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Scott-Fordsmand JJ, Amorim MJB. Using Machine Learning to make nanomaterials sustainable. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 859:160303. [PMID: 36410486 DOI: 10.1016/j.scitotenv.2022.160303] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Revised: 11/06/2022] [Accepted: 11/15/2022] [Indexed: 06/16/2023]
Abstract
Sustainable development is a key challenge for contemporary human societies; failure to achieve sustainability could threaten human survival. In this review article, we illustrate how Machine Learning (ML) could support more sustainable development, covering the basics of data gathering through each step of the Environmental Risk Assessment (ERA). The literature provides several examples showing how ML can be employed in most steps of a typical ERA.A key observation is that there are currently no clear guidance for using such autonomous technologies in ERAs or which standards/checks are required. Steering thus seems to be the most important task for supporting the use of ML in the ERA of nano- and smart-materials. Resources should be devoted to developing a strategy for implementing ML in ERA with a strong emphasis on data foundations, methodologies, and the related sensitivities/uncertainties. We should recognise historical errors and biases (e.g., in data) to avoid embedding them during ML programming.
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Affiliation(s)
| | - Mónica J B Amorim
- Department of Biology & CESAM, University of Aveiro, 3810-193 Aveiro, Portugal.
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2
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De Luca Peña LV, Taelman SE, Préat N, Boone L, Van der Biest K, Custódio M, Hernandez Lucas S, Everaert G, Dewulf J. Towards a comprehensive sustainability methodology to assess anthropogenic impacts on ecosystems: Review of the integration of Life Cycle Assessment, Environmental Risk Assessment and Ecosystem Services Assessment. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 808:152125. [PMID: 34871681 DOI: 10.1016/j.scitotenv.2021.152125] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Revised: 11/22/2021] [Accepted: 11/28/2021] [Indexed: 06/13/2023]
Abstract
Nowadays, a variety of methodologies are available to assess local, regional and global impacts of human activities on ecosystems, which include Life Cycle Assessment (LCA), Environmental Risk Assessment (ERA) and Ecosystem Services Assessment (ESA). However, none can individually assess both the positive and negative impacts of human activities at different geographical scales in a comprehensive manner. In order to overcome the shortcomings of each methodology and develop more holistic assessments, the integration of these methodologies is essential. Several studies have attempted to integrate these methodologies either conceptually or through applied case studies. To understand why, how and to what extent these methodologies have been integrated, a total of 110 relevant publications were reviewed. The analysis of the case studies showed that the integration can occur at different positions along the cause-effect chain and from this, a classification scheme was proposed to characterize the different integration approaches. Three categories of integration are distinguished: post-analysis, integration through the combination of results, and integration through the complementation of a driving method. The literature review highlights that the most recurrent type of integration is the latter. While the integration through the complementation of a driving method is more realistic and accurate compared to the other two categories, its development is more complex and a higher data requirement could be needed. In addition to this, there is always the risk of double-counting for all the approaches. None of the integration approaches can be categorized as a full integration, but this is not necessarily needed to have a comprehensive assessment. The most essential aspect is to select the appropriate components from each methodology that can cover both the environmental and socioeconomic costs and benefits of human activities on the ecosystems.
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Affiliation(s)
- Laura Vittoria De Luca Peña
- Department of Green Chemistry and Technology, Faculty of Bioscience Engineering, Ghent University, Coupure Links 653, 9000 Gent, Belgium.
| | - Sue Ellen Taelman
- Department of Green Chemistry and Technology, Faculty of Bioscience Engineering, Ghent University, Coupure Links 653, 9000 Gent, Belgium
| | - Nils Préat
- Department of Green Chemistry and Technology, Faculty of Bioscience Engineering, Ghent University, Coupure Links 653, 9000 Gent, Belgium
| | - Lieselot Boone
- Department of Green Chemistry and Technology, Faculty of Bioscience Engineering, Ghent University, Coupure Links 653, 9000 Gent, Belgium
| | - Katrien Van der Biest
- Ecosystem Management Research Group, University of Antwerp, Universiteitsplein 1, 2610 Wilrijk, Belgium
| | - Marco Custódio
- Flanders Marine Institute, Wandelaarkaai 7, B8400 Ostend, Belgium
| | - Simon Hernandez Lucas
- Ghent University, Laboratory of Environmental Toxicology and Aquatic Ecology, Faculty of Bioscience Engineering, 9000, Ghent, Belgium; Ghent University, BLUEGent Business Development Center in Aquaculture and Blue Life Sciences, 9000 Ghent, Belgium
| | - Gert Everaert
- Flanders Marine Institute, Wandelaarkaai 7, B8400 Ostend, Belgium
| | - Jo Dewulf
- Department of Green Chemistry and Technology, Faculty of Bioscience Engineering, Ghent University, Coupure Links 653, 9000 Gent, Belgium
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Dur G, Won EJ, Han J, Lee JS, Souissi S. An individual-based model for evaluating post-exposure effects of UV-B radiation on zooplankton reproduction. Ecol Modell 2021. [DOI: 10.1016/j.ecolmodel.2020.109379] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
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4
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Spinu N, Cronin MTD, Enoch SJ, Madden JC, Worth AP. Quantitative adverse outcome pathway (qAOP) models for toxicity prediction. Arch Toxicol 2020; 94:1497-1510. [PMID: 32424443 PMCID: PMC7261727 DOI: 10.1007/s00204-020-02774-7] [Citation(s) in RCA: 53] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2020] [Accepted: 05/04/2020] [Indexed: 01/06/2023]
Abstract
The quantitative adverse outcome pathway (qAOP) concept is gaining interest due to its potential regulatory applications in chemical risk assessment. Even though an increasing number of qAOP models are being proposed as computational predictive tools, there is no framework to guide their development and assessment. As such, the objectives of this review were to: (i) analyse the definitions of qAOPs published in the scientific literature, (ii) define a set of common features of existing qAOP models derived from the published definitions, and (iii) identify and assess the existing published qAOP models and associated software tools. As a result, five probabilistic qAOPs and ten mechanistic qAOPs were evaluated against the common features. The review offers an overview of how the qAOP concept has advanced and how it can aid toxicity assessment in the future. Further efforts are required to achieve validation, harmonisation and regulatory acceptance of qAOP models.
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Affiliation(s)
- Nicoleta Spinu
- School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Byrom Street, Liverpool, L3 3AF, UK
| | - Mark T D Cronin
- School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Byrom Street, Liverpool, L3 3AF, UK
| | - Steven J Enoch
- School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Byrom Street, Liverpool, L3 3AF, UK
| | - Judith C Madden
- School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Byrom Street, Liverpool, L3 3AF, UK
| | - Andrew P Worth
- European Commission, Joint Research Centre (JRC), Ispra, Italy.
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5
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Luque A, De Las Heras A, Ávila-Gutiérrez MJ, Zamora-Polo F. ADAPTS: An Intelligent Sustainable Conceptual Framework for Engineering Projects. SENSORS 2020; 20:s20061553. [PMID: 32168788 PMCID: PMC7147156 DOI: 10.3390/s20061553] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/28/2020] [Revised: 03/06/2020] [Accepted: 03/07/2020] [Indexed: 12/30/2022]
Abstract
This paper presents a conceptual framework for the optimization of environmental sustainability in engineering projects, both for products and industrial facilities or processes. The main objective of this work is to propose a conceptual framework to help researchers to approach optimization under the criteria of sustainability of engineering projects, making use of current Machine Learning techniques. For the development of this conceptual framework, a bibliographic search has been carried out on the Web of Science. From the selected documents and through a hermeneutic procedure the texts have been analyzed and the conceptual framework has been carried out. A graphic representation pyramid shape is shown to clearly define the variables of the proposed conceptual framework and their relationships. The conceptual framework consists of 5 dimensions; its acronym is ADAPTS. In the base are: (1) the Application to which it is intended, (2) the available DAta, (3) the APproach under which it is operated, and (4) the machine learning Tool used. At the top of the pyramid, (5) the necessary Sensing. A study case is proposed to show its applicability. This work is part of a broader line of research, in terms of optimization under sustainability criteria.
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Lotufo GR, Gust KA, Ballentine ML, Moores LC, Kennedy AJ, Barker ND, Ji Q, Chappell P. Comparative Toxicological Evaluation of UV-Degraded versus Parent-Insensitive Munition Compound 1-Methyl-3-Nitroguanidine in Fathead Minnow. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY 2020; 39:612-622. [PMID: 31845397 DOI: 10.1002/etc.4647] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/13/2019] [Revised: 10/09/2019] [Accepted: 12/04/2019] [Indexed: 06/10/2023]
Abstract
The US Army is replacing traditional munitions with insensitive munitions resistant to accidental detonation. Although the parent insensitive munition compound nitroguanidine (NQ) is generally not acutely toxic at concentrations >1000 mg/L in aquatic exposures, products formed by intensive ultraviolet (UV) degradation resulted in multiple-order of magnitude increases in toxicity. A methylated congener of NQ, 1-methyl-3-nitroguanidine (MeNQ), is also being assessed for potential use in insensitive munition explosive formulations; therefore, the present study investigated the hazard of parent versus UV-degraded MeNQ using fathead minnows (Pimephales promelas). Although up to 716 mg/L parent MeNQ caused no significant mortality or effects on growth in larval P. promelas fish in 7-d exposures, a similar concentration of MeNQ subjected to UV treatment resulted in 85% mortality. The UV treatment degraded only 3.3% of the MeNQ (5800 mg/L stock, UV-treated for 6 h), indicating that MeNQ degradation products have potentially high toxicity. The parent MeNQ exposure caused significantly decreased transcriptional expression of genes within the significantly enriched insulin metabolic pathway, suggesting antagonism of bioenergetics pathways, which complements observed, although nonsignificant, decreases in body weight. Significant differential transcriptional expression in the UV-degraded MeNQ treatments resulted in significant enrichment of pathways and functions related to the cell cycle, as well as erythrocyte function involved in O2 /CO2 exchange. These functions represent potential mechanistic sources of increased toxicity observed in the UV-degraded MeNQ exposures, which are distinct from previously observed mechanisms underlying increased toxicity of UV-degraded NQ in fish. Environ Toxicol Chem 2020;39:612-622. © 2019 SETAC.
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Affiliation(s)
- Guilherme R Lotufo
- US Army, Engineer Research and Development Center, Environmental Laboratory, Vicksburg, Mississippi
| | - Kurt A Gust
- US Army, Engineer Research and Development Center, Environmental Laboratory, Vicksburg, Mississippi
| | - Mark L Ballentine
- US Army, Engineer Research and Development Center, Environmental Laboratory, Vicksburg, Mississippi
| | - Lee C Moores
- US Army, Engineer Research and Development Center, Environmental Laboratory, Vicksburg, Mississippi
| | - Alan J Kennedy
- US Army, Engineer Research and Development Center, Environmental Laboratory, Vicksburg, Mississippi
| | | | - Qing Ji
- Bennett Aerospace, Cary, North Carolina, USA
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Slaveykova VI, Couture P, Duquesne S, D'Hugues P, Sánchez W. Recycling, reuse, and circular economy: a challenge for ecotoxicological research. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2019; 26:22097-22100. [PMID: 31104246 DOI: 10.1007/s11356-019-04626-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/18/2018] [Accepted: 02/19/2019] [Indexed: 06/09/2023]
Affiliation(s)
- Vera I Slaveykova
- Environmental Biogeochemistry and Ecotoxicology, Department F.-A. Forel for Environmental and Aquatic Sciences, School of Earth and Environmental Sciences, Faculty of Sciences, University of Geneva, 66, Bvd. Carl-Vogt, CH-1211, Geneva 4, Switzerland.
| | - Patrice Couture
- Institut National de la Recherche Scientifique - Centre Eau Terre Environnement (INRS-ETE), 490 de la Couronne, Québec, Canada
| | - Sabine Duquesne
- German Environment Agency (UBA), Wörlitzer Platz 1, D-06844, Dessau-Roßlau, Germany
| | - Patrick D'Hugues
- Bureau de recherches géologiques et minières (BRGM), D3E/DMP Avenue Claude Guillemin, 45060, Orléans CEDEX 2, France
| | - Wilfried Sánchez
- Fondation Rovaltain, Alixan, France
- Ifremer, Scientific directorat, Avenue Jean-Monnet, F-34200, Sète, France
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Li Y, Blazer VS, Wagner T. Quantifying population-level effects of water temperature, flow velocity and chemical-induced reproduction depression: A simulation study with smallmouth bass. Ecol Modell 2018. [DOI: 10.1016/j.ecolmodel.2018.06.015] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
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Falinski MM, Plata DL, Chopra SS, Theis TL, Gilbertson LM, Zimmerman JB. A framework for sustainable nanomaterial selection and design based on performance, hazard, and economic considerations. NATURE NANOTECHNOLOGY 2018; 13:708-714. [PMID: 29713076 DOI: 10.1038/s41565-018-0120-4] [Citation(s) in RCA: 43] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/18/2017] [Accepted: 03/21/2018] [Indexed: 05/14/2023]
Abstract
Engineered nanomaterials (ENMs) and ENM-enabled products have emerged as potentially high-performance replacements to conventional materials and chemicals. As such, there is an urgent need to incorporate environmental and human health objectives into ENM selection and design processes. Here, an adapted framework based on the Ashby material selection strategy is presented as an enhanced selection and design process, which includes functional performance as well as environmental and human health considerations. The utility of this framework is demonstrated through two case studies, the design and selection of antimicrobial substances and conductive polymers, including ENMs, ENM-enabled products and their alternatives. Further, these case studies consider both the comparative efficacy and impacts at two scales: (i) a broad scale, where chemical/material classes are readily compared for primary decision-making, and (ii) within a chemical/material class, where physicochemical properties are manipulated to tailor the desired performance and environmental impact profile. Development and implementation of this framework can inform decision-making for the implementation of ENMs to facilitate promising applications and prevent unintended consequences.
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Affiliation(s)
- Mark M Falinski
- Department of Environmental Engineering, Yale University, New Haven, CT, USA
| | - Desiree L Plata
- Department of Environmental Engineering, Yale University, New Haven, CT, USA
| | - Shauhrat S Chopra
- Institute for Environmental Science and Policy, University of Illinois at Chicago, Chicago, IL, USA
- School of Energy and Environment, City University of Hong Kong, Hong Kong, China
| | - Thomas L Theis
- Institute for Environmental Science and Policy, University of Illinois at Chicago, Chicago, IL, USA
| | - Leanne M Gilbertson
- Department of Civil and Environmental Engineering, University of Pittsburgh, Pittsburgh, PA, USA
| | - Julie B Zimmerman
- Department of Environmental Engineering, Yale University, New Haven, CT, USA.
- School of Forestry and Environmental Studies, Yale University, New Haven, CT, USA.
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10
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Ankley GT, Edwards SW. The Adverse Outcome Pathway: A Multifaceted Framework Supporting 21 st Century Toxicology. CURRENT OPINION IN TOXICOLOGY 2018; 9:1-7. [PMID: 29682628 DOI: 10.1016/j.cotox.2018.03.004] [Citation(s) in RCA: 61] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
The adverse outcome pathway (AOP) framework serves as a knowledge assembly, interpretation, and communication tool designed to support the translation of pathway-specific mechanistic data into responses relevant to assessing and managing risks of chemicals to human health and the environment. As such, AOPs facilitate the use of data streams often not employed by risk assessors, including information from in silico models, in vitro assays and short-term in vivo tests with molecular/biochemical endpoints. This translational capability can increase the capacity and efficiency of safety assessments both for single chemicals and chemical mixtures. Our mini-review describes the conceptual basis of the AOP framework and aspects of its current status relative to use by toxicologists and risk assessors, including four illustrative applications of the framework to diverse assessment scenarios.
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Affiliation(s)
- Gerald T Ankley
- US Environmental Protection Agency, Office of Research and Development, Mid-Continent Ecology Division, Duluth, MN, USA
| | - Stephen W Edwards
- US Environmental Protection Agency, Office of Research and Development, Integrated Systems Toxicology Division, RTP, NC, USA
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11
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Forbes VE, Salice CJ, Birnir B, Bruins RJF, Calow P, Ducrot V, Galic N, Garber K, Harvey BC, Jager H, Kanarek A, Pastorok R, Railsback SF, Rebarber R, Thorbek P. A framework for predicting impacts on ecosystem services from (sub)organismal responses to chemicals. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY 2017; 36:845-859. [PMID: 28370293 PMCID: PMC6147012 DOI: 10.1002/etc.3720] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/14/2016] [Revised: 11/14/2016] [Accepted: 12/20/2016] [Indexed: 05/29/2023]
Abstract
Protection of ecosystem services is increasingly emphasized as a risk-assessment goal, but there are wide gaps between current ecological risk-assessment endpoints and potential effects on services provided by ecosystems. The authors present a framework that links common ecotoxicological endpoints to chemical impacts on populations and communities and the ecosystem services that they provide. This framework builds on considerable advances in mechanistic effects models designed to span multiple levels of biological organization and account for various types of biological interactions and feedbacks. For illustration, the authors introduce 2 case studies that employ well-developed and validated mechanistic effects models: the inSTREAM individual-based model for fish populations and the AQUATOX ecosystem model. They also show how dynamic energy budget theory can provide a common currency for interpreting organism-level toxicity. They suggest that a framework based on mechanistic models that predict impacts on ecosystem services resulting from chemical exposure, combined with economic valuation, can provide a useful approach for informing environmental management. The authors highlight the potential benefits of using this framework as well as the challenges that will need to be addressed in future work. Environ Toxicol Chem 2017;36:845-859. © 2017 SETAC.
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Affiliation(s)
- Valery E Forbes
- Department of Ecology, Evolution and Behavior, University of Minnesota, St. Paul, Minnesota, USA
| | - Chris J Salice
- Environmental Science and Studies Program and Department of Biological Sciences, Towson University, Towson, Maryland, USA
| | - Bjorn Birnir
- Center for Complex and Nonlinear Science and Department of Mathematics, University of California Santa Barbara, Santa Barbara, California, USA
| | - Randy J F Bruins
- Systems Exposure Division, National Exposure Research Laboratory, US Environmental Protection Agency, Cincinnati, Ohio
| | - Peter Calow
- Humphrey School of Public Affairs, University of Minnesota, Minneapolis, Minnesota, USA
| | | | - Nika Galic
- Department of Ecology, Evolution and Behavior, University of Minnesota, St. Paul, Minnesota, USA
| | - Kristina Garber
- Environmental Fate and Effects Division, Office of Pesticide Programs, US Environmental Protection Agency, Washington, DC
| | - Bret C Harvey
- Pacific Southwest Research Station, US Department of Agriculture Forest Service, Arcata, California
| | - Henriette Jager
- Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA
| | - Andrew Kanarek
- Environmental Fate and Effects Division, Office of Pesticide Programs, US Environmental Protection Agency, Washington, DC
| | - Robert Pastorok
- Ecology Group, Integral Consulting, Woodinville, Washington, USA
| | | | - Richard Rebarber
- Department of Mathematics, University of Nebraska, Lincoln, Nebraska, USA
| | - Pernille Thorbek
- Environmental Safety, Syngenta, Jealott's Hill International Research Centre, Bracknell, United Kingdom
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