Environmental Management Applications Research Articles

Pelatihan penerapan pembelajaran sainstivik dan penataan lingkungan untuk menfasilitasi merdeka belajar pada guru-guru KB TK Bantul

This service is motivated by the problems faced by family planning teachers at Cluster 7 Kindergarten, Kasihan Bantul District, Yogyakarta regarding: 1). Teachers still lack understanding of the implementation of a scientific approach in learning in schools. 2). Teachers in implementing scientific learning such as observing, asking, collecting, associating and communicating information in class activities are still confused/don't understand the whole thing. This service aims to provide training and assistance in the application of scientific learning and environmental management to facilitate independent learning for early childhood. The method in this research uses: lectures, questions and answers, and supervisory actions carried out over 2 cycles. There are four stages in service activities and each cycle consists of: planning, implementation, observation and evaluation (reflection). The results of the training implementation show that PAUD teachers at KB TK Gugus 7, Kasihan Bantul District, Yogyakarta, have improved in implementing scientific learning and environmental arrangements to facilitate independent learning for early childhood children after participating in training and mentoring activities.

Water‐controlled ecosystems as complex networks: Evaluation of network‐based approaches to quantify patterns of connectivity

AbstractThis study provides a new perspective on understanding the intricacies of water‐mediated connectivity in ecosystems, bridging landscape ecology and geomorphology through network science. We highlight dryland and river‐floodplain ecosystems as distinct examples of contrasting water‐controlled systems. We (1) discuss central considerations in developing structural connectivity and functional connectivity networks of water‐mediated connectivity; (2) quantify the emergent patterns in these networks; and (3) evaluate the capacity of network science tools for investigating connectivity characteristics. With a focus on strength (weights) and direction, connectivity is quantified using seven parameters at both network and node levels. We find that link density, betweenness centrality and page rank centrality are highly sensitive to directionality; global efficiency and degree centrality are particularly sensitive to weights; and relative node efficiency remains unaffected by weights and directions. Our study underscores how network science approaches can transform how we quantify and understand water‐mediated connectivity, especially in consideration of the role(s) of weights and directionality. This interdisciplinary perspective, linking ecology, hydrology and geomorphology, has implications for both theoretical insights and practical applications in environmental management and conservation efforts.

Annual Review of Ecology, Evolution, and Systematics, Volume 54

The Annual Review of Ecology, Evolution, and Systematics covers significant developments in the fields of ecology, evolutionary biology, and systematics, as they apply to all life on Earth. Essay reviews cover topics ranging from phylogeny, speciation, and molecular evolution through behavior and evolutionary physiology to population dynamics, ecosystems processes, and applications in invasion biology, conservation, and environmental management. There are 22 articles.

Annual Review of Ecology, Evolution, and Systematics, Volume 54

The Annual Review of Ecology, Evolution, and Systematics covers significant developments in the fields of ecology, evolutionary biology, and systematics, as they apply to all life on Earth. Essay reviews cover topics ranging from phylogeny, speciation, and molecular evolution through behavior and evolutionary physiology to population dynamics, ecosystems processes, and applications in invasion biology, conservation, and environmental management. There are 22 articles.

Enhanced Cadmium Sensing in Fertilizer Samples using Zeolite-modified Graphite Electrode

The presence of heavy metals in fertilizers poses significant environmental and health risks, necessitating robust detection methods to ensure agricultural sustainability and food safety. This study focuses on synthesizing Na-P1 zeolite from coal fly ash and fumed silica wastes, employing it as a potent modifier in graphite electrodes to enhance the electrochemical detection of cadmium (II) in fertilizer samples. Through meticulous assessment using cyclic voltammetry (CV) in a potential window of −1.2 V to 0.5 V, square wave voltammetry (SWV) in a potential region of −1 V to 0.5 V, and electrochemical impedance spectroscopy (EIS) in a frequency ranging from 100 kHz to 10 mHz under open circuit potential polarization, the electrochemical performance of the zeolite-modified graphite electrode (ZGE) was evaluated. The optimization process involved fine-tuning various parameters such as paste composition, solution pH, scan rate, and analyte concentration. Real sample analysis confirmed the applicability of the method in fertilizer samples. Notably, in an HCl medium (pH = 1.0), the SWV oxidation peak of Cd(II) was observed at −0.56 V (vs SCE) with a deposition time of 20 s and a scan rate of 75 mV∙s−1. The ZGE exhibited a remarkable detection limit of 1 μM, a quantification limit of 5 μM, and a high sensitivity of 6.581 μA/μM.cm2 within a linear detection range of 10−3–10−6 M. These findings highlight the potential utility of Na-P1 zeolite in handheld analytic device manufacturing, offering promising applications in environmental monitoring, resource management, and water and soil resource remediation.

Preface

The 5th International Conference of Geography and Disaster Management 2023 (ICGDM 2023) was successfully held by the Faculty of Geography, Universitas Muhammadiyah Surakarta. The conference was held via online Zoom meeting on 5-6th December 2023. ICGDM 2023 had a relevant theme for the tropical regions which is “Exploring Sustainable Solutions for Regional Development in Tropical Geographies: Unveiling the Potential, Embracing the Challenges”. It aimed to be a scientific platform for research dissemination, ideas sharing, and collaboration related to topics of environmental studies, socio-economic, regional development, disaster management, remote sensing, and GIS applications. ICGDM 2023 invited speakers from different backgrounds who are experts in the field of either physical or socio-economic geography. The keynote speakers were Dr. Nawaz M Mian (National University of Singapore, Singapore), Prof. Christopher Gomez (Kobe University, Japan), Muhammad Aufaristama, Ph.D. (University of Twente, Netherlands), Asaba Joyfred, M.A. (Kyambogo University, Uganda), Dr. Mukhamad Ngainul Malawani, M.Sc. (Universitas Gadjah Mada, Indonesia), Dr. Edy Trihatmoko (Impact Team 2050 Member, State Atomic Energy Corporation Rosatom (ROSATOM), Russia). This ICGDM 2023 was attended by 123 participants and presenters. The committee has received 123 paper submissions, and after the review process, 60 papers were selected for publication in the IOP Conference Series: Earth and Environmental Science. We would like to thank all the authors who have actively participated in the conference. We also highly appreciate the full support from Universitas Muhammadiyah Surakarta. List of Committee is available in this pdf.

Detection of Water bodies using Satellite Imagery based on Deep Learning

Abstract: Satellite images are important for monitoring and managing natural resources. Water bodies such as lakes, rivers, and oceans are of great importance to the environment and human populations. The identification of water body pixels in satellite images is therefore an important task for environmental management and planning. In recent years, deep learning has shown great promise in image processing, including object detection and segmentation. This study employs CNNs and RNNs to identify water body pixels in satellite images, aiming to create a model that can accurately distinguish water and non-water pixels. This model has practical applications in environmental monitoring and management

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.

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.

Signalling: Growth Promoters and Inhibitors

Plant growth and development are intricately regulated by a multitude of signaling pathways that respond to internal and external cues. Central to these regulatory mechanisms are the signaling pathways of growth promoters and inhibitors. Various growth-promoting hormones, including auxins, cytokinins, gibberellins, and brassinosteroids, stimulate cell division, elongation, and differentiation, playing vital roles in shaping plant architecture and influencing various developmental processes. The pathways of these growth promoters involve specific receptors and transcription factors that orchestrate growth in response to dynamic signals. In contrast, growth inhibitors, represented by hormones like abscisic acid, ethylene, jasmonic acid, and salicylic acid, act as crucial checkpoints that restrict growth during stress, pathogen attacks, or other adverse conditions. These signaling pathways trigger growth inhibition and activate defense mechanisms, enabling plants to adapt to challenging environments. Balancing the interplay between growth promoters and inhibitors allows plants to allocate resources efficiently and ensure their survival under changing circumstances. Understanding these signaling pathways is not only fundamental to plant biology but also essential for applications in agriculture, horticulture, and environmental management. This abstract provides a concise overview of these essential processes. This knowledge enables us to manipulate plant growth and development for improved crop yields, disease resistance, and stress tolerance. Ongoing research continues to unravel the complexities of these pathways, offering valuable insights into how plants delicately balance growth promotion and inhibition to thrive in an ever-evolving world.

Research on economic growth in smart cities based on wireless sensor networks

With the acceleration of urbanization, the concept of smart city is rising gradually. Wireless sensor network as an important technical support of smart city, its application in environmental monitoring and water resources management has a profound impact on economic growth. Water resource is one of the most dependent resources for human beings. With the growth of world population and the rapid development of economy, water resource crisis is constant, water pollution, water shortage and water waste coexist. How to build a perfect water resource economic policy is a worldwide problem at present. At present, the formulation of water resources policies is often based on experience or the knowledge system of decision makers. Due to the dynamic nature of water resources utilization and the incomplete information of decision makers, there are often policy failures, which affect economic growth. Based on this, this paper uses system dynamics model to study the mechanism of water resources management policies affecting economic growth by taking Gansu, Tianjin and Zhejiang as three qualitatively representative arid areas, transitional areas and water-rich areas. The research results show that under the same water resources policy coupling, different regions also have different eco-economic effects. The effect of coupled water resources policy is better than that of single water resources management policy.

Ground Tire Rubber as a Sustainable Additive: Transforming Desert Sand Behavior

Managing waste tires presents a significant challenge globally, particularly in regions experiencing high temperatures and shortage of landfill sites. This issue is affecting countries like Kuwait, where the abundance of waste tires is a major source of environmental and safety risks, particularly during the intensely hot summer months. This extreme heat has sparked numerous fires, leading to substantial air pollution due to thick black smoke. Given the limited disposal options, recycling waste tires and finding practical applications for ground tire rubber (GTR) is essential. To address the challenge, a comprehensive laboratory testing program was conducted, using locally produced rubber aggregates as an additive to Kuwait's local surface sands. Two new variables were examined namely the size and gradation of the GTR, and the density of the compacted mixes. For this purpose, two different sizes of rubber aggregates, fine and coarse produced locally, were utilized, and the impact of relative compaction on the strength and compressibility of the mixtures was investigated by testing samples compacted to the maximum density and to 95% of the maximum density. The results suggest that combining local surface sands with rubber tire additives results in a lighter, more permeable, and compressible material, contributing significantly to sustainable waste management. With 20% rubber additive the maximum dry density decreased by nearly 20%, and the permeability increased by 1.74–3.11 times and the compression index increased by 6.15 and 3.8 times with fine and coarse rubber respectively. The angle of friction remained unchanged at 36° with the addition of coarse rubber and decreased by 3°–4° with fine rubber. The change in behavior although not an increase in the strength and stiffness, offers a range of suitable practical applications in civil engineering and environmental management, including use as a drainage layer, embankment construction on soft ground, earth fill around retaining walls, an additive in asphalt mixes, and in manufacturing compressible tiles for sports facilities.

Green synthesis of silver nanoparticles by waste of Murcott Mandarin peel as a sustainable approach for efficient heavy metal removal from metal industrial wastewater

This study introduces a sustainable and environmentally friendly method for synthesizing silver nanoparticles (Ag-NPs) using waste from Murcott Mandarin peel (Citrus reticulata Blanco × C. sinensis (L.) Obs.). By repurposing agricultural waste as a precursor for nanoparticle synthesis, the research not only reduces waste but also aligns with green chemistry principles. The synthesis process involved extracting bioactive compounds from Murcott Mandarin peel, which acted as both reducing and stabilizing agents during nanoparticle formation. Characterization techniques, including UV–Vis spectroscopy and X-ray diffraction (XRD), confirmed the successful formation of silver nanoparticles. These nanoparticles demonstrated exceptional efficiency in removing heavy metals from metal industrial wastewater, particularly lead ions. Batch experiments revealed significant adsorption capabilities, with lead ions being uptake by silver nanoparticles at a rate of 42.7 mg/g under optimal conditions of pH 5.5 and 60 min of stirring. Additionally, Murcott Mandarin Solid Residue (MM-SR) obtained from the filtration process during Ag-NP synthesis exhibited promising lead ion uptake, reaching 6.6 mg/g under the same optimal conditions. The eco-friendly synthesis route and the efficient heavy metal removal capabilities of silver nanoparticles underscore the potential of utilizing agricultural waste in nanomaterial synthesis for wastewater treatment. This approach not only tackles waste disposal challenges but also generates value-added materials with practical applications in environmental management. Overall, the study emphasizes the importance of exploring innovative and sustainable pathways for nanoparticle synthesis, highlighting the promising role of silver nanoparticles synthesized from Murcott Mandarin peel waste in cost-effective and environmentally benign strategies for heavy metal removal in metal industrial wastewater treatment.

Response of soil erosion resistance to straw incorporation amount in the black soil region of Northeast China

Straw incorporation has been considered as an effective environmental management application to improve soil erosion resistance (SER) and organic carbon sequestration. SER is useful to evaluate soil erosion subjected to concentrated flow. Nevertheless, few studies have been performed to examine how SER varied with the amount of straw incorporation on sloping croplands in high latitude and cool regions. In the current study, the fixed bed scouring tests were conducted in a large hydraulic flume using undisturbed soil samples taken from Hebei small watershed in the black soil region of Northeast China. The response of SER to different straw incorporation amounts (0, 1.125, 2.25, 4.5, 6.75, 9.0 and 13.5 t ha−1) was quantified after three months of straw decomposition. The major influencing factors and the corresponding mechanisms were determined. The findings demonstrated that rill erodibility firstly decreased exponentially with straw incorporation amount (R2 = 0.93), while it slightly increased when straw incorporation amount was more than 9.0 t ha−1. Critical shear stress firstly increased logarithmically (R2 = 0.90) and then slightly decreased when the amount exceeded 9.0 t ha−1. Compared to the treatment of 0 t ha−1, rill erodibility reduced by 17.0%–92.8% and critical shear stress increased by 59.6%–127.2% across different treatments of straw incorporation. Rill erodibility had significant and negative correlations with soil organic matter content, aggregate stability, cohesion, root mass density, straw mass density and straw decomposition amount. The key mechanisms for promoting SER were derived by the direct and indirect effects of straw incorporation and its decomposition on soil physicochemical properties and crop roots. The amount of 9.0 t ha−1 was recommended as the optimum amount of straw incorporation in croplands in Northeast China. These findings are useful to understand how soil erosion resistance responds to the amount of straw incorporation and make rational environmental management policy for semi-humid and cool regions.

IoT based weather monitoring system for temperature, humidity, rainfall and seismic detection in real time

This paper presents the design and implementation of an IoT-based weather monitoring system enhanced with seismic detection capabilities, employing Node MCU microcontroller and the Blynk mobile application platform. The system incorporates various sensors including a rain sensor, Light light-dependent resistor (LDR), a DHT11 sensor for temperature and humidity measurement, and an accelerometer (MPU6050) for earthquake detection. The hardware components are interconnected with the Node MCU microcontroller, facilitating real-time data acquisition from the sensors. Programming of the Node MCU is conducted using the Arduino IDE, enabling data transmission to the Blynk app via Wi-Fi connectivity. The Blynk app serves as the user interface, allowing seamless visualization and monitoring of weather parameters and seismic activity on smartphones. Key functionalities of the system include periodic data collection from sensors, transmission of sensor data to the Blynk server, and updating of graphical representations in the Blynk app interface. The accelerometer sensor is utilized to detect changes in acceleration, indicative of seismic disturbances. Threshold values are defined to trigger alerts within the Blynk app in the event of potential seismic activity. The implementation undergoes rigorous testing to ensure accuracy, reliability, and responsiveness under diverse environmental conditions. Considerations such as network stability, power efficiency, and data security are addressed to enhance system performance and longevity. The system demonstrates promising capabilities for real-time weather monitoring and seismic event detection, offering valuable insights for disaster preparedness and environmental analysis. IoT-based weather monitoring system integrated with seismic detection provides an effective solution for comprehensive environmental monitoring, leveraging the power of IoT technology and mobile applications for enhanced data accessibility and analysis. Further advancements and optimizations can be explored to extend the functionality and scalability of the system for broader applications in environmental science and disaster management.

Comparative Analysis of Ground-Based Solar Irradiance Measurements and Copernicus Satellite Observations

Solar irradiance data provided by the Copernicus program are crucial for several scientific, environmental, and energy management applications, but their validation by means of ground-based measurements may be necessary, especially if daily and hourly data resolutions are required. The validation process not only ensures that reliable information is available for solar energy resource planning, power plant performance assessment, and grid integration, but also contributes to the improvement of the Copernicus system itself. Ground-based stations offer site-specific data, allowing for comprehensive assessments of the system’s performance. This work presents a comparative statistical analysis of solar irradiance data provided by the Copernicus system and ground-based measurements on a seasonal basis at three specific Italian reference sites, showing a maximum average relative error of less than 7% for hourly horizontal global irradiance in the irradiance range defined by the IEC 61724-2.

Implementation of a Wireless Sensor Network for Environmental Measurements

Nowadays, the need to monitor different physical variables is constantly increasing and can be used in different applications, from humidity monitoring to disease detection in living beings, using a local or wireless sensor network (WSN). The Internet of Things has become a valuable approach to climate monitoring, daily parcel monitoring, early disease detection, crop plant counting, and risk assessment. Herein, an autonomous energy wireless sensor network for monitoring environmental variables is proposed. The network’s tree topology configuration, which involves master and slave modules, is managed by microcontrollers embedded with sensors, constituting a key part of the WSN architecture. The system’s slave modules are equipped with sensors for temperature, humidity, gas, and light detection, along with a photovoltaic cell to energize the system, and a WiFi module for data transmission. The receiver incorporates a user interface and the necessary computing components for efficient data handling. In an open-field configuration, the transceiver range of the proposed system reaches up to 750 m per module. The advantages of this approach are its scalability, energy efficiency, and the system’s ability to provide real-time environmental monitoring over a large area, which is particularly beneficial for applications in precision agriculture and environmental management.

Backward and forward simulation of polycyclic aromatic hydrocarbons by the grid-scale model _validation and applications for environmental management

Polycyclic aromatic hydrocarbons (PAHs) associated with fine particulate matter (PM2.5) can cause serious health problems, but data are scarce. We have previously developed a grid-scale model (GSM) to simulate PM2.5-PAH levels on an hourly basis. This study aims to verify the applicability of the model to different years and to reasonably assess the long-term spatiotemporal effects on PAH variation in Kaohsiung. From the resulting database, the annual mean of PM2.5-PAH was found to have decreased from 3.18 in 2005 to 1.78 ng m−3 in 2018, representing an overall decrease of 44%. Thus, this study found that the progressive decrease in PAH levels was closely related to green transport and the gradual tightening of industrial operation regulations. Namely, in the urban area near the central public transport hubs, the estimated PAHs had significantly decreased by 16% (0.37 ng m−3) in 2009 with the operation of the high-speed railway in 2007 and the mass rapid transit in 2008. Near industrial areas, PAHs were reduced by environmental regulations, including air pollution control fees and cap-and-trade policies. By using GSM simulation, this study demonstrated a useful and feasible urban planning tool, and can serve as a reference for future studies related to epidemiology and environmental management.

Enhancing shallow water quality monitoring efficiency with deep learning and remote sensing: A case study in Mar Menor

Satellite remote sensing technology has proven effective in monitoring various environmental parameters, but its efficiency in assessing shallow lakes has been limited. This study applies state-of-the-art machine and deep learning algorithms supported by classical statistic methods to analyze remote sensing data to measure chlorophyll-a (Chl-a) concentration levels. Focused on a shallow coastal lagoon, Mar Menor, this work analyzes statistically daily Sentinel 3 information behaviour and compares Machine Learning and Deep Learning techniques to enhance efficiency and accuracy data of this satellite. Convolutional Neural Networks (CNNs) stand out as a robust choice, capable of delivering excellent results even in the presence of anomalous events. Our findings demonstrate that the CNN-based approach directly utilizing satellite data yields promising results in monitoring shallow lakes, offering enhanced efficiency and robustness. This research contributes to optimizing remote sensing data to and produce a continuous information flow addressed to monitoring shallow aquatic ecosystems with potential environmental management and conservation applications.

A Critical Review of the Effectiveness of Biochar Coupled with Arbuscular Mycorrhizal Fungi in Soil Cadmium Immobilization.

Cadmium-contaminated soil significantly threatens global food security and human health. This scenario gives rise to significant worries regarding widespread environmental pollution. Biochar and arbuscular mycorrhizal fungi (AMF) can effectively immobilize cadmium in the soil in an environmentally friendly way. Existing studies have separately focused on the feasibility of each in remediating polluted soil. However, their association during the remediation of cadmium-polluted soils remains unclear. This review paper aims to elucidate the potential of biochar, in conjunction with AMF, as a strategy to remediate soil contaminated with cadmium. This paper comprehensively analyzes the current understanding of the processes in cadmium immobilization in the soil environment by examining the synergistic interactions between biochar and AMF. Key factors influencing the efficacy of this approach, such as biochar properties, AMF species, and soil conditions, are discussed. The influences of biochar-AMF interactions on plant growth, nutrient uptake, and overall ecosystem health in cadmium-contaminated environments are highlighted. This review indicates that combining biochar and AMF can improve cadmium immobilization. The presence of AMF in the soil can create numerous binding sites on biochar for cadmium ions, effectively immobilizing them in the soil. Insights from this review contribute to a deeper understanding of sustainable and eco-friendly approaches to remediate cadmium-contaminated soils, offering potential applications in agriculture and environmental management.