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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.

Global freshwater resources are vital to humanity and Earth’s ecosystems, yet about one third of the global population is affected by water scarcity for at least one month per year. In these areas, the overuse of freshwater resources can lead to the threat of depletion, marking them as the global ‘water scarcity hotspots’. This study combines outputs from a global hydrological model (PCR-GLOBWB 2) with an extensive literature search to provide a comprehensive intercomparison of the key drivers, pressures, states, impacts and responses (DPSIR) that shape the water gap between water demand and availability at the most important water scarcity hotspots worldwide. Hydroclimatic change, population growth, and water use for the industrial, municipal and agricultural sectors are the most important driving and pressuring forces on the water gap, affecting both water quality and quantity. These drivers and pressures have been showing increasing trends at all hotspots, which is concerning for the future development of the water gap. Additionally, we identify and characterize seven clusters of hotspots based on shared DPSIR patterns, revealing their common mechanisms. Our work highlights the diversity of water scarcity related issues at hotspots, especially the variety of impacts involved and governmental responses in place. The results of our DPSIR analysis provide valuable insights for building causal networks representing water gap dynamics at the hotspots. They form a foundation for conceptual models that illuminate human-water interactions, trade-offs, and synergies at the hotspots, while guiding policymakers in addressing the multifaceted challenge of closing the water gap.

Photovoltaic development has played a crucial role in mitigating the energy crisis and addressing global climate change. However, it has also had significant impacts on the ecological environment. To ensure the sustainable growth of the photovoltaic industry, it is essential to establish an indicator system to assess the ecological and environmental effects of photovoltaic development. This study utilizes the Driving-Pressure–Status–Impact-Response (DPSIR) framework to create an indicator system for evaluating the ecological and environmental effects of desert photovoltaic development. The study evaluates the ecological and environmental effects at the on-site (WPS), transitional zone (TPS), and off-site (OPS) areas of the Qinghai Gonghe Photovoltaic Park in China. The entropy weight method was utilized to calculate indicator weights, while the evaluation model and indicators were transformed uniformly to obtain standardized scores for ecological and environmental effects. and conducting a thorough analysis of the distribution characteristics and factors influencing the evaluation indicators’ scores. Overall, the large-scale development of desert photovoltaics in Gonghe County has had a positive impact on the ecological environment. The WPS had better ecological and environmental conditions than did the TPS and OPS, and the ecological and environmental evaluation levels of the WPS were categorized as “general” (0.439), while the ecological and environmental effect evaluation levels of the TPS (0.286) and OPS (0.28) were both “poor”, indicating significant room for improvement. Moreover, all indicators in the scheme layer, which are used to evaluate ecological and environmental quality, yielded higher scores for the WPS than for the TPS and OPS, demonstrating that photovoltaic development has a positive effect on desert area ecology and the environment.

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 Yangtze River (hereafter referred to as the YZR), the largest river in China, is of paramount importance for ensuring water resource security. The Yangtze River Basin (hereafter referred to as the YRB) is one of the most densely populated areas in China, and complex human activities have a significant impact on the ecological security of water resources. Therefore, this paper employs theories related to ecological population evolution and the Driving Force-Pressure-State-Impact-Response (DPSIR) model to construct an indicator system for the ecological security of water resources in the YRB. The report evaluates the ecological security status of water resources in each province of the YRB from 2010 to 2019, clarifies the development trend of its water resource ecological security, and proposes corresponding strategies for regional ecological security and coordinated economic development. According to the results of the ecological population evolution competition model, the overall indicator of the ecological security of water resources in the YRB continues to improve, with the safety level increasing annually. Maintaining sound management of water resources in the YRB is crucial for sustainable socioeconomic development. To further promote the ecological security of water resources in the YRB and the coordinated development of the regional economy, this paper proposes policy suggestions such as promoting the continuous advancement of sustainable development projects, actively adjusting industrial structure, continuously enhancing public environmental awareness, and actively participating in international ecological construction and seeking cooperation among multiple departments.

This study employs an integrated analytical framework combining the Social-Ecological System (SES) and Driver-Pressure-State-Impact-Response (DPSIR) models, supplemented by quantitative methodologies including the Entropy Weight Method (EWM), Generalized Additive Model (GAM), Lasso regression, and shallow neural networks, to conduct a systematic resilience assessment of six representative Tibetan villages in western Sichuan based on longitudinal data from 2015 to 2022. The analysis reveals significant differences in resilience levels among the villages, primarily influenced by multiple factors. Disposable income and employment are key positive drivers that enhance adaptive capacity and resilience. Conversely, excessive reliance on policy interventions may constrain local self-organization and adaptive governance. The study highlights the complexity of balancing ecological sustainability with economic growth, underscoring the need for flexible and inclusive policy frameworks. Furthermore, the findings indicate that integrating top-down policies with community-based governance can effectively mitigate external pressures. Key recommendations involve promoting economic diversification via agroecology and cultural tourism, enhancing local governance capacity, and adopting adaptive environmental policies. These strategies are crucial for reducing dependence on traditional agriculture and alleviating resource pressures. The insights gained from this study deepen the understanding of restoration mechanisms in ecologically fragile areas and contribute to the development of effective strategies for sustainable management.

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.

Traditional development models are being slowly replaced by green economic development models. This paper views regional green economic development as a large complex system and develops a conceptual DPSIR (drivers, pressures, state, impact, response model of intervention) to construct a regional green economy development measurement index system, after which an entropy weight-TOPSIS-coupling coordination degree evaluation model is developed to quantitatively horizontally and vertically analyze regional green economy sustainable development trends and the coupled coordination status of each subsystem. The evaluation model is then employed to analyze the sustainable development of the green economy in Shandong Province from 2010 to 2016. The analysis results were found to be in line with the actual green economy development situation in Shandong Province, indicating that the measurement model had strong practicability for regional green economy development. Meanwhile, this model can demonstrate clearly how those indicators impact on the regional green economy sustainable development and fill the absence of existing studies on regional green economy sustainable development.

Building resilient cities has become an emerging risk management strategy, thus it is necessary to make a scientific evaluation on urban resilience. In this study, both the Driving Force-Pressure-State-Impact-Response (DPSIR) framework and the BP neural network are innovatively adopted to construct a comprehensive urban resilience evaluation system. Prefecture-level cities in Hubei Province are examined for empirical analysis. The results show that: (1) The urban resilience in Hubei Province exhibits an intermittent growth pattern, progressing in a west-to-east direction. This growth is characterized by three years of advancement followed by a one-year period of stagnation. (2) There is a spatial negative correlation. Owing to uneven development within Hubei Province, it can be seen that Wuhan, the provincial capital, holds a dominant position. (3) Resource and environmental pressure has become the main obstacle to the construction of resilient cities in Wuhan. The primary limiting factors for other cities are the degree of socioeconomic growth and the capacity of the government to handle affairs. This study, based on the process-oriented nature of resilience, constructs an indicator system for urban resilience evaluation under the DPSIR framework, fully reflecting the characteristics of urban resilience. It not only enriches the theory and methodology of urban resilience evaluation but also offers valuable references for governments to formulate effective strategies for sustainable urban development.

Globally, forests provide several functions and services to support humans’ well-being and the mitigation of greenhouse gases (GHGs). The services that forests provide enable the forest-dependent people and communities to meet their livelihood needs and well-being. Nevertheless, the world’s forests face a twin environmental problem of deforestation and forest degradation (D&FD), resulting in ubiquitous depletion of forest biodiversity and ecosystem services and eventual loss of forest cover. Ghana, like any tropical forest developing country, is not immune to these human-caused D&FD. This paper reviews Ghana’s D&FD driven by a plethora of pressures, despite many forest policies and interventions to ensure sustainable management and forest use. The review is important as Ghana is experiencing an annual D&FD rate of 2%, equivalent to 135,000 hectares loss of forest cover. Although some studies have focused on the causes of D&FD on Ghana’ forests, they failed to show the chain of causal links of drivers that cause D&FD. This review fills the knowledge and practice gap by adopting the Driver-Pressures-State-Impacts-Responses (DPSIR) analytical framework to analyse the literature-based sources of causes D&FD in Ghana. Specifically, the analysis identified agriculture expansion, cocoa farming expansion, illegal logging, illegal mining, population growth and policy failures and lapses as the key drivers of Ghana’s D&FD. The study uses the DPSIR analytical framework to show the chain of causal links that lead to the country’s D&FD and highlights the numerous interventions required to reverse and halt the ubiquitous perpetual trend of D&FD in Ghana. Similar tropical forest countries experiencing D&FD will find the review most useful to curtail the menace.