Complex Environmental Problems Research Articles

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.

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.

Engaging Stakeholders to Solve Complex Environmental Problems Using the Example of Micropollutants

Engaging Stakeholders to Solve Complex Environmental Problems Using the Example of Micropollutants

OXIDATION METHODS FOR PHENOLE-CONTAINING WASTEWATER TREATMENT

One of the most complex environmental problems generated by the development of human economic activity is the problem of the negative impact of chemically polluted territories on the objects of the hydrosphere. A lot of toxic compounds, getting into water reservoirs, cause the water area deterioration, the death of their flora and fauna, make the water unusable either for drinking nor for cultural and household  needs. Recently, the attention of specialists has been attracted by a group of persistent organic pollutants. All these substances belong to the class of organochlorine pollutants, as well as by-products of hydrocarbon production (for example: dioxins, furans, formaldehydes, phenols). These substances are resistant to decomposition and toxic. Among the most dangerous water pollutants, along with heavy metal ions, petroleum products, surfactants and polyaromatic compounds, are phenol and its derivatives. Phenol-containing wastewater is generated at enterprises of the pulp and paper, woodworking, food industries, leather, chemical, coke, petrochemical industries, etc. When even a small amount of phenolic compounds gets into a water body, the reservoir self-cleaning capacity decreases. In this regard, the problem of an objective assessment of hydrosphere pollution by phenols and its derivatives and the search for new effective methods of wastewater treatment are urgent tasks. The paper describes oxidation methods for wastewater treatment from phenol.

The Evolutionary Emergence of Quintuple Helix Coalitions: A Case Study of Place-Based Sustainability Transition

Abstract Complex societal, environmental, and economic challenges are affecting the post-covid-19 societies. They must increasingly rely on multi-stakeholders’ and multi-domain coalitions to find innovative solutions and achieve sustainability transitions in the near future. Triple helix model featuring interactions among academia, industry, and government successfully explained collaboration in technological innovation dynamics. The models integrating a fourth helix., i.e., bringing knowledge from the civil society and a fifth helix i.e., bringing knowledge from the natural environment, emerged to understand innovations addressing complex societal and environmental problems. By adopting an evolutionary perspective and incorporating agency in the quintuple helix, we propose a conceptual framework to shed light on how multi-domain coalitions might emerge in local productive systems engaging in sustainability transitions. Drawing on this framework, we analyze the case of a rural local system where a quintuple helix coalition emerges together with the development and adoption of sustainable agronomic practices triggering a sustainability transition process.

Creating Green Circular Economy in Waste Management: The Kampung Hijau Bank Sampah Al-Haqiqi Case

The concept of the circular green economy strives to address the issue of waste generated by society, aiming to prevent it from becoming a more complex environmental problem. This study aimed to comprehensively analyze the efforts of PT Pertamina Patra Niaga DPPU Bandara Internasional Lombok through the CSR program “Kampung Hijau Bank Sampah Al-Haqiqi” in changing the community’s paradigm in waste management. This study employed a qualitative method with a case study approach. The data used in this research included primary data collected through observations and interviews with beneficiaries. Secondary data were gathered from program implementation reports, monitoring and evaluation reports, and supplemented with relevant journal articles. This study reveals that 1) The CSR program of Al-Haqiqi Waste Bank adopts a new paradigm for waste management and assists in changing community habits regarding household waste management 2) Kampung Hijau Bank Sampah Al-Haqiqi program encourages the emergence of the circular economy, leading to not only environmental sustainability but also economic improvement 3) Kampung Hijau Bank Sampah Al-Haqiqi program accelerates the achievement of development goals, particularly focusing on SDG Goal 12 and the reduction of GHG emissions, amounting to 893 kg of CH4 and 17,860 kg of CO2.

Separating method for multi-source vibration signals in ultra-weak fiber Bragg grating distributed acoustic sensors

Mixing multi-source vibration signals presents a major challenge in target recognition in distributed fiber optic acoustic sensor systems. This article proposes a deep learning method for separating ultra-weak fiber Bragg grating (UW-FBG) distributed acoustic sensor (DAS) multi-source signals. An experimental setup is constructed to create vibration environments for knocking, fan vibration, and steel pipe friction. The UW-FBG DAS system is used to collect single-source vibration signals, as well as two-source and three-source mixed vibration signals. First, a wavelet denoising algorithm is used to preprocess the data. Second, the datasets are constructed for simulated mixed signals and measured mixed signals. The Conv-TasNet deep learning network is utilized to separate DAS vibration signals. Results demonstrate that the proposed method can separate mixed signals of vibration, fan, and steel pipe friction sources, obtaining the corresponding time–frequency entropy similarity of 97.5%, 92.8% and 90.2%, and compared with commonly used multi-source signal separation methods, it has advantages in separation performance and separation time, and exhibits good robustness in different signal environments. This finding the efficacy of the separation method and provides a valuable solution for DAS multi-source signal separation problems in complex environments.

Air Quality Monitoring in Coal-Centric Cities: A Hybrid Approach

Despite the increasing time sensitivity of climate change, many cities worldwide still heavily rely on coal. The extraction, processing, transport, and usage of coal lead to deteriorated air quality, resulting in complex environmental and public health problems for the local communities. Mapping different pollution sources in coal-centric cities is not trivial due to the hyperlocal nature of air pollution and the often low-density network of air quality monitors. This study explores the air quality issues surrounding coal-centric cities using a combination of qualitative and quantitative data from reference-grade air quality monitors, low-cost sensors (LCSs) deployed on citizens’ vehicles, and community engagement activities. It explores how LCSs can be used to characterize air quality at a high spatio-temporal resolution and how this information can be used to decode people’s perceptions of air quality issues and elicit local knowledge. We evaluated our approach in Sparwood (Canada), and Oskemen (Kazakhstan) which are very different cities, but are both heavily dependent on coal. LCSs have been proven an efficient tool to identify pollution hotspots that traditional reference monitors miss, while workshop-based activities making use of data maps and coding tools have successfully elicited information about pollution sources from non-experts, helping collaborative sense-making and informing new LCS deployment strategies. Understanding air quality in coal-centric cities as a complex socio-technical phenomenon can enable the coal industry, city officials, and residents to engage in addressing air quality issues.