Electronic waste (e-waste) is a rapidly developing environmental problem particularly for the most developed countries. There are technological solutions for processing it, but these are costly, and the cheaper option for most developed countries has been to export most of the waste to less developed countries. There are various laws and policies for regulating the processing of e-waste at different governance scales such as the international Basel Convention, the regional Bamoko Convention, and various national laws. However, many of the regulations are not fully implemented and there is substantial financial pressure to maintain the jobs created for processing e-waste. Mexico, Brazil, Ghana Nigeria, India, and China have been selected for a more detailed study of the transboundary movements of e-waste. This includes a systematic review of existing literature, the application of the Driver, Pressure, State, Impact, Response (DPSIR) framework for analysing complex problems associated with social ecological systems, and the application of the Life Cycle Assessment (LCA) for evaluating the environmental impact of electronic devices from their manufacture through to their final disposal. Japan, Italy, Switzerland, and Norway have been selected for the LCA to show how e-waste is diverted to developing countries, as there is not sufficient data available for the assessment from the selected developing countries. GOOD, BAD and UGLY outcomes have been identified from this study: the GOOD is the creation of jobs and the use of e-waste as a source of raw materials; the BAD is the exacerbation of the already poor environmental conditions in developing countries; the UGLY is the negative impact on the health of workers processing e-waste due to a wide range of toxic components in this waste. There are a number of management options that are available to reduce the impact of the BAD and the UGLY, such as adopting the concept of a circular economy, urban mining, reducing loopholes and improving existing policies and regulations, as well as reducing the disparity in income between the top and bottom of the management hierarchy for e-waste disposal. The overarching message is a request for developed countries to help developing countries in the fight against e-waste, rather than exporting their environmental problems to these poorer regions.

Coastal and marine management require the evaluation of multiple environmental threats and issues. However, there are gaps in the necessary data and poor access or dissemination of existing data in many countries around the world. This research identifies how remote sensing can contribute to filling these gaps so that environmental agencies, such as the United Nations Environmental Programme, European Environmental Agency, and International Union for Conservation of Nature, can better implement environmental directives in a cost-effective manner. Remote sensing (RS) techniques generally allow for uniform data collection, with common acquisition and reporting methods, across large areas. Furthermore, these datasets are sometimes open-source, mainly when governments finance satellite missions. Some of these data can be used in holistic, coastal and marine environmental management frameworks, such as the DAPSI(W)R(M) framework (Drivers–Activities–Pressures–State changes–Impacts (on Welfare)–Responses (as Measures), an updated version of Drivers–Pressures–State–Impact–Responses. The framework is a useful and holistic problem-structuring framework that can be used to assess the causes, consequences, and responses to change in the marine environment. Six broad classifications of remote data collection technologies are reviewed for their potential contribution to integrated marine management, including Satellite-based Remote Sensing, Aerial Remote Sensing, Unmanned Aerial Vehicles, Unmanned Surface Vehicles, Unmanned Underwater Vehicles, and Static Sensors. A significant outcome of this study is practical inputs into each component of the DAPSI(W)R(M) framework. The RS applications are not expected to be all-inclusive; rather, they provide insight into the current use of the framework as a foundation for developing further holistic resource technologies for management strategies in the future. A significant outcome of this research will deliver practical insights for integrated coastal and marine management and demonstrate the usefulness of RS to support the implementation of environmental goals, descriptors, targets, and policies, such as the Water Framework Directive, Marine Strategy Framework Directive, Ocean Health Index, and United Nations Sustainable Development Goals. Additionally, the opportunities and challenges of these technologies are discussed.

The issue of marine plastic litter pollution is multifaceted, cross-sectoral, and ongoing in the absence of appropriate management measures. This study analysed the issue of marine plastic litter pollution in the context of the Descriptor 10 of the Marine Strategy Framework Directive and Good Environmental Status of the oceans and seas. The Driver-Pressure-State-Impact-Response (DPSIR) framework was used to assess the causes, effects, and management measures to changes in the marine environment resulting from marine plastics pollution. We noted that less than 10 peer-reviewed publications have applied the Driver-Pressure-State-Impact-Response (DPSIR) model to the issue of marine plastics pollution. Some basic needs such as food security, movement of goods and services, and shelter are also some of the major drivers of marine plastic pollution. The use of plastics is linked to multiple economic sectors (fisheries, agriculture, transport, packaging, construction) and other human activities. A significant amount of the resulting pressures came from the economic sectors for packaging and construction. State changes occurred at the environmental (contamination and bioaccumulation), ecosystem (ingestion of plastics, ghost fishing) and ecosystem service levels (supply of sea food, salt and cultural benefits), with possible loss of jobs and income being some of the observed impacts on human welfare. Responses as management measures, which are tailored to meet each component of the DPSIR framework, were identified. These included policies, regulations, technological advancement and behavioural change. The research acknowledges the issue of marine plastics pollution as a global environmental problem and recommends a trans-disciplinary approach, involving all types of stakeholders. Future research and analysis applying the DPSIR framework will be useful to provide the information necessary for the effective, adaptive management of litter pollution by marine plastics.

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The main landfill in the city of Rabat (Morocco) is based on sandy material containing the shallow Mio-Pliocene aquifer. The presence of a pollution plume is likely, but its extent is not known. Measurements of spontaneous potential (SP) from the soil surface were cross-referenced with direct measurements of the water table and leachates (pH, redox potential, electrical conductivity) according to the available accesses, as well as with an analysis of the landscape and the water table flows. With a few precautions during data acquisition on this resistive terrain, the results made it possible to separate the electrokinetic (~30%) and electrochemical (~70%) components responsible for the range of potentials observed (70 mV). The plume is detected in the hydrogeological downstream of the discharge, but is captured by the natural drainage network and does not extend further under the hills.

Global increases in the occurrence and frequency of flood have highlighted the need for resilience approaches to deal with future floods. The principal component analysis (PCA) has been used widely to understand the resilience of the urban system to floods. Based on feature extraction and dimensionality reduction, the PCA reduces datasets to representations consisting of principal components. Kernel PCA (KPCA) is the nonlinear form of PCA, which efficiently presents a complicated data in a lower dimensional space. In this work the KPCA techniques was applied to measure and map flood resilience across a local level. Therefore, it aims to improve the performance achieved by non-linear PCA application, compared to standard PCA. Twenty-one resilience indicators were gathered, including social, economic, physical, and natural components into a composite index (Flood resilience Index). The experimental results demonstrate the KPCA performance to get a better Flood Resilience Index, guiding q decision making to strengthen the flood resilience in our case of study of M’diq-Fnideq and martil municipalities in Northern of Morocco.