Complex Environmental Problems Research Articles

AN ANALYSIS OF ECOPEDAGOGICAL APPROACH IN SOCIAL STUDIES LEARNING TOWARDS STUDENTS' ECOLOGICAL INTELLIGENCE

Environmental issues are the center attention to ensure the sustainable development. Ecological intelligence is one of the important abilities that students have to maintain sustainable development. The important way to intervene students' ecological intelligence can be done through learning based on ecopedagogical approach. This research aims to determine the effect of the ecopedagogical approach in social studies learning on students' ecological intelligence. This research uses a quantitative using a quasi-experimental method. The sampling in this study used a purposive sampling technique, with a total sample of 60 students at MTs Negeri 1 Pamekasan who were divided into 2 (two) classes, namely class VII A as the control class, and class VII C as the experimental class. Based on the results of the research that has been carried out, the following conclusions can be drawn; In the experimental class the average N-Gain was 71.26. Meanwhile, the control class had an average N-Gain of 48.11. Then the t-test shows that the sig value. (2-tailed) of 0.000<0.05 which can be concluded that there is a significant (real) difference in effectiveness between the effect of using an ecological approach in social studies learning on students' ecological intelligence compared to conventional learning. Finally, an ecopedagogical approach in social studies learning needs to be developed to foster sensitivity regarding the complexity of environmental problems in order to contribute to environmental issues.

Teaching and Learning Social Innovation and Entrepreneurship in Higher Education: A Scoping Review

Social innovation and entrepreneurship (SIE) has emerged as a well-recognised field of practice and research amidst the intensified societal focus on complex social and environmental problems. Universities, as critical producers of knowledge and talents, are increasingly expected to create academic offerings that nurture leaners’ capacities for positive social change. However, research on SIE educational processes remains scant and is scattered among various disciplines. There is a lack of understanding of the overall development of SIE education in universities. This scoping review fills this gap by providing an overview of what drives universities’ adoption of SIE education and the current SIE curricula. It integrates studies that describe various SIE courses, focusing on curricular content, pedagogical practice, and outcome assessment. The review (1) identifies the major educational aims underpinning universities’ SIE offerings, (2) develops an integrative framework that specifies four approaches to SIE education, (3) synthesises and illustrates SIE teaching and learning practices, and (4) outlines opportunities for future research. The framework differentiates between education ‘about’, ‘for’, ‘through’, and ‘embedded with’ SIE. These approaches differ in the way educators conceptualise SIE and the way students engage with societal problems. The review also points to substantial gaps in our understanding of how to assess the impact of SIE education and how to sustain these novel educational practices within the university. It provides a base for integrating and advancing knowledge across the largely disparate literature on SIE education and highlights avenues for future research that can unpack SIE educational processes.

Eksistensi Direktorat Jenderal Penegakan Hukum Lingkungan Hidup dan Kehutanan dalam Penanganan Kasus Pencemaran Lingkungan oleh Pabrik Pengolahan Kelapa Sawit di Riau

Indonesia faces complex environmental problems due to management that is out of balance with economic and population growth. One prominent case is the alleged environmental pollution by PT SIPP in Bengkalis, Riau, involving unauthorized waste disposal and damage to a wastewater treatment plant (WWTP). This study aims to describe the role of the Directorate General of Environmental and Forestry Law Enforcement (DG Gakkum LHK) in handling the case. Using a qualitative approach and descriptive method, data was collected through a literature study covering environmental pollution regulations and similar cases. The DG Gakkum LHK, which falls under the Ministry of Environment and Forestry, plays an important role in environmental law enforcement through technical policies, supervision, investigation, and application of administrative and criminal sanctions. Since its establishment in 2015, DG Gakkum has improved law enforcement with a multi-instrument approach and cooperation with civil society and relevant law enforcement. In the PT SIPP case, DG Gakkum took decisive action by arresting two company officials and revoking the business license. This research highlights the important role of DG Gakkum in maintaining environmental quality and the sustainability of natural resource management, as well as the challenges faced in enforcing environmental law in Indonesia. Efforts to increase public and business awareness about the importance of environmental protection as well as effective cooperation between government agencies and the community are key in addressing environmental issues holistically.

Artificial intelligence and machine learning in environmental impact prediction for soil pollution management – case for EIA process

Scientific predictions are a key component of Environmental Impact Assessments (EIA), which can indicate the level of change within an environmental sphere (e.g., soil). As part of the EIA process, decision-making in mitigating complex environmental problems such as maintaining soil quality can be challenging, especially in data-sparse locations. Artificial Intelligence (AI) can ameliorate but the literature suggests that the deployment of Machine Learning (ML) techniques in soil research is concentrated mostly in developed countries. The potential of ML in managing soil pollution from complex mixture of heavy metals, petroleum hydrocarbons, and physicochemical factors is rarely explored. To address this research gap, we built robust models that increase the accuracy of impact prediction based on new experimental soil data from a data-sparse region of Africa (i.e., Nigeria). The algorithms applied are artificial neural networks (ANN), support vector regression (SVR), regression tree (RT), and random forest (RF). The study also implemented a multivariate linear regression (MLR) model as a baseline. Key findings include (a) the MLR model performed less than the machine learning models largely due to the nonlinearity of data; (b) Log-normalization helped to improve the predictive capability of all models as the effects of statistical variability were removed; (c) the RF model had the best performance in terms of correlation coefficient, mean absolute error, and root mean square error, and (d) the machine learning models showed improved performance with increased correlation and lower error between the actual and predicted soil electrical conductivity values. Our results imply that data sparsity may no longer be an excuse for the non-use of quantitative impact prediction in Environmental Impact Assessment (EIA) processes. This could change how EIAs are conducted and enhance sustainability in natural resource exploitation, globally. Future work will apply algorithms for automated feature selection to obtain optimal subset of soil quality measurements that will further improve the accuracy of the models.

Disintegration and discourse: Cross-sectoral story-lines in the German water and forest debates

Policy integration (PI) has been advocated in the literature as a solution to complex environmental problems. It is commonly defined as the joint development of policies across sectors, and deemed beneficial especially in face of cross-cutting issues. As there is little research addressing the ideational integration of two sectors, we introduce a new framework to discursively analyze horizontal policy integration (HPI) and then apply this framework to the German water and forest sectors. We follow the question whether in the context of interlinked forest and water disturbances cross-sectoral story-lines on German national level have occurred, which we assess by examining the story-line’s complexity, integration of other sector’s concerns, and cross-sectoral use. Although disturbances in the water and forest sectors are becoming more frequent, a fragmentation of the water and forest sectors has been observed in Germany in the past. The analysis is based on Hajer’s (1995) definition of discourse and follows his concept of story-lines which can be understood as the lowest common denominator across actor groups. We analyze policy documents on German national level, covering the debate on water and forest disturbances between 2018 and 21. Our results show that in the debates on water and forest disturbances there are commonly used story-lines across sectoral boundaries. The framework, however, enabled us to show an asymmetrical integration across sectors, where the forest sector addresses water concerns while the water sector treats forests as a non-subject.

The impact of Q-learning parameters on robot path planning problems in different complex environment

With the development of reinforcement learning algorithms, its efficient problem-solving model and the universality of the method have been favoured by many scholars. More and more robot path planning problems are solved using reinforcement learning methods. This article focuses on the Q-learning algorithm, uses MATLAB to study the impact of Q-learning parameters on robot path planning problems in different complex environments, and tries to find the optimal solution to the parameters. Research has found that environmental complexity has a significant impact on the speed at which robots solve path planning problems, and the optimal solutions to problem parameters in different environments require detailed analysis of specific problems.

From input–output analysis to the quantification of metabolic patterns: David Pimentel’s contribution to the analysis of complex environmental problems

AbstractThis paper revisits David Pimentel’s work on input–output analysis of agricultural production systems with the objective of demonstrating its (continued) relevance for the analysis of complex environmental issues. It is shown that his unique accounting procedure is grounded in complexity theory and that it effectively links expected relations over primary inputs and outputs exchanged with the ecosphere and secondary inputs and outputs exchanged with the anthroposphere (including labor). New conceptual building blocks are introduced to demonstrate that Pimentel’s analysis can be extended across different hierarchical levels (crop typologies, commodity supply systems, agricultural regions, etc.) and dimensions of analysis to obtain a formal representation of the metabolic pattern of social–ecological systems. These concepts include: (i) state–pressure relation (extensive properties); (ii) flow–fund ratios (intensive properties), i.e., qualitative benchmarks to define typologies of agricultural production in relation to both the socioeconomic process (e.g., land productivity, labor productivity) and the environmental pressure exerted on the environment (e.g., water consumption, GHG emission and pesticide load per hectare); and (iii) relational analysis to scale up the analysis to higher hierarchical levels so as to acquire policy relevance. Examples of the pertinence of this formalization are illustrated using Pimentel’s original data on grain cultivation in the USA. It is concluded that Pimentel’s work has set an example for a holistic approach to complex environmental problems and has paved the way for a more general conceptualization of social–ecological systems as metabolic systems.

Study on the factors influencing ecological environment and zoning control: a study case of the Dongting Lake area

IntroductionProtecting the ecosystem of the Dongting Lake area is of utmost importance for maintaining ecological balance and achieving human well-being.MethodsThis study identifies the key factors influencing the remote sensing based ecological index (RESI) in the Dongting Lake area based on the spatial and temporal evolution characteristics of the RESI and environmental changes and anthropogenic disturbance factors. The priority zoning for ecological restoration was delineated in combination with the anthropogenic composite index (ACI). By exploring the influence of anthropogenic disturbances on RESI, the zoning locations were determined using spatial statistics and linear regression methods.ResultsThe overall RESI of the Dongting Lake area showed a decline from 2001 to 2020, with the mean value decreasing from 0.52 to 0.48. High-quality zones were mainly located in mountainous and forested areas, while low-quality zones were mainly distributed in more developed cities in the east urban area. Anthropogenic factors were the main reasons for the decline in the ecological environment, while natural factors showed a positive correlation with RESI. Based on the RESI and ACI, four ecological control zones (H-H, H-L, L-H, and L-L) were delineated, which accounted for a total of 45.66% of the Dongting Lake area. Among them, 3.91% required immediate control and management, while 17.80% required artificial maintenance. This study explores the influencing factors and mechanisms of the ecological environment quality in the Dongting Lake area, and explores the effective spatial paths for the implementation of ecological restoration zoning control and differentiated restoration strategies in the Dongting Lake area.DiscussionThis study provides a scientific basis for mitigating ecological and environmental problems in the Dongting Lake area, and provides a reference for ecological restoration and regulation and the realization of sustainable development goals in China and global regions with complex environmental problems.

Modified Noise-Immune Fuzzy Neural Network for Solving the Quadratic Programming With Equality Constraint Problem.

Quadratic programming with equality constraint (QPEC) problems have extensive applicability in many industries as a versatile nonlinear programming modeling tool. However, noise interference is inevitable when solving QPEC problems in complex environments, so research on noise interference suppression or elimination methods is of great interest. This article proposes a modified noise-immune fuzzy neural network (MNIFNN) model and use it to solve QPEC problems. Compared with the traditional gradient recurrent neural network (TGRNN) and traditional zeroing recurrent neural network (TZRNN) models, the MNIFNN model has the advantage of inherent noise tolerance ability and stronger robustness, which is achieved by combining proportional, integral, and differential elements. Furthermore, the design parameters of the MNIFNN model adopt two disparate fuzzy parameters generated by two fuzzy logic systems (FLSs) related to the residual and residual integral term, which can improve the adaptability of the MNIFNN model. Numerical simulations demonstrate the effectiveness of the MNIFNN model in noise tolerance.

Використання інформаційних технологій в екології та процесах охорони навколишнього середовища

The article presents the results of a study of existing software products that are the most popular and in demand in the processes of ecology and environmental protection. An overview of automated design tools for the field of ecology in Ukraine is given. An overview of the market of automated design tools for the field of ecology was conducted, and their characteristics were given. An overview of integrated management systems in ecology and environmental protection is presented. The application of information technologies in the processes of ecology and environmental protection is that natural resources are now under significant pressure due to industrialization, expansion of urban areas and other human activities. This leads to pollution of air, water and soil, destruction of ecosystems, loss of biodiversity and other negative consequences for the environment. The use of information technology can be a key tool in combating these problems. In the field of the use of information technologies in ecology and environmental protection, the significant potential of these technologies for solving various environmental problems is confirmed. Many software products used in the field of ecology are associated with the use of GIS (geographic information systems) [1], the first period of their development began in the 1950s and 1970s with active topographic surveys [2], which in the later 1980s prompted the arrival of government customers to create commercial products using databases. Some key aspects that stand out from these studies include: 1. Monitoring of the state of the environment: Application of modern information technologies: satellite imaging; collection of environmental parameters; registration sensors; the accumulation of observation data and their analysis allows to get an idea, mostly expressed in quantitative estimates, about the state of air, water and soil pollution, as well as about changes or their trends in landscapes and biocenosis. This allows you to effectively identify problem areas and respond to environmental threats in a timely manner. 2. Forecasting environmental events: The use of analytical methods and algorithms of artificial intelligence makes it possible to predict the development of environmental crises, such as natural disasters, climate change, and the destruction of ecosystems. It helps to develop strategies to prevent and minimize negative impact on the environment. 3. Resource and waste management: Information technology is used to optimize the use of natural resources, as well as for efficient waste management and renewable energy sources. This helps to conserve resources and reduce the negative impact on the environment. 4. Public participation and education: Information technologies allow raising public awareness of environmental problems, facilitating the dissemination of information and stimulating active public participation in environmental protection programs. 5. Innovative solutions: The latest technologies, such as blockchain, the Internet of Things (IoT), as well as developments in the field of bioinformatics and nanotechnology, open up new opportunities for solving complex environmental problems and ensuring sustainable development.

Environmental education in the formation of transprofessional competencies among future ecologists

The purpose of the scientific article consider the importance of developing creative thinking among bachelors of technical ecologists. In today's world, where complex environmental problems require new and innovative solutions, environmentalists need to have the ability to think creatively. The article discusses practical methods and strategies that can be used by teachers to develop creative thinking in the educational process. In conclusion, the article points to the need to integrate creative thinking into undergraduate environmental education programs in order to ensure their successful participation in the development and implementation of solutions aimed at preserving the environment. Scientific hypothesis: creative thinking used in active and practical teaching of bachelor students in ecology contributes to the development of their creativity, problem-oriented thinking and environmental problem solving abilities, which improves the quality and efficiency of their professional activities.

Book Review of Modeling and Simulation of Environmental Systems:A Computation Approach

Water and air are important elements of the interactions that make up the environmental continuum, and these factors are critical to our lifestyles, economic well-being, and the health and integrity of ecosystems. With the development of advanced computational modelling, numerical techniques and fast computers, some complex environmental management problems can be solved by computational modelling. Modeling and Simulation of Environmental Systems: A Computation Approach is an English-language monograph in the field of modeling and simulation of environmental systems (published by CRC Press) , which is divided into four chapters, Water Resources, Air Pollution, Internet of Things and Environmental Systems, and Future Algorithms in Environmental Systems. Future Algorithms in Environmental Systems, presents four chapters on modeling and simulation of environmental systems and related case studies, covering computational methods used to solve air and water pollution problems, a general approach to spatio-temporal analytical modeling, the use of formulas, algorithms, and techniques to build mathematical modeling, and a pathway to the implementation of formulas for complex modeling problems. This paper briefly introduces the authors of the work, systematically sorts out the chapter structure of the book, and analyzes the application of some of the environmental models as well as the opportunities and challenges of using them. The work demonstrates how models, metrics, and ecological processes can be directly applied to environmental subdisciplines and can provide guidance and reference for environmental practitioners and research engineers.

A New Blueprint of Collaboration the Science Culture Construction fostering innovation and green development

In an era defined by the urgency of environmental challenges, a transformative paradigm is emerging: a fusion of collaboration and building scientific culture that catalyzes innovation for sustainable green development. This brief explores the dynamic interplay between collaboration and science culture, emphasizing their collective impact on fostering innovative solutions to propel us towards a greener, more sustainable future. The new paradigm of collaboration transcends disciplinary boundaries, fostering the convergence of diverse perspectives and experiences. This brief argues that cross-pollination of ideas and skills, facilitated by collaborative efforts, cultivates an environment conducive to innovation. The synthesis of collective intelligence and the establishment of a collaborative ecosystem become essential drivers to address complex environmental problems, leading to novel solutions in the field of green development.

A Hierarchical Lane-Changing Trajectory Planning Method Based on the Least Action Principle

This paper presents a hierarchical lane-changing trajectory planner based on the least action principle for autonomous driving. Our approach aims to achieve reliable real-time avoidance of static and moving obstacles in multi-vehicle interaction scenarios on structured urban roads. Unlike previous studies that rely on subjective weight allocation and single weighting methods, we propose a novel trajectory planning strategy that decomposes the process into two stages: candidate trajectory generation and optimal trajectory decision-making. The candidate trajectory generation employs a path-velocity decomposition method, using B-spline curves to generate a multi-objective optimal lane-changing candidate path. Collision checking eliminates paths at risk of collision with static obstacles. Dynamic programming (DP) and quadratic programming (QP) are then used to plan the velocity of safe paths, generating candidate lane-changing trajectories based on curvature checking. The optimal trajectory decision-making process follows the decision mechanism of excellent drivers. We introduce a comprehensive evaluation function, the average action, which considers safety, comfort, and efficiency based on the least action principle. Feasible trajectories are ranked based on their average action, and the trajectory with the minimum average action and no collision risk with moving obstacles is selected as the tracking target. The effectiveness of the proposed method is validated through two common lane-changing scenarios. The results demonstrate that our approach enables smooth, efficient, and safe lane-changing while effectively tracking the planned velocity and path. This method offers a solution to local trajectory planning problems in complex environments and holds promising prospects in the field of autonomous driving.

Structure and tribocorrosion properties of ultralubricated (TiAlCrSi)C multicomponent coatings prepared by FCVAD

To address corrosion and friction problems in complex environments, traditional protective coatings are gradually replaced by multicomponent coatings. In this work, a (TiAlCrSi)C multicomponent coating with ultralubrication (COF < 0.1) and excellent corrosion resistance was prepared by FCVAD technology with regulated C2H2 flow. The composition, structure, roughness, dry friction, corrosion and tribocorrosion of the (TiAlCrSi)C coating were analyzed. The results show that the (TiAlCrSi)C coating shows an amorphous structure, and the addition of carbon improves the degree of amorphization of the coating. Carbon exists in the form of carbide and amorphous carbon in the (TiAlCrSi)C coating, the carbon content saturation of the coating is about 70 at.%. The formed carbides and sp2-C in the (TiAlCrSi)C coating have extremely low COFs and good wear resistance. The high proportions of amorphous carbon and sp2-C improve the self-lubricating and nonmetallic properties of the (TiAlCrSi)C coating, which makes the coating have good tribocorrosion resistance in 5.0 wt% H2SO4 solution. The wear mode of the coating changes from abrasive wear to adhesive wear. Therefore, the (TiAlCrSi)C coating has great potential application value for tribocorrosion surface protection in a 5.0 wt% H2SO4 solution environment.

CONVERSION OF CARBON-CONTAINING RAW MATERIAL USING PLASMA TECHNOLOGIES

The state of development of plasma gasification technologies of carbon-containing raw materials in Ukraine is analyzed. It is shown that despite some pessimistic domestic assessments of the prospects for their development, the state of research and development in this field at the global level indicates the inevitable breakthrough directions for the development of such technologies and, first of all, in the field of hydrogen energy. In particular, this concerns the prospects of using such difficult-to-process raw materials for hydrogen production as, for example, sewage sludge or worn automobile tires. This will create an additional powerful effect from their implementation, bearing in mind the solution of complex environmental problems of modern Ukraine. The experimental part of this work is devoted to the study of the prospects of such processing, using the example of a laboratory version of a plasma chemical reactor, made according to the scheme of the process of inverted gasification of solid organic raw materials with the introduction of a plasma jet into the pyrolysis zone. The output of hydrogen depended on the raw material: the lowest one was from sewage sludge pellets, and the highest one was from rubber crumb of worn automobile tires; in the case of gasification of a mixture of sewage sludge pellets and rubber crumb, an intermediate value of this indicator was observed. It is important that the output of hydrogen was determined not so much by its content in the raw material, but by the reactivity of the latter, which also corresponded to the degree of use of water vapor. The level of reactivity determined the degree of use of water vapor in the case of pellets up to 29 %, and rubber crumb up to 56 % and, accordingly, the chemical efficiency of gasification reached 39 % and 55 %. It follows from the results of the research that in the conditions of relatively low temperatures in the experimental reactor, the mixing of pellets of sewage sludge and rubber crumb does not create a synergistic effect of advantages regarding the energy efficiency of the process. Bibl. 58, Fig. 4, Tab. 4.

The Drivers of Farmers&amp;rsquo; Participation in Collaborative Water Management: A French Perspective

Collaborative management has developed as a main approach to solving complex environmental problems such as diffuse water pollution from agriculture. This paper aims to understand the drivers of farmers’ participation in collaborative water quality management. The role of farm characteristics, farmers’ profiles and farmers’ social networks is more particularly investigated while taking into account transaction costs. The study relies on a statistical analysis of data collected in two drinking water catchments in France. The results show that larger, more profitable farms with more equipment and access to off-farm income are more likely to participate in collaborative processes for water quality management. Furthermore, farmers’ involvement in agricultural and nonagricultural networks has a strong positive influence on their participation. These results suggest that significant costs, including transaction costs, are associated with farmers’ participation in collaborative management. Targeted support for smaller, financially constrained farms and less-connected farmers could enhance the effectiveness of the collaborative approach to diffuse pollution control.

Analysis of The Need for Green Open Space (RTH) as an Absorptor of Carbondioxide Gas Emissions in The Semarang-Yogyakarta National Road Corridor, Bergas District, Semarang Regency

Semarang Regency is one of the areas in Central Java Province which has a variety of complex environmental problems, one of which is increasing carbon dioxide gas (CO2) emissions and the limited availability of green open space, especially in the Bergas District area. The increase in CO2 gas emissions is due to the increasing trend of the population in Bergas District and this is directly proportional to the increasing number of ownership of motorized vehicle transportation. This study aims to examine the need for Green Open Space based on the ability of vegetation to absorb carbon dioxide (CO2) on the Semarang-Yogyakarta National Corridor Road, Bergas District, Semarang Regency, Central Java Province. Data collection in this study was carried out by traffic counting to calculate CO2 emissions and field observations to calculate the absorption capacity of CO2 emissions by vegetation. The results of this study indicate that the emissions produced by vehicles passing through the Semarang - Yogyakarta National Road corridor in Bawen District are 4,108,137.18 gr/hour, and emissions that can be absorbed by vegetation are only 642,846.47 gr/hour. So that the remaining emissions that have not been absorbed are 3,465,290.71 gr/hour. In order to optimally absorb the remaining emissions, at least 370 Swietenia mahagoni, 436 Pterocarpus indicus, 358 Samanea saman and 432 Bauhinia purpurea are needed.

Impacts of vegetation restoration on soil erosion in the Yellow River Basin, China

Soil erosion is a serious and complex environmental problem, which directly leads to soil degradation and reduces land productivity. Analyzing the effect of vegetation restoration on soil erosion is the main way to quantitatively evaluate the contribution of vegetation restoration to soil erosion in semi-arid. This study utilized the RUSLE model and Geodetector method to quantitatively characterize the spatio-temporal dynamics of soil erosion and the contribution of FVC to erosion mitigation in the Yellow River Basin (YRB) since the implementation of the Grain for Green Project (GGP). The main findings are concluded as follows: (1) The fractional vegetation cover (FVC) in the YRB showed an overall increasing trend, with an average annual change rate of 0.006 a−1. (2) Soil erosion in YRB increased from 1999 to 2010, with a 10% increase in soil erosion intensity, and from 2010 to 2018, soil erosion improved significantly with a 31% decrease in soil erosion. The severe erosion areas were mainly concentrated in the Loess Plateau (LP) and the source area of the Yellow River (YR), which generally showed northeast-southwest banding changes. (3) FVC has a relatively stronger explanatory power for soil erosion in the YRB. FVC explained 5% of soil erosion, but the combination of FVC and land use, as well as the combination of FVC and slope, collectively explained 47% of soil erosion. The ecology of the YRB greatly benefits from the implementation of the GGP and other water conservation projects. But there are still necessities to formulate targeted soil and water conservation measures base on careful investigation of local conditions.

How tourists’ negative and positive emotions motivate their intentions to reduce food waste

Food waste significantly contributes to complex socioeconomic and environmental problems. The tourism sector is not immune to these sustainability challenges. This research examines how both negative and positive emotions build tourists’ intentions to reduce food waste. The study employs two experiments and a survey to establish causality among the key constructs and test the nomological network of those constructs. Results demonstrate a causal relationship between guilt, regret and hope and how these constructs interplay to explain the impact of a tourist’s perceptions of potential cost and harm from not implementing food waste-reduction practices. Additionally, four tourist categories are developed using fuzzy-set Qualitative Comparative Analysis (fsQCA). The results of fsQCA identify different configurations of tourists who seek to reduce food waste. This study encourages tourism operators to leverage positive emotions, such as hope, in marketing communications to encourage food waste reduction. A key contribution of this work is the examination of the variable of ‘hope’, and its effect in the context of food waste behaviour among tourists. This is the first study to examine how the interaction between tourists’ negative (guilt and regret) and positive (hope) emotions motivates their intentions to reduce food waste.