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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Rok Novak; Johanna Amalia Robinson; Tjaša Kanduč; Dimosthenis Sarigiannis; +2 Authors

    Participatory exposure research, which tracks behaviour and assesses exposure to stressors like air pollution, traditionally relies on time-activity diaries. This study introduces a novel approach, employing machine learning (ML) to empower laypersons in human activity recognition (HAR), aiming to reduce dependence on manual recording by leveraging data from wearable sensors. Recognising complex activities such as smoking and cooking presents unique challenges due to specific environmental conditions. In this research, we combined wearable environment/ambient and wrist-worn activity/biometric sensors for complex activity recognition in an urban stressor exposure study, measuring parameters like particulate matter concentrations, temperature, and humidity. Two groups, Group H (88 individuals) and Group M (18 individuals), wore the devices and manually logged their activities hourly and minutely, respectively. Prioritising accessibility and inclusivity, we selected three classification algorithms: k-nearest neighbours (IBk), decision trees (J48), and random forests (RF), based on: (1) proven efficacy in existing literature, (2) understandability and transparency for laypersons, (3) availability on user-friendly platforms like WEKA, and (4) efficiency on basic devices such as office laptops or smartphones. Accuracy improved with finer temporal resolution and detailed activity categories. However, when compared to other published human activity recognition research, our accuracy rates, particularly for less complex activities, were not as competitive. Misclassifications were higher for vague activities (resting, playing), while well-defined activities (smoking, cooking, running) had few errors. Including environmental sensor data increased accuracy for all activities, especially playing, smoking, and running. Future work should consider exploring other explainable algorithms available on diverse tools and platforms. Our findings underscore ML’s potential in exposure studies, emphasising its adaptability and significance for laypersons while also highlighting areas for improvement.

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    Sensors
    Article . 2023
    Data sources: DOAJ
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    Sensors
    Article . 2023 . Peer-reviewed
    License: CC BY
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Sensorsarrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Sensors
      Article . 2023
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      Sensors
      Article . 2023 . Peer-reviewed
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Luna M. van der Loos; Quinten Bafort; Samuel Bosch; Enric Ballesteros; +40 Authors

    Effective monitoring of non-indigenous seaweeds and combatting their effects relies on a solid confirmation of the non-indigenous status of the respective species. We critically analysed the status of presumed non-indigenous seaweed species reported from the Mediterranean Sea, the Northeast Atlantic Ocean and Macaronesia, resulting in a list of 140 species whose non-indigenous nature is undisputed. For an additional 87 species it is unclear if they are native or non-indigenous (cryptogenic species) or their identity requires confirmation (data deficient species). We discuss the factors underlying both taxonomic and biogeographic uncertainties and outline recommendations to reduce uncertainty about the non-indigenous status of seaweeds. Our dataset consisted of over 19,000 distribution records, half of which can be attributed to only five species (Sargassum muticum, Bonnemaisonia hamifera, Asparagopsis armata, Caulerpa cylindracea and Colpomenia peregrina), while 56 species (40%) are recorded no more than once or twice. In addition, our analyses revealed considerable variation in the diversity of non-indigenous species between the geographic regions. The Eastern Mediterranean Sea is home to the largest fraction of non-indigenous seaweed species, the majority of which have a Red Sea or Indo-Pacific origin and have entered the Mediterranean Sea mostly via the Suez Canal. Non-indigenous seaweeds with native ranges situated in the Northwest Pacific make up a large fraction of the total in the Western Mediterranean Sea, Lusitania and Northern Europe, followed by non-indigenous species with a presumed Australasian origin. Uncertainty remains, however, regarding the native range of a substantial fraction of non-indigenous seaweeds in the study area. In so far as analyses of first detections can serve as a proxy for the introduction rate of non-indigenous seaweeds, these do not reveal a decrease in the introduction rate, indicating that the current measures and policies are insufficient to battle the introduction and spread of non-indigenous species in the study area. European Marine Biological Resource Centre Belgium [GOH3817N]; European Marine Biological Resource Centre Belgium [I001621N]; Fonds Wetenschappelijk Onderzoek [3F020119]; POR PUGLIA FESR-FSE 2014/2020 [Asse VI, Action 6.5]; RESTORESEAS [EU-BiodivERsA BiodivRestore-253]; Institut des Sciences de l’Évolution – Montpellier [ISEM 2023-173]; Italian National Recovery and Resilience Plan [Mission 4, Component 2, ‘From research to business’: 1. NBFC, Investment 1.4, Project CN00000033]; IDEALG [ANR-10-BTBR-04; Institut des Sciences de l’Évolution – Montpellier Institut des Sciences de l’Évolution – Montpellier [ISEM 2023-173]. info:eu-repo/semantics/publishedVersion

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    European Journal of Phycology
    Article . 2023 . Peer-reviewed
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ArchiMer - Instituti...arrow_drop_down
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      European Journal of Phycology
      Article . 2023 . Peer-reviewed
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Jennifer Bailey; Martin Otto Paul Ramacher; Orestis Speyer; Eleni Athanasopoulou; +2 Authors

    While Earth observation (EO) increasingly provides a multitude of solutions to address environmental issues and sustainability from the city to global scale, their operational integration into the Sustainable Development Goals (SDG) framework is still falling behind. Within this framework, SDG Indicator 11.6.2 asks countries to report the “annual mean levels of fine particulate matter (PM2.5) in cities (population-weighted)”. The official United Nations (UN) methodology entails aggregation into a single, national level value derived from regulatory air quality monitoring networks, which are non-existent or sparse in many countries. EO, including, but not limited to remote sensing, brings forth novel monitoring methods to estimate SDG Indicator 11.6.2 alongside more traditional ones, and allows for comparability and scalability in the face of varying city definitions and monitoring capacities which impact the validity and usefulness of such an indicator. Pursuing a more harmonised global approach, the H2020 SMURBS/ERA-PLANET project provides two EO-driven approaches to deliver the indicator on a more granular level across Europe. The first approach provides both city and national values for SDG Indicator 11.6.2 through exploiting the Copernicus Atmospheric Monitoring Service reanalysis data (0.1° resolution and incorporating in situ and remote sensing data) for PM2.5 values. The SDG Indicator 11.6.2 values are calculated using two objective city definitions—“functional urban area” and “urban centre”—that follow the UN sanctioned Degree of Urbanization concept, and then compared with official indicator values. In the second approach, a high-resolution city-scale chemical transport model ingests satellite-derived data and calculates SDG Indicator 11.6.2 at intra-urban scales. Both novel approaches to calculating SDG Indicator 11.6.2 using EO enable exploration of air pollution hotspots that drive the indicator as well as actual population exposure within cities, which can influence funding allocation and intervention implementation. The approaches are introduced, and their results frame a discussion around interesting policy implications, all with the aim to help move the dial beyond solely reporting on SDGs to designing the pathways to achieve the overarching targets.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Remote Sensingarrow_drop_down
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    Remote Sensing
    Other literature type . Article . 2023 . Peer-reviewed
    License: CC BY
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    Remote Sensing
    Article . 2023
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Remote Sensingarrow_drop_down
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      Remote Sensing
      Other literature type . Article . 2023 . Peer-reviewed
      License: CC BY
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Remote Sensing
      Article . 2023
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Agata Gulisano; Antonio Lippolis; Eibertus N. van Loo; Maria-João Paulo; +1 Authors

    Establishing Lupinus mutabilis as a protein and oil crop requires improved varieties adapted to EU climates. The genetic regulation of strategic breeding traits, including plant architecture, growing cycle length and yield, is unknown. This study aimed to identify associations between 16 669 single nucleotide polymorphisms (SNPs) and 9 agronomic traits on a panel of 223 L. mutabilis accessions, grown in four environments, by applying a genome wide association study (GWAS). Seven environment-specific QTLs linked to vegetative yield, plant height, pods number and flowering time, were identified as major effect QTLs, being able to capture 6 to 20% of the phenotypic variation observed in these traits. Furthermore, two QTLs across environments were identified for flowering time on chromosome 8. The genes FAF, GAMYB and LNK, regulating major pathways involved in flowering and growth habit, as well as GA30X1, BIM1, Dr1, HDA15, HAT3, interacting with these pathways in response to hormonal and environmental cues, were prosed as candidate genes. These results are pivotal to accelerate the development of L. mutabilis varieties adapted to European cropping conditions by using marker-assisted selection (MAS), as well as to provide a framework for further functional studies on plant development and phenology in this species.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ NARCIS; Research@WURarrow_drop_down
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    Article . 2023
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    Research@WUR; Frontiers in Plant Science
    Article . 2023 . Peer-reviewed
    License: CC BY
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    Frontiers in Plant Science
    Article . 2023
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      Article . 2023
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      Research@WUR; Frontiers in Plant Science
      Article . 2023 . Peer-reviewed
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      Frontiers in Plant Science
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    Authors: Raghuraj Singh Chouhan; Jan Gačnik; Igor Živković; Sreekanth Vijayakumaran Nair; +6 Authors

    Green synthesis of a magnetite/graphitic carbon nitride 2D nanocomposite for efficient Hg2+ remediation in different aqueous matrices utilising a thermal assist sonication method.

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    Environmental Science Nano
    Article . 2023 . Peer-reviewed
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      Environmental Science Nano
      Article . 2023 . Peer-reviewed
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    Authors: Lőrinc Mészáros; Lőrinc Mészáros; Frank van der Meulen; Geurt Jongbloed; +2 Authors

    Coastal climate impact studies make increasing use of multi-source and multi-dimensional atmospheric and environmental datasets to investigate relationships between climate signals and the ecological response. The large quantity of numerically simulated data may, however, include redundancy, multi-colinearity and excess information not relevant to the studied processes. In such cases techniques for feature extraction and identification of latent processes prove useful. Using dimensionality reduction techniques this research provides a statistical underpinning of variable selection to study the impacts of atmospheric processes on coastal chlorophyll-a concentrations, taking the Dutch Wadden Sea as case study. Dimension reduction techniques are applied to environmental data simulated by the Delft3D coastal water quality model, the HIRLAM numerical weather prediction model and the Euro-CORDEX climate modelling experiment. The dimension reduction techniques were selected for their ability to incorporate (1) spatial correlation via multi-way methods (2), temporal correlation through Dynamic Factor Analysis, and (3) functional variability using Functional Data Analysis. The data reduction potential and explanatory value of these methods are showcased and important atmospheric variables affecting the chlorophyll-a concentration are identified. Our results indicate room for dimensionality reduction in the atmospheric variables (2 principle components can explain the majority of variance instead of 7 variables), in the chlorophyll-a time series at different locations (two characteristic patterns can describe the 10 locations), and in the climate projection scenarios of solar radiation and air temperature variables (a single principle component function explains 77% of the variation for solar radiation and 57% of the variation for air temperature). It was also found that solar radiation followed by air temperature are the most important atmospheric variables related to coastal chlorophyll-a concentration, noting that regional differences exist, for instance the importance of air temperature is greater in the Eastern Dutch Wadden Sea at Dantziggat than in the Western Dutch Wadden Sea at Marsdiep Noord. Common trends and different regional system characteristics have also been identified through dynamic factor analysis between the deeper channels and the shallower intertidal zones, where the onset of spring blooms occurs earlier. The functional analysis of climate data showed clusters of atmospheric variables with similar functional features. Moreover, functional components of Euro-CORDEX climate scenarios have been identified for radiation and temperature variables, which provide information on the dominant mode (pattern) of variation and its uncertainties. The findings suggest that radiation and temperature projections of different Euro-CORDEX scenarios share similar characteristics and mainly differ in their amplitudes and seasonal patterns, offering opportunities to construct statistical models that do not assume independence between climate scenarios but instead borrow information (“borrow strength”) from the larger pool of climate scenarios. The presented results were used in follow up studies to construct a Bayesian stochastic generator to complement existing Euro-CORDEX climate change scenarios and to quantify climate change induced trends and uncertainties in phytoplankton spring bloom dynamics in the Dutch Wadden Sea.

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    Frontiers in Marine Science
    Article . 2022 . Peer-reviewed
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    Frontiers in Marine Science
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      Frontiers in Marine Science
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    Authors: Chen, Gang; Canonaco, Francesco; Slowik, Jay G.; Daellenbach, Kaspar R.; +9 Authors

    97% of the urban population in the EU in 2019 were exposed to an annual fine particulate matter level higher than the World Health Organization (WHO) guidelines (5 μg/m3). Organic aerosol (OA) is one of the major air pollutants, and the knowledge of its sources is crucial for designing cost-effective mitigation strategies. Positive matrix factorization (PMF) on aerosol mass spectrometer (AMS) or aerosol chemical speciation monitor (ACSM) data is the most common method for source apportionment (SA) analysis on ambient OA. However, conventional PMF requires extensive human labor, preventing the implementation of SA for routine monitoring applications. This study proposes the source finder real-time (SoFi RT, Datalystica Ltd.) approach for efficient retrieval of OA sources. The results generated by SoFi RT agree remarkably well with the conventional rolling PMF results regarding factor profiles, time series, diurnal patterns, and yearly relative contributions of OA factor on three year-long ACSM data sets collected in Athens, Paris, and Zurich. Although the initialization of SoFi RT requires a priori knowledge of OA sources (i.e., the approximate number of factors and relevant factor profiles) for the sampling site, this technique minimizes user interactions. Eventually, it could provide up-to-date trustable information on timescales useful to policymakers and air quality modelers. Environmental Science & Technology, 56 (22) ISSN:0013-936X ISSN:1520-5851

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    Environmental Science & Technology
    Other literature type . Article . 2022 . Peer-reviewed
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      Other literature type . Article . 2022 . Peer-reviewed
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  • Authors: Livia Madureira; Pierre Labarthe; Carla S. Marques; Gina Santos;

    International audience; Purpose: To provide novel empirical evidence on the role of advice in technological and non-technological innovation uptake decision-making processes from the perspective of European farmers, we develop the microAKIS (farmer microscale knowledge and innovation systems) framework.Design/methodology/approach: The MicroAKIS framework is expanded to gather empirical evidence built on quantitative data from a sample of 675 European farmers.Findings: Different types of innovation lead to different microAKIS, and farmers' involvement with innovation introduces new dynamics in advice supply. MicroAKIS supporting innovations tend to be small in size and diversity, suggesting the anticipated pluralism of advice resulting from advisory services privatisation across Europe did not work as expected, i.e. not translating into pluralistic microAKIS.Practical implications: Pluralism in advice for innovation is needed and could be enhanced by integrating different sources of advice: professional and non-professional, formal and informal, agricultural and cross-sectorial.Theoretical implications: We advance the scope of the AKIS concept by accounting for the temporal dynamics of innovation uptake decision-making and adopting multi-level analysis that combines micro (farm) and meso (region) scales.Originality/value: Empirical evidence at the European level, gathered from the common farmer's perspective on the dynamics of farm-level microAKIS and the role played by farm advisory, accounting for diversity of innovations and regional contexts.

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    Authors: Nuria Benavent; Anoop S. Mahajan; Qinyi Li; Carlos A. Cuevas; +30 Authors

    This study received funding from the European Research Council Executive Agency under the European Union’s Horizon 2020 Research and Innovation Program (project ERC‐2016‐COG 726349 CLIMAHAL and ERC-2016-STG 714621 GASPARCON) and the European Commission via the EMME-CARE project and was supported by the Consejo Superior de Investigaciones Científicas of Spain. This work was supported by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement no. 856612 and the Academy of Finland (project no. 334514). The Indian Institute of Tropical Meteorology is funded by the Ministry of Earth Sciences, Government of India. Ozone, CO, CH4 and AMS measurements were funded by the Swiss National Science Foundation (grant 200021_188478), the Swiss Polar Institute and U.S. National Science Foundation grants 1914781 and 1807163. J.S. holds the Ingvar Kamprad chair for extreme environments research, sponsored by Ferring Pharmaceuticals. Data reported in this manuscript were produced as part of the international MOSAiC expedition with tag MOSAiC20192020, with activities supported by Polarstern expedition AWI-PS122_00. H.S. was funded by the European ERA-PLANET projects iGOSP and iCUPE (consortium agreement no. 689443 for both projects). We thank FORMAS and the Swedish Polar Research Secretariat for support. We gratefully acknowledge funding by the Deutsche Forschungsgemeinschaft (project no. 268020496 – TRR 172) within the Transregional Collaborative Research Center ‘ArctiC Amplification: Climate Relevant Atmospheric and SurfaCe Processes, and Feedback Mechanisms (AC)3’ in subproject C03. We thank I. Bourgeois (NOAA/CIRES) for providing the ATom NOx data. Unlike bromine, the effect of iodine chemistry on the Arctic surface ozone budget is poorly constrained. We present ship-based measurements of halogen oxides in the high Arctic boundary layer from the sunlit period of March to October 2020 and show that iodine enhances springtime tropospheric ozone depletion. We find that chemical reactions between iodine and ozone are the second highest contributor to ozone loss over the study period, after ozone photolysis-initiated loss and ahead of bromine. 6 pags., 2 figs. Peer reviewed

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    Authors: Ebun Akinsete; Phoebe Koundouri; Xanthi Kartala; Nikos Englezos; +6 Authors

    Rapid population growth along with increased rates of economic growth around the globe are placing valuable natural resources, water in particular, under unprecedented stress; this in turn drives the pursuit of innovative tools to support integrated Water-Energy-Food (WEF) nexus management. This paper presents a framework for the integrated management of the WEF nexus, which brings together four separate models that address the less well-examined socio-anthropological aspects of the nexus. The proposed framework provides insight into the human element as part of the wider ecosystem in terms of socio-cultural and economic activities, the laws and policies that govern these activities, as well as their potential socio-economic impacts and consequences. This paper outlines each individual model, before going on to present a conceptual framework for the integration of the various models for the purpose of supporting more robust decision-making. The framework, which is grounded in systems thinking, adopts the principles of sustainable development as structural foci in order to position the various models in relation to one another; harmonizing their inputs as well as outputs.

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    Frontiers in Water
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    Authors: Rok Novak; Johanna Amalia Robinson; Tjaša Kanduč; Dimosthenis Sarigiannis; +2 Authors

    Participatory exposure research, which tracks behaviour and assesses exposure to stressors like air pollution, traditionally relies on time-activity diaries. This study introduces a novel approach, employing machine learning (ML) to empower laypersons in human activity recognition (HAR), aiming to reduce dependence on manual recording by leveraging data from wearable sensors. Recognising complex activities such as smoking and cooking presents unique challenges due to specific environmental conditions. In this research, we combined wearable environment/ambient and wrist-worn activity/biometric sensors for complex activity recognition in an urban stressor exposure study, measuring parameters like particulate matter concentrations, temperature, and humidity. Two groups, Group H (88 individuals) and Group M (18 individuals), wore the devices and manually logged their activities hourly and minutely, respectively. Prioritising accessibility and inclusivity, we selected three classification algorithms: k-nearest neighbours (IBk), decision trees (J48), and random forests (RF), based on: (1) proven efficacy in existing literature, (2) understandability and transparency for laypersons, (3) availability on user-friendly platforms like WEKA, and (4) efficiency on basic devices such as office laptops or smartphones. Accuracy improved with finer temporal resolution and detailed activity categories. However, when compared to other published human activity recognition research, our accuracy rates, particularly for less complex activities, were not as competitive. Misclassifications were higher for vague activities (resting, playing), while well-defined activities (smoking, cooking, running) had few errors. Including environmental sensor data increased accuracy for all activities, especially playing, smoking, and running. Future work should consider exploring other explainable algorithms available on diverse tools and platforms. Our findings underscore ML’s potential in exposure studies, emphasising its adaptability and significance for laypersons while also highlighting areas for improvement.

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    Sensors
    Article . 2023
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    Sensors
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      Sensors
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    Authors: Luna M. van der Loos; Quinten Bafort; Samuel Bosch; Enric Ballesteros; +40 Authors

    Effective monitoring of non-indigenous seaweeds and combatting their effects relies on a solid confirmation of the non-indigenous status of the respective species. We critically analysed the status of presumed non-indigenous seaweed species reported from the Mediterranean Sea, the Northeast Atlantic Ocean and Macaronesia, resulting in a list of 140 species whose non-indigenous nature is undisputed. For an additional 87 species it is unclear if they are native or non-indigenous (cryptogenic species) or their identity requires confirmation (data deficient species). We discuss the factors underlying both taxonomic and biogeographic uncertainties and outline recommendations to reduce uncertainty about the non-indigenous status of seaweeds. Our dataset consisted of over 19,000 distribution records, half of which can be attributed to only five species (Sargassum muticum, Bonnemaisonia hamifera, Asparagopsis armata, Caulerpa cylindracea and Colpomenia peregrina), while 56 species (40%) are recorded no more than once or twice. In addition, our analyses revealed considerable variation in the diversity of non-indigenous species between the geographic regions. The Eastern Mediterranean Sea is home to the largest fraction of non-indigenous seaweed species, the majority of which have a Red Sea or Indo-Pacific origin and have entered the Mediterranean Sea mostly via the Suez Canal. Non-indigenous seaweeds with native ranges situated in the Northwest Pacific make up a large fraction of the total in the Western Mediterranean Sea, Lusitania and Northern Europe, followed by non-indigenous species with a presumed Australasian origin. Uncertainty remains, however, regarding the native range of a substantial fraction of non-indigenous seaweeds in the study area. In so far as analyses of first detections can serve as a proxy for the introduction rate of non-indigenous seaweeds, these do not reveal a decrease in the introduction rate, indicating that the current measures and policies are insufficient to battle the introduction and spread of non-indigenous species in the study area. European Marine Biological Resource Centre Belgium [GOH3817N]; European Marine Biological Resource Centre Belgium [I001621N]; Fonds Wetenschappelijk Onderzoek [3F020119]; POR PUGLIA FESR-FSE 2014/2020 [Asse VI, Action 6.5]; RESTORESEAS [EU-BiodivERsA BiodivRestore-253]; Institut des Sciences de l’Évolution – Montpellier [ISEM 2023-173]; Italian National Recovery and Resilience Plan [Mission 4, Component 2, ‘From research to business’: 1. NBFC, Investment 1.4, Project CN00000033]; IDEALG [ANR-10-BTBR-04; Institut des Sciences de l’Évolution – Montpellier Institut des Sciences de l’Évolution – Montpellier [ISEM 2023-173]. info:eu-repo/semantics/publishedVersion

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    European Journal of Phycology
    Article . 2023 . Peer-reviewed
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      European Journal of Phycology
      Article . 2023 . Peer-reviewed
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    Authors: Jennifer Bailey; Martin Otto Paul Ramacher; Orestis Speyer; Eleni Athanasopoulou; +2 Authors

    While Earth observation (EO) increasingly provides a multitude of solutions to address environmental issues and sustainability from the city to global scale, their operational integration into the Sustainable Development Goals (SDG) framework is still falling behind. Within this framework, SDG Indicator 11.6.2 asks countries to report the “annual mean levels of fine particulate matter (PM2.5) in cities (population-weighted)”. The official United Nations (UN) methodology entails aggregation into a single, national level value derived from regulatory air quality monitoring networks, which are non-existent or sparse in many countries. EO, including, but not limited to remote sensing, brings forth novel monitoring methods to estimate SDG Indicator 11.6.2 alongside more traditional ones, and allows for comparability and scalability in the face of varying city definitions and monitoring capacities which impact the validity and usefulness of such an indicator. Pursuing a more harmonised global approach, the H2020 SMURBS/ERA-PLANET project provides two EO-driven approaches to deliver the indicator on a more granular level across Europe. The first approach provides both city and national values for SDG Indicator 11.6.2 through exploiting the Copernicus Atmospheric Monitoring Service reanalysis data (0.1° resolution and incorporating in situ and remote sensing data) for PM2.5 values. The SDG Indicator 11.6.2 values are calculated using two objective city definitions—“functional urban area” and “urban centre”—that follow the UN sanctioned Degree of Urbanization concept, and then compared with official indicator values. In the second approach, a high-resolution city-scale chemical transport model ingests satellite-derived data and calculates SDG Indicator 11.6.2 at intra-urban scales. Both novel approaches to calculating SDG Indicator 11.6.2 using EO enable exploration of air pollution hotspots that drive the indicator as well as actual population exposure within cities, which can influence funding allocation and intervention implementation. The approaches are introduced, and their results frame a discussion around interesting policy implications, all with the aim to help move the dial beyond solely reporting on SDGs to designing the pathways to achieve the overarching targets.

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    Remote Sensing
    Other literature type . Article . 2023 . Peer-reviewed
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    Remote Sensing
    Article . 2023
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    Authors: Agata Gulisano; Antonio Lippolis; Eibertus N. van Loo; Maria-João Paulo; +1 Authors

    Establishing Lupinus mutabilis as a protein and oil crop requires improved varieties adapted to EU climates. The genetic regulation of strategic breeding traits, including plant architecture, growing cycle length and yield, is unknown. This study aimed to identify associations between 16 669 single nucleotide polymorphisms (SNPs) and 9 agronomic traits on a panel of 223 L. mutabilis accessions, grown in four environments, by applying a genome wide association study (GWAS). Seven environment-specific QTLs linked to vegetative yield, plant height, pods number and flowering time, were identified as major effect QTLs, being able to capture 6 to 20% of the phenotypic variation observed in these traits. Furthermore, two QTLs across environments were identified for flowering time on chromosome 8. The genes FAF, GAMYB and LNK, regulating major pathways involved in flowering and growth habit, as well as GA30X1, BIM1, Dr1, HDA15, HAT3, interacting with these pathways in response to hormonal and environmental cues, were prosed as candidate genes. These results are pivotal to accelerate the development of L. mutabilis varieties adapted to European cropping conditions by using marker-assisted selection (MAS), as well as to provide a framework for further functional studies on plant development and phenology in this species.

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    Research@WUR; Frontiers in Plant Science
    Article . 2023 . Peer-reviewed
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    Frontiers in Plant Science
    Article . 2023
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      Article . 2023
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      Research@WUR; Frontiers in Plant Science
      Article . 2023 . Peer-reviewed
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    Authors: Raghuraj Singh Chouhan; Jan Gačnik; Igor Živković; Sreekanth Vijayakumaran Nair; +6 Authors

    Green synthesis of a magnetite/graphitic carbon nitride 2D nanocomposite for efficient Hg2+ remediation in different aqueous matrices utilising a thermal assist sonication method.

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    Environmental Science Nano
    Article . 2023 . Peer-reviewed
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      Environmental Science Nano
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    Authors: Lőrinc Mészáros; Lőrinc Mészáros; Frank van der Meulen; Geurt Jongbloed; +2 Authors

    Coastal climate impact studies make increasing use of multi-source and multi-dimensional atmospheric and environmental datasets to investigate relationships between climate signals and the ecological response. The large quantity of numerically simulated data may, however, include redundancy, multi-colinearity and excess information not relevant to the studied processes. In such cases techniques for feature extraction and identification of latent processes prove useful. Using dimensionality reduction techniques this research provides a statistical underpinning of variable selection to study the impacts of atmospheric processes on coastal chlorophyll-a concentrations, taking the Dutch Wadden Sea as case study. Dimension reduction techniques are applied to environmental data simulated by the Delft3D coastal water quality model, the HIRLAM numerical weather prediction model and the Euro-CORDEX climate modelling experiment. The dimension reduction techniques were selected for their ability to incorporate (1) spatial correlation via multi-way methods (2), temporal correlation through Dynamic Factor Analysis, and (3) functional variability using Functional Data Analysis. The data reduction potential and explanatory value of these methods are showcased and important atmospheric variables affecting the chlorophyll-a concentration are identified. Our results indicate room for dimensionality reduction in the atmospheric variables (2 principle components can explain the majority of variance instead of 7 variables), in the chlorophyll-a time series at different locations (two characteristic patterns can describe the 10 locations), and in the climate projection scenarios of solar radiation and air temperature variables (a single principle component function explains 77% of the variation for solar radiation and 57% of the variation for air temperature). It was also found that solar radiation followed by air temperature are the most important atmospheric variables related to coastal chlorophyll-a concentration, noting that regional differences exist, for instance the importance of air temperature is greater in the Eastern Dutch Wadden Sea at Dantziggat than in the Western Dutch Wadden Sea at Marsdiep Noord. Common trends and different regional system characteristics have also been identified through dynamic factor analysis between the deeper channels and the shallower intertidal zones, where the onset of spring blooms occurs earlier. The functional analysis of climate data showed clusters of atmospheric variables with similar functional features. Moreover, functional components of Euro-CORDEX climate scenarios have been identified for radiation and temperature variables, which provide information on the dominant mode (pattern) of variation and its uncertainties. The findings suggest that radiation and temperature projections of different Euro-CORDEX scenarios share similar characteristics and mainly differ in their amplitudes and seasonal patterns, offering opportunities to construct statistical models that do not assume independence between climate scenarios but instead borrow information (“borrow strength”) from the larger pool of climate scenarios. The presented results were used in follow up studies to construct a Bayesian stochastic generator to complement existing Euro-CORDEX climate change scenarios and to quantify climate change induced trends and uncertainties in phytoplankton spring bloom dynamics in the Dutch Wadden Sea.

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    Frontiers in Marine Science
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      Frontiers in Marine Science
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    Authors: Chen, Gang; Canonaco, Francesco; Slowik, Jay G.; Daellenbach, Kaspar R.; +9 Authors

    97% of the urban population in the EU in 2019 were exposed to an annual fine particulate matter level higher than the World Health Organization (WHO) guidelines (5 μg/m3). Organic aerosol (OA) is one of the major air pollutants, and the knowledge of its sources is crucial for designing cost-effective mitigation strategies. Positive matrix factorization (PMF) on aerosol mass spectrometer (AMS) or aerosol chemical speciation monitor (ACSM) data is the most common method for source apportionment (SA) analysis on ambient OA. However, conventional PMF requires extensive human labor, preventing the implementation of SA for routine monitoring applications. This study proposes the source finder real-time (SoFi RT, Datalystica Ltd.) approach for efficient retrieval of OA sources. The results generated by SoFi RT agree remarkably well with the conventional rolling PMF results regarding factor profiles, time series, diurnal patterns, and yearly relative contributions of OA factor on three year-long ACSM data sets collected in Athens, Paris, and Zurich. Although the initialization of SoFi RT requires a priori knowledge of OA sources (i.e., the approximate number of factors and relevant factor profiles) for the sampling site, this technique minimizes user interactions. Eventually, it could provide up-to-date trustable information on timescales useful to policymakers and air quality modelers. Environmental Science & Technology, 56 (22) ISSN:0013-936X ISSN:1520-5851

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    Environmental Science & Technology
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      Environmental Science & Technology
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  • Authors: Livia Madureira; Pierre Labarthe; Carla S. Marques; Gina Santos;

    International audience; Purpose: To provide novel empirical evidence on the role of advice in technological and non-technological innovation uptake decision-making processes from the perspective of European farmers, we develop the microAKIS (farmer microscale knowledge and innovation systems) framework.Design/methodology/approach: The MicroAKIS framework is expanded to gather empirical evidence built on quantitative data from a sample of 675 European farmers.Findings: Different types of innovation lead to different microAKIS, and farmers' involvement with innovation introduces new dynamics in advice supply. MicroAKIS supporting innovations tend to be small in size and diversity, suggesting the anticipated pluralism of advice resulting from advisory services privatisation across Europe did not work as expected, i.e. not translating into pluralistic microAKIS.Practical implications: Pluralism in advice for innovation is needed and could be enhanced by integrating different sources of advice: professional and non-professional, formal and informal, agricultural and cross-sectorial.Theoretical implications: We advance the scope of the AKIS concept by accounting for the temporal dynamics of innovation uptake decision-making and adopting multi-level analysis that combines micro (farm) and meso (region) scales.Originality/value: Empirical evidence at the European level, gathered from the common farmer's perspective on the dynamics of farm-level microAKIS and the role played by farm advisory, accounting for diversity of innovations and regional contexts.

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    Authors: Nuria Benavent; Anoop S. Mahajan; Qinyi Li; Carlos A. Cuevas; +30 Authors

    This study received funding from the European Research Council Executive Agency under the European Union’s Horizon 2020 Research and Innovation Program (project ERC‐2016‐COG 726349 CLIMAHAL and ERC-2016-STG 714621 GASPARCON) and the European Commission via the EMME-CARE project and was supported by the Consejo Superior de Investigaciones Científicas of Spain. This work was supported by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement no. 856612 and the Academy of Finland (project no. 334514). The Indian Institute of Tropical Meteorology is funded by the Ministry of Earth Sciences, Government of India. Ozone, CO, CH4 and AMS measurements were funded by the Swiss National Science Foundation (grant 200021_188478), the Swiss Polar Institute and U.S. National Science Foundation grants 1914781 and 1807163. J.S. holds the Ingvar Kamprad chair for extreme environments research, sponsored by Ferring Pharmaceuticals. Data reported in this manuscript were produced as part of the international MOSAiC expedition with tag MOSAiC20192020, with activities supported by Polarstern expedition AWI-PS122_00. H.S. was funded by the European ERA-PLANET projects iGOSP and iCUPE (consortium agreement no. 689443 for both projects). We thank FORMAS and the Swedish Polar Research Secretariat for support. We gratefully acknowledge funding by the Deutsche Forschungsgemeinschaft (project no. 268020496 – TRR 172) within the Transregional Collaborative Research Center ‘ArctiC Amplification: Climate Relevant Atmospheric and SurfaCe Processes, and Feedback Mechanisms (AC)3’ in subproject C03. We thank I. Bourgeois (NOAA/CIRES) for providing the ATom NOx data. Unlike bromine, the effect of iodine chemistry on the Arctic surface ozone budget is poorly constrained. We present ship-based measurements of halogen oxides in the high Arctic boundary layer from the sunlit period of March to October 2020 and show that iodine enhances springtime tropospheric ozone depletion. We find that chemical reactions between iodine and ozone are the second highest contributor to ozone loss over the study period, after ozone photolysis-initiated loss and ahead of bromine. 6 pags., 2 figs. Peer reviewed

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    Authors: Ebun Akinsete; Phoebe Koundouri; Xanthi Kartala; Nikos Englezos; +6 Authors

    Rapid population growth along with increased rates of economic growth around the globe are placing valuable natural resources, water in particular, under unprecedented stress; this in turn drives the pursuit of innovative tools to support integrated Water-Energy-Food (WEF) nexus management. This paper presents a framework for the integrated management of the WEF nexus, which brings together four separate models that address the less well-examined socio-anthropological aspects of the nexus. The proposed framework provides insight into the human element as part of the wider ecosystem in terms of socio-cultural and economic activities, the laws and policies that govern these activities, as well as their potential socio-economic impacts and consequences. This paper outlines each individual model, before going on to present a conceptual framework for the integration of the various models for the purpose of supporting more robust decision-making. The framework, which is grounded in systems thinking, adopts the principles of sustainable development as structural foci in order to position the various models in relation to one another; harmonizing their inputs as well as outputs.

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    Frontiers in Water
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