Environmental Management Practices Research Articles

Risk assessment of land subsidence based on GIS in the Yongqiao area, Suzhou City, China.

This study focuses on the Yongqiao District in Suzhou City, Anhui Province, China, aiming to analyze the current situation of ground settlement and its influencing factors in the area. The selected risk indices include settlement rate, cumulative settlement amount, groundwater level drop funnel, thickness of loose sediment layer, thickness of soft soil layer, and the number of groundwater extraction layers. Additionally, vulnerability indices such as population density, building density, road traffic, and functional zoning are considered. An evaluation index system for assessing land Subsidence risk was established. The risk evaluation of land Subsidence was conducted using the Hierarchical analysis-composite index method and ArcGIS spatial analysis, The evaluation results show that the area of higher risk area is about 2.82 km2, accounting for 0.96% of the total area, mainly distributed in the area of Jiuli village, Sanba Street. The middle risk area is distributed around the higher area, with an area of about 9.18 km2, accounting for 3.13% of the total area. The lower risk areas were distributed in most of the study area, covering an area of 222.24 km2, accounting for 75.82% of the total area. The low risk assessment area is mainly distributed in Bianhe Street and part of Zhuxianzhuang Town, with an area of about 58.88 km2, accounting for 20.09% of the total area. The findings of this study are not only crucial for informing local policies and practices related to land use planning, infrastructure development, and emergency response but also enhance our understanding of the complexities of land Subsidence processes and their interactions with human activities, informing future research and practice in environmental risk assessment and management.

Sensitivity Analysis and Optimal Control of Cocoa Black Pod Disease Caused by Phytophora Margakarya

To address the critical threat black pod disease poses to global cocoa production and farmer income, this study developed a novel mathematical model that utilizes a system of ordinary differential equations to capture the interactions between various stages of cocoa pods (susceptible cherelles, young/mature pods, ripe pods) and their disease state (exposed, infected). Additionally, the model incorporates the dynamics of the disease-causing pathogen population. Employing Pontryagin’s Maximum Principle, the model optimizes control strategies that minimize disease impact. This optimization identifies the efficient allocation of resources, timing of interventions, and deployment of control measures like infected pod removal, fungicides, and sanitation practices. The finding of the study reveals that control measure u3 which is rouging (pod removal) and any one of the remaining control measures is best for the treatment of cocoa black pod disease caused by Phytophora Megarkaya. These findings translate into valuable, data-driven recommendations for cocoa farmers and disease management professionals. By strategically combining infected pod removal, targeted fungicide use, and environmental management practices, farmers can significantly reduce disease severity, enhance cocoa production, and promote a more sustainable cocoa industry.

ESG-driven ecopreneur selection in European financial institutions: entropy and TOPSIS analysis

PurposeThis is the application of the Entropy and TOPSIS model to assess the eco-efficiency of European financial institutions using environmental, social, and governance (ESG) strategies. The aim is to categorize financial institutions based on key factors such as environmental training and management and to examine the alignment between ideal ESG performance and eco-efficiency.Design/methodology/approachThe study uses environmental, social, and governance (ESG) strategies to identify and categorize eco-entrepreneurs in European financial institutions. The study utilizes data to examine the structure between environmental training, effective management practices, and the green performance of financial institutions.FindingsThe study shows that European financial institutions exhibit varying degrees of eco-efficiency as assessed using the Entropy and TOPSIS model applied to ESG strategies. Surprisingly, the study found that institutions with a high ESG performance do not always match those with the highest eco-efficiency.Research limitations/implicationsThey emphasize the need for financial institutions to align their operations with sustainable practices. This research provides insights to increase eco-efficiency and improve the ESG performance of financial institutions. It also informs policy and decision-making in these institutions in relation to environmental training and management practices, contributing to the wider dialogue on sustainable finance.Originality/valueThis indicates a discrepancy between ESG ratings and actual eco-efficiency, emphasizing the need to reassess the ESG framework. The study findings are crucial for aligning financial institutions with sustainable practices and improving the effectiveness of the ESG framework, especially for institutions at the lower end of the eco-efficiency spectrum.

Pollution Havens in South-East Asia: Examining Japanese Multinational Enterprises in the Philippines

Pollution Havens in South-East Asia: Examining Japanese Multinational Enterprises in the Philippines

Characterization and recognition of three-dimensional excitation-emission matrix spectra of wastewater from six typical categories

In this study, we analyzed the characteristics of three-dimensional excitation-emission matrix spectra (EEMs) of 150 samples from five industrial wastewater types and domestic sewage to track water pollution sources effectively. We then developed a recognition model for wastewater EEMs by establishing a feature dataset containing fluorescence peak values and parameters derived from EEMs, integrated with machine learning techniques. This model enables the rapid and precise identification of pollution sources. Our findings suggest that although the EEMs of the six wastewater categories are distinct, visual differentiation is challenging. This was confirmed by cosine similarity assessments, showing some samples with low within-group (< 0.8) and high between-group (> 0.95) similarities. Despite significant variations in EEMs features across wastewater categories, identifying specific pollutants remains difficult, especially for pulp mills and leather effluents. Among the tested classification algorithms, Support Vector Machine (SVM) achieved the highest performance with 91.7 % accuracy, 94 % precision, 91 % recall, and 92 % F1-score, outperforming K-Nearest Neighbors and Partial Least Squares Discriminant Analysis. The SVM significantly improved identification accuracy for pulp mill and leather processing wastewaters compared to other models. To enhance identification accuracy, further exploration of EEMs features and expanding the training dataset are recommended. Combining EEMs features with machine learning presents a promising method for improving water pollution supervision and source tracing in environmental management practices.

Sustainable supply chain management's impact on triple bottom line performance: Does the firm size matter?

AbstractCompanies worldwide are moving towards sustainability by focusing on its three dimensions: environmental, economic, and social sustainability. This study explores how sustainable supply chain management (SSCM) takes the changing role to affect these three dimensions. Since organizations vary in size, we post and test relationships regarding how firm size can impact the implementation of SSCM practices as a moderator. We posit an empirical research model and test this using structural equation modeling with survey data from 392 managers across various Jordanian manufacturing firms. This study assessed the link between five categories of SSCM practices and TBL performance. We found that firm size is critical and moderates the positive SSCM relationship with economic and social performances. Results shed new light on SSCM and its impacts on environmental, economic, and social performance. According to the study findings, environmental management practices and supply chain integration influenced all sustainability dimensions, whereas socially inclusive community practices influenced none. Furthermore, operations had an impact on economic sustainability. Finally, socially inclusive employee practices had a significant impact on both environmental and economic sustainability. Findings show that when implementing SSCM, larger firms perform better on multiple sustainability measures compared to smaller firms. The model's integration of firm size as a moderator provides additional insights regarding the SSCM construct and its change agent role in stimulating sustainable development.

Detection and Screening of Organic Contaminants in A Riverine System of Georgia Using Non-Targeted Analysis

Numerous organic chemicals exist within aquatic environments, yet effectively screening and prioritizing them is a huge challenge. This study provides a comprehensive investigation into the ecological dynamics of the North Oconee River within Athens-Clarke County, Georgia, with a specific focus on the distribution of 33 identified compounds, including a prominent pesticide. The research, conducted in the riverine ecosystems proximal to the Firefly trail, employs advanced analytical techniques to elucidate potential contamination sources arising from agricultural and urban runoff. Intriguingly, the study reveals North Oconee River near the Firefly Trail as a notable site for heightened pesticide contamination, warranting a meticulous exploration of its origins. Furthermore, the investigation unveils the intricate microbial degradation processes of malathion within the North Oconee River, elucidating the pivotal role played by microbial activity in river water. The detection of degradant byproducts prompts the considerations of bioavailability and toxicity, associating potential implications for the river’s overall ecological health. Ongoing research endeavors to precisely quantify environmental risks and unravel indigenous microbial degradation pathways, presenting pivotal contributions to the scientific community’s understanding of complex riverine ecosystems. This research serves as a foundational piece in informing sustainable environmental management practices and emphasizes the urgency of comprehensive stewardship in safeguarding aquatic ecosystems.

WSN-Driven Advances in Soil Moisture Estimation: A Machine Learning Approach

Soil moisture estimation is crucial for agricultural productivity and environmental management. This study explores the integration of Wireless Sensor Networks (WSNs) with machine learning (ML) and deep learning (DL) techniques to optimize soil moisture estimation. By combining data from WSN nodes with satellite and climate data, this research aims to enhance the accuracy and resolution of soil moisture estimation, enabling more effective agricultural planning, irrigation management, and environmental monitoring. Five ML models, including linear regression, support vector machines, decision trees, random forests, and long short-term memory networks (LSTM), are evaluated and compared using real-world data from multiple geographical regions, which includes a dataset from NASA’s SMAP project, supplemented by climate data, which employs both active and passive sensors for data collection. The outcomes demonstrate that the LSTM model consistently outperforms other ML algorithms across various evaluation metrics, highlighting the effectiveness of WSN-driven approaches to soil moisture estimation. The study contributes to the advancement of soil moisture monitoring technologies, offering insights into the potential of WSNs combined with ML and DL for sustainable agriculture and environmental management practices.

Ethnoecological perspectives on environmental stewardship: Tenets and basis of reciprocity in Gitxsan and nłeʔkepmx (Nlaka'pamux) Territories

Abstract Local and Indigenous Peoples steward and protect a significant proportion of biologically diverse ecosystems globally. This fact is increasingly acknowledged by researchers and international organizations, offering both opportunities and challenges at the intersection of Indigenous and western knowledge production in the context of environmental management research and policy. Drawing on half a century of ethnoecological research and personal experiences in Gitxsan and nłeʔkepmx Territories in the Pacific Northwest of North America, this research considers the role of reciprocity as an inherent philosophy and tenet for successful environmental stewardship. Reciprocity is a legal responsibility and moral perspective that foregrounds many Indigenous worldviews. Such cultural drivers and obligations towards lands and biota appear to be unknown, marginalized or instrumentalized in mainstream and western science and policy. We conclude that fundamental elements of reciprocity may not be adequately blended or braided into western environmental management frameworks. As such, alternatives to blending include acknowledging sole proprietary and self‐determining rights for Indigenous Peoples to govern and steward lands outside of western infrastructures and value systems. This study raises critical questions about the feasibility of reconciling reciprocity with western environmental management practices and regulations. It explores the implications for Indigenous rights and sovereignty, and climate change mitigation. By addressing these complex issues, we contribute to ongoing discourse on the integration of Indigenous and western knowledge in environmental stewardship research, and the ethical, historical and cultural challenges that come with it. Read the free Plain Language Summary for this article on the Journal blog.

Environmental (and random?) sex determination in endangered and invasive Phelsuma geckos.

Sex is a fundamental characteristic of an individual. It is therefore puzzling why in some systems sex is precisely determined by a genotype, while in others it is influenced by the environment or even subtle, not to say random, factors. Some stochasticity in sex determination would be expected if environmental conditions did not have a large sex-specific effect on fitness. Although data are only available for a small fraction of species, geckos show exceptional variability in sex determination. We tested the effects of three incubation temperatures on sex ratio and adult body size in the invasive gecko Phelsuma laticauda and the vulnerable gecko Phelsuma nigristriata. We document temperature-dependent sex determination (TSD) in both species. Only females hatched at a low temperature (24 °C), whereas male production peaked at an intermediate temperature (29 °C) and declined, at least in P. laticauda, again at the highest temperature (31 °C). Interestingly, full siblings hatched from eggs glued together during the incubation at temperatures producing both sexes are often of the opposite sex. We found no significant effect of incubation temperature on adult body length. Documentation of TSD in the day geckos has implications for conservation practice in environmental management of endangered species or eradication of invasive species. However, it appears that a very subtle (random?) factor may also be involved in their sex determination. In line with this, we found no significant effect of incubation temperature on adult body length, suggesting that, at least in this trait, there is no strong selection against producing females at "male" temperatures.

The Link between Sustainable Innovation and Industrial Performance: The Case of the United States

Notwithstanding the impact of sustainable innovation on environmental management, its bearing on industrial performance remains hypothetical. Our study seeks to empirically investigate the link between sustainable innovation and industry performance in the United States by employing the generalized method of moments on a nine-year panel spanning from 2014 to 2022. The sample consists of 94 U.S industries, which covers about 7300 companies. The results show that sustainable innovation is not significantly related to industrial performance in the United States. However, it has a moderating effect on industrial output. The Arellano–Bond test, AR (2), confirms the robustness of our findings given the endogeneity assumption and model specifications, and the Hansen test confirms the validity of the instruments. This study expands our knowledge of the link between sustainable innovation and industry performance. A study of this kind is relevant in current times as the United States seeks to attain Sustainable Development Goal 9 by 2030. Further, it provides theoretical guidance on successful environmental management practices to enhance social welfare and maximize output.

Empowering Smart Cities with AI and RPA: Strategies for Intelligent Urban Management and Sustainable Development

This research explores the transformative potential of Artificial Intelligence (AI) and Robotic Process Automation (RPA) in empowering smart cities to achieve intelligent urban management and sustainable development. Through a comprehensive analysis of literature, case studies, and qualitative research methods, the paper identifies key strategies for leveraging AI and RPA to address urban challenges and promote sustainable urban development. The integration of AI and RPA technologies enables data-driven decision-making processes, streamlines administrative workflows, and enhances service delivery in smart cities. Furthermore, AI and RPA contribute to promoting sustainable development goals by optimizing resource utilization, improving environmental management practices, and enhancing resilience to climate change. However, the widespread adoption of AI and RPA in smart cities faces challenges related to privacy, data security, and equity, which must be carefully addressed to ensure responsible and equitable deployment of these technologies. By adopting comprehensive strategies, fostering collaboration between stakeholders, and embracing a culture of innovation, cities can harness the full potential of AI and RPA to build smarter, more resilient, and sustainable urban environments for all residents. This research provides valuable insights for policymakers, urban planners, and technology providers seeking to leverage AI and RPA to address urban challenges and promote sustainable development in smart cities.

Analysis on The Understanding of Environmental Management Practices among Contractors in Malaysia using Rasch Measurement Model

The rapid development of construction industry in Malaysia has caused a significant impact on the environment and has resulted in increased demand for implementing environmental management practices. This study aimed to analyze the level of understanding on environmental management practices among contractors in Malaysia. A total of 47 contractors from all grades in Malaysia participated in this study. This study also used a 5-point Likert scale for the data collection process. Items in the questionnaire were analyzed using the Rasch Measurement Model to test the validity and reliability of the research instruments. The results showed that the item reliability value was 0.57 and the individual reliability value was 0.89. The value of the item separation index is 1.16 while the value of the individual separation index obtained is 2.78. Overall, person measure for construct of understanding level on environmental management practices ranged from +7.77 logit to -1.30 logit. For construct challenge faced by the contractor, the maximum value for person measure is +6.35 logit and the minimum measurement value is -0.97 logit. For the last construct which is the impact of environmental management practices on the environment, the value of person measure is +8.27 logit to -1.62 logit. Through item suitability analysis, there are some items that need to be dropped or harmonized as they not meet the requirements in one of the Outfit MNSQ and Outfit ZSTD ranges. The Rasch Measurement Model has identified that most contractors in Malaysia still have a moderate level of understanding on environmental management practices. The findings obtained at the end of this study are significant so that these environmental management practices remain practiced by contractors to maintain sustainable development in future.

Investigating the role of stakeholders in leveraging sustainability strategies in sports

ABSTRACT Research question Football is increasing its commitment toward environmental sustainability. However, the research on understanding the role of stakeholders in leveraging the adoption of green strategies in grassroots football seems to be in its infancy. Amidst this context, this study compares the perceptions of football fans, players, and staff regarding green strategies in European grassroots clubs. Research methods This study tests four hypotheses through structural equation modeling based on a sample of 1457 respondents from Belgium, France, Lithuania, Norway, and Sweden. Results and findings The results show that the environmental sensitiveness and knowledge of the stakeholders positively shape pressures on green practices adoption in grassroots clubs. However, environmental sensitiveness and environmental expectations from the football world are less strong in the case of grassroots football fans as compared to players and staff. The results also highlight that the environmental knowledge of football fans does not influence their environmental expectations while their environmental sensitiveness does so. These stakeholders’ pressures are effective in the adoption of resource efficiency as well as environmental management practices by grassroots clubs. Implications From an academic perspective this study corroborates the findings of previous studies focused on sports or related to the relationship between stakeholders’ pressures and green strategies in other industrial sectors. Moreover, this study suggests that the football world may follow its path in building fans’ loyalty through the adoption of environmentally responsible practices supported by powerful environmental communication, and by fostering fans’ engagement in environmentally responsible behaviors.

Work Climate and Students’ Academic Achievement in Catholic Secondary Schools in Ogun State, Nigeria

This research investigated work climate and students’ academic achievement in Catholic secondary schools in Ogun State. Two research questions guided the investigation. It employed a correlational survey method adopting ex-post-facto design. The participants included thirty-six principals and vice-principals working in all the Catholic secondary schools in Ogun State. The sample for the study consists of the total population, principals and vice principals in Catholic secondary schools in Ogun State. Census sampling method was utilized for the research. Questionnaire and checklist were self-developed by the researcher. The checklist titled “Students’ Academic Achievement Checklist” (SAAC), was utilized to gather data on students’ academic achievement using the promotional results of 2021, 2022 and 2023. The checklist was evaluated from A1 to F9, with D7 to F9 denoting failure and A1 to C6 showing a pass rating while questionnaire titled “Work Climate and Academic Achievement” Questionnaire, (WCAA)” was used by the researcher to gather information from the respondents. Mean scores and standard deviation, were employed to answer research questions. The finding in the study identified substantial connection between school environment and academic achievement of learners in Catholic secondary education in Lagos State. Moreover, a favourable relationship between conducive environments and higher academic achievement was established. The study highlights the interaction between school environment, retention of teachers and academic attainment of students, emphasizing their benefit in the context of Catholic secondary schools in Ogun State. Arising from this research, it was suggested among others that Catholic schools in Ogun State should strive to boost a positive school environment for both tutors and learners. Schools should apply various ways to retain effective, hardworking and experienced teachers. In addition, schools should continuously assess the standard of academic achievement, school environment, and human resource management practices.

Are family firms green?

AbstractThis study examines environmental management practices of 1690 family and nonfamily firms from 29 countries and 19 industrial sectors over an 8-year period. We show that the family effect on firm environmental management practices ranges substantially, from extremely negative to no effect at all. Moreover, the magnitude of the effect depends on the type of firm, the industrial context, the type of economy, and the stages of the business cycle. This study offers a novel understanding of the extreme heterogeneity of environmental management practices of family businesses and serves as a springboard for future research aiming to better understand the environmental strategies of publicly traded firms with concentrated ownership structures. It also provides important and novel evidence for policymakers, investors, and business owners, particularly for firms with different ownership and management structures.

WASTE SORTING IN A FRONT-LINE CITY: OPINIONS OF KHARKIV RESIDENTS

The article is devoted to the analysis of the problem of social attitude towards waste sorting in exceptional conditions. The author considers this problem within the framework of the general problematic of positions and practices of environmental consumption. The focus of the study is the peculiarities of attitudes towards environmental waste management practices in atypical conditions. The article examines Kharkiv as a front-line city in which military security threats come to the fore, create additional threats to food security, and at the same time disguise them as less important. The goal is to find out how mass consciousness in war conditions distributes empirical material for analysis – an online survey of 309 Kharkiv residents. The results of the study show that a positive attitude towards environmental waste sorting practices has been formed in the minds of Kharkiv residents. However, there is a gap between the declarative level of attitude and the implementation of practices. This gap can be explained both by the lack of a materially designed environment for the formation of sustainable waste sorting practices, and by the shortcomings of the information environment. At the same time, military living conditions in a front-line city do not affect the opinions of citizens about the importance of waste sorting.

Evaluation of the AquaCrop Model for Simulating Cotton Yield Under a Semi-Arid Environment and Different Field Management Practices

Evaluation of the AquaCrop Model for Simulating Cotton Yield Under a Semi-Arid Environment and Different Field Management Practices

Molecular Detection and Isolation of Lumpy Skin Disease Virus during an Outbreak in West Hararghe Zone, Eastern Ethiopia.

Lumpy skin disease (LSD) is a highly contagious viral disease that causes significant economic losses in cattle populations globally. This study aimed to isolate and detect the LSD virus responsible for an outbreak in selected areas (Daaroo Labuu, Hawwii Guddina, and Gumbi Bordede district) of the West Hararghe Zone in Ethiopia between January 2020 and December 2021. Out of the 625 animals examined for the presence of LSD, only 73 animals showed clinical signs, and skin scrapes were collected from these animals for further analysis. Among those, 12 animals (1.9%) succumbed to the disease. Skin biopsy samples from 45 animals displaying clinical signs of LSD were inoculated in Vero cell lines because of limited equipment. After three blind passages, all samples developed cytopathic effects (CPEs). The presence of the LSD virus was confirmed using real-time PCR. Conventional PCR detected LSDV in 47 (64.4%) of the skin scrap samples, while high-resolution melt qPCR detected it in 49 (67.1%) samples. The study revealed a morbidity rate of 11.68%, a mortality rate of 1.92%, and a case fatality rate of 16.44% based on clinical data. The findings suggest that LSD causes significant economic losses, even in vaccinated animals prior to an outbreak. To effectively control and eradicate LSD, the government should develop new strategic policies. Community awareness campaigns are necessary to improve vector control measures and drainage systems. In addition, the present vaccination policy and strategy should be re-evaluated for effectiveness. This study focused on a specific region and timeframe, limiting generalizability. Factors such as environmental conditions and management practices were not extensively explored. Similar studies should be conducted in different regions to assess the prevalence and genetic diversity of LSDV. The effectiveness of control measures and vaccination strategies should be investigated. The impact of environmental factors and management practices on LSD transmission and disease severity warrants further exploration. This study provides insights into the detection and isolation of the LSD virus during an outbreak in the West Hararghe Zone of Ethiopia. The results highlight the need for continued surveillance and monitoring of emerging infectious diseases in the region. Furthermore, the importance of using molecular methods for detecting and characterizing viral outbreaks in livestock populations is emphasized.

The Concept Of Environmental Management And Discussing Its Impact On Production/Operations Management (POM)

This study delves into the concept of environmental management and explores its implications on Production/Operations Management (POM). Environmental management, as a multidisciplinary approach, addresses the sustainable utilization of resources and the minimization of environmental impact in organizational processes. The research investigates the integration of environmental considerations into POM strategies, emphasizing the potential impacts on production efficiency, waste reduction, and overall sustainability. By analyzing relevant literature and case studies, this study aims to provide insights into the symbiotic relationship between environmental management practices and POM, highlighting the potential benefits of aligning production operations with environmentally conscious principles. The findings contribute to a better understanding of how environmental considerations can be strategically incorporated into production processes, fostering a more sustainable and responsible approach to operations management.