Sustainable Resource Management Research Articles

A thorough assessment of various forest management planning initiatives and development of improvement strategies towards an ecosystem-based planning

Management planning for forests in Turkey has undergone gradual evolution over the last century. Developing and implementing a comprehensive management planning framework present significant challenges. This paper evaluates the effectiveness of various forest management planning approaches implemented across the country over different time periods, with overarching planning principles. It formulates a robust planning framework and proposes improvements grounded in scientific advancements and international standards. The assessment indicated that the management plans were developed using reputable scientific methods and principles aimed at ensuring the sustainable management of forest resources with certain strengths and opportunities presented by SWOT analysis. All management plans shared a common planning concept primarily focused on maximizing wood production through the area-control harvest scheduling method (except for continuous cover forest, which employed the single tree selection method). Each management plan established its unique vision, targets, policies, objectives, and planning guidelines. Forest inventory data were gathered through a combination of ground surveys and remotely sensed data to characterize and stratify the landscape. A robust in-house management authority and governance system with appropriate technical capacity and guidelines were developed and implemented, fostering a sound common working culture and tools. However, some notable drawbacks were identified, including political pressure, biomass/carbon accounting, growth-yield modelling, economic analysis, limited characterization of the full range of ecosystem services, risk and uncertainty analysis, food security and, particularly, long-term sustainability and scenario analysis with the appropriate decision-making tools and methods. Despite a few strengths, these limitations may raise concerns about the far-sighted design and application, potentially jeopardizing the sustainable management of forest ecosystems. Proposed improvement strategies for an efficient forest ecosystem management planning system include characterization of ecosystem services, modelling their productivity, scenario analysis with a decision support system, stakeholder involvement, balancing utilization and conservation targets, conducting risk and uncertainty analysis and economic analysis of management actions.

Development of alginate beads loaded with bioactive ingredients from Chlorella vulgaris cultivated in food industry wastewaters

Microalgae are increasingly recognized for their potential in the food sector due to their rapid growth and rich content in proteins, carbohydrates, and pigments. The extraction of pigments from microalgal biomass holds promise for their utilization as natural colorants and antioxidants. To address the economic challenges associated with microalgae cultivation, particularly high nutrient costs, this study focused on cultivating Chlorella vulgaris in a mixture of food industry wastewaters (brewery wastewater, expired orange juice and cheese whey). This resulted in a microalgae-bacteria consortium with a concentration of 2.2 g·L−1 dry weight after 5 days of cultivation. The wastewater bioremediation ranged between 23 and 77 %, and the produced microalgae biomass contained 21.68 ppm lutein, 36.47 ppm a-chlorophyll and 11.19 ppm b-chlorophyll. The extraction process employed a solvent screening strategy with food industry-accepted solvents used to extract high-value compounds efficiently. Ethanol was the most effective solvent, outperforming acetone, ethyl acetate, and hexane. An upscaled extraction process was conducted using 10 g lyophilized microalgae. After ethanol evaporation, the microalgal extract was re-diluted in sunflower oil and encapsulated in alginate beads, achieving an encapsulation yield of 93.3 %. Lutein, identified as one of the main compounds in the extract, exhibited a satisfactory encapsulation efficiency of 55 %. The efficient encapsulation of the microalgae components in alginate beads was verified by the alteration of the colorimetric parameters of these alginate beads compared to those loaded with pure sunflower oil as well as empty beads. These findings highlight the potential of microalgae as a valuable tool for transforming food industry wastewater into high-value products, especially when microalgal extract is encapsulated in alginate beads. This strategy presents substantial prospects for the food industry, merging effective wastewater valorization with biomass production and bioactive compound extraction. It exemplifies a circular bioeconomy, showcasing sustainable resource management and value creation.

The Relationship between Perceptions of High-Performance Work Systems and Corporate Social Responsibility (CSR) Considering the Moderating Effect of a Positive Diversity Climate

Companies have shown interest in advanced human resource management as a means to secure distinctive competitive advantages for organizational survival and growth through sustainable management systems. Hence, in the current context, where sustainability in business is a growing concern, the objective of this study was to investigate the relationship between high-performance work systems and a company’s social performance, taking into account the organizational climate as a situational variable. Specifically, this study aimed to analyze the impact of perceptions of a high-performance work system on the perception of a company’s social responsibility (CSR) among employees of Jordanian companies with an organizational size of 300 or more. This study used 175 valid questionnaires, and SPSS and AMOS 24 were used to test the hypotheses. The results showed that there was a positive relationship between the perception of a high-performance work system and the perception of a company’s CSR. Furthermore, this study found that a positive diversity climate could enhance the positive relationship between the two. These findings suggest that high-performance work systems can contribute to the development of sustainable human resource management systems and that a positive diversity climate is essential in shaping these systems. Based on these results, it is recommended that companies implement HPWSs and encourage workforce diversity to maximize the value of CSR activities and ensure their sustainability.

Digital technologies for the development of sustainable tourism in mountain areas

The promotion of sustainable tourism models in mountain areas represents a critical success factor for the territory and the environment. In political and economic literature there has been much debate in the attempt to interpret the phenomenon of growth and development with the changing socio-economic environment. Today the topic remains at the center of the debate of many economic policy authorities due to the exodus phenomena occurring in internal areas. In this study, we examined how the resources of mountain areas can create income opportunities as a function of the diffusion of sustainable income. On the one hand, in mountain environments, we have natural resources that represent common goods that must be maintained precisely according to the opportunities they create for sustainable tourism where they represent its essential feature. The complexity of the economic phenomena, which on the one hand leads to an exodus from these environments, determines the need to create new management structures, that can satisfy the needs of the local community and guarantee appropriate management of natural resources. In this study, we analyzed the relationships between sustainable tourism models and natural resource management considering the case of the Ficuzza Forest and applying new digital technologies such as mobile apps that allow you to make hotel reservations, read reviews about the best restaurant in the area, and buy museum tickets to avoid the queue. Starting from the theoretical framework, and subsequently analyzing the empirical case, we highlighted the utility flows that descend from the Bosco. The resulting results have considerable relevance for the planning of mountain territories. The study highlights that the interconnection between public and private management models can guarantee the growth and development of mountain territories.

Deploying a Computer Vision Model Based on YOLOv8 Suitable for Drones in the Tuna Fishing and Aquaculture Industry

In recent years, the global tuna fishing and aquaculture industry has encountered significant challenges in balancing operational efficiency with sustainable resource management. This study introduces an innovative approach utilizing an advanced computer vision model, PA-YOLOv8, specifically adapted for drones, to enhance the monitoring and management of tuna populations. PA-YOLOv8 leverages the capabilities of YOLOv8, a state-of-the-art object detection system known for its precision and speed, tailored to address the unique demands of aerial surveillance in marine environments. Through comprehensive modifications including downsampling techniques, feature fusion enhancements, and the integration of the Global Attention Module (GAM), the model significantly improves the detection accuracy of small and juvenile tuna within complex aquatic landscapes. Experimental results using the Tuna dataset from Roboflow demonstrate marked improvements in detection metrics such as precision, recall, and mean average precision (mAP), affirming the model’s effectiveness. This study underscores the potential of integrating cutting-edge technologies like UAVs and computer vision in promoting sustainable practices in the aquaculture sector, setting a new standard for technological applications in environmental and resource management. The advancements presented here provide a scalable and efficient solution for real-time monitoring, contributing to the long-term sustainability of marine ecosystems.

Quantifying spatial dynamics of urban sprawl for climate resilience sustainable natural resource management by utilizing geostatistical and remote sensing techniques

Quantifying spatial dynamics of urban sprawl for climate resilience sustainable natural resource management by utilizing geostatistical and remote sensing techniques

An Improved Q-Learning Algorithm for Optimizing Sustainable Remanufacturing Systems

In our modern society, there has been a noticeable increase in pollution due to the trend of post-use handling of items. This necessitates the adoption of recycling and remanufacturing processes, advocating for sustainable resource management. This paper aims to address the issue of disassembly line balancing. Existing disassembly methods largely rely on manual labor, raising concerns regarding safety and sustainability. This paper proposes a human–machine collaborative disassembly approach to enhance safety and optimize resource utilization, aligning with sustainable development goals. A mixed-integer programming model is established, considering various disassembly techniques for hazardous and delicate parts, with the objective of minimizing the total disassembly time. The CPLEX solver is employed to enhance model accuracy. An improvement is made to the Q-learning algorithm in reinforcement learning to tackle the bilateral disassembly line balancing problem in human–machine collaboration. This approach outperforms CPLEX in both solution efficiency and quality, especially for large-scale problems. A comparative analysis with the original Q-learning algorithm and SARSA algorithm validates the superiority of the proposed algorithm in terms of convergence speed and solution quality.

Investigating seawater intrusion and salinization using the integration of hydrochemical and geoelectrical techniques

Seawater intrusion poses a significant environmental threat to water resources, agriculture, and ecosystems. We investigated the extent of seawater intrusion and salinization in the eastern coastal aquifers of Saudi Arabia. Hydrochemical measurements and electrical resistivity tomography (ERT) techniques were employed to assess groundwater quality and subsurface extension of seawater intrusion. Two resistivity profiles, 475 m long each, were analyzed to gain insights into subsurface geology and seawater intrusion. The inversion of the recorded resistivity data revealed four distinct subsurface layers. The uppermost layer consists of surficial deposits, followed by a sandy seawater intrusion layer, beneath that lies a marl layer, and at the bottom, a dolomitic-limestone layer representing the brackish-water aquifer. The ERT results are integrated with hydrochemical and hydrogeological results from 12 wells to overcome the limitations of the ERT. Our conclusions are required to develop efficient mitigation strategies and sustainable management of groundwater resources in the study area or similar coastal regions affected by seawater intrusion. Understanding and delineating the boundary between saline and fresh water is crucial for safeguarding water resources for agricultural purposes, preserving ecosystem health, and ensuring the long-term sustainability of water supplies in coastal areas.

Morphometric Analysis of Waghora Micro Watershed of Jam River Basin Using ALOS-PALSAR DEM

Intergrating Remote sensing and Geographic Information System(GIS) Proves useful for Evaluating and understanding morphometric parameters, especially Watershed Management of - Soil and Water Conservation at microlevel for sustainable Natural Resource management. The Linear , Areal and Relief characteristics of the basins Drainage can be analytsed Morphometrically. In this investigation, geospatial techniques were employed to assess the hydrological features of the Waghora Micro watershed within the Jam River basin, covering an area of 13.03 km². Utilizing the ALOS-PALSAR RTC DEM -12.5 m resolution, the basin and drainage network were delineated using ArcGIS software. The analysis revealed a dendritic drainage pattern within the Waghora micro-watershed, with drainage streams delineated up to the fourth order. The ratio of bifurcation (Rb) can be ranged within ~ 3 - 4.66, with an mean average of 3.76, showcases Geologic Structures are undistorted and the drainage system sorted by moderate peaks and lower orer streams. Additional morphometric parameters were assessed, using Form-factor(Rf), Circulatory-Ratio(Rc), and finally Elongation-Ratio(Re) values of 0.32, 0.68, and 0.62 respectively. This is a clear indication of Micro watershed being moderately Elongated with time. The Estimated Relief, Relief Ratio(Rr), relative Relief (RR) and Ruggedness Ratio Number were determined to be 75 m, 1.2, 0.97, respectively, indicating a moderate erosion potential. Overall, the study underscores the necessity for implementing – Soil and Water Conservation measures to be taken within the watershed. These findings hold significant implications for various stakeholders, including managers and decision-makers involved in Management of Watersheds and Conservation of the Natural resources using sustainable initiatives.

Synergizing trade and sustainability: advancing SDG 14 through international trade dynamics

This paper explores the intricate relationship between international trade and the achievement of the United Nations Sustainable Development Goal 14 (Life Below Water), focusing on the potential of trade to contribute positively to marine conservation and sustainable use of ocean resources. By examining the intersection of economic, social, and environmental dimensions, the study delves into how trade policies and practices can be aligned with environmental objectives, particularly concerning marine ecosystems. A principal challenge identified is the tension between economic growth driven by international trade and the sustainability of marine ecosystems, exacerbated by practices such as overfishing and pollution from maritime transport. Another significant challenge is the lack of robust enforcement mechanisms for existing environmental provisions in trade agreements. To address these challenges, the paper recommends the integration of stringent and enforceable environmental clauses in trade agreements, coupled with the promotion of sustainable trade practices through international cooperation and capacity building. Furthermore, the study suggests the adoption of innovative trade mechanisms, such as eco-certification and the implementation of Marine Protected Areas (MPAs), to enhance the protection of marine life, support sustainable fisheries, and reduce ocean pollution. The paper concludes with specific policy recommendations for leveraging international trade as a tool for the sustainable management of marine resources, ultimately contributing to the broader agenda of sustainable development.

The impact of GHRM and EGB on organization’s financial and operational performance – an empirical analysis on Indian ICT sector

PurposeThe study aims to conduct an empirical research to examine how green human resource management (GHRM) can influence sustainable organizational performance (SOP) in terms of financial performance (FP) and operational performance (OpP), both directly and through employee green behavior (EGB), in the backdrop of the Indian information and communication technology (ICT) sector.Design/methodology/approachThe study is based on primary data collected through a questionnaire survey from 387 employees engaged in the ICT sector. Confirmatory factor analysis validates the measurement model, while structural equation modeling (SEM) using the partial least squares (PLS) method examines the hypothesized relations.FindingsResults confirm that GHRM significantly contributes to EGB, FP and OpP, with a theoretical underpinning concerning resource-based view (RBV) and ability-motivation-opportunity (AMO) concepts. The study also confirms that connections of GHRM with both FP and OpP are significantly and positively mediated by EGB.Practical implicationsThe study provides evidence-based implications of different GHRM practices toward EGB, FP and OpP, which are highly pertinent to strategists, policymakers, managers and supervisors in implementing GHRM for adding value to both operational and financial statements while protecting nature and natural resources through the green efforts of employees.Originality/valueThe study bridges a significant theoretical and practitioner gap by providing a deeper understanding of GHRM as a sustainable human resource management (HRM) model in the context of the Indian ICT sector. It empirically explores the connections between GHRM and OpP, which is a crucial dimension of SOP, and highlights noteworthy implications for promoting EGB, an individual micro-sustainability dimension directed toward the achievement of broader organizational goals, which are essentially oriented to macro-sustainability.

A Review: Tree Species Classification Based on Remote Sensing Data and Classic Deep Learning-Based Methods

Timely and accurate information on tree species is of great importance for the sustainable management of natural resources, forest inventory, biodiversity detection, and carbon stock calculation. The advancement of remote sensing technology and artificial intelligence has facilitated the acquisition and analysis of remote sensing data, resulting in more precise and effective classification of tree species. A review of the remote sensing data and deep learning tree species classification methods is lacking in its analysis of unimodal and multimodal remote sensing data and classification methods in this field. To address this gap, we search for major trends in remote sensing data and tree species classification methods, provide a detailed overview of classic deep learning-based methods for tree species classification, and discuss some limitations of tree species classification.

Matrix-free laser desorption/ionization mass spectrometry imaging for rapid evaluation of wood biomass conversion.

This study overcomes traditional biomass analysis limitations by introducing a pioneering matrix-free laser desorption/ionization (LDI) approach in mass spectrometry imaging (MSI) for efficient lignin evaluation in wood. The innovative acetic acid-peracetic acid (APA) treatment significantly enhances lignin detection, enabling high-throughput, on-site analysis. Wood slices, softwood from a conifer tree (Japanese cypress) and hardwood from a broadleaf tree (Japanese beech), were analyzed using MSI with a Fourier transform ion cyclotron resonance mass spectrometer. The developed APA treatment demonstrated effectiveness for MSI analysis of biomass. Our imaging technique successfully distinguishes between earlywood and latewood and enables the distinct visualization of lignin in these and other wood tissues, such as the radial parenchyma. This approach reveals significant contrasts in MSI. It has identified intense ions from β-O-4-type lignin, specifically in the radial parenchyma of hardwood, highlighting the method's precision and utility in wood tissue analysis. The benefits of matrix-free LDI include reduced peak overlap, consistent sample quality, preservation of natural sample properties, enhanced analytical accuracy, and reduced operational costs. This innovative approach is poised to become a standard method for rapid and precise biomass evaluation and has important applications in environmental research and sustainable resource management and is crucial for the effective management of diverse biomass, paving the way towards a sustainable, circular society.

Sustainable Human Resources Management and Psychological Contracts: Exploring Theoretical Anchors to Solve Relational Tensions in Employment Relationships

A core aspect of Sustainable Human Resource Management (S-HRM) has been its focus on developing high-quality employment relationships. This endeavor, however, has become increasingly complex, because the employee-employer relationship has undergone a profound transformation in recent years. This problem is further exacerbated by inherent tensions that surface when organizations aim to develop high-quality employment relationships in concert with sustainability-related goals. In this article, we intend to align theory and practice toward a more sustainable HRM by explaining how the psychological contract (PC) literature can provide new insights and perspectives to understand these tensions. We begin by delving into the nature and drivers of these sustainability-related tensions that arise when organizations strive to develop high-quality employment relationships. Next, we recount previous PC research that can inform the S-HRM literature to better understand how those tensions unfold. Finally, we identify concrete avenues for future research and discuss why integrating the PC and S-HRM literature could be an important path to expand our understanding of how to create more sustainable employment relationships.

Sustainable human resource management practices and corporate sustainable supply chain: the moderating role of firm technology orientation

ABSTRACT This study investigates how corporate human resource management practices contribute to sustainable supply chain practices. The two types of human resource management practices relating to corporate social responsibility, include (1) employee standardised work conditions practices and (2) employee well-being and development practices. Corporate technology orientation is investigated as a moderating factor on the empirical evidence from 15 companies in the mobile technology industry. Results show that employee well-being and development practices lead to stronger community-oriented social responsibility, thus the increasing adoption of sustainable supply chain practices. Corporate technology orientation strengthens the positive impacts of employee well-being and development practices. These results imply the importance of adopting appropriate human resource management strategies, to deploy a sustainable supply chain.

Circular Economy Principles and Their Integration into Global Supply Chain Strategies

The concept of circular economy has gained significant traction in recent years as a holistic approach to sustainable development and resource management. This review explores the principles of circular economy and their integration into global supply chain strategies. The transition from a linear 'take-make-dispose' model to a circular model focused on resource recovery, reuse, and regeneration is driving a paradigm shift in how businesses operate and manage their supply chains. Key principles of circular economy, including designing out waste and pollution, keeping products and materials in use, and regenerating natural systems, are examined in the context of supply chain management. Strategies for implementing circular economy principles across various stages of the supply chain, from product design and manufacturing to distribution, consumption, and end-of-life management, are discussed. The review highlights the benefits of adopting circular economy principles in supply chain strategies, including reduced resource consumption, waste reduction, cost savings, and enhanced resilience to external shocks. Case studies and examples from diverse industries illustrate successful implementation of circular economy principles in supply chain management, demonstrating tangible environmental, social, and economic benefits. Challenges and barriers to the adoption of circular economy principles in global supply chains are also addressed, including regulatory hurdles, technological limitations, and cultural barriers. Strategies for overcoming these challenges and promoting a circular mindset among stakeholders are explored, emphasizing the importance of collaboration, innovation, and cross-sector partnerships. The integration of circular economy principles into global supply chain strategies offers significant opportunities for sustainable growth, resilience, and value creation. By embracing the principles of circularity, businesses can unlock new sources of competitive advantage while contributing to the transition towards a more sustainable and regenerative economy. Keywords: Circular Economy, Supply Chain, Sustainability, Integration, Challenges, Opportunities.

A Study on Managing Cultural Diversity and Governance Process in the Education Sector

Background of the study: The domain of education employs people from diverse backgrounds and cultures. Each faculty member has their distinct characteristics and personality traits making it challenging for the Human resource department to keep them all content and satisfied with their work and fellow members under one roof. Aim/Purpose: This study aims to investigate the application of governance for managing cultural diversity among faculty members for achieving sustainable human resource management in Community Colleges. Methodology: A thorough investigation of the conceptual and empirical literature available in the domain has helped create a strong foundation for the research. With the help of an extensive review of the literature, the relationship between diversity management and the governance process among faculty members is reviewed. Findings: Finally, the study concludes with the significance of the relationship between diversity management and the governance process among faculty members to achieve sustainable human resource management in the education sector. Results: Reviewing the correlation between diversity management and the governance process among faculty members solves the problems of communication and interaction among employees having diverse backgrounds. Practical, Research & Social Implications: The paper highlights the need for suitable management of diversity in community colleges which can lead to broader and more impelling implications for the policy makers and the colleges to adopt more welcoming and inclusive principles to cater to all needs and make diversity richer and a strong suit. Originality/value: Sustainable human resource management leads to greater productivity among employees and sustainability for the organization. In the contemporary world where competition is vast, there is a need to maintain internal harmony and balance. Thus, our research provides an in-depth analysis of the myriad ways adopted by the education sector for diversity management and practices and governance process.

UAV and Deep Learning: Detection of selected riparian species along the Ganga River

Abstract. Environmental protection and sustainable natural resource management are being recognised worldwide as essential goals to safe guard human health and well-being. Riparian zones, that face the highest decline in freshwater biodiversity, are of prime conservation priority because they are essential for regulating climate, preserving aquatic-terrestrial biodiversity, maintaining ground water recharge and restoring rivers. In today's fast-paced data-driven environment, artificial intelligence (AI) is the precise answer to a wide range of problems including biodiversity conservation and wildlife management. Leveraging advancements like Uncrewed/Unmanned Aerial Vehicles (UAVs) and AI has resulted innovative strides in wildlife conservation. This study utilised UAV imagery to record high-resolution data of aquatic habitat and species along the Ganga River and employed deep learning algorithms to analyse the data. Through extensive field surveys in the Hastinapur Wildlife Sanctuary, 7,025 photos representing a variety of environments, including 20,000 annotated samples of aquatic animals such as turtles and gharials were generated. Vision based computing capabilities such as pattern recognition model were developed to identify these species. To enrich and enhance the dataset and model, we used different image pre-processing techniques. Slight rotation (±5 degrees), minor cropping (up to 10%), and adjustments in brightness, saturation, and shear (±15%) were applied. Controlled blur (up to 0.5%) and exposure modifications (±5%) were also implemented on the image dataset to improve accuracy. Three Convolutional Neural Network (CNN) architectures, single-stage detectors named YOLO v7, YOLO v8, and Roboflow 3.0, were used for detecting the select species. Results show YOLO v8 excels, achieving mean average precision (mAP) of 98.8% for gharial and 92.2% for turtle detection, with a rapid average detection time of 0.308 seconds per frame at 3200 × 3200 resolution. Additionally, our model demonstrates real-time species detection capability through innovative frame sampling techniques with UAVs. This methodology provides promising technique to collect scientific data on IUCN red listed turtles and critically endangered gharials, allowing detection, monitoring, and real time counting with minimal intrusion. In conclusion, the fusion of UAVs and deep learning promises to revolutionize habitat monitoring, aiding conservation decision-making.

Sustainable human resource management and job satisfaction—Unlocking the power of organizational identification: A cross‐cultural perspective from 54 countries

AbstractSustainable human resource management is gaining importance in organizations due to its role in developing a sustainable work environment and well‐being. This paper discusses the relationship between employee perceptions of sustainable human resource management and job satisfaction in 54 countries. We propose that sustainable HRM is positively associated with job satisfaction but that this relationship is moderated by employees' identification with the organization and country‐level individualism–collectivism. Thus, we suggest national culture functions as a second‐level moderator of the relationship of sustainable HRM with organizational identification on job satisfaction. Findings from the multi‐level analyses using data from 14,502 employees nested within 54 countries provided support for our hypotheses, namely that employee perceptions of sustainable HRM were positively associated with job satisfaction and that this relationship was more pronounced for employees with lower levels compared to higher levels of organizational identification in individualistic rather than collectivistic countries. These findings bear important implications for both theory and practice.

Bangladesh towards green growth: a review of environmental sustainability indicators

Pursuing green growth is crucial for Bangladesh to transition from an unsustainable economic trajectory to a more sustainable and inclusive one. Bangladesh is picked for this study because of impending and severe economic and environmental threats. This study intends to review the present scenario of various environmental sustainability-related indicators in Bangladesh, focusing on renewable energy consumption, freshwater resources, water productivity, CO2 emissions, energy intensity, air pollution, and natural resource rents. The World Bank database has been utilized to obtain secondary time series data of Bangladesh spanning from 2000 to 2020. As a descriptive study, cross-sectional and observational research methods as well as descriptive statistics and figures are used to elucidate the secondary data. Data demonstrate that Bangladesh now generates 41.16% of its energy from renewables, despite considerable variability. Regardless of the variation in freshwater availability, averaging at 708.19 cubic meters per capita, efficient water productivity remains consistent, indicating a robust water management system. The country demonstrates a relatively low carbon footprint, emitting 0.35 metric tons of CO2 per capita, alongside varying energy intensity levels, highlighting the need for enhanced efficiency measures. While pervasive PM2.5 air pollution poses a significant health risk, Bangladesh's reliance on natural resource rents underscores the importance of sustainable resource management practices for long-term economic stability. The observations of this study might assist in the formulation of policies of water management systems, air pollution control initiatives, and conservation of ecology to promote Bangladesh's long-term sustainability objectives and formulate policies.