Construction and demolition waste (CDW) is one of the largest contributors to global waste streams, simultaneously posing significant environmental and resource management challenges. The management of CDW, particularly its potential for energy recovery and industrial symbiosis, has garnered increasing attention as part of a circular economy approach. This comprehensive review explores global practices in CDW management, analysing theoretical developments, technological advancements, and emerging resource recovery and reuse trends. Background: CDW accounts for more than a third of all waste generated in the EU. A wide variety of materials, such as concrete, bricks, wood, glass, metals, and plastics, make it a very un-homogenous waste stream with high potential for material recovery through different approaches. Methods: This review draws on an extensive analysis of scientific literature, case studies, and industry reports to assess current practices in the CDW stream and assessment of the feasibility of energy recovery, industrial symbiosis, and object reconstruction. Results: The originality of the current research is based on a Latvian case study on CDW management that provides valuable insights into household-level practices and progress towards relevant UN SDGs. Conclusions: Various CDW streams have an undeniable potential for valorization through various approaches. Currently, the most common approach is recovery and recycling, although CDW has the potential to broaden its application within the circular economy framework. For instance, industrial symbiosis is a solution that can not only boost the valorization of CDW but also significantly increase material circularity.

The article considers the problem of determining the criteria of petrol stations vulnerability in terms of the consequences of a possible accident under 3 proposed scenarios. The criteria, which include lost lives, economic, social and environmental consequences of a possible accident, are determined using a system analysis. The analytic hierarchy process and a survey of experts using a web form (ranking) are performed to determine the weight of the criteria for the petrol stations vulnerability and to reduce their amount in a reasonable basis.

This article examines the potential for enhancing the efficiency of inventory management and utilization of construction and demolition waste to create and apply secondary resources during the reconstruction of damaged infrastructure, including objects destroyed by war. This is achieved through the development of an intelligent information technology (IIT). The urgency of addressing this issue is underscored by the fact that large-scale reconstruction of damaged infrastructure demands significant expenditures of domestic and investment-based primary resources. Given the inevitable scarcity of these resources, the development of a secondary raw material market and the ability to extract valuable materials from waste streams for effective reuse become critically important. An analysis of European colleagues' experiences in effectively implementing a circular economy business model to address the limitations of primary resource utilization highlights the necessity of developing IIT for construction and demolition (C&D) waste inventory and utilization. Prior developer experience indicates that IIT can be implemented as a geoinformation system (GIS), enabling the identification of infrastructure objects through a knowledge base. The developed GIS knowledge base contains spatial and attribute data that align with the requirements of the circular economy business model, forming the foundation for a conceptual object inventory system. The intelligent component of the IIT is based on the use of large language models to analyze images of waste generation sites (Sources). This analysis involves interpreting visual cues, classifying types of construction materials, and providing an approximate volume assessment. The article also presents solutions for the preliminary classification of waste reception centers (Sinks) based on attribute and geospatial data, along with the development of an interactive Sinks-Sources map and the determination of efficient routes for transporting C&D waste to facilitate the creation of secondary resources.

Theses consider the development of intelligent information technology (IT) for the multi-criteria assessment of the petrol stations vulnerability to major accidents. On the basis of the authors' previous research on the methodology of assessing accidents and risks at petrol stations, it was proposed to develop IT for petrol stations vulnerability assessment, which would include methods of multi-criteria decision analysis, intelligent data analysis and fuzzy logic. The proposed IT construction method consists of 10 consecutive steps. The implementation of the first steps is related to the determination of the main types of accidents at petrol stations and consideration of the petrol stations vulnerability from the point of view of possible adverse consequences, for which the involved experts created 41 criteria of the primary space for assessing the petrol stations vulnerability, including economic, social and environmental criteria, as well as lost lives. To solve such a multi-criteria problem, it is proposed to apply the analytical hierarchy process for the analysis of expert data to obtain the secondary space of vulnerability criteria, without considering the lost lives. Based on the secondary space of criteria, data on the network of 17 petrol stations was collected and a scheme for their pre-processing and coding was proposed. A generalized model was developed based on the obtained data to assess the petrol stations vulnerability. To interpret the obtained results of the petrol stations vulnerability assessment, the use of a linguistic variable, which includes fuzzy sets in the form of trapezoidal membership functions, is proposed. Intelligent IT for petrol stations vulnerability assessment is implemented in the form of a decision support system (DSS). The decision-maker, based on the entered data according to the vulnerability criteria of a certain petrol station, will receive the preliminary value of the petrol station vulnerability assessment and an explanation of the way to obtain it. An integral part of the DSS is a formed knowledge base, which includes a database of pre-assessed petrol stations, as well as a base of rules for deriving the interpretation of the vulnerability assessment, with the possibility of its further editing and expansion. To visualize the results, petrol station data is displayed on a normalized coordinate graph, as well as on a graph of defined membership functions. The use of the proposed intelligent IT for multi-criteria assessment of the petrol stations vulnerability and DSS based on it provides an opportunity to make informed decisions on the assessment of potentially hazardous facilities and risk management, which allows to reduce the potential negative impact of accidents on petrol stations, improving the economic and social well-being of the country, considering the environmental impact.

The paper considers the creation of intelligent information technology (IT) for multi-criteria vulnerability assessment of gas stations (GSs) to the main types of accidents. The proposed IT consists of 10 consecutive stages. The implementation of the first stages was related to the definition of the main types of accidents for GSs and consideration of GS vulnerability from the point of view of possible adverse consequences, for which 41 criteria were created by experts. It is proposed to apply the analytical hierarchy process for the analysis of expert data in order to obtain a secondary space of vulnerability criteria, without considering the lost lives. On the basis of the secondary space of criteria, data on the GS network was collected and a scheme for their pre- processing and coding was proposed. The GS vulnerability assessment was carried out on the basis of the developed generalized model. To interpret the results of GS vulnerability assessment, the use of fuzzy sets in the form of trapezoidal membership functions is proposed. Intelligent IT for GS vulnerability assessment is implemented in the form of a decision support system (DSS). The decision-maker, based on the entered data according to the vulnerability criteria of a certain GS, will receive a preliminary value of the GS vulnerability and an explanation of how it was obtained. A component of the DSS is a formed knowledge base on pre- evaluated GS with the possibility of editing and expanding it. The use of the proposed intelligent IT of multi- criteria GS vulnerability assessment and DSS based on it provides an opportunity to make informed decisions on the assessment of potentially vulnerable facilities and risk management.