Search Results (4)

Land Degradation Neutrality (LDN) is an ambitious initiative by the United Nations Convention to Combat Desertification (UNCCD) to tackle land degradation. Inspired by the “no net loss” concept, LDN seeks to counterbalance unavoidable land degradation—primarily driven by food systems—through targeted regenerative actions at multiple scales—such as regenerative agriculture or grazing practices that simultaneously support production and preserve land fertility. The objective is to ensure that degradation does not surpass the 2015 baseline. While the UNCCD’s Science–Policy Interface provides guidance and the LDN Target Setting Programme has led many countries to define baselines using agreed indicators (soil organic carbon, land use change, and primary productivity), concrete intervention strategies often remain poorly defined. Moreover, the voluntary nature of LDN has limited its effectiveness. A key shortcoming is the lack of integrated planning. LDN should function as a “Plan of Plans”—a coordinating framework to align policies across sectors and scales, reconciling conflicting agendas in areas such as food, energy, and water. To this end, we advocate for a systemic approach to uncover synergies, manage trade-offs, and guide decision-making in complex socio-ecological landscapes. Land degradation is intricately linked to issues such as food insecurity, land acquisitions, and transboundary water stress. Although LDN is implemented at the national level, its success also depends on accounting for global dynamics—particularly “LDN leaks”, where land degradation is outsourced through international trade in food and raw materials. In an increasingly complex world shaped by globalization, resource depletion, and unpredictable system dynamics, effective responses demand an integrated socio-ecological management approach. LDN is not simply a strategy to address desertification. It offers a comprehensive framework for sustainable resource management, enabling the balancing of trade-offs and the promotion of long-term resilience. Full article

The increasing demand for critical raw materials (CRMs), driven by global energy transition, underscores the need for innovative approaches to identify secondary resources, such as mining residues. Mining residues, often overlooked during initial mining activities, now represent valuable sources of raw materials thanks to technological advancements, including hyperspectral remote sensing. This study investigates the potential of hyperspectral satellite imagery to detect and map CRMs in mining residues of the abandoned Sidi Bou Azzouz mine in Morocco. The proposed approach is based on the integration between satellite data, field spectroscopy, chemical, and mineralogical analyses in a strong multi-scale and interdisciplinary framework. The integration between advanced laboratory techniques, including LIBS, XRF, XRPD, and SEM-EDS, was employed to enhance hyperspectral data interpretation. The integration of remote sensing and laboratory results provided a comprehensive understanding of mineral composition, confirming the effectiveness of hyperspectral methods for characterizing heterogeneous surface deposits. This research demonstrates the potential of hyperspectral observations to identify valuable raw materials and to map them using PRISMA imagery in abandoned mining residues, offering a tool useful for planning cost-effective and sustainable solutions aimed at answering the growing demand for CRMs crucial to industrial competitiveness and sustainable growth. Full article

The rapid pace of urbanization and the increasing concentration of populations in urban areas have generated a substantial demand for architectural structures, resulting in a significant increase in building stock and continuous material flows that interact with the environment. This study emphasizes the importance of high-spatial-resolution mapping of residential building stock for effective urban-construction resource management, planning, and waste management. Focusing on Xi’an as a case study, the research develops a comprehensive framework for mapping urban residential building stock by integrating diverse data dimensions, including temporal, spatial, network, and multi-attribute aspects. The findings indicate that between 1990 and 2020, approximately 4758 residential communities were established in central Xi’an. The analysis of seven key residential construction materials revealed that the building stock escalated from 1.53 million tons to 731.12 million tons, with a steady spatial expansion of material distribution. The study attributes this growth to factors such as population increase, economic advancement, and policy initiatives, which, in turn, have driven the demand for residential building materials and reinforced the interdependence between urban expansion and residential construction development. Remarkably, from 1990 to 2020, the population surged by 2.1-fold, the economy by 66-fold, and the stock of residential building materials by 477-fold, indicating that the growth rate of material stock consistently outpaced that of both population and economic growth. Over the past three decades, the rapid expansion of residential buildings has led to the encroachment of urban ecological spaces by concrete structures. The methodology proposed in this study for quantifying building material offers valuable insights for policymakers and urban and environmental planners to foster responsible resource consumption and supports component-level circularity in the built environment. Full article

The Demand-Driven Material Resource Planning (DDMRP) method is one of the newer methods of inventory management in an enterprise. Its creation was initiated by a change in the business environment and the characteristics of today’s supply chains. DDMRP brings a combined pull/push approach to inventory management based on creating strategic stacks in the supply chain and managing inventory at these strategic points based on customer orders. The DDMRP system provides a simple methodology that is easy to apply, even in smaller businesses, without the need for advanced information systems. However, a simple methodology also has its limitations because, in many cases, intuitive and subjective approaches are used to set inventory management parameters (variability factor, running time factor, seasonality factor, thresholds, etc.). Simplified parameter determination may, under certain conditions, lead to some storage tanks being too high or too low for certain periods of time. We know from classical inventory management, in the conditions of setting stack parameters in DDMRP, that the deficiency can be eliminated by the use of statistical–analytical approaches and optimisation techniques. This article deals with the issue of setting optimal values of storage tanks in DDMRP, while the correctness of the methodology is verified through simulation of the demand-driven planning process. The correctness and usability of the proposed approaches in sizing strategic reservoirs in DDMRP was confirmed through the results of stimulation experiments. Full article