Environmental Science & Policy最新文献

The Sustainable Development Goals (SDGs) consist of a set of multidimensional indicators comprising 17 goals and 169 targets from various perspectives. The use of a composite index is crucial for assessing the overall performance of each country in relation to the SDGs, given the extensive range of indicator measures involved. However, different weight schemes may lead to different results. Therefore, incorporating an objective weight is required to ensure the comparability and accuracy of the index. The main objective of this paper is to construct an SDG index for Organisation for Economic Co-operation and Development (OECD) countries using an effectiveness-based hierarchical data envelopment analysis (H-DEA) model and apply it to assess SDG effectiveness in OECD countries. The results of this study provide countries with more valuable insights based on the weights of the goals (indicators) that are endogenous to the dataset, assisting them in identifying priorities and strategies to improve future SDG performance.

The urgent need for climate change adaptation is becoming more pronounced as climate impacts pervade across all scales. To overcome growing constraints on adaptation, research on the social dimensions of adaptation behaviour is of increasing importance. In this respect, there is an expanding body of literature exploring how place attachment influences climate adaptation. However, studies on this relationship have thus far been sporadic and disconnected. We set out to evaluate existing literature with the goal of seeking a comprehensive perspective of current trends and gaps in research practice, and to identify whether place attachment aided or constrained adaptation. A systematic review was undertaken which identified 72 relevant research articles. We quantitatively assessed the research focus of these studies including the type of climate impact and type of adaptation being studied, as well as, study location, methods used and findings. We also conducted a thematic analysis of studies to elicit major emerging links related to attachment and adaptation. Our findings affirm the complex and dynamic nature of this relationship; specifically, we find that effect of place attachment on climate adaptation action are subject to the climate risk perceptions and personal values of the individual, contextual manifestations of climate change impacts, and local sociocultural processes. We identify several gaps in current research, particularly in terms of geography and demography which has implications for equitable climate adaptation. We highlight the need for longitudinal studies, especially from the perspective of successful climate planning and policy and changing environments; and emphasise the importance of incorporating comprehensive insight on place attachment in climate adaptation planning and decision-making processes.

The purpose of this paper was to analyze the performance of the G20 nations in terms of efficiency and productivity concerning achieving the seventh Sustainable Development Goal (SDG 7) of providing affordable and clean energy between 2010 and 2019 under a circular economy framework. The diagnostic tools to measure included the output-oriented Data Envelopment Analysis (DEA, SBM) to determine efficiency and the Malmquist Productivity Index (MPI) to measure productivity. In the DEA model, renewable energy is the primary energy source as inputs and outputs as total Greenhouse Gases (GHG) emissions, electricity consumption, and renewable energy consumption. The results indicated that the efficiency and productivity of developed and emerging countries towards the 7th SDG targets were heterogeneous throughout the analysis. The results showed that among the G20 countries that ranked as efficient were emerging countries (South Africa, Brazil, India, and China). Developed countries have more to gain in efficiency by designing strategies with sustainable development and environmental policies consistent with CE actions than emerging countries. In addition, since productivity gains increased more due to efficiency changes than technology gains, as indicated by the MPI analysis, it seems reasonable to infer that strengthening research and development of resource-efficient technologies could help to reach the 7th SDG faster by increasing productivity through adopting new technologies. In the short run, all countries could benefit from a multilateral effort to reduce climate change and GHG emissions if developed countries provided technological support to emerging countries and the latter offered carbon credits to the former in exchange for measures to mitigate the emissions resulting from their rapid economic growth driven by capital investment.

The science, technology, engineering, and mathematics (STEM) education research delves into the core of sustainable development goals (SDGs), including the pillars of quality education (SDG4), robust economic growth (SDG8), and diminished inequalities (SDG10). These pursuits stand as keystones in sculpting inclusive societies and bridging societal gaps. While previous studies utilising data envelopment analysis (DEA) have explored educational performance mainly from a macro-perspective, there is a lack of micro-perspective investigation. Our study aims to fill this gap by proposing a DEA approach to assess the relative efficiency of engineering classes. We analysed 70 classes covering 38 subjects in the first semester of 2022 at a South American school. Methodologically, we employed the slack-based measure (SBM) model under the benefit of doubt (BoD) condition. Unlike prior research, we analysed classes' relative performance considering different pedagogical approaches - 11 active-learning classes (15.7 %) and 59 passive-learning classes (84.3 %). Our results showed that 18 classes were efficient (25.7 %). Active classes were more efficient, but few subjects maintained similar efficiencies for all classes. Moreover, efficient classes were concentrated in the last two years prior to graduation (57.9 %). This may represent an additional barrier for low-income students, who tend to drop out in the first years. The findings support several improvement recommendations, such as integrating digital technologies, boosting active learning opportunities, and bolstering classes in foundational subjects. Also, implications for researchers, decision- and policy-makers are discussed. Our approach can be replicated in diverse educational contexts, enabling the identification of strengths and weaknesses for more efficient educational management.

This paper presents an examination of water risks in rural communities within Nagaon district of Assam, India. It employs a participatory approach to integrate community perspectives into the assessment process. The objective is to engage local people, gain an understanding of water risks they encounter in their everyday lives, and incorporate their opinions and experiences. To achieve this objective, the present analyses employ mixed methods, including stakeholder interviews, focus group discussions, household surveys, and community forums. Additionally, the development of the Participatory Water Risk Index (PWRI) provides a novel metric for quantifying and prioritizing water risks, aligning with local priorities and perspectives. The findings highlight the identification and evaluation of seven key parameters of water risk which include availability and sufficiency of drinking water, water quality issues, prevalence of water-related diseases, irrigation facilities, vulnerability to floods, and utilization of public water infrastructure. The study underscores the importance of community involvement and empowerment in addressing water-related challenges and promoting resilience. Policy recommendations derived from the research emphasize the need for context-specific approaches to water resource management, recognizing the unique challenges and strengths of each community within the district. The transferability of the PWRI to other locations offers substantial opportunities for improving water security worldwide, contingent upon careful consideration of context-specific parameters and community engagement. Thus, this paper contributes to the advancement of sustainable water management practices by integrating local knowledge into the assessment process, guiding future interventions to build a water-secure future for rural communities in Nagaon district and beyond.

Understanding lay people’s flood risk perceptions has become an essential component of flood risk management especially with respect to ascertaining possible responses both to risk situations and to government actions. However, different contextual factors determine how they respond, and little has been done in the African urban context to study flood risk perception trends. Using data from 612 household questionnaires, this paper documents the hazard-related and cognitive factors of flood risk perception (measured using perceived likelihood of flood-induced property damage, as the dependent variable) in 3 neighbourhoods of Kampala, Uganda. Correlation and ordinal regression analysis established a positive influence of flood experience on flood risk perception in 2 of the neighbourhoods. In contrast, it has a negative influence in the third neighbourhood, which also goes for existing mitigation measures. However, in the latter, flood-induced property damage and existing mitigation measures showed a positive influence. Additionally, flood-induced financial costs positively influence risk perception in two of the three neighborhoods. These differences are associated with case characteristics, including the widening of drainage channels and socio-economic characteristics, and partially confirm the findings from previous studies. The contextual trends provide insights to improve the application of the Protection Motivation Theory.

Formalization is an important aspect of the provision of scientific advice, which has received limited scholarly attention, and needs further conceptualization. Drawing on Adler and Bory’s distinction between enabling and coercive formalization, we analyze advisory processes in a boundary organization. We do so with a case study of the provision of annual fisheries advice by the International Council for the Exploration of the Sea (ICES). Based on interviews, we describe advantages and drawbacks of formalization in the views of ICES practitioners. Our findings highlight the importance of formalization and reveals ongoing challenges with navigating trade-offs between formalization and ad hoc adaptation. Despite a high level of formalization, respondents generally perceive that formalization approaches in ICES provide suitable guidance for the processes of stock assessment and advice formulation. However, they also emphasize the needs for deviations from standard procedures, justified with reference to peculiarities of situations. Lessons from ICES’ approach to formalization can be of use for other advisory contexts.

The efficient use of water must be enhanced and promoted to achieve the Sustainable Development Goal (SDG) 6. Thus, to contribute to the achievement of SDG Target 6.4 and close a research gap in SDGs’ progress, this paper carries out a water usage efficiency analysis of 126 countries leveraging the AQUASTAT database maintained by the Food and Agriculture Organization of the United Nations (FAO), providing information that can help assess and promote the sustainable use and management of water. The methodology uses a conceptual model that considers a Water Withdrawal (WW) stage and a Water Productivity (WP) stage, each one with its own set of variables, designing a customised non-parametric frontier analysis solution that identifies the countries with the best practices and uses them as benchmarks for global efficient water usage. In particular, the proposed approach uses a non-radial Directional Distance Function (DDF) that estimates the inefficiency along the different dimensions, both desirable and undesirable, quantifying potential improvement and computing an efficiency score for each stage and for the whole system. Due to the heterogeneity of the sample, a metafrontier analysis has been carried out. The results indicate that there are significant differences between countries and regions in terms of water usage efficiency. The regions with highest efficiency include Australia, Western and Central Europe and Southern and Eastern Asia, while Central Asia has the lowest. Most of the inefficiency corresponds to the Gross Value Added dimension and the WW stage efficiency is generally higher than that of the WP stage.

Improving green economic efficiency (GEE) and productivity are crucial for China to realize sustainable development goals. However, the economic growth of China has followed an extensive development model with high energy consumption and heavy pollution. This study conducts data envelopment analysis (DEA) to evaluate the GEE of China. First, we introduce the polar coordinates theory in the epsilon-based measure (EBM) model to construct a Ray epsilon-based measure (REBM) model. In addition to the merits of EBM model, the REBM model accounts for the weak disposable relationship between undesirable and desirable outputs. Second, based on REBM model, a REBM-Malmquist-Luenberger (REBM-ML) index is constructed to evaluate the green total factor productivity (GTFP). Finally, we conduct spatial econometric analysis to reveal the dynamic evolution of GTFP. According to the empirical results, the GEE of China is generally low, and the urban agglomerations located at coastal regions own higher GEE. However, the GTFP made progress overall, mainly benefited from the technical progress. Accordingly, in the process of sustainable development, China still faces the challenge of energy saving and emission reduction. The spatial econometric analysis reveals that the GTFP of China existed a significant divergence trend and there was spatial spillover effect between cities, as well as urban agglomerations. Furthermore, we provide policy implications and suggestions for Chinese sustainable development.

The promotion of sustainable tourism to advance the United Nations Sustainable Development Goals has garnered considerable attention. This paper aims to present a comprehensive analytical framework with data envelopment analysis (DEA) based index systems for examining the interaction between energy and the economic growth of tourism, with a specific focus on tourism destinations within the Yangtze River Delta region of China. The significance of energy in enhancing tourism economy efficiency is established by treating energy input as separable and disposable, while non-energy inputs are considered quasi-fixed. Subsequently, a quasi-fixed energy input directional distance function within the DEA framework has been developed to assess tourism economy efficiency. Furthermore, this paper explores the relationships among environmental pollution, tourism carbon emissions, and tourism economy growth using coupling coordination and decoupling models, respectively. The results indicate that, although improving, there remains a gap for tourism destinations to achieve integrated development between environmental and economic systems. The decoupling type of tourism destinations transitions from expansive negative decoupling to strong decoupling, and the relationship between tourism economic development and tourism carbon emissions tends to be coordinated. This paper provides an empirical study on the measurement of tourism economy efficiency and the relationship between carbon emissions, environmental pollution, and tourism performance. It advances understanding towards implementing sustainable and integrated regional development strategies.