Disaster Waste Research Articles

Effective utilization of waste plastics and ammonia as biodiesel to assess performance and emission

Purpose This study aims to examine the environmental effects of plastic waste on the atmosphere and its implications for disaster waste management. It focuses on using ammonia, pyrolyzed plastic oil and the effectiveness of alumina nanoparticles as a catalyst. Design/methodology/approach The research explores different combinations of conventional diesel and nano Al2O3 derived from pyrolyzed plastic oil (ranging from P10 to P40). Critical performance metrics evaluated include brake mean effective pressure (BMEP), brake specific fuel consumption, brake thermal efficiency and emissions of CO2, CO and NOx. The study specifically investigates the impact of adding 50 ppm of Al2O3 nanoparticles to these blends. Findings The findings indicate that using blended fuels with nanoadditives significantly lowers pollution. Specifically, the P30 blend with 50 ppm of Al2O3 nanoparticles greatly reduced CO emissions. Additionally, the same blend reduced NOx emissions and CO2 emissions. The P30 mix showed improved BMEP and brake thermal efficiency due to its density, calorific value and viscosity (6.3 bar). The P30 blend exhibited higher thermal efficiency due to decreased heat loss, whereas conventional diesel demonstrated the best mechanical efficiency due to its longer ignition delay. Originality/value This study highlights the potential of using Al2O3 nanoparticles and pyrolyzed plastic oil to reduce emissions and enhance the performance of internal combustion engines. It underscores the environmental benefits and implications for disaster waste management by converting plastic waste into useful resources and reducing air pollution.

The impact of Kahramanmaraş (2023) earthquakes: A comparative case study for Adıyaman and Malatya

This study examines the effects of two major earthquakes of magnitude 7.7 and 7.6 that struck Kahramanmaraş on February 6th, 2023, followed by a magnitude 6.4 quake in Hatay on February 20th, which caused major damage in 11 Turkish provinces. The study focuses on Adıyaman and Malatya and uses an interdisciplinary approach to analyze the economic and environmental impacts. Primary data sources, including field visits and interviews, reveal clear labor-related challenges in both provinces, characterized by a government-induced labor shortage. In both provinces, physical capital has been severely damaged, particularly affecting small businesses, historic bazaars, and old industrial areas. The impact on businesses varies by size and location, with Adıyaman suffering more severe setbacks than other cities. The shortage of skilled labor related to the earthquake damage affects the quality of production, which can have a serious economic impact. Transportation disruptions continue to hamper supply chains and affect companies' ability to meet their export commitments. The environmental consequences, particularly the large amount of debris, pose a major challenge. The lack of a comprehensive disaster waste plan at the central government level leads to inadequate waste management. The study recommends sorting the debris at temporary sites to obtain reusable items while paying attention to the sustainability and transparency of debris management processes. In summary, this comparative case study highlights the need for tailored approaches to address the different impacts in the 11 provinces. A one-size-fits-all solution is insufficient and an individual needs assessment is needed for each province in order to implement targeted economic and environmental recovery measures.

Degradation of Disaster Waste By Using Insects

Degradation of Disaster Waste By Using Insects

Optimization-driven artificial intelligence-enhanced municipal waste classification system for disaster waste management

This research addresses the critical challenge of disaster waste management, a growing concern exacerbated by the increasing frequency and intensity of natural disasters like flooding. Traditional waste systems often struggle with the volume and heterogeneity of disaster waste, highlighting the need for innovative solutions. In this study, we present a novel disaster waste classification model integrating advanced artificial intelligence (AI) and optimization techniques to streamline waste categorization in post-disaster environments. Our approach leverages a dual ensemble deep learning framework. The first ensemble combines various image-segmentation methods, while the second integrates outputs from diverse convolutional neural network architectures. A modified artificial multiple intelligence system serves as a decision fusion strategy, enhancing accuracy at both ensemble points. We rigorously evaluated our model using three datasets: the “TrashNet” dataset for benchmarking against existing methods, as well as two meticulously curated, real-world datasets collected from flood-affected areas in Thailand. The results demonstrate that our method outperforms existing algorithms like VGG19, YoloV5, and InceptionV3 in general solid waste classification, achieving an average improvement of 11.18%. Regarding disaster waste specifically, our model achieves 96.48% and 96.49% accuracy on the curated datasets, consistently outperforming ResNet-101, DenseNet-121, and InceptionV3 by an average of 3.47%. These findings demonstrate the potential of our AI-enhanced model to revolutionize disaster waste management practices. Thus, we advocate integrating such technologies into municipal waste management policies to enhance resilience and optimize disaster responses. Future research will explore scaling the model to diverse disaster types and incorporating real-time data for adaptable waste management strategies.

Disaster waste and debris clean-up decisions of government actors in the United States: social process and socio-material systems

ABSTRACT In the United States, debris removal is one of the costliest and most time-consuming elements of disaster response and recovery. It is essential to reducing secondary environmental and health risks, and to community recovery and rebuilding. Analysis of debris removal and waste management, though, primarily treats it as a series of operational steps and technical decisions. In contrast, this article analyses disaster debris removal decision-making as a social process. We present the findings of an ethnographic study that engaged over 70 government actors from federal, state, local, and Tribal agencies in focus groups and interviews. By examining the experiences of these actors, who are central to debris removal decisions, this article identifies decision points that send waste down particular pathways from collection to final disposal. Three operational areas of concern that emerge from the analysis are: local control and capacity, cost and reimbursement, and balance between urgency and sustainability. This article shows how social processes in particular socio-material systems shape these decisions, such as the interplay of waste and disaster institutional arrangements. Finally, it shares practical implications for social process workarounds to operational challenges, such as interagency and interlevel relationships, that can support on-the-ground decision-making.

Application and comparison of remote sensing techniques for data-driven disaster debris quantification

ABSTRACT Effective disaster debris management requires reasonable predictions pre-hazard and estimates post-hazard of debris for a community to get back to normal sooner. However, there is a lack of data related to post-disaster waste quantities that could validate and improve debris predictions. This knowledge gap can be addressed by using remote sensing technology to quantify disaster debris promptly following a hazard. This study aimed to demonstrate and compare multiple remote sensing tools available for quantifying disaster debris using post-disaster data collected following Hurricane Ida. The tools used in this study are satellite imagery, emergency response airborne imagery, unmanned aerial vehicles (UAVs), and terrestrial laser scanning (TLS). We found that satellite imagery is useful for quantifying vegetative debris generation and transportation across vast areas, however it is often limited by spatial and temporal resolutions. Emergency response airborne imagery, collected within days following the hazard, is well-suited for quantifying transported vegetative debris and can assist debris clearance of emergency service routes across large areas, although it can be limited spatially and temporally to the interests of the acquiring agency. UAVs and TLS can provide precise volumes of debris but UAVs may be a better option due to their lower cost and computational demand. Guidance is provided for selecting a remote sensing tool based on the desired application and available resources, which can assist decision making for disaster waste managers.

Hazardous Solid Waste Landfill Site Selection for İstanbul, Türkiye using Multi-Criteria Decision-Making Methods and GIS Data

The high toxicity of materials in disaster waste poses a significant risk to the environment, including the air, water, soil, and all living beings. One of the commonly used disposal methods for hazardous solid waste is landfilling. The selection of sites for hazardous solid waste disposal requires extreme care and attention to multiple factors from environmental, social, and economic points of view. Considering the anticipated earthquake in Istanbul and the city’s excessive population and urbanization, experts estimate that debris waste will be approximately 25 million tons. In this study, we propose a Geographic Information System (GIS) based fuzzy Multi-Criteria Decision Making (MCDM) approach to select hazardous solid waste landfill (HSWL) locations within the scope of disaster waste management for Istanbul. First, the evaluation criteria were identified through a literature review and expert opinions. Next, criteria are prioritized using the Fuzzy Analytic Hierarchy Process (FAHP). Then, GIS data for the criteria are gathered from multiple resources and entered into ArcGIS 10.8 for spatial analysis. Last, the suitability map of Istanbul for the HSWL construction is built. Considering five candidates, the Analytic Hierarchy Process (AHP) is applied to select the most suitable locations for Asian and European sites in the city. Accordingly, Fevzipaşa/Silivri for the European side and Hasanlı/Şile for the Asian side were selected as the most suitable two options. Last, a sensitivity analysis was performed to investigate the impact of the highest weight criterion on the final solution.

Disaster waste management process: The case of February 6 earthquake

Disaster waste management process: The case of February 6 earthquake

Review of International Trends regarding Disaster Waste and Summary of Japanʼs International Efforts

Review of International Trends regarding Disaster Waste and Summary of Japanʼs International Efforts

Conceptualizing disaster waste governance using network governance perspectives

The establishment of an effective disaster waste management (DWM) system is necessary for a resilient and sustainable society. Although some DWM guidelines have been developed and there has been some progress in DWM research, little progress has been made in developing a theory of how the various aspects of DWM relate to each other and lead to effective, collaborative DWM. Here, we present a new conceptual model of disaster waste governance. Empirical studies on DWM were reviewed to clarify the current understanding of how DWM operation is affected by other nontechnical aspects. This knowledge was then incorporated into the disaster waste governance model, based on the perspectives of network governance theory, to capture the collaborative nature of DWM. The new model assumes that waste governance competency, consisting of actor capacity and network competency, rests at the core, connecting waste management after disasters with solid waste management, preparedness, and mitigation in normal times. A detailed description of this disaster waste governance model is further provided by drawing on examples from recent disasters in Japan and other countries. The proposed model allows stakeholders to comprehensively understand the relationship between key aspects of collaborative DWM, which can serve as a common framework to compare DWM experiences from different cities/countries and as a tool to help identify gaps in policies when aiming to achieve an effective and collaborative DWM system.

Assessment of deep learning-based image analysis for disaster waste identification

Accurately predicting different types and quantities of wastes is crucial for proper waste management and sustainable growth and development. High levels of disaster waste (DW) can negatively impact emergency responses, public health, and recovery and rebuilding processes, making the effective management of DW highly important. Most existing waste identification methods cannot suitably identify DW since it is highly subjective in form. In this study, we examined the applicability of different deep learning-based image recognition techniques for DW recognition. A DW image dataset was collected and categorized into normal and hard cases. Then, experiments were conducted using these three network models: DeepLabV3+, ResNeSt-50, and ResNeSt-101. The experimental results indicated that the mean intersection over union (mIoU) of the DeepLabV3+ model was 0.802 for the normal case and that of the ResNeSt-101 model was 0.676 for the hard case, indicating favorable performances. Overall, the deep learning-based image analysis method is more robust than existing methods, particularly in terms of its ability to accurately identify waste in various forms, such as mixed or piled up waste.

Developing capacity for post-typhoon disaster waste management in Lautoka, Fiji, and Makati, Philippines

In recent years, Asia and the Pacific have been ravaged by strong typhoons that caused widespread destruction. The powerful winds from these typhoons ripped off roofs, windows, doors and walls from houses, and destroyed trees and other vegetation, leaving a vast amount of wooden, metallic, plastic, and glass debris and waste scattered across a wide area. Proper management of disaster waste is a critical task during the initial phase of disaster recovery. It is essential for coastal cities that are frequently affected by typhoons to have adequate capacity for post-disaster waste management. This capacity development project aimed to contribute to this end by providing appropriate knowledge and training to government and non-government stakeholders. The project was implemented in Lautoka City, Fiji and Makati City, Philippines, with the support of four prominent universities. In total, six training sessions were conducted under the project. The primary outputs of this project are the disaster waste management contingency plans of the two participating cities. The project team disseminated information about the capacity development project through the project website and through presentations in academic conferences, webinars, workshops, training, non-academic conferences, and radio guest appearances.

Mapping groundwater resilience to climate change and human development in Asian cities

In recent years, Asia and the Pacific have been ravaged by strong typhoons that caused widespread destruction. The powerful winds from these typhoons ripped off roofs, windows, doors and walls from houses, and destroyed trees and other vegetation, leaving a vast amount of wooden, metallic, plastic, and glass debris and waste scattered across a wide area. Proper management of disaster waste is a critical task during the initial phase of disaster recovery. It is essential for coastal cities that are frequently affected by typhoons to have adequate capacity for post-disaster waste management. This capacity development project aimed to contribute to this end by providing appropriate knowledge and training to government and non-government stakeholders. The project was implemented in Lautoka City, Fiji and Makati City, Philippines, with the support of four prominent universities. In total, six training sessions were conducted under the project. The primary outputs of this project are the disaster waste management contingency plans of the two participating cities. The project team disseminated information about the capacity development project through the project website and through presentations in academic conferences, webinars, workshops, training, non-academic conferences, and radio guest appearances.

Efficient disaster waste management: identifying suitable temporary sites using an emission-aware approach after the Kahramanmaraş earthquakes

Efficient disaster waste management: identifying suitable temporary sites using an emission-aware approach after the Kahramanmaraş earthquakes

Multi-criteria evaluation of suitable locations for temporary disaster waste storage sites: the case of Cavite, Philippines

AbstractOne of the problems that arise due to typhoon and flooding is the generation of large volumes of disaster wastes, which poses threats to the environment and human health when not managed properly. This study focused on the identification of suitable locations of temporary storage sites (TSS) for disaster wastes using geographic information system to address gaps in disaster waste management. A set of criteria for selection was established based on the guidelines of the United Nations Environment/Office for the Coordination of Humanitarian Affairs Joint Unit (UNEP/OCHA), with constraints set based on existing guidelines and past studies. Map layers were standardized using Boolean logic, and the criteria were analyzed using ArcGIS Pro and Google Earth Pro. Areas in the Province of Cavite having high disaster risks, particularly Cavite City, Noveleta, and Kawit, were selected as study sites. From the analysis, a total of 18 TSS candidates were identified. It was determined that land use and distances from fishponds and built-up areas were the most sensitive criteria as they cover large portions of the area. For each TSS candidate, a 15-min service area map was generated using the ArcGIS Pro Network Analyst which showed that selected locations may serve multiple cities/municipalities.

Estimation of House Cleanup Work Volume Based on Disaster Volunteer Center Work Management Data —The Case of the 2015 Joso City—

To understand the workload of house cleanup and related workforce shortage after a disaster, the actual work situation in disaster-stricken areas is accounted for by disaster volunteer work management data created by the Disaster Volunteer Center of Joso City in Ibaraki Prefecture at the time of the Kanto–Tohoku Heavy Rain Disaster in September 2015. Using the classification of inundation depth, judged from ground elevation, the weekly workload of house cleanup according to the work content is recorded to clarify the characteristics of each area. Comparing this with the inundated areas without destructions by water flow, near the bank break with house destructions, in the urban area, and around the farmland along the old road, a model to estimate the workload is constructed. It was observed that indoor work to recommence living in urban areas continued for a long time, while the work was completed in a relatively short time in the area along the old road. The area near the bank break, with a small number of houses, witnessed very few house destructions. Hence, it is not necessary to separately calculate the workload caused by house destructions. The appropriateness of the estimated results was verified by using a method to estimate the workload based on the amount of disaster waste. As a result, the total workload estimated by disaster volunteers and victims for the busy period of two months was a million people. In the case of the Joso City flood, very few houses were completely destroyed, therefore, regular living could be resumed swiftly and people settled there after the disaster due to its proximity to the metropolitan area. Hence, the population decreased by the flood was recovered in two years.

Disaster waste management challenges and enabling factors for strategic planning: The case of the Beirut Port explosion.

Disasters occur in both developed and developing countries, generating large amounts of disaster waste including construction and demolition (C&D) waste that needs to be appropriately managed. While developed countries are capable of implementing adequate disaster waste management (DWM) strategies to facilitate their recovery processes, developing countries generally struggle to find the resources and expertise needed to develop such strategies. Lebanon is a developing country vexed by several systemic challenges that hindered its abilities to manage disaster waste. In this paper, we focus on the Beirut Port explosion (4 August 2020), which generated more than 800,000 tonnes of disaster wastes. This study first assesses the executed strategies and identifies their enabling factors and implementation challenges. It then proposes a framework for the proper management of disaster waste, which was validated through 18 in-depth interviews with experts and stakeholders involved in disaster management. Interview notes and transcripts were analyzed using an inductive-deductive process that allowed to identify themes using the constant comparative method. The data revealed that the main barriers toward implementing a successful DWM strategy were the absence of appropriate technologies, infrastructure, expertise, legislative framework and financial resources. The study concludes by proposing a DWM roadmap that includes contingency, risk reduction and implementation plans (IPs) that can enhance decision-making and ease the recovery process.

Local planning responsibilities for disaster waste management (DWM): Building knowledge from storm Alex in the South Region of France

As natural disasters increase, the stakes around disaster waste management (DWM) are rising and planning becomes necessary. Yet, planning for DWM faces many obstacles, in particular regarding the lack of clear responsibilities. Who should be mandated to plan for DWM? What benefits and downsides does each potential planner offer? Is a centralised DWM planning process more effective than several? This article aims at answering these questions and assessing the assets and weaknesses of potential DWM planners, by looking into the case study of DWM after storm Alex in the Roya Valley (South France). Eight criteria can be considered to analyse the links between the stakeholders and their environment, and assess their relevance as DWM planners: geographic scale, time scale, resources, responsibilities, planning tools, coordination capacities, disaster, and waste. According to the existing literature, it seems that a comprehensive DWM plan is more detailed, centralises all the information and enables systematic waste treatments. However, in practice, the study shows that it is difficult to find an adequate stakeholder to develop such a plan and enhance the participation and collaboration of other stakeholders on this subject.

Managing post-conflict demolition wastes in Gaza Strip: a case study on May 2021 conflict

Gaza Strip is considered as one of the armed conflicts prone areas in Middle East. Several intensive conflicts occurred in Gaza Strip in 2008, 2012, 2014 and 2021. These conflicts caused massive destroying the infrastructures, facilities, and buildings, which affected all services and activities in Gaza Strip. One of the major post-conflict issues in Gaza strip is the management of resulted demolition waste including its removal, sorting, recycling, and material recovery. In May 2021, over than 370,000 tons of demolition waste composed of rubbles and debris was generated during 11 days of armed conflict. The accumulated previous experience of rubbles and debris removal and recycling in Gaza Strip supported to perform a quick management approach for safe removal of the post-conflict demolition waste and reuse/recycle the resulted waste materials in various applications. The sorting and transporting process of concreate and non-concreate rubble elements of the waste were carried out in cooperation between local and international agencies as emergency recovery-funded projects. The most proportion of rubbles are concrete aggregates, thus, the material recovery was conducted through crushing process for concrete rubbles and then reusing it for road rehabilitation or producing concrete building blocks. The large concrete blocks reused to be placed for shoreline protection for specific area along Gaza beach. The recycling of post-conflict demolition waste management projects in Gaza Strip brought economic and social benefits through the reuse and recycle of resources and creation of job opportunities. In conclusion, although the post-conflict demolition waste management is quite different from municipal/industrial waste management in Gaza Strip, it is conducted through applying similar techniques of disaster waste management in waste removal, and those of construction and demolition (C&D) waste management in sorting, crushing, and sieving for recycling.

Strengthening Capacity in Disaster Waste Management in Vanuatu

This paper explores the effectiveness of a training program in strengthening the capacity of disaster waste management (DWM) in Vanuatu, drawing on an action research project undertaken during the delivery of a Training of Trainers (ToT) program in Port Vila and Ifira Island. The researchers gathered feedback through questionnaires, host group discussions, and park sheets from the participants. This feedback was used to inform revisions of the Disaster Waste Management Handbook to be provided to participants, and to understand the potential benefits for similar programs in other countries across the Pacific Region. The ToT proved to be well-received by participants with 64.7% of the participants giving a rating of “Excellent” and the remaining participants rating it “Good”. It demonstrated to be a cost-effective mode of training with scalability and promoted self-reliance and empowerment of the community. Key challenges in the delivery included time management, and internet connectivity disruptions. By addressing these key challenges and with further research to ensure that it is context-specific, the ToT model could be used effectively to strengthen DWM capacity in other Pacific Island nations.