Hasil untuk "Environmental law"

Marc-Philipp Bohnet, Philip Fliegel, Anne Schoenauer et al.

Limiting global warming in line with the Paris Agreement requires net-zero emissions by mid-century. To address uncertainties in this transition, prior research has developed low-carbon scenarios. We contribute by eliciting expert judgement through online surveys with 21 experts and applying the Cross Impact Balances method to construct exploratory qualitative scenarios for the European Union. These scenarios complement quantitative approaches and reflect interactions among financial markets, technological innovation, political economy, and climate policy variables. We identify two internally consistent scenarios: one aligned with mitigation goals and one diverging. The mitigation scenario leads to 1.5 °C warming and features high and stable CO2 prices, a green mandate from the European Central Bank, high-quality climate risk data, accelerated economic development, and reduced inequality, despite public resistance and corporate lobbying by high-carbon sectors. Within the expert-based scenario analysis, results indicate that green financial policies are not essential for shifting market expectations towards the low-carbon transition.

Andrew Paul Gutierrez, Luigi Ponti, Markus Neteler et al.

Abstract Background Globally, research and policy groups often lack the expertise to develop models to analyze invasive and native species of agroecological and veterinary/human health importance; models to inform management and policy under extant and climate change scenarios at various geographic scales. Species distribution models (SDMs) correlate weather and other variables to species presence records and are currently the mainstay for predicting the geographic distribution of species, but SDMs do not predict the underpinning dynamics required to develop policy and management strategies. Weather-driven physiologically based demographic models (PBDMs) of single and multi-trophic dynamics based on sound biological data can bridge much of this gap. The development of web platform software is proposed to assist non-experts in formulating PBDMs to help solve agroecological and veterinary/human health pest problems. Results PBDMs are time-varying life tables (TVLTs) that capture the weather-driven biology of per capita resource acquisition and allocation to growth and reproduction in age-mass structured trophic settings independent of time and place. Two approaches are used to parameterize PBDMs: (1) mass/energy acquisition and allocation, and (2) biodemographic functions fitted to vital rates estimated from age-specific life table studies conducted under a range of abiotic conditions; vital rates that result from resource acquisition and allocation under experimental conditions. To outline the development and demonstrate the utility of this approach as web platform software for nonexperts, PBDMs for thirteen species of agroecological and medical/veterinary importance to Africa are developed and used to predict prospectively their geographic distribution, relative abundance, and dynamics across the continent. Where possible, PBDM predictions are compared to published studies and references are made to their use in management and policy development. Conclusions The development and utility of web platform software based on the PBDM paradigm is outlined, which aims to guide non-experts in formulating realistic models and gathering the biological data to parameterize them while providing links to relevant weather data for running the models and tools for GIS mapping and statistical analysis of model output for policy and management development. Numerous published heritage PBDMs that the web platform software would make available are summarized in the Supplementary Information.

Tripanji Aryawardhana, Lazarus Tri Setyawanta, Lita Tyesta Addy Listya Wardhani

The complexity of coastal and marine resource management in Indonesia is often caused by overlapping authorities between institutions and sectoral regulatory disharmony. This phenomenon has resulted in legal uncertainty, marginalization of coastal communities, and marine environmental damage. The research aims to reconstruct a governance model that promotes legal certainty, justice, and sustainability. Using a normative legal research method supported by statutory, conceptual, case, and historical approaches, this article analyzes the distribution of authority and its implications for coastal governance in the post-decentralization era. The findings reveal that the withdrawal of maritime authority from districts to provinces has created administrative gaps, weakened local participation, and increased legal uncertainty. This article offers a reconstructive approach based on seven pillars that integrate the principles of the rule of law, balance between central and regional relations, revitalization of assistance tasks, internalization of Pancasila values of justice, strengthening of local institutions, utilization of Geographic Information System (GIS) technology, and mainstreaming of ecological awareness and legal spirituality.

Fei Li, Hongtao Yi, Chengzhi Chen et al.

Davoud Hosseinpour, seyed mahdi alvani, Hossein Aslipour et al.

Despite the plethora of studies on street-level bureaucrats, only a very limited body of research has focused on their role in the environmental scene. This is surprising; Because they play an important role in the chain of policy-making and in the actual realization and implementation of policies; Therefore, the current research was conducted with the aim of identifying and prioritizing the role of street-level bureaucrats in the implementation of environmental policies (case of study: the law on protection and exploitation of forests in the north of the country). To achieve this goal, first a qualitative study was conducted using thematic analysis method. A semi-structured interview was used to collect data. Using purposeful sampling, subject saturation was achieved after conducting eleven interviews. The method of fuzzy hierarchical analysis process was used to give weight to these themes. The data of this stage was collected using a paired comparison questionnaire that was collected from a sample of eleven employees and foresters in three northern provinces. The extraction of semantic units led to the identification of 169 basic themes, 30 organizing themes and 9 overarching themes, in which nine main themes are "emotional attitude towards citizens, organizational characteristics, changing the nature of the policy, knowledge weakness of employees, individual decision characteristics" It was classified as the recipient, determining how to govern the forest, adopting coping strategies, localizing the policy and making the policy operational. The results of the fuzzy hierarchical analysis showed that among the nine main themes, changing the nature of the policy, determining how to govern the forest and adopting coping strategies were in the first to third place. The final weights of the subthemes were obtained by multiplying the weight of the main themes by the relative weight of the subthemes; Based on this, the sub-topics of adaptation of policies to local conditions, government-citizen relations, hidden politics and weak expertise and skills of employees were ranked first to fourth.The final weights of the subthemes were obtained by multiplying the weight of the main themes by the relative weight of the subthemes; Based on this, the sub-topics of adaptation of policies to local conditions, government-citizen relations, hidden politics and weak expertise and skills of employees were ranked first to fourth.The final weights of the subthemes were obtained by multiplying the weight of the main themes by the relative weight of the subthemes; Based on this, the sub-topics of adaptation of policies to local conditions, government-citizen relations, hidden politics and weak expertise and skills of employees were ranked first to fourth.The final weights of the subthemes were obtained by multiplying the weight of the main themes by the relative weight of the subthemes; Based on this, the sub-topics of adaptation of policies to local conditions, government-citizen relations, hidden politics and weak expertise and skills of employees were ranked first to fourth.The final weights of the subthemes were obtained by multiplying the weight of the main themes by the relative weight of the subthemes; Based on this, the sub-topics of adaptation of policies to local conditions, government-citizen relations, hidden politics and weak expertise and skills of employees were ranked first to fourth.

Gonzalo F. Iglesias Rossini

El presente estudio aborda la responsabilidad administrativa por infracción a las normas ambientales, regulada principalmente en el artículo 47 de la Constitución de la República, la Ley N.º 16.466, de 19 de enero de 1994 (Ley de Evaluación de Impacto Ambiental), y la Ley N.º 17.283, de 28 de noviembre de 2000 (Ley General del Ambiente). Analizaremos las distintas normas ambientales que regulan infracciones a las normas ambientales, sus posibles sanciones, así como las peculiaridades de dicho régimen, incluyendo el régimen de prescripción previsto en el artículo 169 de la Ley N.º 19.535, de 25 de setiembre de 2005, del cual el autor de este artículo ha sido redactor.

Thi Phuong Thao Vu, Quoc Hung Le

In Vietnam, achievements in research and application of remote sensing technology have significantly improved the efficiency of many socio-economic activities. Although the application and development of this technology are underway, numerous inadequacies have been revealed. The lack of a comprehensive remote sensing law in Vietnam to address and support socio-economic activities has become evident, leading to many difficulties in assessing the quality of remote sensing products of different agencies, making it challenging to develop remote sensing applications and services. Furthermore, remote sensing application agencies are mainly concentrated in central agencies, while remote sensing in localities has high practical significance and is essential to serve the state management of natural resources and the environment locally. In addition, there is no close coordination between local agencies and central agencies - the main reason for overlapping work contents, causing a waste of budget investment and, at the same time, leading to confusion and passivity in arranging annual plans and allocating expenditures for remote sensing. Thus, institutionalising the management of remote sensing activities based on legal and practical requirements in Vietnam is an urgent need. This includes the management of space and ground segments, commercialisation of remote sensing, international training and cooperation, and the creation of a legal corridor to promote remote sensing development, overcome policy gaps, and support the socio-economic life, national defence, security, and environmental monitoring.

Jamie Milton Freestone

The word semantics, in robotics and AI, has no canonical definition. It usually serves to denote additional data provided to autonomous agents to aid HRI. Most researchers seem, implicitly, to understand that such data cannot simply be extracted from environmental data. I try to make explicit why this is so and argue that so-called semantics are best understood as data comprised of conventions of human behaviour. This includes labels, most obviously, but also places, ontologies, and affordances. Object affordances are especially problematic because they require not only semantics that are not in the environmental data (conventions of object use) but also an understanding of physics and object combinations that would, if achieved, constitute artificial superintelligence.

Omar Hammad, Md Rezwanur Rahman, Nicholas Clements et al.

Planned disruptions such as highway constructions are commonplace nowadays and the communities living near these disruptions generally tend to be environmental justice communities -- low socioeconomic status with disproportionately high and adverse human health and environmental effects. A major concern is that such activities negatively impact people's well-being by disrupting their daily commutes via frequent road closures and increased dust and air pollution. This paper addresses this concern by developing a personalized navigation service called PureNav to mitigate the negative impacts of disruptions in daily commutes on people's well-being. PureNav has been designed using active engagement with four environmental justice communities affected by major highway construction. It has been deployed in the real world among the members of the four communities, and a detailed analysis of the data collected from this deployment as well as surveys show that PureNav is potentially useful in improving people's well-being. The paper describes the design, implementation, and evaluation of PureNav, and offers suggestions for further improving its efficacy.

Weiying Zhao, Ganzorig Chuluunbat, Aleksei Unagaev et al.

This study introduces a framework for forecasting soil nitrogen content, leveraging multi-modal data, including multi-sensor remote sensing images and advanced machine learning methods. We integrate the Land Use/Land Cover Area Frame Survey (LUCAS) database, which covers European and UK territory, with environmental variables from satellite sensors to create a dataset of novel features. We further test a broad range of machine learning algorithms, focusing on tree-based models such as CatBoost, LightGBM, and XGBoost. We test the proposed methods with a variety of land cover classes, including croplands and grasslands to ensure the robustness of this approach. Our results demonstrate that the CatBoost model surpasses other methods in accuracy. This research advances the field of agricultural management and environmental monitoring and demonstrates the significant potential of integrating multisensor remote sensing data with machine learning for environmental analysis.

Xinhao Zhang, Jinghan Zhang, Wujun Si et al.

Deep Reinforcement Learning has shown excellent performance in generating efficient solutions for complex tasks. However, its efficacy is often limited by static training modes and heavy reliance on vast data from stable environments. To address these shortcomings, this study explores integrating dynamic weight adjustments into Deep Q-Networks (DQN) to enhance their adaptability. We implement these adjustments by modifying the sampling probabilities in the experience replay to make the model focus more on pivotal transitions as indicated by real-time environmental feedback and performance metrics. We design a novel Interactive Dynamic Evaluation Method (IDEM) for DQN that successfully navigates dynamic environments by prioritizing significant transitions based on environmental feedback and learning progress. Additionally, when faced with rapid changes in environmental conditions, IDEM-DQN shows improved performance compared to baseline methods. Our results indicate that under circumstances requiring rapid adaptation, IDEM-DQN can more effectively generalize and stabilize learning. Extensive experiments across various settings confirm that IDEM-DQN outperforms standard DQN models, particularly in environments characterized by frequent and unpredictable changes.

Van Khanh Pham, Minh Le

In the times we live in today, humanity faces unprecedented environmental challenges. The emergence of artificial intelligence (AI) has opened new doors in our collective efforts to address our planet's pressing problems; however, many have doubts on the actual extent of impact that AI have on the environment. In particular, AI also assisting dirty production is a drawback that is largely absent from the literature. To investigate the impact of AI on the environment, we establish mathematical models to model the economy and the production process of goods based on outdated and advanced technologies. The secondary results are stated in the form of lemmas, the main results are stated in the form of theorems. From the theorems we conclude that AI may not on its own prevent an environmental disaster, a reason of which is its concurrent contribution to dirty production. With temporary government intervention, however, AI is able to avert an environmental disaster.

Yun-Chieh Cheng, Yu-Tong Shen, Guanqun Song et al.

This study investigates how the new release of MacBook Pro I/O devices affects the obsolescence of related accessories. We also explore how these accessories will impact the environment and the economic consequences. As technology progresses, each new MacBook Pro releases outdated prior accessories, making more electronic waste. This phenomenon makes modern people need to change their traditional consumption patterns. We analyze changes in I/O ports and compatibility between MacBook Pro versions to determine which accessories are obsolete and estimate their environmental impact. Our research focuses on the sustainability of current accessories. We explore alternate methods of reusing, recycling, and disposing of these accessories in order to reduce waste and environmental impact. In addition, we will explore the economic consequences of rapid technological advances that make accessories obsolete too quickly. Thereby assessing the impact of such changes on consumers, manufacturers, and the technology industry. This study aims to respond to the rapid advancement of technology while promoting more sustainable approaches to waste management and product design. As the MacBook Pro I/O unit evolves, certain accessories become obsolete with each subsequent version. The purpose of this study is to identify and quantify the environmental and economic impacts of parts end-of-life. We can detect which accessories have become obsolete and assess the environmental impact by comparing I/O port changes and compatibility across MacBook Pro generations. In response to these environmental images, methods are developed to reuse, recycle, and dispose of obsolete accessories to reduce waste and promote sustainable development. Additionally, we evaluate the economic impact of obsolete equipment on consumers and producers.

Lin Ge, Ce Yang, David Zucker et al.

Environmental exposures are often defined using buffer zones around geocoded home addresses, but these static boundaries can miss dynamic daily activity patterns, leading to biased results. This paper presents a novel measurement error correction method for spatially defined environmental exposures within a survival analysis framework using the Cox proportional hazards model. The method corrects high-dimensional surrogate exposures from geocoded residential data at multiple buffer radii by applying principal component analysis for dimension reduction and leveraging external GPS-tracked validation datasets containing true exposure measurements. It also derives the asymptotic properties and variances of the proposed estimators. Extensive simulations are conducted to evaluate the performance of the proposed estimators, demonstrating its ability to improve accuracy in estimated exposure effects. An illustrative application assesses the impact of greenness exposure on depression incidence in the Nurses' Health Study (NHS). The results demonstrate that correcting for measurement error significantly enhances the accuracy of exposure estimates. This method offers a critical advancement for accurately assessing the health impacts of environmental exposures, outperforming traditional static buffer approaches.

Miftahol Fajar Sodik, Dimas Bima Setiyawan

The ratification of job creation law or omnibus law that changes clauses and establishes new regulations in a legal codification format has led to rejection in several regions in Indonesia because justice is not been reflected in terms of licensing aspects and weakened responsibilities. The omnibus law legislative process, which has so much been able to be completed in a short time, during the Covid-19 situation. This matter triggers the question of how the omnibus law legalization process is carried out based on the perspective of siyasah dusturiyah so how to analyze environmental content on environmental fiqh. This research is library research based on a normative approach by qualitative analysis methods. The theory used in this study is the theory of siyasah dusturiyah and environmental fiqh. The results of this study indicate that the omnibus law legislative process is not in line with the expectations of the benefit of dharuriyah, justice, and a sense of responsibility. The environmental content in the omnibus law does not yet represent environmentally friendly development so its management must be based on the principle of balance between utilization and environmental conservation.

Bartosz Rakoczy

Cel niniejszego artykułu stanowi analiza rozwiązań normatywnych nakładających na posiadacza odpadów obowiązek dołączenia do określonych wniosków zaświadczenia o niekaralności wspólnika, gdy jest nim osoba prawna. Rozwiązania te, zawarte w ustawie o odpadach i ustawie nowelizującej, naruszają zasadę proporcjonalności. Rozumiejąc ideę, by nie dopuszczać do działalności w zakresie gospodarki i gospodarowania odpadami podmiotów, które popełniły czyny zabronione przeciwko środowisku, należy jednak zdecydowanie sprzeciwić się wyciąganiu negatywnych konsekwencji wobec podmiotu wnioskującego w sytuacji, gdy takiego czynu dopuścił się tylko wspólnik. Oczekiwanie dotyczące przedłożenia stosownego zaświadczenia o niekaralności wspólnika trzeba uznać za niekonstytucyjne, jeśli skutkiem jego nieprzedłożenia jest odmowa przyznania decyzji niezbędnej do prowadzenia działalności gospodarczej. Podobny skutek wystąpi, jeśli wspólnik był karany za czyn zabroniony przeciwko środowisku. Wątpliwości konstytucyjne budzi również ograniczenie regulacji jedynie do spółki z ograniczoną odpowiedzialnością, z pominięciem spółki akcyjnej.

Dhanasree Jayaram, Marie Claire Brisbois

The military is emerging as an important actor in climate change mitigation and adaptation, particularly when it comes to responding to climate extremes. While not generally considered a “governance actor” in scholarship on climate governance, militaries increasingly participate in climate-related knowledge production, resource provision, and decision-making. However, the nature and degree of involvement of militaries in these issues vary from context to context, based on political, socio-cultural, institutional, and economic conditions. This Perspective examines this expanding role through the five Earth System Governance research lenses. We argue that it is necessary to more fully account for the emergence of this powerful actor within accepted democratic frameworks of climate governance. Key research questions relate to the implications of military involvement, the appropriateness of military involvement in different contexts, and the consequences of the involvement of an authoritarian actor for climate governance norms.

Linda Steg, Goda Perlaviciute, Benjamin K. Sovacool et al.

The Social Sciences and Humanities (SSH) have a key role to play in understanding which factors and policies would motivate, encourage and enable different actors to adopt a wide range of sustainable energy behaviours and support the required system changes and policies. The SSH can provide critical insights into how consumers could be empowered to consistently engage in sustainable energy behaviour, support and adopt new technologies, and support policies and changes in energy systems. Furthermore, they can increase our understanding of how organisations such as private and public institutions, and groups and associations of people can play a key role in the sustainable energy transition. We identify key questions to be addressed that have been identified by the Platform for Energy Research in the Socio-economic Nexus (PERSON, see person.eu), including SSH scholars who have been studying energy issues for many years. We identify three main research themes. The first research theme involves understanding which factors encourage different actors to engage in sustainable energy behaviour. The second research theme focuses on understanding which interventions can be effective in encouraging sustainable energy behaviour of different actors, and which factors enhance their effects. The third research theme concerns understanding which factors affect public and policy support for energy policy and changes in energy systems, and how important public concerns can best be addressed as to reduce or prevent resistance.

Emilio A. L. Gianicolo, Marco Cervino, Antonello Russo et al.

Abstract Background In an industrial area, the asymmetry between the weights of the economic interests compared to the public-health needs can determine which interests are represented in decision-making processes. This might lead to partial interventions, whose impacts are not always evaluated. This study focuses on two interventions implemented in Taranto, Italy, a city hosting one of the largest steel plants in Europe. The first intervention deals with measures industrial plants must implement by law to reduce emissions during so called “wind days” in order to reduce PM10 and benzo [a] pyrene concentrations. The second one is a warning to the population with recommendations to aerate indoor spaces from 12 pm to 6 pm, when pollutant concentrations are believed to be lower. Methods To analyse the impact of the first intervention, we analysed monthly PM10 data in the period 2009–2016 from two monitoring stations and conducted an interrupted-time-series analysis. Coefficients of time-based covariates are estimated in the regression model. To minimise potential confounding, monthly concentrations of PM10 in a neighbourhood 13 km away from the steel plant were used as a control series. To evaluate the second intervention, hourly concentrations of PM10, SO2 and polycyclic-aromatic-hydrocarbons (PAHs) were analysed. Results PM10 concentrations in the intervention neighbourhood showed a peak just a few months before the introduction of the law. When compared to the control series, PM10 concentrations were constantly higher throughout the entire study period. After the intervention, there was a reduction in the difference between the two time-series (− 25.6%). During “wind days” results suggested no reduction in concentrations of air pollutants from 12 pm to 18 pm. Conclusion Results of our study suggest revising the warning to the population. Furthermore, they evidence that in complex highly industrialised areas, air quality interventions cannot focus on only a single pollutant, but rather should consider the complex relationships between the different contaminants. Environmental interventions should be reviewed periodically, particularly when they have implications for social constraints. While the results of our study can be related only to the specific situation reported in the article, the methodology applied might be useful for the environmental management in industrial areas with similar features.

Frank Kulwa, Chen Li, Jinghua Zhang et al.

Environmental microorganism (EM) offers a high-efficient, harmless, and low-cost solution to environmental pollution. They are used in sanitation, monitoring, and decomposition of environmental pollutants. However, this depends on the proper identification of suitable microorganisms. In order to fasten, low the cost, increase consistency and accuracy of identification, we propose the novel pairwise deep learning features to analyze microorganisms. The pairwise deep learning features technique combines the capability of handcrafted and deep learning features. In this technique we, leverage the Shi and Tomasi interest points by extracting deep learning features from patches which are centered at interest points locations. Then, to increase the number of potential features that have intermediate spatial characteristics between nearby interest points, we use Delaunay triangulation theorem and straight-line geometric theorem to pair the nearby deep learning features. The potential of pairwise features is justified on the classification of EMs using SVMs, k-NN, and Random Forest classifier. The pairwise features obtain outstanding results of 99.17%, 91.34%, 91.32%, 91.48%, and 99.56%, which are the increase of about 5.95%, 62.40%, 62.37%, 61.84%, and 3.23% in accuracy, F1-score, recall, precision, and specificity respectively, compared to non-paired deep learning features.