Environmental Risk Research Articles

Sustainable recycling management: configuration of risk factors and resilience strategies

Purpose Recycling is associated with positive social and environmental impact, but previous studies have overlooked the cost of recycling operations. Based on the dynamic capability view, the purpose of this study was to identify and evaluate risk factors and resilience strategies within the recycling industry, prioritize these factors and identify the optimal combination of resilience strategies and risk factors to improve market performance. Design/methodology/approach The research questions were addressed in three subsequent studies. In Study 1, qualitative interviews were conducted to identify risk factors and strategies to mitigate those risks. In Study 2, quality function deployment methodologies were implemented via case studies derived from three different companies. Based on the results of Studies 1 and 2, in addition to the use of fuzzy set qualitative comparative analysis, Study 3 aimed to determine the optimal combination of risk factors and strategies impacting market performance. Findings The results across the three studies revealed a number of risk factors as well as which risk factors and resilience strategies have the greatest impact on market performance. Specifically, it was found that higher levels of readiness, response and recovery strategies lead to greater market performance, whereas weak readiness, response and recovery strategies, along with low societal, environmental and health and safety risk factors, significantly inhibit performance. Originality/value This research extends current understandings of market performance in relation to recycling industry management and offers insight for decision-makers toward combating significant risk factors in business-to-business settings.

Sun exposure and protection habits: Self-reported attitudes, knowledge and behaviours.

As exposure to UV radiation is the primary modifiable environmental risk factor associated with skin cancer, it remains the principal focus of most prevention strategies. Numerous sun protection campaigns have been implemented worldwide; however, their impact on the actual incidence and mortality rates of skin cancer seems to be limited. To create successful skin cancer prevention campaigns, it is important to have a comprehensive understanding of individuals' attitudes and behaviours regarding sun protection. The aim of the current study was to determine and report on the prevalence of self-reported attitudes, knowledge and behaviours regarding two of the major sun protection recommendations-avoidance of sun exposure and use of sunscreens-in an international representative sample across five continents. This cross-sectional study was conducted in 20 countries using a web-based online survey. A total of 50,552 individuals, comprising 25,388 men (50.22%) and 25,164 women (49.78%), participated in the survey. Among them, 83.2% reported having been voluntarily exposed to the sun (for sun-basking reasons) at least once in the last 12 months, and 47.96% acknowledged being exposed to the sun between the hours of 10 AM and 4 PM. The primary reason for non-adherence was that these hours were the most convenient times (32.28%). Only 24.05% reported applying sunscreen every 2 h when outdoors. Forgetfulness was the primary reason as provided by 27.79% of participants. Males and older age groups were less likely to adopt sun-protective behaviours around the world. Forgetfulness and the challenges posed by time constraints seem to be the biggest barriers to proper adherence. These findings should prompt the collaboration with health authorities and the manufacturers to enhance adherence by setting reasonable sunscreen prices and creating formulations that make their application less burdensome.

Identifying the association between polymorphisms in the GZMB and IFIH1 genes and psoriasis in Egyptians

ABSTRACT Objectives This study aims to examine whether the genetic variants in the genes for Granzyme B (GZMB) and Interferon Induced with Helicase C domain 1 (IFIH1) were associated with psoriasis. Background Psoriasis, a papulosquamous skin disease, was initially thought of as a disorder primarily of epidermal keratinocytes but is now recognized as one of the most common immune-mediated disorders. It is caused by the interplay between multiple genetic and environmental risk factors. Subjects and methods This case-control study has 65 participants with psoriasis and 65 healthy controls. Real-time PCR was used to genotype GZMB (rs8192917) and IFIH1 (rs35667974). Results Genotype occurrence and allelic spreading for both SNPs are in Hardy – Weinberg equilibrium. The genotype and allele distributions of rs35667974 showed no differences between the studied groups. Regarding rs8192917, compared to Group II, there is a statistically significant rise in the CC genotype and C allele in Group I. Higher PASI scores are detected in the C/C and C/T genotypes more than the T/T genotype. Univariate and multivariate analyses revealed that BMI, catalase, MDA, and rs8192917 (C/C) are associated with psoriasis. Conclusion GZMB rs8192917 was significantly related to psoriasis risk; its C allele is likewise associated with psoriasis vulnerability. However, our investigation found no link between rs35667974 and psoriasis.

Social environment, lifestyle, and genetic predisposition with dementia risk: A long-term longitudinal study among older adults.

The role of social environment, i.e., the aggregate effect of social determinants of health (SDOHs), in determining dementia is unclear. We developed a novel polysocial risk score for dementia based on 19 SDOH among 5,199 participants in the Health and Retirement Study, US, to measure the social environmental risk. We used a survival analysis approach to assess the association between social environment and dementia risk in 2006-2020. We further studied the interaction between social environment and lifestyles, and explored racial disparities. The study participants (mean age=73.4 years, SD=8.3; 58.0% female; 11.6% African American) were followed up for an average of 6.2 years, and 1,089 participants developed dementia. Every one-point increase in the polysocial risk score (ranging from 0-10) was associated with a 21.6% higher risk (aHR=1.21, 95% CI=1.15-1.26) of developing dementia, other things being equal. Among participants with high social environmental risk, regular exercise and moderate drinking were associated with a 43-60% lower risk of developing dementia (p<0.001). In addition, African Americans were 1.3 times (aHR=2.28, 95% CI=1.96-2.66) more likely to develop dementia than European Americans, other things being equal. An adverse social environment is linked to higher dementia risk, but healthy lifestyles can partially offset the increased social environmental risk. The polysocial risk score can complement the existing risk tools to identify high-risk older populations, and guide the design of targeted social environmental interventions, particularly focusing on improving the companionship of the older people, to prevent dementia.

Artificial Intelligence in enhancing sustainable practices for infectious municipal waste classification

This research paper focuses on effective infectious municipal waste management in urban settings, highlighting a dearth of dedicated research in this domain. Unlike general or specific waste types, infectious waste poses distinct health and environmental risks. Leveraging advanced artificial intelligence techniques, we prioritize infectious waste categorization and optimization, integrating metaheuristics into optimization methods to create a robust dual-ensemble framework. Our model, the “Enhanced Artificial Intelligence for Infectious Municipal Waste Classification System,” combines ensemble image segmentation methods and diverse convolutional neural network models. Innovative geometric image augmentation enhances model robustness, diversifies training data, and improves accuracy across waste types. A pivotal aspect is the integration of a reinforcement learning-differential evolution algorithm as a decision fusion strategy, optimizing classification by harmonizing outputs from ensemble methods and convolutional neural network models. Computational results, using a newly collected dataset, demonstrate our model’s accuracy exceeding 96.54% while using the existing solid waste dataset we achieve the accuracy of 97.81%, outperforming advanced approaches by margins ranging from 2.02% to 8.80%. This research significantly advances sustainable waste management, showcasing artificial intelligence’s transformative potential in addressing intricate waste challenges. It establishes a foundational framework prioritizing efficiency, effectiveness, and sustainability for future waste management solutions. Acknowledging the importance of diverse datasets, customization for urban contexts, and practical integration into existing infrastructures, our work contributes to the broader discourse on the role of artificial intelligence in evolving waste management practices.

Environmental Risk Identification and Green Finance Development Based on Multi-scale Fusion Recognition Network

AbstractThis paper aims to enhance the resilience of financial enterprises against environmental risks by leveraging financial data analysis tools. The approach involves designing environmental risk assessment indicators and rating criteria. The study utilizes a convolutional neural network model extended by a multi-scale feature fusion module to analyze environmental risk information in the industry. The proposed model achieves impressive results with accuracy (Acc), precision (P), recall (R), and F1 scores reaching 99.09, 96.31, 95.32, and 95.64, respectively. These metrics outperform those of comparison models. The success of this model is anticipated to pave the way for the transformation of green finance through automated industry-level environmental risk assessment. Furthermore, the method’s adaptability extends beyond environmental risks, offering a scalable solution for identifying and assessing environmental risks in various contexts.

Enhancing Methane Gas Sensing through Defect Engineering in Ag-Ru Co-doped ZnO Nanorods.

Detection of leaks of flammable methane (CH4) gas in a timely manner can mitigate health, safety, and environmental risks. Zinc oxide (ZnO), a polar semiconductor with controllable surface defects, is a promising material for gas sensing. In this study, Ag-Ru co-doped into self-assembled ZnO nanorod arrays (ZnO NRs) was prepared by a one-step hydrothermal method. The Ag-Ru co-doped sample shows a good hydrophobic property as a result of its particular microstructure, which results in high humidity resistance. In addition, oxygen vacancy density significantly increased after Ag-Ru co-doping. Density functional theory (DFT) calculations revealed an exceptionally high charge density accumulated at the Ru sites and the formation of a localized strong electric field, which provides additional energy for the CH4 reaction with •O2- at the surface at room temperature. Optimized AgRu0.025-ZnO demonstrated an outstanding CH4 sensing performance, with a limit of detection (LOD) as low as 2.24 ppm under free-heat and free-light conditions. These findings suggest that introducing defects into the ZnO lattice, such as oxygen vacancies and localized ions, offers a promising approach to improving the gas sensing performance.

Identification of potential landfill site suitability for urban solid waste disposal of Balurghat Municipality of Dakshin Dinajpur District using GIS and multi-criteria decision-making approach

The production of urban solid waste is one of the most dangerous environmental health risks on the planet. By selecting suitable landfill sites, it is possible to resolve the issue of health risks and environmental pollution driven by the unscientific disposal of solid waste. The current research is centered on determining suitable landfill locations for solid waste disposal within the Balurghat municipality through the integration of Geographic Information System (GIS) and Multi-Criteria Decision-Making (MCDM) approach. Ten factors were taken into consideration according to their weightage including elevation (0.022), Lithology (0.027), Slope (0.032), Land use and land cover LULC (0.040), Depth of water (0.057), Population density (0.075), Distance from sensitive places (0.107), Distance from road (0.154), Distance from river (0.205) and Land value (0.282). After conducting thorough field visits, an analytical hierarchy process (AHP) under the MCDM approach using GIS reveals acceptable sites that were noted and referenced. Final results are validated through a receiver operating characteristic (ROC) curve using randomly selected 80 potential landfill-suitable site location points with higher accuracy, and a total of 93% of the area under the curve (AUC) has been found worthy to validate the spatial result. The present investigation revealed that only 0.65% of land is very highly suitable, 31.06% of land is highly suitable, 52.54% of land is moderately suitable and 14.74% of land is not suitable for landfilling in Balurghat Municipal area and surroundings respectively. The highly suitable site belongs to the Mamna, Katna, Kuaran, Amtali, Noksha, Bannapara, and Malancha villages of the study area which is a very negligible area. So, the planners should adopt alternative strategies like source minimization, composting, sanitary landfills and awareness programmes for sustainable solid waste management. Hence, the Balurghat Municipality administration, urban planners, and administrative authorities stand to gain valuable insights from the findings of this study as they endeavour to enhance the management of urban solid waste in the area.

Neutrality and impartiality in Midwestern U.S. newspapers: community-oriented newspaper journalists reporting of environmental water problems in agricultural and ranching states

ABSTRACT Background U.S. journalists embedded in rural and agricultural communities could adversely affect the health of residents if they avoid alerting and engaging their readers – farmers, ranchers, and community members – on environmental and health issues. We expected reporters would maintain community status quo and inaction by framing local water pollution and quality issues neutrally deemphasizing threats and solutions to maintain their own credibility as unbiased informational sources. Method In a content analysis of local water quality newspaper articles from five farming and cattle ranching states in the west central U.S. Midwest, we employed seven variables to investigate whether journalists practiced neutral, detached forms of journalism (i.e. dissemination versus interpretative role enactment, government-frame) as well as whether they deemphasized water pollution as a concerning issue (i.e. problem, threat), water pollution solutions, and readers’ efficaciousness. Results The results showed these journalists relied heavily on government-driven narratives presenting water quality issues from an impartial, straight reporting lens in which they primarily followed the journalistic dissemination role enactment, while neglecting to provide readers with interpretative, threat, efficacy, or solution’s information. Conclusions The study seeks to help communicators understand the information diet people living in this part of the country likely receive on environmental and health risks in the context of water pollution. Communicators seeking to reach and affect audiences in this region should understand local information practices to navigate how to craft culturally specific public health messages.

Design of Radial Distribution System to Study Load-Flow and Short Circuit Analysis Using ETAP Software

This work's analysis provides information on fault analysis and load flow studies, which help to understand how radial distribution networks operate both in normal and emergency circumstances. The research explores optimization methods, describing capacitor placement, transformer size, and feeder reconfiguration in order to lower losses and increase system efficacy. Moreover, the work looks at reliability-focused maintenance techniques, stressing the need of predictive maintenance and condition monitoring in raising the dependability of radial distribution networks. Modern electrical power networks depend heavily on their radial distribution system, which effectively and dependable distributes electricity to customers. Many radial distribution system-related topics are covered in detail on this website, including analytical methods, optimization processes, and dependability enhancement strategies. Power flow, voltage control, and losses in radial networks are investigated in this paper under a range of operational situations. The last and crucial stage of a power system, the electrical distribution system makes sure that customers have a steady supply of electricity. Regretfully, because it is often neglected and exposed to environmental risks, our distribution network has a number of problems. Our distribution feeder is rigorously analyzed for load flow and short-circuits in order to overcome these challenges and find and fix problems. The main topics of this study are the load flow and short-circuit analysis of a radial distribution feeder, which is mostly constructed with (ETAP). The final and crucial part of a power system, the electrical distribution system ensures that consumers receive an uninterrupted and steady supply of electricity. Our distribution feeder undergoes a rigorous and cautious process to address these issues front on because of the uncontrollable nature and susceptibility of our network to environmental hazards. This paper delves deeply into the issues of short-circuiting and load flow in radial distribution feeders. Both symmetrical and asymmetrical faults are thoroughly investigated by mathematical computations and ETAP simulations; the results of the software simulations are contrasted with those of the mathematical analysis. These discoveries will definitely influence the development and management of our system and point us in the direction of workable and practical solutions.

Evaluating the temperature–mortality relationship over 16 years in Cyprus

ABSTRACT In many regions of the world, the relationship between ambient temperature and mortality is well-documented, but little is known about Cyprus, a Mediterranean island country where climate change is progressing faster than the global average. We Examined the association between daily ambient temperature and all-cause mortality risk in Cyprus. We conducted a time-series analysis with quasipoisson distribution and distributed lag non-linear models to investigate the association between temperature and all-cause mortality from 1 January 2004 to 31 December 2019 in five districts in Cyprus. We then performed a meta-analysis to estimate the overall temperature-mortality dose-response relationship in Cyprus. Excess mortality was computed to determine the public health burden caused by extreme temperatures. We did not find evidence of heterogeneity between the five districts (p = 0.47). The pooled results show that for cold effects, comparing the 1st, 2.5th, and 5th percentiles to the optimal temperature (temperature associated with least mortality, 25 ℃), the overall relative risks of mortality were 1.55 (95% CI: 1.32, 1.82), 1.41 (95% CI: 1.21, 1.64), and 1.32 (95% CI: 1.15, 1.52), respectively. For heat effects, the overall relative risks of mortality at the 95th, 97.5th and 99th percentiles were 1.10 (95% CI: 1.04, 1.16), 1.17 (95% CI: 1.07, 1.29), and 1.29 (95% CI: 1.11, 1.5), respectively. The excess mortality attributable to cold days accounted for 8.0 deaths (95% empirical CI: 4.5–10.8) for every 100 deaths, while the excess mortality attributable to heat days accounted for 1.3 deaths (95% empirical CI: 0.7–1.7) for every 100 deaths. The results prompt additional research into environmental risk prevention in this under-studied hot and dry region that could experience disproportionate climate change related exposures. Implications: The quantification of excess mortality attributable to temperature extremes shows an urgent need for targeted public health interventions and climate adaptation strategies in Cyprus and similar regions facing rapid climate change. Future steps should look into subpopulation sensitivity, coping strategies, and adaptive interventions to reduce potential future risks.

Performances of the sandwich panel structures under fire accident due to hydrogen leaks: Consideration of structural design and environment factor using FE analysis

Abstract This study presents a comprehensive analysis using the finite element method (FEM) to examine and evaluate the behavior of fuel carrier ship structure. Sandwich panels are effective structures for use in ship structures due to their lightweight yet robust nature. Sandwich panels used in ship structures have various core shapes, such as hexagonal, circular, and square, as needed. The sandwich panel structure can be widely implemented in ship construction, for example, on the deck, hull, and bulkhead of the ship’s cabin. Hydrogen is an alternative fuel that can replace fossil fuels. In this modern era, hydrogen is high valuable energy commodity, so accidents involving carrier ships could have significant consequences. Hydrogen is produced from liquefied natural gas (LNG), so if a leak occurs, for instance, in a storage tank or fuel tank, it has the potential to lead to accidents such as fires. Corrosion is a significant concern for the maritime industry, as it can jeopardize the structural integrity of these vessels and pose substantial safety and environmental risks. In this research, FEM was utilized to model and simulate the effects of corrosion on hydrogen carrier ships when exposed to fire, considering various environmental and operational factors. Through a systematic investigation, it is aimed to gain insights into the impact of corrosion on ship structural components during fires, such as hulls and storage tanks. The result of this study will contribute to improving corrosion and fire mitigation strategies, ensuring the safety and longevity of hydrogen and LNG carrier ships, and supporting the sustainable transportation of hydrogen to meet global energy demands. No research has been conducted on the structural behavior resulting from hydrogen fires and corrosion simultaneously. To achieve this, it is assumed to use the corrosion properties of steel in heavily traveled ship routes such as the Panama Canal Zone, Barent Sea, North Sea, and Suez Canal Zone. This study utilized an approach by modeling corrosion using shell thickness in Abaqus Quasi-Static and applying boundary conditions in the form of temperature increase up to 800°C and subsequent cooling back to the initial temperature. At the maximum temperature, the most significant mid-span displacement occurred in the circular core sandwich panel, with a value of 4 mm. The axial force in the structure was inversely proportional to the mid-span displacement. In the case of the circular core sandwich panel, the axial force was 96 kN. The most resilient core type was hexagonal because it experiences the least deformation when compared to circular and square cores.

Distribution patterns and environmental risk assessments of microplastics in the lake waters and sediments from eight typical wetland parks in Changsha city, China

The quality of water in urban parks is closely related to people’s daily lives, but the pollution caused by microplastics in park water and sediments has not been comprehensively studied. Therefore, eight typical parks in the urban area of Changsha, China, were selected, and Raman spectroscopy was used to explore the spatial distributions and compositions of the microplastics in the water and sediments, analyze their influencing factors, and evaluate their environmental risks. The results showed that the abundances of surface water microplastics in all parks ranged from 150 to 525 n L−1, and the abundances of sediment microplastics ranged from 120 to 585 n kg−1. The microplastics in the surface water included polyethylene terephthalate (PET), chlorinated polyethylene (CPE), and fluororubber (FLU), while those in the sediments included polyvinyl chloride (PVC), wp-acrylate copolymer (ACR), and CPE. Regression analyses revealed significant positive correlations between human activities and the abundances of microplastics in the parks. Among them, the correlations of population, industrial discharge and domestic wastewater discharge with the abundance of microplastics in park water were the strongest. However, the correlations of car flow and tourists with the abundance of microplastics in park water were the weakest. Based on the potential ecological risk indices (PERI) classification assessment method, the levels of microplastics in the waters and sediments of the eight parks were all within the II-level risk zone (53–8,549), among which the risk indices for Meixi Lake and Yudai Lake were within the IV risk zone (1,365–8,549), which may have been caused by the high population density near the park. This study provides new insights into the characteristics of microplastics in urban park water and sediment.

Surveying the Landscape of Environmental Social Science: A Bibliometric and Network Analysis

Abstract Social science research on the environment has grown exponentially in the past four decades alongside increasing awareness that environmental risks, such as climate change, cannot be understood by natural science interventions alone. While prior research examines how specific disciplines, like sociology, have attended to the environment or how specific problems have been engaged across disciplines, less attention has been offered to the entire landscape of research on the environment in the social sciences. In this article, we ask: What is the landscape of environmental social science? Focusing on 124,906 social scientific articles from the Web of Science, we analyze the relationship between journals publishing research on the environment. Specifically, we construct journal citation networks and topic models on bibliographic records from 1990 to 2022. Results suggest that journals form coherent communities associated with both disciplinary and interdisciplinary research topics, indicating that journal communities may be a central organizing feature of ESS. Moreover, research topics prevalent in this field have changed over time, potentially in relation to the ongoing neoliberalization of climate change politics. As scholars want to influence policy and industrial practice, their research implicitly reflects values consistent with the current political economic order. We conclude by highlighting the implications of these findings for the field of environmental social science.

Transcriptomic point of departure determination: a comparison of distribution-based and gene set-based approaches

A key step in assessing the potential human and environmental health risks of industrial and agricultural chemicals is to determine the toxicity point of departure (POD), which is the highest dose level that causes no adverse effect. Transcriptomic POD (tPOD) values have been suggested to accurately estimate toxicity POD values. One step in the most common approach for tPOD determination involves mapping genes to annotated gene sets, a process that might lead to substantial information loss particularly in species with poor gene annotation. Alternatively, methods that calculate tPOD values directly from the distribution of individual gene POD values omit this mapping step. Using rat transcriptome data for 79 molecules obtained from Open TG-GATEs (Toxicogenomics Project Genomics Assisted Toxicity Evaluation System), the hypothesis was tested that methods based on the distribution of all individual gene POD values will give a similar tPOD value to that obtained via the gene set-based method. Gene set-based tPOD values using four different gene set structures were compared to tPOD values from five different individual gene distribution methods. Results revealed a high tPOD concordance for all methods tested, especially for molecules with at least 300 dose-responsive probesets: for 90% of those molecules, the tPOD values from all methods were within 4-fold of each other. In addition, random gene sets based upon the structure of biological knowledge-derived gene sets produced tPOD values with a median absolute fold change of 1.3–1.4 when compared to the original biological knowledge-derived gene set counterparts, suggesting that little biological information is used in the gene set-based tPOD generation approach. These findings indicate using individual gene distributions to calculate a tPOD is a viable and parsimonious alternative to using gene sets. Importantly, individual gene distribution-based tPOD methods do not require knowledge of biological organization and can be applied to any species including those with poorly annotated gene sets.

Assessing the German Act on Corporate Due Diligence Obligations in Supply Chains: a perspective from the smallholder cocoa farmer

This research examines the potential outputs, outcomes, and impacts of the German Act on Corporate Due Diligence Obligations in Supply Chains (LkSG) on the smallholder cocoa farmers in West Africa. The study primarily relies on a literature review and an impact pathway to conduct a systematic analysis to identify the potential effects of the LkSG on smallholder cocoa farmers. The findings indicate that some, but not all of the risks addressed by the LkSG align with those faced by smallholder cocoa farmers and their families. Additionally, the research also reveals weaknesses, particularly in managing environmental risks, which the LkSG does not adequately cover. Our findings show that in the short- and medium-term, the LkSG has no potential effects on smallholder cocoa farmers. Furthermore, the potential positive impacts of the law on smallholder cocoa farmers will take a long time to realize, as the LkSG considers primarily tier-1 suppliers. Companies in Germany might reassess their supply chains to strive for an LkSG-risk-free supply chain, which could in the long term have sustained impacts on smallholder cocoa farmers. However, we recommend a comprehensive risk analysis of the cocoa supply chain to enhance the human rights of cocoa farmers.

Environmental Fate and Dietary Risk Assessment Associated with Triafamone, Ethoxysulfuron and Their Metabolites in Rice Ecosystem

ABSTRACT Triafamone and ethoxysulfuron are ALS inhibitor herbicides belonging to sulfonamide and sulfonylurea group of herbicides used for control of weeds in rice ecosystem. Considering the environmental risk of these herbicides, the fate of triafamone and ethoxysulfuron was assessed to understand the best use of these herbicides. Degradation studies were carried out under field conditions in direct seeded rice (DSR) and transplanted rice (TPR) at an application rate of 67.5 and 135 g ha−1 and adsorption-desorption studies were carried out using batch equilibration technique. Residues of triafamone, ethoxysulfuron and their metabolites were extracted by ultrasonic assisted extraction method from soil and rice grain samples and liquid liquid extraction from straw samples and quantified using HPLC. Degradation half-life (DT50) of triafamone varied from 13.02–20.93 and 12.09–14.67 days under DSR and TPR conditions, respectively while for ethoxysulfuron DT50 ranged from 11.71–15.64 and 9.90–12.19 days. Among both the herbicides, triafamone was more persistent in the soil and at harvest, concentrations of triafamone and ethoxysulfuron in soil and rice were below the acceptable limit (<0.01 mg kg−1) imposed by principal regulatory agencies. Appearance and persistence of studied metabolites corroborated the degradation of parent molecule. Hazard quotient (HQ) of triafamone and ethoxysulfuron was 0.0013 and 0.000657 suggesting that application of these herbicides was safe for use in rice. Triafamone and ethoxysulfuron had a transient effect on soil biochemical and microbiological parameters depending on herbicide dose and moisture conditions. Freundlich adsorption coefficient (Kf) was 1.81 and 1.06 µg1–1/ng−1ml1/n for triafamone and ethoxysulfuron, respectively. GUS index for triafamone and ethoxysulfuron were 1.4 and 2.0 indicating low and moderate mobility, respectively. Principal component analysis (PCA) indicated that ethoxysulfuron has higher leachability than triafamone. Low to moderate persistence, adsorption and leaching of triafamone and ethoxysulfuron and transient ecological impacts on soil microorganisms may pave the way for safe and efficient weed control in rice cultivation.

Developing a smart green supplier risk assessment system integrating natural language processing and life cycle assessment based on AHP framework: An empirical study

Global carbon reduction drives the transformations of corporations, emphasizing carbon and environmental impact within supply chains. A critical challenge in risk management is converting unstructured data into quantifiable information, and ruining the conversion often leads to ineffective risk assessments. While artificial intelligence is increasingly used in supply chain risk management, previous studies seldom integrate text analysis for risk extraction and lack accurate risk assessment methods. This study pioneers an intelligent green supplier risk assessment system integrating natural language processing (NLP) and life cycle assessment (LCA) based on an analytic hierarchy process (AHP) framework. The proposed approach utilizes NLP keyword extraction to identify and assess risk and uses LCA to uncover environmental risks, minimizing negative impacts. The text classification model attains 81.7 % accuracy, ensuring a trustworthy risk assessment system. The proposed method could significantly improve risk analysis efficiency, foster sustainable procurement, and elevate enterprise competitiveness in sustainable business practices.

Do typologies of pesticide risk knowledge influence the adoption of IPM strategies? Evidence from rice farmers' behavior in northern Iran.

The active participation of farmers in adopting eco-friendly practices is vital to mitigate the environmental and health risks linked to pesticide usage. Farmers' awareness of these risks significantly influences their adoption of integrated pest management (IPM) methods over traditional pesticide applications. This study sought to explore the range of understanding on pesticide effects, categorize IPM strategies employed in pest management, and examine the correlation between knowledge levels and IPM strategy choices. Data was gathered through structured questionnaires from 391 rice farmers in Sari County, Mazandaran province, Northern Iran. Exploratory factor analysis revealed three distinct dimensions of pesticide risk knowledge: personal risk of pesticide, environmental risk of pesticide, and community risk of pesticide. Furthermore, the study identified three primary categories of IPM strategies: high familiarity, intermediate familiarity, and low familiarity. The results of the regression analysis indicated that the personal risk of pesticides (β = 0.556; P < 0.01) and the environmental risk of pesticides (β = 0.262; P < 0.01) are significantly correlated with the adoption of high familiarity IPM strategies. Furthermore, the study revealed that there was no significant statistical evidence to support the notion that different types of pesticide risk knowledge had any influence on the adoption of intermediate and low familiarity strategies. The findings of this study imply the critical importance for agricultural extension programs to focus on enhancing farmers' knowledge of pesticide risks and various IPM strategies. © 2024 Society of Chemical Industry.

An investigation into the effect of UV irradiation and biofilm colonization on adsorption and desorption behavior of polyurethane (PU) microplastics for bisphenol A (BPA)

Recent studies have demonstrated that microplastics (MPs) can act as a transport vector for pollutants in the environment. However, most studies have focused on carbon-carbon backbone polymers, with little known about heteroatom backbone polymers. In this study, polyurethane (PU) MPs were modified by UV irradiation and microorganism colonization to assess the different aging treatments on the interaction behavior (adsorption/desorption) between PU MPs and bisphenol A (BPA). The results of the adsorption kinetics experiment illustrated that the adsorption process of BPA could be described well by a pseudo-second order kinetic equation on both fresh and aged PU MPs. Although fresh PU MPs revealed the highest saturated adsorption capacity, at low BPA exposure concentrations (≤ 100 μg/L) the adsorption capacities for UV aged and biofilm colonized PU MPs were very similar to fresh MPs or even slightly higher than for fresh MPs, the main adsorption mechanisms including H-bonding interactions and π–π interactions. Fourier-transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM) investigations suggested obvious physicochemical property changes (e.g., generation of new functional groups, erosion, etc.) after UV irradiation and biofilm colonization. This study also showed that different exposure environments (ultrapure water, artificial seawater, simulated gastric fluid) could affect BPA adsorption/desorption via hydrophobic and electrostatic interaction on PU surfaces. These results further clarify the adsorption mechanisms of BPA on PU MPs that have undergone different aging treatments, and provides a theoretical basis for the assessment of environmental behavior and exposure risks when PU MPs and BPA coexist.