial trucks transporting live pigs and compared with 23 market trucks, which served as controls. C&D was assessed through visual inspection, adenosine triphosphate (ATP) testing, and microbiological analyses of environmental samples, including total viable count (TVC) on all trucks. Samples were collected at the three functional sections of the trucks. Trial trucks achieved significantly higher visual scores than control trucks (82.10 ± 9.72 vs. 72.20 ± 7.48; p = 0.0018). The 80% cleanliness threshold required for ATP testing was achieved by nearly half of the trial trucks (46.7%) but by only one control truck (4.3%) (p = 0.0065). Microbiological results further highlighted the protocol effectiveness: all cleaned trial trucks showed low mean TVC values (<10 CFU/cm2 or a 3 log₁₀ CFU/cm2 reduction, as acceptable threshold). In contrast, only 33.3% of driver’s cabin swabs and 50.0% of cargo-area swabs from control trucks met this threshold, while none of the boot storage samples did (p = 0.0254). Bacteriological testing revealed MRSA in 100% of trial trucks before C&D, but in 0% after cleaning (p = 0.0079). Overall, the standardized protocol markedly improved the sanitary status of pig-transport vehicles. The combined use of different assessment methods proved valuable for identifying critical control points, particularly the boot-storage area, the most contaminated site. The protocol also showed strong potential for eliminating MRSA from trucks, contributing to reduce antimicrobial resistance transmission. These findings provide a replicable and field-ready model for improving C&D compliance and biosecurity across the swine transport sector.

Adeshola Akintobi, Adeshola Akintobi, Sabine O’Hara et al.

IntroductionThis article explores clinical law programs of Historically Black Colleges and Universities (HBCU) and their role in advancing equitable development in urban communities which have been impacted by disinvestment, redlining, and gentrification. Building on the legacy of the Great Migration and subsequent urban decline, the communities where the six HBCU law schools, accredited by the American Bar Association (ABA), are located have experienced a range of development challenges. They are Orlando, Florida, Durham, North Carolina, Washington, D. C., Houston, Texas, and Baton Rouge, Louisiana. The study examines whether these law schools deliver what their stated priorities promise, namely, to meaningfully contribute to the equitable development goals of the communities where they are located.MethodsUsing a systematic review of publicly available documents as well as case study materials from the five metro areas, the study reveals a strong alignment between the clinical work offered by the law schools in our sample and the development needs of the metropolitan areas where they are located.ResultsThese alignments are particularly evident in the areas of affordable housing, youth advocacy, immigration, and economic justice.DiscussionWhile the study is limited by its reliance on publicly available data, the findings suggest that HBCU law schools and their clinical programs provide critical contributions to the civic infrastructure of US metropolitan areas seeking to achieve equitable urban revitalization. The findings also identify opportunities for further research, to investigate the dynamics between law school clinical programs and equitable community development in more depth.

Tomi Setiawan, Rita Myrna, Neneng Weti Isnawati et al.

Abstract This paper explains the ecological crisis in rural coastal areas by reconstructing an ecological governance model that integrates environmental dynamics variables, with a focus on Pangandaran, West Java, a representative region of Indonesia’s coastal challenges, including overfishing and unsustainable practices. This study examines the impact of the following factors: environmental dynamics, including economic and financial, physical infrastructure, social, spiritual, and environmental management, on sustainable development, with ecological governance serving as a mediator. This research employs quantitative methods, utilizing Partial Least Squares-Structural Equation Modeling (PLS-SEM) tools, on survey data collected from 178 villagers in Pananjung, Wonoharjo, Babakan, and Pangandaran villages. The study shows a significant positive influence of economic-financial (0.497) and social (1.558) environments on sustainable development. Ecological governance also has a positive impact on sustainable development (0.205), while environmental management has a more negligible positive effect on ecological governance (0.078). The direct impact of the physical infrastructure environment on sustainable development is very minimal (0.056). Particularly, the natural and spiritual environment variables did not show a significant effect. The model emphasizes the importance of synergizing sustainable infrastructure development with community awareness, advocating for multi-actor collaboration among government, the private sector, academia, and local villagers to create effective cross-sectoral policies that address local environmental dynamics. Despite the limitations of the sample size and cross-sectional design, this study makes a theoretical contribution to understanding ecological governance. It offers practical implications for integrative sustainable development planning in coastal areas. All variables showed acceptable reliability and discriminant validity. The findings highlight the need for governance models to prioritize locally relevant environmental dynamics.

Li Wang, Ruyi Zhou, Zhenming Shen et al.

This study explores the relationship between forest structure and human comfort in local forested green spaces. To enhance the model’s applicability to forest settings, we optimized its parameters based on Meteorological and Environmental Comfort (MEC) considerations, resulting in the Forest Meteorological Environmental Comfort Index (F-MECI). Our research site was the Tianmu Mountain Nature Reserve, Lin’an District, Zhejiang Province, China. We selected eight sample plots and one control site, measuring meteorological parameters (air temperature, relative humidity, wind speed, light, noise, O3, PM2.5, and PM10) and forest stand structural parameters (tree height, diameter at breast height, cover plant ratio, stand density, canopy diameter width, and clear bole height). Using the golden section method and Fechner’s law, we calculated the F-MECI values for the control points and sample plots, reclassified human-comfort levels, and conducted an in-depth analysis of disparities in comfort across the six forest types and control points. F-MECI varied significantly between forests and open areas and among different forest types. Natural forest notably enhanced human comfort, with mixed broadleaf–conifer forests offering optimal conditions for cooling and humidification, particularly during summer. Correlations between forest-stand structure and human comfort revealed negative associations with parameters such as tree height, canopy diameter width, and the cover plant ratio, with cover plant ratio and canopy diameter width exerting the strongest influence on F-MECI. These findings can inform forest management decisions and activities, including forest stand selection, tree species allocation in recreational base construction, and enhancement of small-scale forest spaces to create comfortable environments by adjusting stand structure. This study aimed to develop forest spaces that seamlessly integrate climatic comfort and forest services.

Shubham Kejriwal, Enrico Barausse, Alvin J. K. Chua

The upcoming Laser Interferometer Space Antenna (LISA) will detect up to thousands of extreme-mass-ratio inspirals (EMRIs). These sources will spend $\sim 10^5$ cycles in band, and are therefore sensitive to tiny changes in the general-relativistic dynamics, potentially induced by astrophysical environments or modifications of general relativity (GR). Previous studies have shown that these effects can be highly degenerate for a single source. However, it may be possible to distinguish between them at the population level, because environmental effects should impact only a fraction of the sources, while modifications of GR would affect all. We therefore introduce a population-based hierarchical framework to disentangle the two hypotheses. Using simulated EMRI populations, we perform tests of the null vacuum-GR hypothesis and two alternative beyond-vacuum-GR hypotheses, namely migration torques (environmental effects) and time-varying $G$ (modified gravity). We find that with as few as $\approx 20$ detected sources, our framework can statistically distinguish between these three hypotheses, and even indicate if both environmental and modified gravity effects are simultaneously present in the population. Our framework can be applied to other models of beyond-vacuum-GR effects available in the literature.

Xi Long, Paul P. Plucinsky, Terrance J. Gaetz et al.

We present results from the Chandra X-ray Observatory Large Project (878 ks in 28 observations) of the Large Magellanic Cloud supernova remnant N132D. We measure the expansion of the forward shock in the bright southern rim to be $0.\!^{\prime\prime}10 \pm 0.\!^{\prime\prime}02$ over the $\sim14.5$ yr baseline, which corresponds to a velocity of $1620\pm400~\mathrm{km\,s^{-1}}$ after accounting for several instrumental effects. We measure an expansion of $0.\!^{\prime\prime}23 \pm 0.\!^{\prime\prime}02$ and a shock velocity of $3840\pm260~\mathrm{km\,s^{-1}}$ for two features in an apparent blowout region in the northeast. The emission-measure-weighted average temperature inferred from X-ray spectral fits to regions in the southern rim is $0.95\pm0.17$ keV, consistent with the electron temperature implied by the shock velocity after accounting for Coulomb equilibration and adiabatic expansion. In contrast, the emission-measure-weighted average temperature for the northeast region is $0.77\pm0.04$ keV, which is significantly lower than the value inferred from the shock velocity. We fit 1-D evolutionary models for the shock in the southern rim and northeast region, using the measured radius and propagation velocity into a constant density and power-law profile circumstellar medium. We find good agreement with the age of $\sim2500$ years derived from optical expansion measurements for explosion energies of $1.5-3.0 \times 10^{51}\,\mathrm{erg}$, ejecta masses of $2-6 \,\mathrm{M_{\odot}}$ and ambient medium densities of $\sim0.33-0.66$ $\mathrm{amu~cm}^{-3}$ in the south and $\sim0.01-0.02$ $\mathrm{amu~cm}^{-3}$ in the northeast assuming a constant density medium. These results are consistent with previous studies that suggested the progenitor of N132D was an energetic supernova that exploded into a pre-existing cavity.

Daniele Pannone, Danilo Avola

This paper introduces a deep learning framework for generating point clouds from WiFi Channel State Information data. We employ a two-stage autoencoder approach: a PointNet autoencoder with convolutional layers for point cloud generation, and a Convolutional Neural Network autoencoder to map CSI data to a matching latent space. By aligning these latent spaces, our method enables accurate environmental point cloud reconstruction from WiFi data. Experimental results validate the effectiveness of our approach, highlighting its potential for wireless sensing and environmental mapping applications.

Heechan Yuk, Xinyu Dai, Marko Mićić

We present the multi-wavelength and environmental properties of 37 variability-selected active galactic nuclei (AGNs), including 30 low luminosity AGNs (LLAGNs), using a high cadence time-domain survey (ASAS-SN) from a spectroscopic sample of 1218 nearby bright galaxies. We find that high-cadence time-domain surveys uniquely select LLAGNs that do not necessarily satisfy other AGN selection methods, such as X-ray, mid-IR, or BPT methods. In our sample, 3% of them pass the mid-infrared color based AGN selection, 18% pass the X-ray luminosity based AGN selection, and 60% pass the BPT selection. This result is supported by two other LLAGN samples from high-cadence time-domain surveys of TESS and PTF, suggesting that the variability selection method from well-sampled light curves can find AGNs that may not be discovered otherwise. These AGNs can have moderate to small amplitudes of variability from the accretion disk, but, of many of them, with no strong corona, emission lines from the central engine, or accretion power to dominate the mid-IR emission. The X-ray spectra of a sub-sample of bright sources are consistent with a power law model. Upon inspecting the environments of our sample, we find that LLAGNs are more common in denser environments of galaxy clusters in contrast with the trend established in the literature for luminous AGNs at low redshifts, which is broadly consistent with our analysis result for luminous AGNs limited by a smaller sample size. This contrast in environmental properties between LLAGN and luminous AGNs suggests that LLAGNs may have different trigger mechanisms.

Łukasz Dębowski

We inspect the deductive connection between the neural scaling law and Zipf's law -- two statements discussed in machine learning and quantitative linguistics. The neural scaling law describes how the cross entropy rate of a foundation model -- such as a large language model -- changes with respect to the amount of training tokens, parameters, and compute. By contrast, Zipf's law posits that the distribution of tokens exhibits a power law tail. Whereas similar claims have been made in more specific settings, we show that the neural scaling law is a consequence of Zipf's law under certain broad assumptions that we reveal systematically. The derivation steps are as follows: We derive Heaps' law on the vocabulary growth from Zipf's law, Hilberg's hypothesis on the entropy scaling from Heaps' law, and the neural scaling from Hilberg's hypothesis. We illustrate these inference steps by a toy example of the Santa Fe process that satisfies all the four statistical laws.

Min-Kyu Kim, Tae-An Yoo, Ji-Bum Chung

Generative AI is spreading rapidly, creating significant social and economic value while also raising concerns about its high energy use and environmental sustainability. While prior studies have predominantly focused on the energy-intensive nature of the training phase, the cumulative environmental footprint generated during large-scale service operations, particularly in the inference phase, has received comparatively less attention. To bridge this gap this study conducts a scoping review of methodologies and research trends in AI carbon footprint assessment. We analyze the classification and standardization status of existing AI carbon measurement tools and methodologies, and comparatively examine the environmental impacts arising from both training and inference stages. In addition, we identify how multidimensional factors such as model size, prompt complexity, serving environments, and system boundary definitions shape the resulting carbon footprint. Our review reveals critical limitations in current AI carbon accounting practices, including methodological inconsistencies, technology-specific biases, and insufficient attention to end-to-end system perspectives. Building on these insights, we propose future research and governance directions: (1) establishing standardized and transparent universal measurement protocols, (2) designing dynamic evaluation frameworks that incorporate user behavior, (3) developing life-cycle monitoring systems that encompass embodied emissions, and (4) advancing multidimensional sustainability assessment framework that balance model performance with environmental efficiency. This paper provides a foundation for interdisciplinary dialogue aimed at building a sustainable AI ecosystem and offers a baseline guideline for researchers seeking to understand the environmental implications of AI across technical, social, and operational dimensions.

Efrain Mendez-Flores, Agaton Pourshahidi, Magnus Egerstedt

Environmental monitoring is used to characterize the health and relationship between organisms and their environments. In forest ecosystems, robots can serve as platforms to acquire such data, even in hard-to-reach places where wire-traversing platforms are particularly promising due to their efficient displacement. This paper presents the RaccoonBot, which is a novel autonomous wire-traversing robot for persistent environmental monitoring, featuring a fail-safe mechanical design with a self-locking mechanism in case of electrical shortage. The robot also features energy-aware mobility through a novel Solar tracking algorithm, that allows the robot to find a position on the wire to have direct contact with solar power to increase the energy harvested. Experimental results validate the electro-mechanical features of the RaccoonBot, showing that it is able to handle wire perturbations, different inclinations, and achieving energy autonomy.

Seth D. Seidel, Nathan P. Arnold, Brandon Wolding

Our goal in this study is to characterize the relationship between lower tropospheric environmental humidity and convective mass flux in the tropics. To do so, we have created gridded convective mass flux datasets from five global storm-resolving models (GSRMs). We have three principal findings. First, in humid environments, mass flux increases with height from the surface through the depth of the lower free troposphere, forming a ``deep-inflow". In dry environments, mass flux does not increase with height in the lower free troposphere. Second, mid-tropospheric mass flux increases nonlinearly with increasing lower tropospheric humidity, resembling a widely reported pickup in tropical precipitation. Third, increased lower tropospheric humidity is associated with reduced deep convective updraft buoyancy. To interpret these findings, we employ a simple three-equation parcel model with stochastic entrainment. The parcel model suggests that the response of convective mass flux to lower tropospheric humidity is governed by two effects: (1) survival, in which a greater share of entraining parcels ascend rather than detrain with greater humidity; and (2) dilution, in which the average entrainment rate among surviving parcels increases with environmental humidity. Together, survival and dilution account for the three mass flux responses to humidity.

M. Talaei, B. Moghaddam, M. Pishvaee et al.

F.M. Galassi, L. Ingaliso, V. Papa et al.

Recognized since antiquity, gout is still a relevant pathology with rising prevalence and incidence. This study aims to assess the reference accuracy in journal articles mentioning the early use of the word ‘gout’. Specifically, it investigates whether the term was indeed coined in the 13th century by the Dominican monk Randolphus of Bocking, as widely believed. Several historical sources in their original Latin were consulted to test the hypothesis of literary mentions predating Randolphus of Bocking’s description. At the same time, biomedical articles spanning the last two decades were perused using specific keywords in different combinations to determine the accuracy level of references related to the earliest use of the word ‘gout’. The results showed that several biomedical publications wrongly ascribed the origin of the word ‘gout’ to Randolphus of Bocking. Indeed, various texts predate his mention by many years. In particular, gutta, the Latin word used to indicate a host of rheumatological conditions including gout, is recorded as early as the 10th century in a biography dedicated to the martyred nun Saint Wiborada of St. Gall. Written by Swiss monks between AD 960 and 963, this text should be regarded as containing the earliest known adoption of the word. For this reason, scholars should now avoid quoting Randolph of Bocking’s description as the first use of the word ‘gout’ in Western literature.

Rafael E. Acevedo P.

Chun Kit Law, Savannah Yan Tsing Lai, Joseph Hung Kit Lai

Light pollution has become an increasingly knotty environmental management problem, but little has been done to review and compare light pollution controls across the world. To address this research gap, a comparative review study has been undertaken. Among the light pollution laws of the most light-polluted regions, those pertaining to Shanghai, New York, Hong Kong, Seoul, London and Valletta were examined. We systematically evaluate the impact of legal systems, regulatory approaches and control parameters on light pollution regulation. The findings reveal that civil law jurisdictions, such as Shanghai and Seoul, typically adopt dedicated legislation while common law jurisdictions, like New York and London, often rely on bolt-on regulations to broader environmental laws. The study also finds that jurisdictions employing dedicated legislation and a metrics-based system offer a more comprehensive and preemptive solution to light pollution challenges. However, certain exceptions are noted, and the balance between regulatory certainty and flexibility is highlighted. The nuanced relationship between environmental protection and legal instruments is discussed, and the potential for unintended consequences of stringent regulation is acknowledged. The paper closes with a call for ongoing research and iterative regulatory reviews, emphasizing the need to incorporate scientific advancements and stakeholder interests into regulatory updates.