Environmental Management Model Research Articles

Exploring spatial machine learning techniques for improving land surface temperature prediction

Land Surface Temperature (LST) is a crucial parameter in Earth observation and environmental studies due to its significance in various fields. The purpose of this study is to investigate the effects of including spatial information into the Random Forest (RF) and eXtreme Gradient Boosting (XGBoost) models for forecasting LST. The significance and impact of each input parameter on the models' predictive capabilities are assessed using the SHAP (SHapley Additive exPlanations) approach and the model intercomparisons were done using the error evaluation metrices. The predictions were further validated using the Pearson correlation, independent samples t-test and potential geographic anomalies in the predictions are examined by spatial comparison of predicted errors using classification maps and error envelopes. The projected errors are within the acceptable range and range from −2.267 °C to 1.292 °C for the spatially enhanced RF model and from −1.675 °C to 1.439 °C for the spatially enhanced XGBoost model. These error ranges closely align with the training data's quality flag of ±2 °C, demonstrating the models' capability to predict LST accurately and within a reasonable error range. The findings show the significance of adding spatial information for precise LST prediction and draw attention to possible uses for such models in environmental monitoring and management. The work advances our understanding of spatial modelling strategies and offers practical guidelines for enhancing LST forecasts.

Integrating IoT Sensors, Cloud AI, and Satellite Broadband for Enhanced ESG Governance in Smart Cities: A Tripartite Approach to Real-Time Environmental Monitoring

Urbanization is accelerating at an unprecedented rate, pushing the limits of environmental sustainability and demanding innovative solutions for effective management. Traditional methods for monitoring the environment fall short, lacking the scalability, immediacy, and comprehensive coverage required for modern urban settings. Our paper introduces an innovative solution to bridge these gaps, harnessing the power of Internet of Things (IoT) sensors, advanced cloud-based AI through Claude 3 Sonnet models on Amazon Bedrock, and the extensive reach of Project Kuiper's satellite broadband. This threefold integration forms a cutting-edge approach to urban environmental governance. It enables the analysis of environmental data in real time, offers predictive insights, and achieves wide-ranging coverage. The system equips city leaders, policymakers, and citizens with precise, actionable information, fostering decisions that align with Environmental Social Governance (ESG) goals. More than just improving urban life and sustainability, our approach makes environmental data accessible to all, promoting a collaborative and inclusive model of urban environmental management.

Rantau Baru Village: An Eco-Socio-Educational Model for Environmental Management in Fishing Communities

Rantau Baru Village: An Eco-Socio-Educational Model for Environmental Management in Fishing Communities

Circular Business Models (CBMs) in Environmental Management—Analysis of Definitions, Typologies and Methods of Creation in Organizations

A circular economy (CE) is an economic model that involves more sustainable management of raw materials and waste. Implementation of CE assumptions is highly recommended in the form of dedicated CE technologies as well as CE business models, so-called circular business models (CBMs), which are an integral part of environmental management in organizations. Depending on the application and the type of sector or enterprise, CBMs are defined differently, focusing on various areas of raw materials and waste management. In general, they should create added value for the given enterprise that meets the CE assumptions or integrate CE principles with the organization’s business practices. This paper aims to analyze different approaches to CBMs with the use of comparative analysis and desk research methods. The scope of this paper includes a comparative analysis of CBM definitions and their typologies, as well as the basics for creating CBMs in enterprises. Moreover, good practices of implemented CMBs in various enterprises are presented. The general definition of CBM is developed as “a business model that assumes creating, delivering and capturing added value for the consumer while considering the CE principles”. Furthermore, the basics of building CBM using a modified Business Model Canvas are proposed. In general, CBM should consider the key CE assumption, i.e., increased raw material efficiency. In the coming years, a further increase in interest in CBMs dedicated to specific sectors and their areas of activity is expected. Various stakeholders could use them as a benchmark to compare and define the best practices for the successful adoption of CBMs in the future.

Deep learning-based models for environmental management: Recognizing construction, renovation, and demolition waste in-the-wild

The construction industry generates a substantial volume of solid waste, often destinated for landfills, causing significant environmental pollution. Waste recycling is decisive in managing waste yet challenging due to labor-intensive sorting processes and the diverse forms of waste. Deep learning (DL) models have made remarkable strides in automating domestic waste recognition and sorting. However, the application of DL models to recognize the waste derived from construction, renovation, and demolition (CRD) activities remains limited due to the context-specific studies conducted in previous research. This paper aims to realistically capture the complexity of waste streams in the CRD context. The study encompasses collecting and annotating CRD waste images in real-world, uncontrolled environments. It then evaluates the performance of state-of-the-art DL models for automatically recognizing CRD waste in-the-wild. Several pre-trained networks are utilized to perform effectual feature extraction and transfer learning during DL model training. The results demonstrated that DL models, whether integrated with larger or lightweight backbone networks can recognize the composition of CRD waste streams in-the-wild which is useful for automated waste sorting. The outcome of the study emphasized the applicability of DL models in recognizing and sorting solid waste across various industrial domains, thereby contributing to resource recovery and encouraging environmental management efforts.

Integrating the Spatial Configurations of Green and Gray Infrastructure in Urban Stormwater Networks

AbstractGreen infrastructure (GI) practices improve stormwater quality and reduce urban flooding, but as urban hydrology is highly controlled by its associated gray infrastructure (e.g., stormwater pipe network), GI's watershed‐scale performance depends on its siting within its associated watershed. Although many stormwater practitioners have begun considering GI's spatial configuration within a larger watershed, few approaches allow for flexible scenario exploration, which can untangle GI's interaction with gray infrastructure network and assess its effects on watershed hydrology. To address the gap in integrated gray‐green infrastructure planning, we used an exploratory model to examine gray‐green infrastructure performance using synthetic stormwater networks with varying degrees of flow path meandering, informed by analysis on stormwater networks from the Minneapolis‐St. Paul Metropolitan Area, MN, USA. Superimposed with different coverage and placements of GI (e.g., bioretention cells), these gray‐green stormwater networks are then subjected to different rainfall intensities within Environmental Protection Agency's Storm Water Management Model to simulate their hydrological benefits (e.g., peak flow reduction, flood reduction). Although only limited choices of green and gray infrastructure were explored, the results show that the gray infrastructure's spatial configuration can introduce tradeoffs between increased peak flow and increased flooding, and further interacts with GI coverage and placement to reduce peak flow and flooding at low rainfall intensity. However, as rainfall intensifies, GI ceases to reduce peak flow. For integrated gray‐green infrastructure planning, our results suggest that physical constraints of the stormwater networks and the range of rainfall intensities must be considered when implementing GI.

Research on the Performance Evaluation of Agricultural Non-point Source Pollution Prevention and Control in Anhui Province

Agricultural and rural pollution control is a key and difficult issue in the revitalization of rural ecology in China, and agricultural non-point source pollution, as the main source of pollution, is of the utmost importance. Building a performance audit system for agricultural non-point source pollution prevention and control is beneficial for measuring the degree of agricultural non-point source pollution prevention and control, identifying constraints, and is of great significance for agricultural non-point source pollution prevention and control. This article selects Anhui Province as the research object, and based on the PSR model of environmental resource management, constructs an agricultural non-point source pollution performance evaluation system. On the basis of this evaluation system, the entropy weight TOPSIS method is used to empirically investigate the agricultural non-point source pollution prevention and control data in Anhui Province from 2017 to 2021, and corresponding suggestions are proposed based on the specific analysis results.

Retention Pond Planning for Flood Management Using Epa SWMM in Sayung Village Demak Regency

The area of Sayung Village, Sayung District, and Demak Regency is an area that is often hit by annual floods. According to the Sayung Village Government, floods in 2019 resulted in 5,884 residents of Sayung Village being displaced and 1,471 houses being flooded. The area of submerged rice fields is 300 hectares, with the number of farmers who failed to harvest reaching 436. Comprehensive handling is needed to deal with the flood. For flood management, a simulation of a flood management system was made with EPA SWMM (Environmental Protection Agency Storm Water Management Model) software. The selection of handling concepts is obtained through re-simulation of the capacity of drainage channels in order to accommodate planned discharge. To be able to perform simulations, hydrological data and measurements of existing channels are needed. Flood discharge obtained from the calculation results is Q2 of 110.1 m3 per second, Q5 of 134.9 m3 per second, and Q10 of 147.8 m3 per second. The handling concept obtained from this study is the creation of retention ponds in Dukuh Sayung Kidul and Dukuh Sayung Wetan.

ФОРМИРОВАНИЕ ДИНАМИЧЕСКОЙ МОДЕЛИ УПРАВЛЕНИЯ ПРИРОДОПОЛЬЗОВАНИЕМ В РОССИЙСКОЙ ФЕДЕРАЦИИ

The rate of environmental change facing modern society has been accelerating in recent decades. The paper presents a dynamic model of environmental management taking into account environmental restrictions on the use of resources in a local area of the natural environment. The main reasons for these changes to support management decisions include low barriers to entry and significant changes in the boundaries between markets, the frequent emergence of new technologies, crises and political changes. In this regard, management theory and practice are aimed at the constant search for a management system capable of responding to the challenges of the modern market context. In such conditions, market entities can often be only temporary in nature, which significantly complicates the practice of corporate governance The result is a variety of concepts that improve upon previous models in process control The authors proposed a dynamic model of environmental management based on the dynamic capacity of natural resources, where special attention is paid to the management of the environmental planning process and its dynamic capabilities, expressed in promising directions for the rationalization of environmental management, which means searching for and maintaining a dynamic basis. The article examines the literature review and practical experience of using dynamic management models in the environmental management system.

Machine learning parallel system for integrated process-model calibration and accuracy enhancement in sewer-river system

The process-based water system models have been transitioning from single-functional to integrated multi-objective and multi-functional since the worldwide digital upgrade of urban water system management. The proliferation of model complexity results in more significant uncertainty and computational requirements. However, conventional model calibration methods are insufficient in dealing with extensive computational time and limited monitoring samples. Here we introduce a novel machine learning system designed to expedite parameter optimization with limited data and boost efficiency in parameter search. MLPS, termed the machine learning parallel system for fast parameter search of integrated process-based models, aims to enhance both the performance and efficiency of the integrated model by ensuring its comprehensiveness, accuracy, and stability. MLPS was constructed upon the concept of model surrogation + algorithm optimization using Ant Colony Optimization (ACO) coupled with Long Short-Term Memory (LSTM). The optimization results of the Integrated sewer network and urban river model demonstrate that the average relative percentage difference of the predicted river pollutant concentrations increases from 1.1 to 6.0, and the average absolute percent bias decreases from 124.3% to 8.8%. The model outputs closely align with the monitoring data, and parameter calibration time is reduced by 89.94%. MLPS enables the efficient optimization of integrated process-based models, facilitating the application of highly precise complex models in environmental management. The design of MLPS also presents valuable insights for optimizing complex models in other fields.

Development of a Sustainable Community Environmental Management Model by Using the Process Engage Educational Institutions and Communities

Background and Aims: The amount of municipal solid waste generated tended to increase during the year 2017-2019 and there is more reuse of municipal solid waste, in which incorrect disposal tends to decrease, but with the situation of the spread of the coronavirus disease 2019 since the beginning of March 2020, and continued until a new wave of outbreaks in late 2020 and early 2021. The problem of solid waste is increasing, the Local authorities will collect and transport waste, which the municipality will do by itself, but some hire private companies to carry out the collection in the area for waste management problems that are mostly found as residual waste. Thus, this research was; (1) to study the problems and needs of sustainable community environmental management. (2) To find a model and develop a sustainable community environmental management model by using the participation process of educational institutions and communities. Materials and Methods: This research was a qualitative study in Kaeng Loengchan Sub-district, Mueang District, Maha Sarakham Province. The research tools were semi-structured, observational, and recording interviews with a target population of 30 participants. Use content analysis. Results: The results showed that; (1) The community environmental problem that is currently facing is the continuous increase of solid waste from consumption and household consumption which, if not properly managed, will cause chronic problems. (2) Sustainable community environmental management model found that (1) the implementation of the 5R principles in the household, (2) the establishment of a community waste bank, and (3) the use of an application system to help collect solid waste management data. Conclusion: The local government should develop further by incorporating them into local ordinances to develop and support the budget for expanding the results to other areas. And the development of a sustainable community environmental management model by using the participation process of educational institutions and communities.

Maternal responsibility and blame in technological disaster: radiation risk management as gendered labor after Fukushima

State governance after the Fukushima Daiichi nuclear accident created a culture of silence and tolerance surrounding radiation risk, and deliberately fueled the popular understanding that acting upon radiation-related concern was antithetical to national and regional economic recovery. Outright denial of danger by Japanese leaders, paired with loosened safety standards and limited state support for affected residents by way of guidance and compensation, led to a privatization of radiation risk management that placed responsibility for exposure reduction onto families while also constraining their action. Drawing on in-depth interviews and participant observation, this article explores how such dynamics fell most heavily on concerned mothers, who were far more likely to take on this additional realm of domestic labor and care work due to deeply ingrained norms of gendered labor and citizenship. Yet such maternal labor was not lauded as a valuable social contribution. Rather, concerned mothers found themselves in a double bind in which to care for their families through vigilant avoidance of potential risk was to betray the state. Risk mitigation came to require a significant amount of emotion work associated with not appearing overly anxious or paranoid, constantly assessing the risk perception of others, and at times suppressing concern and compromising on risk tolerance. The results of this study suggest that neoliberal models of environmental risk management, particularly in moments of high uncertainty surrounding the risk in question, can not only create internal, interpersonal, and community conflict but also exacerbate existing gender inequalities.

OPPORTUNITIES AND CHALLENGES IN MODELING AN ENVIRONMENTAL MANAGEMENT SYSTEM

The business ecosystem provides full integration of economic and environmental objectives. Every company, including those from the Bulgarian mining industry, implements specific actions, mechanisms, innovations for environmental management. The aim of the present study is to analyse the relationship between the economic and non-economic priorities of enterprises of the mining industry, especially now in the context of solving the global problem of transformation towards sustainable development. The following research tasks have to be settled for reaching the above-mentioned goal: 1. to analyze the influence of modern technologies, the remote control of machines underground, including remote control and self-learning drones in underground mines on the optimization and improvement of work processes and the protection of a cleaner environment; 2. to focus on some relevant aspects of green transformation of the mining industry, incl. in the development of environmental, social and new management models as a factor for successful business; 3. to research the impact of the initiated cycle of interest rate tightening on the implementation of the planned activities for environmental management of the mining industry. In the course of the study shall be justified the thesis that the future of the mining industry in Bulgaria is digital, green and sustainable. The methodology of structured interview was used. The sample was formed by the method of random non-recurrent selection. For the purposes of the research, we have carried out analysis of the whole assessment of the favourable opportunities and potential risks, as well as the strengths and weaknesses of the new model for an environmental management system. The results of the research are expressed in establishing the trend for digitalization and innovation, tracking the importance of environmental management and protection.

Evaluation of Environmental Management and Conservation of Natural Resources in Tourism Enterprises in Ayacucho, Peru: Workers’ Perceptions

Nowadays, it is important to promote environmental management in organisations so that natural resources are subject to a conservation process that allows them to be maintained over time. In addition, this is a good way to increase the environmental awareness of the different actors in society. Therefore, the objective of this study is to evaluate the perceptions of workers concerning the relationship between environmental management and the conservation of natural resources in tourism companies in Ayacucho, located in the Andean region of Peru. The research is of a basic type, with a quantitative approach and a non-experimental, correlational-exploratory design. The survey technique was used and the data-collection instrument was a questionnaire addressed to 600 workers on environmental management, with the dimensions of planning, implementation and operation and verification; and on conservation of natural resources, with the dimensions of biodiversity monitoring and consolidation of the protected area. The results show that 39% of workers disagree with the planning of their company, 47% neither agree nor disagree with the operations of their company and the implementation of its projects and 47% disagree with their company’s methods of assessing the success of its operations. These results show that an environmental management model should be proposed to improve the conservation of natural resources and to contribute to the revaluation of resources and the promotion of biodiversity protection in order to create environmental awareness in society.

Approaching a Sustainable Vector Model for Environmental Crisis Management

Approaching a Sustainable Vector Model for Environmental Crisis Management

An Efficient and Reliable Blockchain-based Trust Management Model for Electricity Trading Terminal

<p>A safe and reliable terminal environment is crucial to ensure the security of the electricity trading system. The existing terminal security system based on identity authentication and access control has internal threats that are difficult to solve. For example, multiple internal malicious nodes cause broadcast message tampering attacks and malicious packet loss, resulting in message dissemination failure. Existing blockchain-based trust management systems are good for addressing insider threats, but suffer from low efficiency. In order to solve the internal threat problem of the electric electricity trading system, from the perspective of trust evaluation and trust management of the terminal environment, an efficient and reliable blockchain-based electric trading terminal (ERBTM) trust management model is proposed. First of all, we collect a variety of trust factors to evaluate the credibility of the terminal, which solves the problem of accuracy in the process of trust assessment; secondly, we improve the speed of storing trust values on the chain and ensure the robustness of the system by improving the consensus algorithm; Finally, we designed the structure of the block that stores the trust value to ensure that the trust value is not tampered with. The experimental results show that, compared with similar methods, the ERBTM model can effectively deal with the endogenous security threats of terminals in the electricity trading environment, and has significant advantages in terms of efficiency and reliability. </p> <p> </p>

Estado del arte sobre el pago por servicios ambientales en Paraguay: Dieciséis años de gestión

Due to the increasing academic interest in Payment for Environmental Services (PES) globally and the scattered state of PES in Paraguay, this paper presents a review of Paraguay to provide an overview of the current state of the subject at the national level and develop new theoretical and methodological approaches. The main objectives of this article are to compile the history of management and systematization of technical, academic, and scientific information on PES in Paraguay and contribute to defining economic valuation methods to enhance PES at the local and regional levels. This will serve as a strategy for designing environmental management models that guarantee the provision of long-term environmental services (16 years of analysis).The study design was qualitative, documentary, bibliographic and descriptive, based on the preparation and analysis of a database with 41 technical documents that facilitated the systematization and mapping of the information. Results show that 46% of the documents analyzed correspond to peer-reviewed literature, with five identified management periods. The most worked aspect was the economic valuation of environmental goods and services, especially those derived from the forest, where market-based valuation techniques based have been applied to a greater extent. As for the valuation of environmental damage, no publications or works were found during the studied period. Economic valuation studies were important for the current PES regulation process in Paraguay. that the Payment for Environmental Services (PES) mechanism in Paraguay has made significant progress over the past 16 years. However, both the market and policies related to PES are still not fully established due to critical issues identified, primarily the lack of regulation of other certification modalities that contribute to both sustainable production and conservation strategies. Hence, there is a need to address these challenges to ensure the effective implementation of PES in Paraguay. * The photo corresponds to Tuyuyús cuarteleros (Jabiru mycteria) in the flooding savannah of the Chaco. Photo: Karim Musalem

Patterns of dreissenid mussel invasions in western US lakes within an integrated gravity model framework

Freshwater invasive species, such as the quagga mussel (Dreissena rostriformis bugensis), are causing over $1 billion USD annually in damages to water infrastructure, recreation, and the environment. Once established, quagga and other dreissenid mussels are extremely difficult to eradicate. Preventing the spread of these invasives is critical and of high management concern. Invasive dreissenid establishment is predicated upon both successful dispersal from a source and suitable habitat in the uninfested waterbody to which they are transported. Recreational boaters have become predominant dispersal vectors making it possible to forecast the risk of invasion of waterbodies for more targeted management and prevention. We developed an integrated mussel dispersal model that couples a constrained gravity model and habitat suitability model to forecast future invasions. The model simulates boater movement between lakes, the likelihood of boats transporting mussels, and the likelihood that those mussels survive in the environmental conditions of the new lake. Model output was most sensitive to changes in boater threshold, then buffer zones, while not as sensitive to changes in habitat suitability. From an initial infested source pool of 11 among 402 Western inland US lakes, we forecast additional lakes infested in several possible simulation scenarios. Constraining movement reduced connectivity between waterbodies with amplifying effects at different distance levels. This model can be used to determine waterbodies most at risk for dreissenid mussel invasion and to highlight the importance of multifactor integrated models in environmental management.

Does the “Environmental Kuznets Curve” Phenomenon Happening in High, Medium, and Low Income Countries?

The most significant reduction in environmental quality is thought to have occurred in low-income countries, while low environmental degradation occurred in those high-income countries. Using the cluster purposive sampling technique, countries from 5 continents were examined to see if they had complete data and represented three categories. Seventy-eight countries were found to meet these requirements and were then used as research samples from 2015 to 2019. The Data Panel Regression technique was used to analyses the data. This study is expected to be able to produce policies in the form of a sustainable environmental management model that continues to support economic growth. This study proved that the Environmental Kuznets Curve (EKC) phenomenon applies from 2015 to 2019 in high-income countries, and population growth rates have a significant negative impact on Carbon Dioxide (CO2) emissions. This means that the more prosperous a country, the less the environmental degradation, while in low-income countries, carbon emissions increase when economic growth increases. In developing countries, as the population increases, environmental degradation increases, while in low-income countries the amount of carbon emissions is affected by economic growth and population. Some compensate and subsidies low-income countries which are able to care for their environment.

Analysis of flood control in Lambidaro sub-watershed using EPA SWMM

In the Lambidaro sub-watershed, precisely on Jalan Colonel Sulaiman Amin, the problem of flooding continues, especially when it rains. The occurrence of flooding around the canal along the Colonel Sulaiman Amin road drainage is caused by several factors, one of which is the capacity of the reservoir which is not able to control the flood discharge optimally so that water cannot overflow into the canal. and eventually caused flooding in the surrounding area. This study aims to determine whether the drainage capacity is still able to drain surface runoff water or not and determine alternative flood control solutions for Colonel Sulaiman Amin Street. The method used is the EPA Model SWMM (Environmental Protection Agency Storm Water Management Model). From this study, the simulation results obtained from EPA SWMM showed alternative solutions offered such as the use of flood pumps, retention ponds, and optimization of drainage, the most effective solution of the six flood mitigation experiments was channel optimization in the form of changing the shape and size of the channel 7 to a square channel with a width of 1 .5 meters. This alternative is 5.26% more effective with an effective percentage of 85.538% and can drain 36.36% more water flow than drainage with a widening of 1.1 meters.