An approach for environmental risk assessment of engineered nanomaterials using Analytical Hierarchy Process (AHP) and fuzzy inference rules

Due to new regulations, laws and increasing demand from consumers, companies begin to enhance their environmental management practices. Hence, environmental risk assessment became one of the critical success factors for companies in order to be successful. Environmental risk assessment approaches under Occupational Health and Safety (OHS) activities vary among industries and taking precautions about environmental issues lead researchers and practitioners to create new approaches. Also, subjectivity of existing methods, advancement of technology, and aim to minimize risk levels and rivalry among competitors are some of the main reasons for development of new approaches. This study aims to propose a new fuzzy-based approach for environmental risk assessment along with Analytical Hierarchy Process (AHP) for environmental risk assessment. Hereby, along with the consideration of categorical impacts such as to human health and environment, new approach is applied and compared with classic AHP results. According to the implementation results on a chemical ranch of a textile company, new approach minimizes subjectivity besides of flexible, original, and easy to implement for researchers and practitioners.

Linguistic Hedges and Reasonable Fuzzy Inferences

An innovative index to incorporate transcriptomic data into weight of evidence approaches for environmental risk assessment

Second International Symposium on Ionising Radiation:`Environmental Protection Approaches for Nuclear Facilities', Ottawa, Canada, 10-14 May 1999

The scientific organizers of the symposium put much emphasis on the identification and definition of hazard and the potential consequences thereof and three full sessions with a total of 13 presentations encompassing a wide range of related themes were planned for this topic. Unfortunately, one talk had to be cancelled because of illness of the speaker (BM Khadi, India). Some presentations covered conceptual approaches for environmental risk assessment (ERA) of GM plants (problem formulation in the risk assessment framework, familiarity approach, tiered and methodological frameworks, non-target risk assessment) and the use of models in assessing invasiveness and weediness of GM plants. Other presentations highlighted the lessons learned for future ERA from case studies and commercialized GM crops, and from monitoring of unintended releases to the environment. When the moderators of the three sessions came together after the presentations to align their summaries, there was an obvious need to restructure the 12 presentations in a way that allowed for a consistent summarizing discussion. The following new organization of the 12 talks was chosen: (1) Concepts for problem formulation and non-target risk assessment, (2) Modeling as a tool for predicting invasiveness of GM plants, (3) Case-studies of ERA of large-scale release, (4) Lessons learned for ERA from a commercialized GM plant, (5) Monitoring of unintended release of Bt maize in Mexico. The new thematic structure facilitates a more in-depth discussion of the presentations related to a specific topic, and the conclusions to be drawn are thus more consistent. Each moderator agreed to take responsibility for summarizing one or more themes and to prepare the respective report.

The European Partnership for next generation, systems-based Environmental Risk Assessment (PERA) is a strategic initiative launched by the European Food Safety Authority (EFSA). This initiative is in response to the recognition that the current ERA paradigm has “fallen out of step with scientific knowledge and progress” and the new policy and societal ambitions e.g. the EU Green Deal strategy to better safeguard the environment. As part of the initiative, EFSA commissioned the development of a roadmap to facilitate a transition to an integrated and cross-sectoral environmental risk assessment (ERA) approach. The PERA systems-based approach aims to connect relevant partners from various sectors across regulatory silos, promotes and facilitates the sharing of data and expertise, and improves efficiency and transparency of the risk assessment process. In this External Scientific Report, we present the PERA roadmap that comprises of a problem description (current state), a vision (future state) and a series of steps to move towards the vision (transition process). The PERA roadmap was developed after extensive desk research and multiple stakeholder interviews, that were used to identify partners, areas needing further development, challenges, blockers and collaboration opportunities. We designed a vision for next generation ERAs, initially focused on pesticides, based on the ideas of stakeholders and accounting for the identified strengths and weaknesses of the current ERA system. Workshops were held during which stakeholders were invited to comment on these draft concepts providing valuable feedback for further revision. The PERA vision is a visual framework for systems-based ERA, with a concentric circle model. Its core circle builds upon and strengthens current ERA processes by focusing on pesticide specific aspects useful for comparability and decreasing the assessment complexity of pesticides. The inner core circle is surrounded by a supportive circle of landscape scale ERA, that addresses ecosystems properties of generic relevance for all pesticides. These two ERA circles are in turn connected to surrounding circles representing the agricultural, ecological and production systems as well as the political, economic and social systems. To fully optimize the process these circles need to be interconnected with information feed-back loops. The vision and roadmap were designed to incorporate the strengths, knowledge and expertise of the current state into a new holistically framed systems-based ERA. Strategies for transition, as well as concrete projects to spark the transition process are proposed and include concrete and tangible steps in a holistic direction within the current regulatory framework.

In recent years, the development of innovative tools in genomics, transcriptomics, proteomics and metabolomics (designated collectively as 'omics technologies) has opened up new possibilities for applications in scientific research and led to the availability of vast amounts of analytical data. The interpretation and integration of 'omics data can provide valuable information on the functional status of an organism and on the effect of external factors such as stressors. The European Food Safety Authority's (EFSA) 24th Scientific Colloquium on 'omics in risk assessment: state of the art and next steps explored the opportunities for integration of datasets produced via specific 'omics tools within the remit of EFSA's risk assessment approaches and tried to build further towards concrete paths of implementation. Discussions focused on genomics in microbial strain characterisation, metabolomics for the comparative assessment of GM plants and the use of 'omics for toxicological and environmental risk assessment. From the Colloquium it became clear that 'omics technologies are a valuable addition in some aspects of risk assessment of food and feed products and the environment, especially now that this technology is almost mature and stable. However, a consistent reporting framework for data collection, processing, interpretation, storage and curation should be further drawn up together with national and international organisations before 'omics technologies can be routinely used in risk assessment. For 'omics datasets in chemical and environmental risk assessments, the use of 'omics technologies alongside current toxicological or environmental risk assessment approaches is needed to re-inforce confidence and expertise before implementation of these datasets as a standalone tool in risk assessment. Test cases could be worked out to enhance confidence in the use of 'omics datasets in risk assessment.

Nanopesticides or nano plant protection products represent an emerging technological development that, in relation to pesticide use, could offer a range of benefits including increased efficacy, durability, and a reduction in the amounts of active ingredients that need to be used. A number of formulation types have been suggested including emulsions (e.g., nanoemulsions), nanocapsules (e.g., with polymers), and products containing pristine engineered nanoparticles, such as metals, metal oxides, and nanoclays. The increasing interest in the use of nanopesticides raises questions as to how to assess the environmental risk of these materials for regulatory purposes. Here, the current approaches for environmental risk assessment of pesticides are reviewed and the question of whether these approaches are fit for purpose for use on nanopesticides is addressed. Potential adaptations to existing environmental risk assessment tests and procedures for use with nanopesticides are discussed, addressing aspects such as analysis and characterization, environmental fate and exposure assessment, uptake by biota, ecotoxicity, and risk assessment of nanopesticides in aquatic and terrestrial ecosystems. Throughout, the main focus is on assessing whether the presence of the nanoformulation introduces potential differences relative to the conventional active ingredients. The proposed changes in the test methodology, research priorities, and recommendations would facilitate the development of regulatory approaches and a regulatory framework for nanopesticides.

Korean traditional medicine has obtained more attention from the public and IT service industry especially after 'Dong-eui-bo-gam' was registered to UNESCO Memory of the World. However, there are many obstacles in developing and commercializing an on-line self-diagnosis system by Korean traditional medicine. From the service point of view, since people are accustomed to the westernized style of diagnosis (symptom-disease pair), it is not easy to understand what traditional Korean medicine diagnoses and how one can react. Technically speaking, we need a special symptom-disease database because Korean traditional medicine has been built upon the innate characteristics of Korean people's body. Thus, in this paper, we propose a self-diagnosis system of Korean traditional medicine based on Korean Standard Causes of Death Disease Classification Index (KCD) and fuzzy ART/inference method. Since this is for self-diagnosis, our system has graphical user-friendly interface that accepts symptoms of user from a certain part of body where the user feels inconvenient. Then, fuzzy ART algorithm and fuzzy inference engine picks up five most probable diseases with their causes and treatments extracted from Korean traditional medicine books. The power of our system comes from a fuzzy inference module combined with fuzzy ART algorithm that helps classifying related disease from database with accuracy. Our system is verified by field experts of Korean traditional medicine in collecting symptom-disease-treatments relationships and performance evaluation of experiment results.

The geometric accuracy and surface roughness are mainly affected by the flank wear at the minor cutting edge in finish machining. A genetic algorithm-based fuzzy estimator obtained by a fuzzy inference algorithm to evaluate the minor flank wear length in finish milling is introduced. The fuzzy inference rules are trained by genetic algorithms (GA) through practice. Fuzzy membership functions and rules are usually decided upon subjectively. In this paper, the performance of the fuzzy estimator may be improved if the fuzzy inference model is supplemented by a genetic-based learning mechanism. The features sensitive to minor flank wear are extracted from the dispersion analysis of a time series AR model of the feed directional acceleration of the spindle housing. Linguistic rules for fuzzy estimation are constructed using these features, and then fuzzy inferences are carried out with test data sets under various cutting conditions. The proposed system turns out to be effective for estimating minor flank wear length, and its mean error is less than 13%.

As environmental pressures increase globally, the need arises to understand and manage present and emerging environmental risks. The aim of this chapter is to introduce a new Environmental Risk Assessment (ERA) approach to identify, assess, and report the level of environmental risks that can lead to significant interruptions, infrastructure damages, safety threats, and long-term effects on airport operations. ERA evaluates the quantitative and qualitative characteristics of environmental hazards, which involve physical, chemical, and biological factors that can imperil humans and infrastructure. The presented ERA framework is deployed in six phases, namely airport preparation, definition of the assessment scope and parameters, data collection and development of projection scenarios, risk assessment, mitigation and adaptation strategies, report, monitor, and review. In essence, the outlined ERA approach serves as a managerial tool to facilitate policy assessment and sustainable decision-making.

Environmental risk assessment is a step towards identification, analysis, and classification of risk factors and thus reduction of the possibility of adverse consequences. In this research, a novel approach for environmental risk assessment on groundwater pollution is applied. By combination of aquifer vulnerability DRASTIC map, pollution severity and prioritizing of the plain regions by the TOPSIS method, more sensitive regions of Qazvin aquifer in Iran are identified. In the first step, seven hydro-geological characteristics of the aquifer are overlaid to produce the potential vulnerability map. Nitrate is used as the pollution parameter and its value in monitoring wells is measured by sampling. Spatial distribution of nitrate concentration is investigated using the ordinary kriging method. The TOPSIS ranking method is also applied to estimate the probability of occurrence of pollution based on five affecting criteria defined and quantified in regions of the aquifer. By production of these three layers, the risk map of the aquifer is generated. Results indicate that 9% of the area of the aquifer is categorized in the high risk level which needs an emergency recovery action plan. Also, sensitivity analysis on the parameters of the aquifer vulnerability shows the effect of the soil media more than other parameters.

Seabirds play a key role in ecosystem functioning, and they may serve as a useful indicator of its health status. The lack of predictive performance to extrapolate the toxicity results of model species to native species is a major source of uncertainty in an environmental risk assessment approach, calling for the use of non-conventional model species. The focus of this chapter is on the analysis of the external exposure stage of risk factor/s in an environmental risk assessment. Here, we explore different approaches to assessing the vulnerability of seabirds to environmental risks, discuss current challenges, propose a trait-based solution to these challenges and explore additional complicating factors in using non-model species in environmental risk assessments. The trait-based approach is an ecological dimension reduction technique to make sense of datasets with a high species dimension. This approach exists hand-in-hand with additional experimental approaches that investigate the internal response of a specific biological receptor of interest to risk factors given a prescribed level of exposure. When combined, these approaches should provide a more complete picture of the impact of risk factor/s to native species and their communities. Integrating non-conventional species in environmental risk assessments is one important step toward this goal.

Expert judgment is widely used for activity duration estimation in software project management. While there are both advantages and disadvantages of expert judgment-based estimation, we propose the use of fuzzy inference rules for semi-automatic estimation to reduce the potential negative aspects of the expert judgment-based estimation. Fourteen fuzzy inference rules are introduced to elicit and adjust expert tacit knowledge, and expert judgment-based estimation results are complemented by fuzzy inference rules. The results from expert judgment and fuzzy inference rules are compared with the expert judgment-based approach using surveys and one-on-one interviews with project managers from different disciplines through analyses with data from past software projects. The use of fuzzy inference rules improves the estimation accuracy of the expert judgment-based approach by 39.35%. The proposed approach facilitates the experts to derive a more realistic and reliable activity duration estimation in software project management.

Purpose – The purpose of this paper is to develop an analytic hierarchy planning-based framework to establish criteria weights and to develop a school performance system commonly called school inspections. Design/methodology/approach – The analytic hierarchy process (AHP) model uses pairwise comparisons and a measurement scale to generate the weights for the criteria. The validity of the approach is confirmed by comparing the outputs of school inspection and the outputs of the model in a sample of schools. Findings – The framework proposed enables school management to address several issues pertaining to its competitive advantage with other schools, the two most important being establishing its performance ranking in the marketplace and identifying the service elements that most require improvement. This study develops a cohesive approach to identify which quality attributes or dimensions require attention. Research limitations/implications – For school inspections, the data collection and computational problems would increase with the increase in the number of criteria and sub-criteria, as well as the number of schools considered in the selection. Although the range of reported AHP applications is extensive in many disciplines, examples in school quality and inspection remain still rare; as a result, this study could not compare its results with other AHP applications in school inspection or assessment. Practical implications – The AHP method has the distinct advantage that it decomposes a decision problem into its constituent parts and builds hierarchies of criteria. AHP enables assessors to capture both subjective and objective evaluation measures of school quality. By providing a useful mechanism for assessing the consistency of the evaluation measures and alternatives, the AHP reduces bias in decision making. Social implications – The AHP model also provides a more systematic evaluation of a given school’s qualitative performance criteria. The proposed AHP model is attractive to assessors and decision makers because its pairwise comparison procedure enables them to offer a relative (rather than absolute) individual criterion assessment on those qualitative factors. Originality/value – The AHP model could become a sustainable component of overall school system quality improvement by maturing over time. The AHP annual scores could be used as realistic and measureable gauges for measuring school improvement.