Environmental System Research Articles

Machine Learning-Based Morel Mushroom Environmental Monitoring System

As living standards improve, the demand for edible fungi increases, making their efficient cultivation crucial for food supply and agricultural productivity. Traditional manual monitoring has limited accuracy, but the introduction of IoT and embedded technology enhances the intelligence and precision of agricultural monitoring, saving both labor and resources. This study designs a machine learning-based environmental monitoring and prediction system for edible fungi, utilizing low-power ZigBee networks and Kalman filtering to improve data accuracy. The system ensures real-time data transmission via the MQTT protocol and enhances security and scalability through cloud storage. By comparing Transformer, LSTM, and LSTM-Attention models, it was found that the Transformer model performed best in predicting environmental parameters, enabling proactive regulation, boosting yield and quality, and promoting the development of intelligent agriculture.

Environmental study delays in Nepal: A comparison with India and Bangladesh and policy recommendations

This research examines the environmental approval process in Nepal and compares it with those in India and Bangladesh, focusing on the time taken to complete the assessment of environmental study reports. The study conducts three levels of analysis. First, the policy review outlines all relevant environmental policies and laws, highlighting key provisions related to approval timelines. While not every step of the environmental study process has a mandated time frame, the legal time limits for report forwarding and approval are explicitly defined. Second, statistical analysis reveals a significant discrepancy between the statutory and actual approval times. While the legal mandate is just 35 days for Environmental Impact Assessment (EIA), assessing a report actually takes 339 days on average. The trend line reveals that the average time taken is decreasing. However, it is still much higher than India’s average EIA approval time of 64 days. Third, through a comparative analysis of eighteen different components of the environmental assessment process, this paper identifies the possible factors contributing to the delays, such as ambiguous jurisdiction, lack of nodal agency, lack of integrated guidelines, high centralization, and no use of e-governance. This paper also compares the thresholds that trigger the environmental study across eight sectors for three countries and finds that Nepal’s thresholds are narrower than India’s and comparable to Bangladesh’s. Recommendations made include clarifying jurisdictional roles, developing integrated guidelines, establishing specialized nodal agencies, and implementing digital systems. Overall, this research attempts to address flaws in Nepal’s environmental assessment system, offering solutions for efficient environmental regulation and improving the business environment in Nepal.

Integrating corporate sustainability reporting and environmental management systems into environmental performance management: an audit perspective

ABSTRACT Environmental performance management is critical worldwide because it helps mitigate climate change, conserve ecosystems, and preserve the earth for future generations by emphasizing sustainability and accountability. The study aims to investigate the influence of corporate sustainability reporting practices and environmental management systems on environmental performance management concerning the compliance of the organization’s audit. We used the 10-year data of the 400 listed firms from 2014 to 2023. The data for the variables is extracted from the DataStream database. The regression analysis technique is used as the method of estimation with the use ofgeneralized method of movement (GMM) as robustness method. Our findings show that corporate sustainability reporting practices have a significant positive relationship with the environment performance Management (EPM). Moreover, from the audit of the selected firms, it is shown that the selected organization has strong corporate sustainability reporting practices that improve EPM and auditor judge easily by the law compliances by transparent reporting promotes accountability, stimulates sustainable practices, and drives improvements in environmental management inside businesses. Moreover, our findings show that the environmental management system has a significant positive relationship with the environment performance by estabilishing structure that enable effcetive monitoring, mitigations, and improvemnet of consequences. Our study advocated significant implications forpolicymakers, government, and investors.

AI-Based Environmental Monitoring System with Farm Automation

This project presents an innovative approach to environmental monitoring in agricultural settings using AI-based solutions integrated with IoT technology. The system leverages data collected from various sensors such as soil moisture, gas sensors, and other environmental indicators to monitor the conditions in real-time. By utilizing an Arduino microcontroller, ESP module, and ThingSpeak server, the project is able to capture, store, and transmit sensor data effectively. The highlight of the project is the AI-based weather prediction module implemented using a Convolutional Neural Network (CNN) in Python, providing critical insights into weather conditions and allowing for data-driven decision-making. The system also includes a user-friendly web interface to display real-time monitoring and predictions, enabling farmers to better manage their resources and plan ahead for changes in environmental conditions

Development And Testing of Arduino Based Autonomous Environmental Monitoring System

This paper presents the development of an Autonomous Environmental Monitoring System (AEMS) designed to track various environmental parameters. With the growing demand for autonomous monitoring systems in today’s modern era, we propose an Arduino-based real-time hardware solution to measure parameters such as flame, temperature, humidity, and distance. The system leverages advanced and cost-effective electronic sensors and hardware to monitor these environmental factors. We developed individual sensor modules for each parameter and integrated them into a unified multi-sensor system through sensor fusion. The collected data is then displayed on a 16 × 2 LCD module. The result is a fully functional autonomous monitoring system, tested under laboratory environmental conditions using a compact, handheld device.

Greenland Wind-Wave Bivariate Dynamics by Gaidai Natural Hazard Spatiotemporal Evaluation Approach

The current work presents a case study for the state-of-the-art multimodal risk assessment approach, which is especially appropriate for environmental wind-wave dynamic systems that are either directly physically observed or numerically modeled. High dimensionality of the wind-wave environmental system and cross-correlations between its primary dimensions or components make it quite challenging for existing reliability methods. The primary goal of this investigation has been the application of a novel multivariate hazard assessment methodology to a combined windspeed and correlated wave-height unfiltered/raw dataset, which was recorded in 2024 by in situ NOAA buoy located southeast offshore of Greenland. Existing hazard/risk assessment methods are mostly limited to univariate or at most bivariate dynamic systems. It is well known that the interaction of windspeeds and corresponding wave heights results in a multimodal, nonstationary, and nonlinear dynamic environmental system with cross-correlated components. Alleged global warming may represent additional factor/covariate, affecting ocean windspeeds and related wave heights dynamics. Accurate hazard/risk assessment of in situ environmental systems is necessary for naval, marine, and offshore structures that operate within particular offshore/ocean zones of interest, susceptible to nonstationary ocean weather conditions. Benchmarking of the novel spatiotemporal multivariate reliability approach, which may efficiently extract relevant information from the underlying in situ field dataset, has been the primary objective of the current work. The proposed multimodal hazard/risk evaluation methodology presented in this study may assist designers and engineers to effectively assess in situ environmental and structural risks for multimodal, nonstationary, nonlinear ocean-driven wind-wave-related environmental/structural systems. The key result of the presented case study lies within the demonstration of the methodological superiority, compared to a popular bivariate copula reliability approach.

Space technologies for development? Practicing sovereignty, beyond inclusion

The increasing use and integration of space technologies in International Development projects raises fundamental questions about the ways in which these technologies are produced and applied, for what purposes and what ideas of innovation underpin their knowledge frameworks. With reference to two UK Space Agency (UKSA)-funded projects aiming to create an environmental information system using remotely sensed data, this article considers the possibilities and threats of user-centred technology design for the management of Indigenous territories. The team of Indigenous and non-Indigenous researchers grapples with the contradictions and sites of tension emerging at the intersection of the space sector, development, Earth system science and Indigenous sovereignty. Can space science and development be re-interpreted in the light of local needs, knowledges and right to self-determination? While common reliance on Western epistemologies feeds into deterministic understandings of technological benefits, this article presents Indigenous worldviews and practices as integral to codesign and co-implementation of innovations that are both technical and social. It argues that data are grounded and must be kept in connection with the contexts, culture and knowledges that make up a place. Praxis – as a theoretically inspired practice of doing development projects – thus emerges as a worldmaking activity inspired by a vision of design that foregrounds Indigenous sovereignty.

Environmental Impact Assessment System: Case Analysis of Existing Legal Disputes

Abstract: Environmental Impact Assessment (EIA) refers to the process of assessing the possible impact of planning activities on the environment. This paper contends that the current international legal framework does not adequately delineate the activation criteria for EIA and overlooks the significance of international collaborative duties that come into play when sovereign states embark on the initiation and execution of EIA processes. Only in relation to the general principles of international law can the nature of the EIAs obligation be comprehended. When dealing with cross-border damage, the requirement for due diligence is complemented by an implicit responsibility to collaborate. This latter obligation arises under identical situations as the due diligence requirement, particularly in response to 'the likelihood of significant environmental damage,' and thus, it needs to be satisfied by the national government under equivalent circumstances. This paper argues that the courts interpretation of environmental impact assessment is incomplete which is reflected in two aspects: (1) the ambiguity in the court's grasp of the EIA threshold's unpredictability. The International Court of Justice fails to clarify the criteria for establishing a 'substantial environmental risk'. (2) The court's oversight in considering the duty to collaborate could result in an overemphasis on the material aspects of EIA-treating it merely as a technical instrument. By reintegrating the cooperation duty, a more balanced perspective on the procedural elements of EIA could be achieved. Delving into strategies to rectify these two deficiencies and obtaining a holistic insight into the International Court of Justice's approach to EIA will yield substantial implications and relevance for future EIA-related endeavors.

Comprehensive Management of Water Resources: A Step-By-Step Path Towards a Sustainable Campus At The U.D.C.A (Bogotá, Colombia)

Universities are recognized as essential agent of change since future decision-makers related to sustainability are going and will pass through their classrooms. This circumstance becomes an excellent opportunity to demonstrate, with example, and instill in the students how these types of organizations control and approach implementing practices that guarantee sustainability and the appropriate use of resources over time. The Universidad de Ciencias Aplicadas y Ambientales has undertaken different actions related to the Integrated Water Resources Management (IWRM) on campus since 1990. This work focuses on the actions carried out by the Integrated Environmental Management System (latest institutional management model) between the 2014-2016 period to improve the university campus's IWRM (drinking water and wastewater management) from a systemic point of view. The actions implemented were part of the project: Reusing treated water at the University's Wastewater Treatment Plant (WWTP). This project included the following objectives: 1) Reduce the volume and economic costs of sludge water disposal; 2) Reduce drinking water consumption; and 3) Promote environmental education about water resources in students of the different programs of the University. The results were: 1) A decrease of 68.3% in volume and 69.5% in costs of sludge water disposal; 2) A 41.2% saving in drinking water consumption; and 3) 2,475 members of the university community impacted by issues related to the management of water resources.

A New Wax Gourd (Benincasa hispida (Thunb.) Cogn.)‐Assisted Green Synthesis Method of Metal Oxides (TiO2, MgO)

AbstractIn the reaction environment of wax gourd extract, titanium dioxide (TiO2) and magnesium oxide (MgO) were synthesized by microemulsion method. Under atmospheric pressure, the optimum conditions for preparing TiO2 and MgO nanoparticles were investigated at different reaction temperatures and time. The obtained optimal reaction conditions are as follows: when the amount of TiCl3 solution was 70 µL, the mass ratio of wax gourd extract to water was 1:2, the reaction time was 60 min, and the reaction temperature was 35 °C, rod‐like TiO2 particles with the best dispersion and crystallinity were obtained. When the amount of MgCl2 solution was 10 mL, the amount of wax gourd extract was 40 mL, the reaction time was 120 min, and the reaction temperature was 70 °C, the prepared MgO particles exhibited a spindle shape with the best dispersion and crystallinity. Wax gourd‐assisted synthesis of TiO2 and MgO provides not only a new synthesis idea for the preparation of metal oxides, but also a green environmental protection system, which conforms to the concept of sustainable development.

How have regional evacuation conditions changed over time? evacuation model for alternative scenarios given the accident environment, regional environment, and social systems.

The rapid evacuation in major leak accidents during hazardous chemical transportation is critical for protecting people in risk areas. An approach integrating the accident environment, regional environment, and social system is proposed to perform evacuation evaluation in such accidents. An agent-based modeling framework consisting of warning mechanisms, evacuation preparation process, as well as evacuation modes and movement process, is developed to comprehensively model the evacuation process. The regional environmental and social system data from 1964 to 2020 of Jiangsu Province in China is applied to analyze whether the changes in evacuation conditions have correspondingly affected evacuation effectiveness. A regional evacuation model simulating a real liquid chlorine leak accident during transportation in Wuzhong of Jiangsu Province is constructed to test the effectiveness and applicability of the proposed method. It is found that a 9% change in the diffusion rate of warning messages triggered by environmental cues with the evolution of the study area settlements following the chronological changes; while the evolution of media technology allows for the rapid diffusion of warning messages and the rapid loading of a large number of individuals into the regional evacuation network; Years with faster warning diffusion have not been the most efficient ones in terms of overall evacuation; The distribution of buildings and population substantially impacts the overall evacuation effectiveness, while the former has a more significant impact. The study results can provide information for public emergency authorities to develop effective early warning resource allocation and evacuation organization plans.

Design and research of a monitoring and environmental testing analysis system for substation status

Abstract By testing and analyzing the real substation environment, and analyzing and fitting on-site data, a system that simulates the operating environment of the real substation is designed, and the goal of replicating a typical on-site electricity environment is achieved. Testing and analysis are conducted on the selected substation area, and light and heavy load noise is collected for spectrum analysis and measurement point attenuation analysis. The LMF (Late Multimodal Fusion) algorithm is used and test data are fitted based on the trust region theory. Conducting noise testing and attenuation analysis in the substation area has laid the foundation for research on substation status monitoring and environmental monitoring.

Assessment of the efficiency of functioning of the environmental management system of enterprises

Purpose. A multifactor model is developed to assess the efficiency level of an enterprise’s environmental management system, depending on the effectiveness of organizational environmental measures. Methodology. The authors’ method for determining a comprehensive criterion for monitoring the effectiveness of the environmental management system, which characterizes the efficiency of operation and determines the level of environmental safety of enterprises, is proposed and used. To solve the tasks, a complex research method was also used, which included the analysis and generalization of literary and patent sources, and analytical, experimental research using computer and mathematical modeling methods. Findings. According to the studies and calculations of the generalized environmental quality indicator – 0.64, 0.66 and 0.66, the largest negative impact on the environment is caused by the activities of enterprises in the Pecherskyi, Podilskyi, and Solomianskyi districts of Kyiv, respectively. The obtained data testify to the relationship between the effectiveness of the implemented environmental measures (saving and rational use of resources, application of environmental technologies, advanced training, and environmental competence of employees) and the level of efficiency of the environmental management system of enterprises. Originality. As a result of the studies conducted using actual data, a system of indicators of the generalized environmental quality indicator has been proposed for the first time, which allows determining the environmental efficiency and effectiveness of the implemented environmental measures to assess the effectiveness of the functioning of the implemented environmental management system of the enterprise. Practical value. Based on the research results, a technique is proposed to assess the effectiveness of the environmental management system of enterprises by determining a generalized environmental quality indicator in terms of reducing the negative impact of the enterprise’s activities on the environment. Such an assessment system will help the management of the enterprise to promptly introduce corrective actions to improve the efficiency of the environmental management system and increase the level of environmental safety.

Ambient particulate matter and frequency of outpatient visits for chronic rhinosinusitis in the United States.

Emerging evidence has underscored the harmful effects of air pollution on the upper airway. We investigated the relationship between ambient particulate matter (PM) level and the frequency of outpatient visits for chronic rhinosinusitis (CRS). We conducted an ecological cohort study of US adults enrolled in The Merative MarketScan outpatient database from 2007 to 2020. For each geographical subunit (core-based statistical area [CBSA]), we calculated the annual rate of CRS-related outpatient visits per 1000 well-patient checkup visits (CRS-OV). Using data from the Environmental Protection Agency's Air Quality System, we mapped the rolling statistical average of daily PM2.5 and PM10 over the preceding year onto each CBSA×year combination. We employed multivariable negative binomial regression modeling to estimate the association between PM levels and subsequent CRS-OV. Across 3933 observations (CBSA×year combinations), encompassing ∼4 billion visits, the median CRS-OV was 164 (interquartile range 110-267). The mean PM2.5 level was 8.9µg/m3 (SD 2.6) and the mean PM10 level was 20.2µg/m3 (SD 7.2). Adjusting for patient demographics and respiratory comorbidities, a compounded rise in subsequent CRS-OV was observed with increasing PM levels. Each µg/m3 rise in PM2.5 independently predicted a 10% increase in CRS-OV (adjusted incidence rate ratio [aIRR]) 1.10, 95% confidence interval [CI] 1.08-1.13) and each µg/m3 rise in PM10 independently predicted a 3% increase in CRS-OV (aIRR 1.03, 95% CI 1.02-1.04). Elevated ambient PM2.5 and PM10 levels are associated with a subsequent compounded increase in the frequency of CRS-OV, with PM2.5 predicting a more pronounced rise compared to PM10.

Sustainable Environmental Management: Evaluating the Effects of the Tail Number Restriction Policy on Air Quality in Lanzhou, China

In recent years, haze pollution in China has garnered significant attention from both the government and the public, with vehicle emissions being identified as a key source of pollution. This study analyzes the impact of the tail number restriction policy (TNRP) on air quality using daily data from Lanzhou, China, in 2020, by employing the regression discontinuity in time (RDiT) method. The results show that the TNRP significantly reduced the air quality index (AQI) and concentrations of PM2.5, PM10, NO2, and CO, indicating a positive effect on air quality, though this is not a long-term standalone solution. Unlike previous policies, the current TNRP restricts traffic during peak hours, yielding consistent effects. This study recommends continuing the restriction policy and developing a comprehensive environmental governance system to promote new energy vehicles and enhance public transportation infrastructure.

AI-driven predictive maintenance and optimization of renewable energy systems for enhanced operational efficiency and longevity

The rapid growth of renewable energy systems necessitates advanced strategies for maintenance and optimization to ensure long-term operational efficiency and sustainability. Traditional approaches often fall short in predicting failures and optimizing performance across diverse and dynamic renewable energy infrastructures. This study investigates the application of artificial intelligence (AI) techniques for predictive maintenance and optimization of renewable energy systems, with the aim of enhancing operational efficiency and extending system longevity. We employ a combination of machine learning algorithms, including deep neural networks and reinforcement learning, to develop predictive models and optimization strategies. These models are trained on large-scale datasets collected from operational wind farms, solar installations, and hydroelectric plants. Our results demonstrate that AI-driven approaches can predict equipment failures with 92% accuracy, reducing unplanned downtime by 35% compared to traditional methods. Moreover, AI-optimized operational parameters improved overall energy output by 8.5% across the studied systems. The proposed framework also showed adaptability to various environmental conditions and system configurations, suggesting broad applicability across the renewable energy sector. This research underscores the significant potential of AI in revolutionizing maintenance practices and operational strategies in renewable energy systems, paving the way for more reliable, efficient, and sustainable clean energy production.

Can ESG Disclosure Stimulate Corporations’ Sustainable Green Innovation Efforts? Evidence from China

The Environmental, Social, and Governance (ESG) Composite Rating denotes corporations’ capability for supporting sustainable development activities, social responsibility, and transparent and ethical governance. It aims to inform investors and stakeholders about the company’s sustainability and social responsibility risks. ESG has increasingly become an informal yet significant driving force in promoting sustainable green innovation within the diversified co-governance environmental management system. This paper examines the dynamic relationship between ESG performance and sustainable green innovation practices in Chinese A-share listed companies from 2011 to 2022. The results show a positive correlation between ESG performance and the level of corporate sustainable green innovation. They also validate the moderating roles of informal external pressure and internal development demands. While the moderating effect of public environmental concern (PEC) is not significant, corporate digital transformation (CDT) significantly and positively moderates the relationship between ESG performance and sustainable green innovation. These findings offer policymakers and corporations a means to formulate a framework to shape the conduct of corporations to meet the market’s green development needs and to establish instruments that promote green innovation.

Spatial impact of green finance reform pilot zones on environmental efficiency: A pathway to mitigating China's energy trilemma

The energy trilemma is a critical global challenge requiring urgent resolution; however, existing solutions remain inefficient. This study utilizes a detailed environmental input-output indicator system, applying the SBM-DEA model for measurement and incorporating the Spatial Difference-in-Differences (SDID) model to assess the impact of Green Finance Policy (GFP) on environmental efficiency in Chinese cities from 2006 to 2021. The findings demonstrate that GFP significantly enhances environmental efficiency within a 500-km radius, as confirmed by various robustness tests. Mechanism analyses indicate that optimizing industrial structure, reducing energy consumption, advancing green innovation, and strengthening environmental regulations are critical pathways to improving environmental efficiency. Heterogeneity tests further examine the spatial policy effects under different factor endowments. Ultimately, the study concludes that improving environmental efficiency through GFP can alleviate the energy trilemma. This paper highlights the importance of implementing city-specific policies, offering new insights into energy economics, and providing fresh perspectives for policymakers, financial institutions, and enterprises. Despite the study's contributions, future research should further explore the comprehensive effects of GFP on energy, the environment, and the economy to provide more precise and holistic solutions for addressing the energy trilemma.

Wastewater-Based Epidemiology of Influenza Viruses: a systematic review

Abstract Background Influenza viruses (IVs) are responsible for annual epidemic outbreaks during the winter months. Beyond conventional surveillance systems, the circulation of these pathogens can be monitored using Wastewater-Based Epidemiology (WBE), an epidemiological tool that describes the health status of an entire community by analyzing the presence of pathogens within wastewater. Systematically reviewing existing experiences in this emerging field is crucial to highlight the best practices to establish a WBE surveillance system providing useful information for public health actions. Methods The study protocol for this systematic review has been registered on the PROSPERO website (registration ID: CRD42024532435). Three academic databases (PubMed, Web of Science and Scopus) were accessed to collect studies examining the presence of IVs in wastewater. Studies included were those reporting quantitative measures of viral concentration or detailing molecular/phylogenetic characterization of IVs in wastewater. Results Databases were searched on July 8th, 2024. After de-duplication and screening of the 400 remaining records, 42 were included in the review. IVs detection in wastewater was reported in all papers except from one, although with high variability in terms of positivity titers and concentration levels. More than half of the collected papers (52.4%) evaluated association between environmental viral concentration and clinical data, generally showing concordance between the two aspects. Moreover, 28.6% of papers described subtyping of IVs in wastewater through different methods (specific PCR assays being the most used). Conclusions WBE is a promising approach for surveilling viral circulation, and IVs represent a high value target for implementing this innovative system. Systematically reviewing previous experiences can be useful to obtain information for the establishment of a novel environmental surveillance system of Influenza Viruses Key messages • Nucleic acids belonging to Influenza Virus are detectable in wastewater, even though we report high levels of variability in sampling techniques, laboratory methods and data management systems. • Association between environmental data and number of clinical cases is reported to be generally strong in collected papers; subtyping of IVs present in wastewater is also feasible.

IoT-Based Connected Environmental Monitoring System Using NodeMCU

The Connected Environmental Monitoring System leverages the NodeMCU ESP8266 microcontroller in conjunction with various sensors, including the MQ-135, DHT22, BMP280, and a sound sensor, to enable real-time monitoring of critical environmental parameters. This project aims to provide comprehensive insights into air quality, temperature, humidity, atmospheric pressure, and noise levels, fostering awareness and informed decision-making regarding environmental conditions. Data collected by the sensors is transmitted wirelessly to the ThingSpeak cloud platform, where it is stored and visualized through user-friendly dashboards. The system also incorporates alert mechanisms to notify users when specific parameters exceed predefined thresholds, facilitating timely interventions. The modular architecture of the system allows for scalability and flexibility, making it adaptable for various applications, including urban management and smart city initiatives. Overall, this project demonstrates the efficacy of IoT solutions in addressing environmental monitoring challenges, contributing to the development of sustainable practices and enhanced community well-being.