Journal of Environmental & Earth Sciences

Intelligent Perception Systems for Vehicles: A Review of Observation Technologies in Environmental Risk Mitigation and Resource Optimization

2026-04-15T16:07:50+08:00

Vehicles that have intelligent perception systems are the first in the new wave of innovation that is geared towards enhancing transportation safety, sustainability, and efficiency. Such systems are a collection of sensors, artificial intelligence (AI), machine learning (ML), and real-time data processing to allow vehicles to sense and understand their surroundings with a great level of accuracy. In this review, we discuss the use of intelligent perception technologies in reducing environmental hazards and leveraging resources to the fullest. It discusses important sensor technologies, such as cameras, Light Detection and Ranging (LiDAR), radar, and ultrasonic sensors, as well as AI-based decision-making systems that enable vehicles to respond to changing driving conditions. Intelligent perception systems can help reduce vehicle emissions and minimize the environmental effects of cars by optimizing driving behaviors and consuming less fuel. The significance of optimizing resources is also addressed in the review, with references to the applications of intelligent routing, eco-driving, and autonomous vehicle systems. Although these technologies are promising, there are challenges such as the integration of the technologies, issues related to sensor fusion, data privacy, and infrastructure upgrade that are required. Also, new technologies like 5G connectivity, edge computing, and sensor technology will develop further to add additional features to the intelligent perception systems. The article ends by highlighting that such technologies can be transformative in the pursuit of sustainable, efficient, and safe forms of transportation.

From Cobalt to Kaolin: Molecular Signatures and Resource Recovery Pathways in Blue Porcelain Manufacturing Wastewater

2026-04-10T09:36:12+08:00

Manufacturing blue porcelain produces wastewater containing more cobalt, kaolin, silicates, and organic additives, which is a threat to the environment, as well as a resource recovery opportunity. This review summarizes existing information on the molecular composition of said effluents with a particular focus on cobalt speciation, mineral particle properties, and their interaction with organic ligands. Methods such as ICP-MS, XRD, SEM/TEM, and spectroscopy types offer important information concerning the behavior of metals and clays that will be used in designing targeted recovery operations. The most important methods of resource recovery, such as chemical precipitation, adsorption, electrochemical extraction, and physical separation of kaolin, are critically assessed, and emphasis is placed on integrated multi-stage technologies that maximize efficiency and the quality of a material. The environmental considerations, regulatory issues, and life-cycle are elaborated in order to put recovery strategies in the framework of sustainable manufacturing. The review highlights the possibility of integrating molecular-level knowledge and practical recovery technologies in making blue porcelain wastewater into a source of high-value products. Connecting analytical characterization, treatment procedures, and industrial application, this work offers a baseline of practices of the circular economy in the production of ceramics and lays down the direction of further research into the creation of sustainable and resource-efficient processes.

Next-Generation Environmental Management: A Review of Artificial Intelligence for Ecosystem Monitoring and Sustainable Decision-Making

2026-04-22T13:31:10+08:00

Artificial Intelligence (AI) has become one of the disruptive technologies in environmental management, providing new ways of monitoring the ecosystem, optimising resources, and making environmentally friendly decisions. This review examines how AI can potentially be used in different environmental areas, such as biodiversity monitoring, ecological change predictions, and how natural resources can be better distributed. Thanks to the incorporation of AI technologies like machine learning, remote sensing, and Internet of Things sensors, real-time data acquisition and analysis can now be conducted, which allows for more informed and timely decisions related to the environment. Predictive models based on AI offer useful information on the possible effects of climate change, loss of biodiversity, and habitat degradation to enable policymakers to engage in proactive environmental management. Nonetheless, the use of AI in environmental governance does not come without its problems. Challenges like data quality and availability, the complexity of ecosystems, ethics, and technological constraints need to be resolved to guarantee the effectiveness and equity of AI-based solutions. This paper addresses these issues and outlines future research opportunities, focusing on the importance of interdisciplinary cooperation and building a strong data infrastructure to maximize the potential of AI. With these obstacles resolved, AI has the potential to become a key factor in sustainability and resilience in ecosystems around the world.

Revitalising the Earth: Cross-International Solution Communication for Promoting Healthy Environmental Development

2026-04-13T16:29:43+08:00

With rising international environmental issues, there is a need to ensure effective communication of solutions across international boundaries to enhance sustainable development and environment sustainability. International solution communication entails the process of transmitting and localizing environmental innovations, technologies and policy-based or social, among nations and regions. This article discusses the actors, channels, and strategies that are significant to the transfer of environmental solutions with regard to identifying the obstacles that inhibit their universal adoption, and also the ethical concerns that would require consideration. Although there are viable solutions, the successful execution of these solutions is usually hampered by issues of governance mismatch, capacity gaps, political resistance, and cultural differences in different settings. This review offers an understanding of how trust, evidence-based communication, and local adaptation can improve solution transfer by the analysis of the mechanisms of delivering solutions and adopting them. Ethical issues, including data equity and environmental justice, are also addressed, and inclusive and open communication is essential. The article suggests an integrative model that connects the context, the mechanism of communication, and the outcome to provide a holistic model of maximizing cross-national solution communication. This framework will promote a situation in which environmental solutions result in measurable and sustainable enhancement of environmental health in the world by promoting collaboration and resolving barriers to communication.

From Prevention to Intervention: Technological Strategies for Pipeline Integrity and Immediate Pollutant Control

2026-03-06T15:21:56+08:00

The synthesis of technological strategies used in this review links the traditional pipeline integrity prevention methods with the rapidity of intervention of immediate pollutant control. Although inherent gains of materials, coating, cathodic protection, in-line inspection, and risk-based integrity programs have diminished the likelihood of failures, loss-of-containment events are still being experienced because of interacting degradation mechanisms, exogenous interference, geohazards, and transitory operative conditions. The scale of environmental and safety impacts is thus more and more controlled by system performance once prevention is violated, especially time-to-detect, time-to-localize, and time-to-isolate. We review leak and rupture detection systems involved with computational pipeline monitoring and negative pressure wave or acoustic, distributed fiber-optic sensing, and remote sensing with a strong focus on event classification, false alarm reduction, and uncertainty-sensitive localization and release quantification. The next step is to look at intervention technologies that restrict the avenues of released mass and exposure, such as automated and remotely controlled valves, risk-based segmentation, liquid, vapor, and gas release containment and recovery apparatus, robots/ remote response instruments, as well as real-time environment probing to inform adaptive reaction. This cumulation across these layers concludes with the biggest risk-reduction value, which relates to integration: the standardization of data architectures, resiliency in edges to clouds, verified analytics, and schemas ensuring a skilled combination of automation and human judgment. This review has revealed the continued gaps in field validation, standard performance measures relating detection to reduction of consequences, and cyber-physical resilience. We bring our findings to the recent pathways to deployment and investigate priorities so that end-to-end, consequence-centered integrity management becomes possible.

Applying the Integration Method of Logistics Management for Post-Sale Waste Recycling of Enterprise Products of Six Special Municipalities in Taiwan

2026-02-28T10:54:29+08:00

Logistics Management for Post-Sale Waste Recycling of Enterprise Products is very important in Taiwan. When recycling of waste resources of the six special municipalities cannot be managed effectively, ecological environment in supply chain will be harmed and body health of the public will be affected. Nowadays, enterprises attach great importance to ESG (Environment, Society and Governance). Hence, evaluating management situation of the six special municipalities over influence of major wastes resource recycling on ecological environment and the public's health will be helpful for regulators of Taiwan environment protection agencies to work out future strategies for the six special municipalities to manage influence of all waste resource recycling on ecological environment and health of the public. VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method, and link linear regression analysis method and grey prediction model, as well as dynamic waste recycling quantity management method were adopted to predict predictive value of Taiwan’s six special municipalities’ waste recycling quantity in advance and generate predicted results of management evaluation. Good effects were achieved in predicting and pre-warning evaluation in the research by applying VIKOR method and link linear regression analysis method and grey prediction model. The predicted ranking of the six special municipalities’ waste recycling quantity management is 100% consistent with the actual values of the management ranking situation of the six special municipalities. The reason for accurately predicting and knowing the resource recycling ranking of the six cities is that the state can know the resource recycling capacity of the six cities in advance and allocate recycling personnel and equipment to them.