/ SMURBS - SMart URBan Solutions for air quality, disasters and city growth
22 solutions addressing air quality and health currently implemented in 23 cities
AREA
Urban air quality (including health impacts)
STAGE OF DEVELOPMENT
END USERS
Stakeholders from academia, industry, citizens, organizations and authorities
DESCRIPTION
There are 22 solutions addressing air quality and health with different foci:
- Advancing in situ monitoring networks
- Modelling solutions targeting the city scale
- Addressing AQ impacts on health
- Utilizing innovative platforms and IoT
They provide
-Support for decision making, e g
- identification of AQ hot spots and proposed mitigation measures
- feedback on effects of source-targeted mitigation policies
- a dissemination and communication tool for tourist operators and local administrations
- cost-effective mitigation measures for PM pollution
- quantitative evaluation of current and planned mitigation measures
-Personalized AQ information and alerts
-Spatially resolved exposure concentrations
-Methodologies for incorporating smart sensors in monitoring networks
-Tools for citizen engagement and crowdsourcing
-Present situation and forecasts of AQ and health risks
Examples of smart aspects of solutions:
- smart dissemination through web and smartphone app, crowdsourcing, integration of fragmented EO information and provision of tailored and comprehensible indices
- Utilization and fusion of AQ data from a state-of-the-art satellite, integration to regular monitoring
- Real time and forecast air quality and health risk information for citizens utilizing concentration-response functions from epidemiological studies
OBJECTIVES
Support decision making, citizen engagement
DEMO LINK
13 solutions addressing urban growth, including migration aspects currently implemented in 7 cities
AREA
Urban growth, including migration aspects
STAGE OF DEVELOPMENT
END USERS
Stakeholders from academia, industry, citizens, organizations and authorities
DESCRIPTION
There are 13 solutions addressing urban growth, including migration aspects, with different foci:
- Assessing suitability of migrant host areas
- Urban classification and detection of changes
- Supporting city planning and mitigation of health impacts due to extreme weather
They provide (among others)
- Identification of new built-up areas with a pixel resolution of 5m within the urban fabric
- Identification of illegal building in post-fire situations
- Direct or indirect monitoring of the ratio of land consumption rate to population growth rate (SDG indicator 11.3.1)
- Calculation of urban indicators, e.g. annual percentage increase in soil, consumption, loss of agricultural, natural and semi-natural areas
- Support for city authorities and relevant stakeholders for changes and urban development monitoring
- Protection of citizens and management of extreme temperature events
- Baseline establishment of current city resilience to migration processes, enabling future resilience scenario analysis also involving other policy sectors, such as transportation infrastructure, land-use planning, education and employment of migrants
Smart aspects include:
- Integration of EO data and socio-economic data
- Weighted indicators based on local policy prioritization
- Online and open access to all products
- Automated analysis that enables extraction of class trends in large areas
- Tailored Multiple Hazards Risk Assessment based on the specific needs of the relevant end-users.
- High resolution data that is beyond the usual modus operandi in current city authorities' approach
OBJECTIVES
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DEMO LINK
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Six (6) solutions involve disaster management and are currently implemented in 5 cities
AREA
Natural and manmade urban and periurban disasters
STAGE OF DEVELOPMENT
END USERS
Stakeholders from academia, industry, citizens, organizations and authorities
DESCRIPTION
Six (6) solutions involve disaster management addressing different foci:
- Pre-, during and post-flood management
- Mapping urban infrastructure for disasters' management
- Monitoring urban land deformation
- Urban and peri-urban fires detection and management
They provide (among others):
- Flood risk management plans
- Urban and peri-urban flood early warning system using operational crowdsourced data collection platform
- Support for decisions e g
o local / regional authorities during and immediately after disaster (floods, fires, extreme winds with MMS and UAV swarms)
o disaster preparedness via mapping of critical urban infrastructure and disaster scenario simulation
o preparedness for peri-urban fire management by identifying best waiting positions for first responders, allocating firefighting stations per vehicle type, calculating least cost path and travel time
- Industrial infrastructure for accidents pre- and post- assessment
- Alerts to specific networks
Smart aspects include:
- Near real time information during the disaster for floods management and monitoring
- Synergy of a wide variety of EO platforms, including crowdsourcing
- User friendly frontend for stakeholders provided via web-portal
- Dedicated crowdsourcing by providing fire fighters with GPS devices.
- A web portal based on open-source and free software delivering information to relevant public services and public organizations
OBJECTIVES
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DEMO LINK
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Latest publications (2019 and beyond)
-Hussein, T., Li, X., Al-Dulaimi, Q., Daour, S., Atashi, N., Viana, M., Alastuey, A., Sogacheva, L,. Arar, S., Al-Hunaiti, A. and Petäjä, T. (2020). Particulate Matter Concentrations in a Middle Eastern City – An Insight to Sand and Dust Storm Episodes. Aerosol Air Qual. Res. 20: 2780–2792. https://doi.org/10.4209/aaqr.2020.05.0195
-Zaidan, Martha A., Ola Surakhi, Pak L. Fung, and Tareq Hussein. (2020). Sensitivity Analysis for Predicting Sub-Micron Aerosol Concentrations Based on Meteorological Parameters. Sensors 20, no. 10: 2876. https://doi.org/10.3390/s20102876
-Fung, Pak L., Martha A. Zaidan, Salla Sillanpää, Anu Kousa, Jarkko V. Niemi, Hilkka Timonen, Joel Kuula, Erkka Saukko, Krista Luoma, Tuukka Petäjä, Sasu Tarkoma, Markku Kulmala, and Tareq Hussein. (2020). Input-Adaptive Proxy for Black Carbon as a Virtual Sensor. Sensors 20, no. 1: 182. https://doi.org/10.3390/s20010182
-Hussein, Tareq, Nahid Atashi, Larisa Sogacheva, Simo Hakala, Lubna Dada, Tuukka Petäjä, and Markku Kulmala. (2020). Characterization of Urban New Particle Formation in Amman—Jordan. Atmosphere 11, no. 1: 79. https://doi.org/10.3390/atmos11010079
-Hussein, Tareq, Lubna Dada, Simo Hakala, Tuukka Petäjä, and Markku Kulmala. (2019). Urban Aerosol Particle Size Characterization in Eastern Mediterranean Conditions. Atmosphere 10, no. 11: 710. https://doi.org/10.3390/atmos10110710
-Hussein, Tareq, Shatha S.A. Saleh, Vanessa N. dos Santos, Brandon E. Boor, Antti J. Koivisto, and Jakob Löndahl. (2019). Regional Inhaled Deposited Dose of Urban Aerosols in an Eastern Mediterranean City. Atmosphere 10, no. 9:530. https://doi.org/10.3390/atmos10090530
-Hussein, Tareq, Shatha S.A. Saleh, Vanessa N. dos Santos, Huthaifah Abdullah, and Brandon E. Boor (2019). Black Carbon and Particulate Matter Concentrations in Eastern Mediterranean Urban Conditions: An Assessment Based on Integrated Stationary and Mobile Observations. Atmosphere 10, no. 6: 323. https://doi.org/10.3390/atmos10060323
-Zaidan, Martha A., Lubna Dada, Mansour A. Alghamdi, Hisham Al-Jeelani, Heikki Lihavainen, Antti Hyvärinen, and Tareq Hussein. (2019). Mutual Information Input Selector and Probabilistic Machine Learning Utilisation for Air Pollution Proxies. Applied Sciences 9, no. 20: 4475. https://doi.org/10.3390/app9204475
-Hussein, T., Sogacheva, L. and Petäjä, T. (2018). Accumulation and Coarse Modes Particle Concentrations during Dew Formation and Precipitation. Aerosol Air Qual. Res. 18: 2929-2938. https://doi.org/10.4209/aaqr.2017.10.0362
-Zaidan, Martha A., Darren Wraith, Brandon E. Boor, and Tareq Hussein. (2019). Bayesian Proxy Modelling for Estimating Black Carbon Concentrations using White-Box and Black-Box Models. Applied Sciences 9, no. 22: 4976. https://doi.org/10.3390/app9224976
-Johanna Amalia Robinson, David Kocman, Orestis Speyer & Evangelos Gerasopoulos (2021) Meeting volunteer expectations — a review of volunteer motivations in citizen science and best practices for their retention through implementation of functional features in CS tools, Journal of Environmental Planning and Management, DOI: 10.1080/09640568.2020.1853507
-Bassani, C., Vichi, F., Esposito, G. et al. Nitrogen dioxide reductions from satellite and surface observations during COVID-19 mitigation in Rome (Italy). Environ Sci Pollut Res (2021). https://doi.org/10.1007/s11356-020-12141-9
-Sulc. L., Cupr P., Exposure to chemicals and their health risks in human population, RECETOX Ph.D. conference, 2020. View file
-Grivas, G., Athanasopoulou, E., Kakouri, A., Bailey, J., Liakakou, E., Stavroulas, I., Kalkavouras, P.,Bougiatioti, A., Kaskaoutis, D.G., Ramonet, M.,Mihalopoulos, N., Gerasopoulos, E. Integrating in situ Measurements and City Scale Modelling to Assess the COVID–19 Lockdown Effects on Emissions and Air Quality in Athens, Greece. Atmosphere, 11, 1174.https://doi.org/10.3390/atmos11111174, 2020.
-Furger, M., Rai, P., Slowik, J.G., Cao, J., Visser, S., Baltensperger, U., Prévôt, André.S.H., Automated alternating sampling of PM10 and PM2.5 with an online XRF spectrometer, Atmospheric Environment: X (2020), doi: https://doi.org/10.1016/j.aeaoa.2020.100065
-Tobler, A., Bhattu, D., Canonaco, F., Lalchandani, V., Shukla, A., Thamban, N., Mishra, S., Tiwari, S., Mocnik, G., Baltensperger, U., Tripathi, S. N., Slowik, J. G., and Prévôt , A. S. H.: Chemical characterization of PM2.5and source apportionment of organic aerosol in New Delhi, India, Sci. Total Environ.,745, 140924, https://doi.org/10.1016/j.scitotenv.2020.140924, 2020a
-Tobler, A. K., Skiba, A., Wang, D. S., Croteau, P., Styszko, K., Nęcki, J., Baltensperger, U., Slowik, J. G., and Prévôt, A. S. H.: Improved chloride quantification in quadrupole aerosol chemical speciation monitors (Q-ACSMs), Atmos. Meas. Tech., 13, 5293–5301, https://doi.org/10.5194/amt-13-5293-2020, 2020b.
-Tong, Y., Pospisilova, V., Qi, L., Duan, J., Gu, Y., Kumar, V., Rai, P., Stefenelli, G., Wang, L., Wang, Y., Zhong, H., Baltensperger, U., Cao, J., Huang, R.-j., Prevot, A. S. H., and Slowik, J. G.: Quantification of solid fuel combustion and aqueous chemistry contributions to secondary organic aerosol during wintertime haze events in Beijing, Atmos. Chem. Phys. Discuss. 10.5194/acp-2020-835, 2020. (under review)
-Canonaco et al., A new method for long-term source apportionment with time-dependent factor profiles and uncertainty assessment using SoFi Pro: application to one y
/ GEO-essential - Essential Variables workflows for resource efficiency and environmental management
Special issue: Towards integrated essential variables for sustainability
AREA
SDGs
STAGE OF DEVELOPMENT
END USERS
Earth Observation and environmental policy experts
DESCRIPTION
GEOEssential has put forward a new EVs general framework. The Earth System can be decomposed in the Atmosphere characterized by the Essential Climate Variables (ECV), the Hydrosphere characterized by the Essential Water Variables (EWV) and Essential Ocean Variables (EOV), the Biosphere characterized by the Essential Biodiversity Variables (EBV) and the Geosphere characterized by Essential Geosphere Variables. All these systems provide services to humanity through Ecosystem Services (ES), Climate Services (CS), Water Services (WS) and Geological Services (GS). The term ‘Service’ can be understood as a service for human well-being as defined in the context of Ecosystem Services, but also as an information service as defined for Climate Services. Through its services, the Earth System provides an ensemble of services called Natural Capitals (NC) to the Socio-Economic System that can be decomposed into Urban environment, Energy and Minerals, Health, Agriculture, Transport and Infrastructure. For each one of these sectors corresponding broadly to GEO Societal Benefit Areas (SBAs), we could define essential variables. The Socio-Economic System has, in turn, societal impacts on the Earth System modifying the quantity and quality of the natural capitals on which it depends. Eventually, the interaction between both systems could be characterized in terms of their imbalances of sustainable goals.
OBJECTIVES
Measuring the achievement of a sustainable development requires the integration of various data sets and disciplines describing bio-physical and socio-economic conditions. These data allow characterizing any location on Earth, assessing the status of the environment at various scales (e.g. national, regional, global), understanding interactions between different systems (e.g. atmosphere, hydrosphere, biosphere, geosphere), and modeling future changes. The Group on Earth Observations (GEO) was established in 2005 in response to the need for coordinated, comprehensive, and sustained observations related to the state of the Earth. GEO’s global engagement priorities include supporting the UN 2030 Agenda for Sustainable Development, the Paris Agreement on Climate, and the Sendai Framework for Disaster Risk Reduction. A proposition is made for generalizing and integrating the concept of EVs across the Societal Benefit Areas of GEO and across the border between Socio- Economic and Earth systems EVs. The contributions of the European Union projects ConnectinGEO and GEOEssential in the evaluation of existing EV classes are introduced. Finally, the main aim of the 10 papers of the special issue is shortly presented and mapped according to the proposed typology of SBA-related EV classes.
DEMO LINK
GEOEssential web site
AREA
SDGs
STAGE OF DEVELOPMENT
END USERS
Earth Observation experts interested by the outputs of the project; Project partners
DESCRIPTION
GEOΕssential web presence has been developed using the open source solution, Wordpress CMS (content management system) and takes advantage of the open community support that guarantees the longevity and future proof of use, update and sustainability, which is an important requirement from the European Commission. www.GEOEssential.eu displays and handles a modern design architecture which is optimized to work on multiple devices, browsers, and systems using a customized fully responsive free theme. The website is highly reliable with image optimization of its elements and it supports the scalability that provides fast loading of the content to user. It is optimized for search engines tools and integrates connectivity and sharing with social media networking sites. Security tools and supporting plugins are setup and used to extend functionality and maintenance and to enhance the reporting activity and traffic measurement of the website use.
OBJECTIVES
The objective of the website is to give access to all the activities and outputs of the project:
- List of deliverables: https://www.geoessential.eu/progress/deliverables/
- List of publications: http://www.geoessential.eu/publications/
- List of workflows: http://www.geoessential.eu/sdg-showcases/
- List of partners: http://www.geoessential.eu/partners/
DEMO LINK
Open Data Cube with the example of the Swiss Data Cube
AREA
SDGs
STAGE OF DEVELOPMENT
END USERS
EO expert, National research institutions, Governmental agencies
DESCRIPTION
The Swiss Data Cube (SDC) is a tera-scale analytical cloud-based platform offering access to 36 years (e.g., 1984 to present days) of satellite data from Landsat 5-7-8, Sentinel-1, and Sentinel-2 sensors. The SDC facilitates national-scale analyses of large volume of spatially aligned and consistently calibrated satellite EO data. It is an initiative implemented and operated by the United Nations Environment Programme (UNEP)/Global Resource Information Database (GRID)-Geneva in partnership with the University of Geneva, the University of Zurich, and the Swiss Federal Institute for Forest, Snow and Landscape Research (WSL). The SDC is supported by the Federal Office for the Environment (FOEN) and is aiming to contribute to its environmental and reporting mandate while at the same time enabling any Swiss institutions to benefit from the information power of satellite EO data. The archive is updated on a daily basis and contains approximately 12,500 scenes corresponding to a total volume of 5 TB and more than 1000 billion observations/pixels.
OBJECTIVES
The objective of the SDC is to deliver unique and near real-time capabilities to access and analyse EO data, enabling more effective responses to problems of national significance. It can provide the long-term and baseline data required to determine trends, quantify past and present changes, and inform future decisions. This near real-time information can be readily used as an evidence base for the design, implementation and evaluation of policies, programs and regulation, as well as for developing policy advice. Ultimately, it can support the Swiss government for environmental monitoring and reporting commitments, while enabling national scientific institutions to benefit from satellite EO data for research and innovation. Indeed, this technology is significantly improving the way non-expert users can work with EO data ready for analysis; for example, it reduces the time and scientific knowledge required to handle satellite imagery by automating the complex tasks of searching, downloading and pre-processing scenes, while at the same time facilitating the processing of large amount of satellite data.
DEMO LINK
Latest publications (2019 and beyond)
2021
- Giuliani, G., Cazeaux, H., Burgi, P.-Y., Poussin, C., Richard, J.-P. and Chatenoux, B., (2021). SwissEnvEO: A FAIR National Environmental Data Repository for Earth Observation Open Science. Data Science Journal, 20(1), p.22.http://doi.org/10.5334/dsj-2021-022
- Jagdhuber, T; Montzka, C; Lopez-Martinez, C; Baur, MJ; Link, M; Piles, M; Das, NN; Jonard, F, (2021). Estimation of Vegetation Structure Parameters From SMAP Radar Intensity Observations, https://doi.org/10.1109/TGRS.2020.2991252
- Rana, FM; Adamo, M, (2021). Multi-Scale LG-Mod Analysis for a More Reliable SAR Sea Surface Wind Directions Retrieval, https://doi.org/10.3390/rs13030410
- De Marchi, S; Marchetti, F; Perracchione, E; Poggiali, D, (2021). Multivariate approximation at fake nodes, https://doi.org/10.1016/j.amc.2020.125628
- Ibrahim E., Jinghyi J., Lema L., Barnabé P., Giuliani G., Lacroix P., Pirard E. ,(2021). Cloud and cloud-shadow detection for applications in mapping small-scale mining in Colombia using Sentinel-2 imagery. Remote Sensing 13(4), 736
- McIsaac Michael A. , Sanders Eric, Kuester Theres, Aronson, Kristan J., Kyba, Christopher C. M., (2021). The impact of image resolution on power, bias, and confounding. A simulation study of ambient light at night exposure, http://dx.doi.org/10.1097/EE9.0000000000000145
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Zabala, A.; Masó, J.; Bastin, L.; Giuliani, G.; Pons, X. (2021). Geospatial User Feedback: How to Raise Users’ Voices and Collectively Build Knowledge at the Same Time. ISPRS Int. J. Geo-Inf. , 10, 141, https://doi.org/10.3390/ijgi10030141
- Giuliani, G.; Petri, E.; Interwies, E.; Vysna, V.; Guigoz, Y.; Ray, N.; Dickie, I., (2021). Modelling Accessibility to Urban Green Areas Using Open Earth Observations Data: A Novel Approach to Support the Urban SDG in Four European Cities. Remote Sens. 2021, 13, 422, https://doi.org/10.3390/rs13030422
- Bayat, B., Camacho, F., Nickeson, J., Cosh, M., Bolten, J., Vereecken, H., Montzka, C., (2021). Toward operational validation systems for global satellite-based terrestrial essential climate variables. Int. J. Appl. Earth Obs. Geoinf. 95, 102240, https://doi.org/10.1016/j.jag.2020.102240
2020
- N. Kussul et al.,(2020). “Crop monitoring technology based on time series of satellite imagery,” 2020 IEEE 11th International Conference on Dependable Systems, Services and Technologies (DESSERT), pp. 346-350, https://doi.org/10.1109/DESSERT50317.2020.9125031
- N. Kussul, M. Lavreniuk and L. Shumilo, (2020), “Deep Recurrent Neural Network for Crop Classification Task Based on Sentinel-1 and Sentinel-2 Imagery,” IGARSS 2020 – 2020 IEEE International Geoscience and Remote Sensing Symposium, pp. 6914-6917, https://doi.org/10.1109/IGARSS39084.2020.9324699
- Kussul, N., Lavreniuk, M., Kolotii, A., Skakun, S., Rakoid, O., Shumilo, L. A workflow for Sustainable Development Goals indicators assessment based on high-resolution satellite data (2020) International Journal of Digital Earth, 13 (2), pp. 309-321, https://doi.org/ 10.1080/17538947.2019.1610807
- Ibrahim E., Lema L., Barnabé P., Lacroix P., Pirard E. (2020). Small-scale surface mining of gold placers: detection, mapping and temporal analysis through the use of free satellite imagery. International Journal of Applied Earth Observation and Geoinformation 93:102194, https://doi.org/10.3390/rs13040736
- Moomen A., Lacroix P., Bertolotto M., Jensen D.(2020). The Drive towards Consensual Perspectives for Enhancing Sustainable Mining. Resources 9:147 https://doi.org/10.3390/resources9120147
- Aracri G., Caruso A., Folino A. (2020). An ontological model for semantic interoperability within an Earth Observation knowledge base, in “Knowledge Organization at the Interface Proceedings of the Sixteenth International ISKO Conference”, Aalborg, Denmark, in «ADVANCES IN KNOWLEDGE ORGANIZATION», edited by M. Lykke, T. Svarre, M. Skov, D. Martínez-Ávila, Ergon-Verlag, vol. 17, pp. 13-22, http://dx.doi.org/10.5771/9783956507762-13
- CCM.Kyba, A.Ruby, HU.Kuechly, B.Kinzey, N.Miller, J.Sanders, J.Barentine, R. Kleinodt, B. Espey (2020). Direct measurement of the contribution of street lighting to satellite observations of nighttime light emissions from urban areas, https://doi.org/10.1177/1477153520958463
- Inbal Ayalon, Yaeli Rosenberg, Jennifer I.C.Benichou, Celine Luisa D.Campos, Sherry Lyn G.Sayco, Michael Angelou L.Nada, Jake Ivan P.Baquiran, Charlon A.Ligson, Dror Avisar, Cecilia Conaco, Helga U.Kuechly, Christopher C.M.Kyba, Patrick C.Cabaitan, Oren Levy (2020). Coral Gametogenesis Collapse under Artificial Light Pollution, https://doi.org/10.1016/j.cub.2020.10.039
- Giuliani, G., Egger, E., Italiano, J., Poussin, C., Richard, J.-P., Chatenoux, (2020). Essential Variables for Environmental Monitoring: What are the Possible Contributions of Earth Observation Data Cubes? https://doi.org/10.3390/data5040100
- Travis Longcore, Dan Duriscoe, Martin Aubé, Andreas Jechow, Christopher C. M. Kyba, Kellie L. Pendoley (2020). Commentary: Brightness of the Night Sky Affects Loggerhead (Caretta caretta) Sea Turtle Hatchling Misorientation but Not Nest Site Selection, https://doi.org/10.3389/fmars.2020.00706
- Saverio Vicario, Maria Adamo, Domingo Alcaraz-Segura, Cristina Tarantino (2020). Bayesian Harmonic Modelling of Sparse and Irregular Satellite Remote Sensing Time Series of Vegetation Indexes: A Story of Clouds and Fires, https://doi.org/10.3390/rs12010083
- John C.Barentine, František Kundracik, Miroslav Kocifaj, Jessie C.Sanders, Gilbert A.Esquerdo, Adam M.Dalton, Bettymaya Foott, AlbertGrauer, Scott Tucker, Christopher C.M.Kyba (2020). Recovering the city street lighting fraction from skyglow measurements in a large-scale municipal dimming experiment, https://doi.org/10.1016/j.jqsrt.2020.107120
- Jacqueline Coesfeld, Theres Kuester, Helga U. Kuechly, Christopher C. M. Kyba, (2020). Reducing Variability and Removing Natural Light from Nighttime Satellite Imagery: A Case Study Using the VIIRS DNB, https://www.mdpi.com/1424-8220/20/11/3287
- Alejandro Sanchez de Miguel, Christopher C. M. Kyba, Jaime Zamorano, Jesús Gallego, Kevin J. Gaston, (2020). The nature of the diffuse light near cities detected in nighttime satellite imagery, https://doi.org/10.1038/s41598-020-64673-2
- Andreas Christopher C.M.Kyba, FranzHölker, 2020). Mapping the brightness and color of urban to rural skyglow with all-sky photometry, https://doi.org/10.1016/j.jqsrt.2020.106988
- Kai Pong Tong, Christopher C.M.Kyba, Georg Heygster, Helga U.Kuechly, Justus Notholt, Zoltn Kollth, (2020). Angular distribution of upwelling artificial light in Europe as observed by Suomi–NPP satellite, https://doi.org/10.1016/j.jqsrt.2020.107009
- Christopher C. M. Kyba, Jeff Conrad, Tom Shatwell, (2020). Lunar illuminated fraction is a poor proxy for moonlight exposure, https://doi.org/10.1038/s41559-020-1096-7
- Giuliani G., Mazzetti P., Santoro M., Nativi S., Bemmelen J.V., Colangeli G., Lehmann A., (2020). Knowledge generation using satellite earth observations to support sustainable development goals (SDG): A use case on Land degradation, https://doi.org/10.1016/j.jag.2020.102068
- Giuliani G., Chatenoux B., Benvenuti A., Lacroix P., Santoro M., Mazzetti P. (2020). Monitoring Land Degradation at national level using satellite Earth Observation time-series data to support SDG15 – Exploring the potential of Data Cube, Big Earth Data
https://www.tandfonline.com/doi/full/10.1080/20964471.2020.1711633 - Christopher C.M. Kyba, Sara B. Pritchard, A. Roger Ekirch, Adam Eldridge, Andreas Jechow, Christine Preiser, Dieter Kunz, Dietrich Henckel, Franz Hölker, John Barentine, Jørgen Berge, Josiane Meier, Luc Gwiazdzinski, Manuel Spitschan, Mirik Milan, Susanne Bach, Sibylle Schroer, Will Straw (2020). Night Matters—Why the Interdisciplinary Field of “Night Studies” Is Needed, https://doi.org/10.3390/j3010001
- Gregory Giuliania, Bruno Chatenoux, Thomas Piller, Frédéric Moser, Pierre Lacroix (2020). Data Cube on Demand (DCoD): Generating an earth observation Data Cube anywhere in the world
https://doi.org/10.1016/j.jag.2019.102035 - Wellmann, T; Lausch, A; Andersson, E; Knapp, S; Cortinovis, C; Jache, J; Scheuer, S; Kremer, P; Mascarenhas, A; Kraemer, R; Haase, A; Schug, F; Haase, D, (2020). Remote sensing in urban planning: Contributions towards ecologically sound policies? https://doi.org/10.1016/j.landurbplan.2020.103921
- Lausch, A; Schaepman, ME; Skidmore, AK; Truckenbrodt, SC; Hacker, JM; Baade, J; Bannehr, L; Borg, E; Bumberger, J; Dietrich, P; Glasser, C; Haase, D; Heurich, M; Jagdhuber, T; Jany, S; Kronert, R; Moller, M; Mollenhauer, H; Montzka, C; Pause, M; Rogass, C; Salepci, N; Schmullius, C; Schrodt, F; Schutze, C; Schweitzer, C; Selsam, P; Spengler, D; Vohland, M; Volk, M; Weber, U; Wellmann, T; Werban, U; Zacharias, S; Thiel, C (2020). Linking the Remote Sensing of Geodiversity and Traits Relevant to Biodiversity-Part II: Geomorphology, Terrain and Surfaces https://doi.org/10.3390/rs12223690
- Bachini, E; Putti, M (2020). Geometrically intrinsic modeling of shallow water flows https://doi.org/10.1051/m2an/2020031
- Buhmann, MD; de Marchi, S; Perracchione, E. (2020). Analysis of a new class of rational RBF expansions https://doi.org/10.1093/imanum/drz015
- Campagna, R; Cuomo, S; De Marchi, S; Perracchione, E; Severino, G, (2020). A stable meshfree PDE solver for source-type flows in porous media https://doi.org/10.1016/j.apnum.2019.08.015
- Facca, E; Daneri, S; Cardin, F; Putti, M (2020). Numerical Solution of Monge-Kantorovich Equations via a Dynamic Formulation https://doi.org/10.1007/s10915-020-01170-8
- Ritonja, J; McIsaac, MA; Sanders, E; Kyba, CCM; Grundy, A; Cordina-Duverger, E; Spinelli, JJ; Aronson, KJ (2020). Outdoor light at night at residences and breast cancer risk in Canada https://doi.org/10.1007/s10654-020-00610-x
- Honeck, E; Moilanen, A; Guinaudeau, B; Wyler, N; Schlaepfer, MA; Martin, P; Sanguet, A; Urbina, L; von Arx, B; Massy, J; Fischer, C; Lehmann, A (2020). Implementing Green Infrastructure for the Spatial Planning of Peri-Urban Areas in Geneva, Switzerland https://doi.org/10.1038/s41559-020-1096-7
- Lehmann, A; Maso, J; Nativi, S; Giuliani, G (2020). Towards integrated essential variables for sustainability https://doi.org/10.1080/17538947.2019.1636490
- De Marchi, S; Marchetti, F; Perracchione, E; Poggiali, D (2020). Polynomial interpolation via mapped bases without resampling https://doi.org/10.1016/j.cam.2019.112347
- De Marchi, S; Erb, W; Marchetti, F; Perracchione, E; Rossini, M (2020). SHAPE-DRIVEN INTERPOLATION WITH DISCONTINUOUS KERNELS: ERROR ANALYSIS, EDGE EXTRACTION, AND APPLICATIONS IN MAGNETIC https://doi.org/10.1137/19M1248777
- De Marchi, S; Marchetti, F; Perracchione, E (2020). Jumping with variably scaled discontinuous kernels (VSDKs) https://doi.org/10.1007/s10543-019-00786-z
- Soudzilovskaia, NA; van Bodegom, PM; Terrer, C; van’t Zelfde, M; McCallum, I; McCormack, ML; Fisher, JB; Brundrett, MC; de Sa, NC; Tedersoo, L (2020). Global mycorrhizal plant distribution linked to terrestrial carbon stocks https://doi.org/10.1038/s41467-019-13019-2
- Park, CH; Montzka, C; Jagdhuber, T; Jonard, F; De Lannoy, G; Hong, J; Jackson, TJ; Wulfmeyer, V (2020). A Dielectric Mixing Model Accounting for Soil Organic Matter https://doi.org/10.2136/vzj2019.04.0036
- Shelestov, A; Kolotii, A; Borisova, T; Turos, O; Milinevsky, G; Gomilko, I; Bulanay, T; Fedorov, O; Shumilo, L; Pidgorodetska, L; Kolos, L; Borysov, A; Pozdnyakova, N; Chunikhin, A; Dudarenko, M; Petrosian, A; Danylevsky, V; Miatselskaya, N; Choliy, V (2020). Essential variables for air quality estimation https://doi.org/10.1080/17538947.2019.1620881
- McCallum, I; Montzka, C; Bayat, B; Kollet, S; Kolotii, A; Kussul, N; Lavreniuk, M; Lehmann, A; Maso, J; Mazzetti, P; Mosnier, A; Perracchione, E; Putti, M; Santoro, M; Serral, I; Shumilo, L; Spengler, D; Frit, S (2020). Developing food, water and energy nexus workflows https://doi.org/10.1080/17538947.2019.1626921
- de Paula, MD; Gimenez, MG; Niamir, A; Thurner, M; Hickler, T (2020). Combining European Earth Observation products with Dynamic Global Vegetation Models for estimating Essential Biodiversity Variables https://doi.org/10.1080/17538947.2019.1597187
- Lehmann, A; Nativi, S; Mazzetti, P; Maso, J; Serral, I; Spengler, D; Niamir, A; McCallum, I; Lacroix, P; Patias, P; Rodila, D; Ray, N; Giuliani, G (2020). GEOEssential – mainstreaming workflows from data sources to environment policy indicators with essential variables https://doi.org/10.1080/17538947.2019.1585977
2019
- Shahrokhabadi, MA; Neisy, A; Perracchione, E; Polato, M (2019). Learning with subsampled kernel-based methods: Environmental and financial applications https://doi.org/10.14658/pupj-drna-2019-1-3
- Salzano, R; Salvatori, R; Valt, M; Giuliani, G; Chatenoux, B; Ioppi, L (2019). Automated Classification of Terrestrial Images: The Contribution to the Remote Sensing of Snow Cover https://doi.org/10.3390/geosciences9020097
- de Miguel, AS; Bara, S; Aube, M; Cardiel, N; Tapia, CE; Zamorano, J; Gaston, KJ (2019). Evaluating Human Photoreceptoral Inputs from Night-Time Lights Using RGB Imaging Photometry https://doi.org/10.3390/jimaging5040049
- Lausch, A; Baade, J; Bannehr, L; Borg, E; Bumberger, J; Chabrilliat, S; Dietrich, P; Gerighausen, H; Glasser, C; Hacker, JM; Haase, D; Jagdhuber, T; Jany, S; Jung, A; Karnieli, A; Kraemer, R; Makki, M; Mielke, C; Moller, M; Mollenhauer, H; Montzka, C; Pause, M; Rogass, C; Rozenstein, O; Schmullius, C; Schrodt, F; Schron, M; Schulz, K; Schutze, C; Schweitzer, C; Selsam, P; Skidmore, AK; Spengler, D; Thiel, C; Truckenbrodt, SC; Vohland, M; Wagner, R; Weber, U; Werban, U; Wollschlager, U; Zacharias, S; Schaepman, ME (2019. Linking Remote Sensing and Geodiversity and Their Traits Relevant to Biodiversity-Part I: Soil Characteristics. https://doi.org/10.3390/rs11202356
- Maso, J; Zabala, A; Serral, I; Pons, X (2019). A Portal Offering Standard Visualization and Analysis on top of an Open Data Cube for Sub-National Regions: The Catalan Data Cube Example https://doi.org/10.3390/data4030096
- Levin, N; Kyba, CCM; Zhang, Q (2019). Remote Sensing of Night Lights-Beyond DMSP https://doi.org/10.3390/rs11121472
- Ambrosone M., Giuliani G., Chatenoux B., Rodila D., Lacroix P. (2019). Definition of candidate Essential Variables for the monitoring of mineral resources exploitation, Geo-spatial Information Science
https://www.tandfonline.com/doi/full/10.1080/10095020.2019.1635318 - Dantas de Paula, M., Gómez-Giménez, M., Niamir, A., Thurner, M., Hickler, T., (2019). The Potential of European earth observation products for driving and evaluating processed-based ecosystem models. International Journal of Digital Earth. https://doi.org/10.1016/j.scitotenv.2019.02.150
- Espinosa M.T., Giuliani G., Ray N. (2019). Reviewing the discoverability and accessibility to data and information products linked to Essential Climate Variables, International Journal of Digital Earth
https://www.tandfonline.com/doi/full/10.1080/17538947.2019.1620882 - Fabio Michele Rana, Maria Adamo, Richard Lucas, Palma Blonda, Sea surface wind retrieval in coastal areas by means of Sentinel-1 and numerical weather prediction model data, Remote Sensing of Environment, Volume 225, (2019), Pages 379-391, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2019.03.019
- Giuliani G., Maso J., Mazzetti P., Nativi S., Zabala A. (2019). Paving the way to increased interoperability of Earth Observations Data Cube. Data 4(3):113
https://www.mdpi.com/2306-5729/4/3/113 - Gómez-Giménez, M., Dantas de Paula, M., Niamir, A., and Hickler, T. “Process-Based Models and the Copernicus Programme Contribute to Monitoring Essential Biodiversity Variables and Ecosystem Function” in proceedings of Living Planet Symposium, 13-17 May 2019, Milan, Italy.
- Hyde, Emilee; Kyba, Christopher (2019). Analysis boundaries and lighting trends (2012-2018) for selected International Dark Sky Places. V. 1.0. GFZ Data Services. http://doi.org/10.5880/GFZ.1.4.2019.002
- Jechow A., Hölker F., Kyba C., Using all-sky differential photometry to investigate how nocturnal clouds darken the night sky in rural areas, Scientific Reports 9, Article number: 1391 (2019). https://www.nature.com/articles/s41598-018-37817-8.
- Jechow A., Kyba C.C.M., Hölker F., (2019). Beyond All-Sky: Assessing Ecological Light Pollution Using Multi-Spectral Full-Sphere Fisheye Lens Imaging.
doi.org/10.3390/jimaging5040046 - KolotiI, A., Shelestov, A., Borisova, T., Turos, O., Milinevsky, G., Gomilko, I., Bulanaya, T., Fedorov, O., Pidgorodetska, L., Kolos, L., Borysov, A., Pozdnyakova, N., Chunikhin, A., Dudarenko, M., Petrosian, A., Danylevsky, V., Miatselskaya, N., Choliy, V., (2019). Essential Variables on Air Quality Estimation within ERA-PLANET Project. International Journal of Digital Earth https://doi.org/10.1080/17538947.2019.1620881
- Kabisch, N., Selsam, P., Kirsten, T., Lausch, A., Bumbergerg, J., A multi-sensor and multi-temporal remote sensing approach to detect land cover change dynamics in heterogeneous urban landscapes, Elsevier Ecological Indicators, Volume 99, April 2019, Pages 273-282, https://doi.org/10.1016/j.ecolind.2018.12.033
- N. Kussul, M. Lavreniuk, L. Shumilo and A. Kolotii, “Nexus Approach for Calculating SDG Indicator 2.4.1 Using Remote Sensing and Biophysical Modeling,” IGARSS 2019 – 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019, pp. 6425-6428, https://doi.org/10.1109/IGARSS.2019.8898549
- Kyba C., Giuliani G. Franziskakis F., Tockner T., Lacroix P. (2019). Artisanal and small-scale mining sites in the Democratic Republic of the Congo are not associated with nighttime light emissions, J2(2):152-16 https://doi.org/10.3390/rs13040736
- Kyba C., Spitschan M, Comment on ‘Domestic light at night and breast cancer risk: a perspective analysis of 105000 UK women in the Generations Study’, British Journal of Cancer, 120, 276-277 (2019), https://www.nature.com/articles/s41416-018-0203-x.
- Lacroix P., Moser F., Benvenuti A., Piller T., Jensen D., Petersen I., Planque M., Ray N.,m (2019). MapX: an open geospatial platform to manage, analyse and visualise data on natural resources and the environment, SoftwareX 9: 77-84 https://doi.org/10.1016/j.softx.2019.01.002
- Lavreniuk, M., Kussul, N., Kolotii, A., Skakun, S., Rakoid, O., Shumilo, L., (2019). A workflow for Sustainable Development Goals Indicators Assessment Based on High Resolution Satellite Data, International Journal of Digital Earth. https://doi.org/10.1080/17538947.2019.1610807
- * Masó, J., Serral, I., Domingo-Marimon, C. and Zabala, A., (2019). Earth observations for sustainable development goals monitoring based on essential variables and driver-pressure-state-impact-response indicators, International Journal of Digital Earth. https://doi.org/10.1080/17538947.2019.1576787
- McCallum, I., Fritz, S., Kollet, S., Kolotii, A., Kussul, N., Lavreniuk, M., Lehmann, A., Maso, J., Montzka, C., Mosnier, A., Perracchione, E., Putti, M., Serral, I., Shumilo, L., Spengler, D., Santoro, M., Mazzetti, P., (2019). Addressing the food water energy nexus with Earth observation International Journal of Digital Earth. https://doi.org/10.1080/17538947.2019.1626921
- Miranda Espinosa, M.T., Giuliani, G., Ray, N., (2019). Essential Climate Variables: Reviewing the accessibility to data and information product. International Journal of Digital Earth. https://doi.org/10.3389/fenvs.2019.00023
- Moomen A., Bertolotto M., Lacroix P., Jensen D.(2019). Exploring Spatial Symbiosis of Agriculture and Mining for Sustainable Development in Northwest Ghana. IEEE 8th International Conference on Agro-Geoinformatics (Agro-Geoinformatics). Istanbul, Turkey, 1:6 https://doi.org/10.1109/Agro-Geoinformatics.2019.8820500
- Moomen A., Jensen D., Lacroix P., Bertolotto M. (2019). Assessing the Policy Adoption and Impact of Geoinformation for enhancing Sustainable Mining in Africa. Journal of Cleaner Production, 241:118361 https://doi.org/10.1016/j.jclepro.2019.118361
- Moomen A., Bertolotto M., Lacroix P., Jensen D.Inadequate Adaptation of Geospatial Information for Sustainable Mining towards Agenda 2030 Sustainable Development Goals. (2019). Journal of Cleaner Production, 238:11795 https://doi.org/10.1016/j.jclepro.2019.117954
- Nativi, S., Santoro, M., Giuliani, G., Mazzetti, P., (2019). Towards a GEOSS Knowledge Base. International Journal of Digital Earth. https://doi.org/10.1080/17538947.2018.1559367
- Nativi S., Santoro S., Giuliani G., Mazzetti P. (2019) Towards a knowledge base to support global change policy goals, International Journal of Digital Earth https://www.tandfonline.com/doi/full/10.1080/17538947.2018.1559367
- Naz, B.S., Kurtz, W., Montzka, C., Sharples, W., Goergen, K., Keune, J., Gao, H., Springer, A., Franssen, H.J.H., Kollet, S., (2019). Improving soil moisture and runoff simulations at 3 km over Europe using land surface data assimilation. Hydrol. Earth Syst. Sci. 23(1), 277-301. https://doi.org/10.5194/hess-23-277-2019
- Noam Levin, Christopher C.M. Kyba, Qingling Zhang, Alejandro Sánchez de Miguel, Miguel O. Román, Xi Li, Boris A. Portnov, Andrew L. Molthan, Andreas Jechow, Steven D. Miller, Zhuosen Wang,
Ranjay M. Shrestha, Christopher D. Elvidge (2019). Remote sensing of night lights: A review and an outlook for the future
https://doi.org/10.1016/j.rse.2019.111443 - Plag, H.P., Jules-Plag, S., (2019). A Goal-Based Approach to the Identification of Essential Transformation Variables in Support of the Implementation of the 2030 Agenda for Sustainable Development. International Journal of Digital Earth. https://doi.org/10.1080/17538947.2018.1561761
- Ranchin, T., Trolliet, M., Ménard, L., Wald, L., (2019). Which variables are essential for renewable energies? International Journal of Digital Earth. https://doi.org/10.1080/17538947.2019.1679267
- Salzano R., Salvatori R., Valt M., Giuliani G., Chatenoux B., Ioppi L. (2019) The contribution of terrestrial photography to the remote sensing of snow cover, Geosciences 9(2):97, https://www.mdpi.com/2076-3263/9/2/97/htm.
- Sánchez de Miguel A., Kyba C., Aubé M., Zamorano J., Cardiel N., Tapia C., Bennie J., Gaston K., Colour remote sensing of the impact of artificial light at night (I): The potential of the International Space Station and other DSLR-based platforms, Remote Sensing of Environment, V 224, April 2019, pp. 92-103, https://doi.org/10.1016/j.rse.2019.01.035.
- Tassopoulou M., Patias P., Georgoula O., Fragkoulidou V., Use of Satellite Imagery to Compute Essential Variables and SDG Indicators for Monitoring Compliance to Environmental Legislation. A Workflow for Lefkas’ Lagoon, Greece, poster presentation on the Living Planet Symposium 2019 (13-17 May 2019, Milan, Italy), https://lps19.esa.int/NikalWebsitePortal/living-planet-symposium-2019/lps19/Agenda/AgendaItemDetail?id=9963f680-bc10-402f-9c07-aac53ce502ae
- Tassopoulou M., Verde N., Mallinis G., Georgiadis Ch., Kaimaris D., Patias P., Demonstrating the potential of remote sensing to support sustainable development goals implementation: Case studies over Greece, 7th International Conference on Remote Sensing and Geoinformation of Environment (18-21 March, 2019 – Cyprus) https://doi.org/10.1117/12.2533634
- Verde N., Chrysafis I., Mallinis G., Korakis G., Georgiadis Ch., Patias P., Forest species mapping in a mountainous region using Sentinel-2 time-series and an object-based dynamic time warping technique, poster presentation on the Living Planet Symposium 2019 (13-17 May 2019, Milan, Italy)
- Patias, P., Verde, N., Tassopoulou, M., Georgiadis, C., & Kaimaris, D. (2019, June). Essential variables: describing the context, progress, and opportunities for the remote sensing community. In Seventh International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2019) (Vol. 11174, p. 111740C). International Society for Optics and Photonics. https://doi.org/10.1117/12.2533604
/ IGOSP - Integrated Global Observing Systems for Persistent Pollutants
The GOS4M Knowledge Hub
AREA
Development of a transnational environmental observation system in support of European & International Policies
STAGE OF DEVELOPMENT
END USERS
Scientific Community, Policy makers, interested citizens
DESCRIPTION
The GOS4M Knowledge Hub (GOS4M-KH) is an operational integrated multi-model and multi-domain computational platform where scientist, decision-makers and citizens can discover, analyse and understand information for characterizing the linkages between impacts and effect of mercury contamination on Earth system and human health at different geographical and temporal scales. The GOS4M-KH was designed to evaluate the potential effectiveness of measures that nations may undertake to reduce the impact of mercury contamination on human health and ecosystems. The GOS4M-KH provides information on mercury fate, from sources to receptors, and in the future estimate of costs associated with policies. This platform includes analyses of complex chemo-physical atmospheric model outputs, biogeochemical models to simulate processes in the ocean and ecological models to estimate mercury uptake by the trophic net. The first level macro-indicator is the Hg bioaccumulation in biological endpoints, which can be Hg in fish at upper trophic level, the second level is the Hg concentration in ambient air and precipitation samples. Long- term trends of macro-indicators can be analysed to assess the effectiveness of measures on medium-long term time period and eventually estimate associated socio-economic costs.
OBJECTIVES
To analyse and understand information for characterizing the linkages between impacts and effect of mercury contamination on Earth system and human health at different geographical and temporal scales.
DEMO LINK
Data Catalog & Monitoring Network Spatial Data Infrastructure
AREA
Observation system in support of European & International Policies, Data resources, metadata, datasets, QA/QC
STAGE OF DEVELOPMENT
END USERS
Scientific Community, Policy makers, interested citizens
DESCRIPTION
Datasets regarding mercury by topic: Environment; Oceans; Geoscientific information; Climatology, meteorology and atmosphere.
OBJECTIVES
One stop site for data/metadata and overviews of data available, includes data in various formats including maps, as well as links to the Knowledge Hub
DEMO LINK
https://sdi.iia.cnr.it/gos4mcat/srv/eng/catalog.search#/home
iGOSP Thesaurus
AREA
Key-enabling technologies
STAGE OF DEVELOPMENT
END USERS
Multi and inter-disciplinary Communities, Academic area, interested citizens, policy makers
DESCRIPTION
The iGOSP thesaurus is a web-integrated semantic tool aimed at providing a common terminology for metadata, information and knowledge in compliance with the relevant European and international standards in the domain of Earth Observation (EO) systems. Indeed, the creation of this semantic resource is included as an horizontal activity of iGOSP project focusing on achieving a high level of semantic interoperability as well as an harmonized access and sharing of information. It has been designed to manage the terminology variations and the semantic ambiguity (e.g., polysemy, synonymy) and also to support the retrieval process of specific documentation about the field of study under analysis through the use of different terms and their semantic configurations, i.e., hierarchical, synonymous and associative connecting structures as specific indicators of the domain-terminology organization. The thesaurus has been meant to be integrated within the GOS4M-KH interoperable platform in its SKOS-RDF migrated version as representing the starting semantically-organized framework from which to systematize the queries outlines referring to a predetermined structured specific knowledgedomain asset of terms.The thesaurus contains the most representative terms of the projects domain of study which have been retrieved subsequently to the extraction of the information contained in the source corpus, a task carried out through the aid of a semi-automatic software. The selection of the candidate technical terms has been executed by taking into account the TF/IDF statistical filterning measurement as well as by implementing a mapping procedure with the main gold EO knowledge organization systems existing standards (EarTh, Inspire, Agrovoc,GEMET) in order to fix the accuracy of the terminology shared.
OBJECTIVES
To help multi and inter-discilplinary communities of expers in managing the terminology about the enrvironmental pollution through the development of a knowledge organization system, a thesaurus, capable of structuring the technical information and of supporting the retrieval procedure of salient documentation through a highly specific semantic network framework.
DEMO LINK
GMP Data Warehouse (GMP DWH) portal - global release of 2020 data planned for 10/2021)
AREA
Development of a transnational environmental observation system in support of European & International Policies
STAGE OF DEVELOPMENT
END USERS
Policy-makers, academia, industry, general public
DESCRIPTION
The GMP DWH is a web-based application whose is to provide long-term reliable and cost-effective information and services to global community, support POPs monitoring activities and data management under the Stockholm Convention and offer tools for collection, storage, organisation, comparison, analysis, and evaluation of performance in relation to monitoring programmes on POPs. It encompasses data input, storage, processing (compiling and archiving) of both primary data as well as aggregated data, including supplementary data in cases where no primary data are made available. The system holds data on POPs in four core matrices: air, human milk, human blood, and water. By respecting the requirements of uniform and harmonised presentation of data, all outputs of the GMP DWH are shown on the visualisation portal (www.popsgmp.org). The GMP DWH architecture consists of three layers guiding the data flow from the initial upload to the final publication. Each layer is connected with appropriate tools and processes of the data flow, user administration, security, user support etc. Data repository and data visualisation are the main parts of the system accessible by a wider group of users.
OBJECTIVES
The main objective is the collection of global data on POPs levels, assessment of their spatial and temporal trends.
DEMO LINK
Latest publications (2019 and beyond)
- Bohlin-Nizzetto, P.; Melymuk, L.; White, K. B.; Kalina, J.; Madadi, V. O.; Adu-Kumi, S.; Prokeš, R.; Přibylová, P. & Klánová, J. (2020), 'Field- and model-based calibration of polyurethane foam passive air samplers in different climate regions highlights differences in sampler uptake performance', Atmospheric Environment 238, 117742.
- De Simone, F.; D’Amore, F.; Marasco, F.; Carbone, F.; Bencardino, M.; Hedgecock, I. M.; Cinnirella, S.; Sprovieri, F. & Pirrone, N. (2020), 'A Chemical Transport Model Emulator for the Interactive Evaluation of Mercury Emission Reduction Scenarios', Atmosphere 11(8).
- De Simone, F.; D’Amore, F.; Bencardino, M.; Carbone, F.; Hedgecock, I. M.; Sprovieri, F.; Cinnirella, S. & Pirrone, N. (2021), 'The GOS4M Knowledge Hub: A web-based effectiveness evaluation platform in support of the Minamata Convention on Mercury', Environmental Science & Policy 124, 235--246.
- Kalina, J.; White, K. B.; Scheringer, M.; Přibylová, P.; Kukučka, P.; Audy, O. & Klánová, J. (2019), 'Comparability of long-term temporal trends of POPs from co-located active and passive air monitoring networks in Europe', Environ. Sci.: Processes Impacts 21, 1132-1142.
- Melymuk, L.; Nizzetto, P. B.; Harner, T.; White, K. B.; Wang, X.; Tominaga, M. Y.; He, J.; Li, J.; Ma, J.; Ma, W.-L.; Aristizábal, B. H.; Dryer, A.; Jiménez, B.; Muñoz-Arnanz, J.; Odabasi, M.; Dumanoglu, Y.; Yaman, B.; Graf, C.; Sweetman, A. & Klánová, J. (2021), 'Global intercomparison of polyurethane foam passive air samplers evaluating sources of variability in SVOC measurements', Environmental Science & Policy 125, 1--9.
- Moretti, S.; Tassone, A.; Andreoli, V.; Carbone, F.; Pirrone, N.; Sprovieri, F. & Naccarato, A. (2021), 'Analytical study on the primary and secondary organic carbon and elemental carbon in the particulate matter at the high-altitude Monte Curcio GAW station, Italy.', Environmental science and pollution research international.
- Naccarato, A.; Tassone, A.; Martino, M.; Moretti, S.; Macagnano, A.; Zampetti, E.; Papa, P.; Avossa, J.; Pirrone, N.; Nerentorp, M.; Munthe, J.; Wдngberg, I.; Stupple, G. W.; Mitchell, C. P. J.; Martin, A. R.; Steffen, A.; Babi, D.; Prestbo, E. M.; Sprovieri, F. & Wania, F. (2021), 'A field intercomparison of three passive air samplers for gaseous mercury in ambient air', Atmospheric Measurement Techniques 14(5), 3657--3672.
- Naccarato, A.; Tassone, A.; Martino, M.; Elliani, R.; Sprovieri, F.; Pirrone, N. & Tagarelli, A. (2021), 'An innovative green protocol for the quantification of benzothiazoles, benzotriazoles and benzosulfonamides in PM10 using microwave-assisted extraction coupled with solid-phase microextraction gas chromatography tandem-mass spectrometry', Environmental Pollution 285, 117487.
- Pernov, J. B.; Jensen, B.; Massling, A.; Thomas, D. C. & Skov, H. (2021), 'Dynamics of gaseous oxidized mercury at Villum Research Station during the High Arctic summer', Atmospheric Chemistry and Physics Discussions 2021, 1--28.
- Pleijel, H.; Klingberg, J.; Nerentorp, M.; Broberg, M. C.; Nyirambangutse, B.; Munthe, J. & Wallin, G. (2021), 'Mercury accumulation in leaves of different plant types – the significance of tissue age and specific leaf area', Biogeosciences Discussions 2021, 1--27.
- Skov, H.; Hjorth, J.; Nordstrøm, C.; Jensen, B.; Christoffersen, C.; Bech Poulsen, M.; Baldtzer Liisberg, J.; Beddows, D.; Dall'Osto, M. & Christensen, J. H. (2020), 'Variability in gaseous elemental mercury at Villum Research Station, Station Nord, in North Greenland from 1999 to 2017', Atmospheric Chemistry and Physics 20(21), 13253--13265.
- Urík, J. & Vrana, B. (2019), 'An improved design of a passive sampler for polar organic compounds based on diffusion in agarose hydrogel.', Environmental science and pollution research international 26, 15273-15284.
- Vrana, B.; Rusina, T.; Okonski, K.; Prokeš, R.; Carlsson, P.; Kopp, R. & Smedes, F. (2019), 'Chasing equilibrium passive sampling of hydrophobic organic compounds in water', Science of The Total Environment 664, 424--435.
- White, K. B.; Kalina, J.; Scheringer, M.; Přibylová, P.; Kukučka, P.; Kohoutek, J.; Prokeš, R. & Klánová, J. (2021), 'Temporal Trends of Persistent Organic Pollutants across Africa after a Decade of MONET Passive Air Sampling', Environ. Sci. Technol. 55(14), 9413--9424.
- Wong, F.; Hung, H.; Dryfhout-Clark, H.; Aas, W.; Bohlin-Nizzetto, P.; Breivik, K.; Mastromonaco, M. N.; Lundén, E. B.; Ólafsdóttir, K.; Sigurðsson, Á.; Vorkamp, K.; Bossi, R.; Skov, H.; Hakola, H.; Barresi, E.; Sverko, E.; Fellin, P.; Li, H.; Vlasenko, A.; Zapevalov, M.; Samsonov, D. & Wilson, S. (2021), 'Time trends of persistent organic pollutants (POPs) and Chemicals of Emerging Arctic Concern (CEAC) in Arctic air from 25 years of monitoring', Science of The Total Environment 775, 145109.
ICUPE - Integrative and Comprehensive Understanding on Polar Environments
Impact assessment of persistent organic pollutants in the Arctic
AREA
Predictive modeling and data synthesis
STAGE OF DEVELOPMENT
END USERS
Conference of the Parties of the Stockholm Convention
DESCRIPTION
Two case studies of impacts of organic pollutants globally and in the Arctic that were developed in iCUPE were summarized in the Third Regional Monitoring Report for the Western Europe and Other States (WEOG) region (http://chm.pops.int/implementation/globalmonitoringplan/monitoringreports/tabid/525/default.aspx).The regional monitoring reports support the periodic (every 5 years) evaluation of the effectiveness of the Stockholm Convention on Persistent Organic Pollutants. The two iCUPE case studies are in section 5.3 of the WEOG report, pages 216-220 and pages 223-227.
OBJECTIVES
The first case study included in the WEOG report describes prediction of human exposure and bioaccumulation of PCB153 at the global scale from historical emission estimates. The case study relies on modeling using the BETR Global transport model and the ACCHUMAN bioaccumulation model. BETR Global in particular was one of the models that was under continued development in iCUPE.
Concentrations of PCB153 in human breastmilk were compared to measured concentrations in the WHO/UNEP database that is maintained for effectiveness evaluation of the Stockholm Convention. The case study illustrates the feasibility of modeling global scale exposure to POPs using BETR Global and ACCHUMAN, and was also published in a leading international journal (https://doi.org/10.1039/C8EM00023A).
The second case study also uses the BETR Global model, but in this case to propose a global gridded emission inventory for an organic chemical that may be considered for nomination as a POP in the future, tris-(1-chloro-2-propyl) phosphate (TCPP). While this investigation of TCPP should be considered preliminary, it provides valuable insights about the link between emissions and concentrations in the global environment. Plausible environmental fate parameters have been established for TCPP in air and the ‘top-down’ emission inventory provided by this assessment serves as a reference point for future studies that could establish temporal and spatial trends.
DEMO LINK
-
p>Biogeochemical cycles of emerging organic contaminants
AREA
Bio-geochemistry
STAGE OF DEVELOPMENT
END USERS
European Chemicals Agency (ECHA)
United Nations Environment Programme (UNEP)
Arctic Monitoring and Assessment Programme (AMAP)
DESCRIPTION
Atmospheric long-range transport is a significant route for anthropogenic contaminants to reach the polar areas, which can adversely affect human health and the polar ecosystems. Besides, climate change may significantly affect the environmental fate of anthropogenic contaminants in the Polar environmental system and drive the interaction between environmental spheres (atmosphere, hydrosphere, biosphere, cryosphere). This product provide the data sets of organophosphate esters and per- and polyfluoroalkyl substances (PFASs) in the Arctic and Antarctic.
OBJECTIVES
The objectives of the product are: (1) characterization of the concentrations of EOCs in the atmosphere, seawater, snow in the central Arctic; (2) evaluation of the air–water and air-snow exchange process intervening in the transport of EOCs in the Arctic; (3) modeling the input of EOCs into the central Arctic via atmospheric dry and wet deposition. Data and feedback from this project may improve models to predict the environmental progression and assess the effect of climate change on the long-range transport and the fate of the emerging organic contaminants in the polar region.
DEMO LINK
https://www.atm.helsinki.fi/icupe/index.php/datasets/delivered-datasets
p>Integrated approach to validate and refine Arctic black carbon emissions from gas flaring
AREA
Russian Arctic (wider Arctic)
STAGE OF DEVELOPMENT
END USERS
Arctic Council (AC) (EG Black Carbon & Methane, AC AMAP/ACAP WGs), CLRTAP, EU Action on Black Carbon, IPCC, SDG 13
DESCRIPTION
Short-lived climate forcers (SLCFs) such as black carbon (BC), tropospheric ozone and methane warm the Earth’s climate and are contributing to rapid warming in the Arctic. Deposition of black carbon onto snow and sea-ice reduces surface albedo leading to accelerated melting and further warming. Black carbon emitted from combustion sources is transported into the Arctic from mid-latitudes. It is also emitted in the Arctic or sub-Arctic from sources such as wood burning, boreal fires and oil/gas extraction. Mitigation of black carbon emissions is targeted by the Arctic Council member states with a current goal to reduce black carbon emissions by 25-33 percent relative to 2013 levels by 2025 (https://arctic-council.org/en/news/arctic-states-on-track-to-reach-the-collective-goal-on-black-carbon-emissions/).
Reductions to emission from specific sectors, such as oil and gas extraction, are being actively pursued (https://arctic-council.org/en/news/how-to-reduce-emissions-of-black-carbon-and-methane-in-the-arctic/) Emissions from gas flaring activities are an important source of Arctic black carbon (AMAP 2015, 2021). To successfully mitigate these emissions, current estimates require validation and improvement to reduce uncertainties. As part of the iCUPE project, an integrated approach combining analysis of in-situ and satellite data, and prior modelling, has been developed and is being applied to gas flaring emissions in Russia. Improved emission estimates will lead to improvements in integrated chemistry-aerosol-climate models, which include detailed treatments of SLCFs, and which are the tools used to assess SLCF climate impacts. Results may also inform the need for improved observation strategies to monitor and assess SLCFs and their response to emission mitigation.
OBJECTIVES
In order to evaluate and examine uncertainties in Arctic SLCF emissions, the integrated approach developed in iCUPE has been applied to black carbon emissions from Russian gas flaring. Combined analysis of pollution plumes sampled by the YAK-AEROSIB aircraft (https://yak.aeris-data.fr/) and VIIRS night-light satellite data (https://eogdata.mines.edu/products/vnf/), together with source-receptor modelling, has been used to identify discrepancies in recent gas flaring emission estimates and regions where emissions are missing. The analysis shows that discrepancies between observed black carbon and detailed chemical-aerosol model simulations can be partly explained by inconsistencies in emission datasets or missing emissions. Refnements to the black carbon emissions from gas flaring are being investigated.
DEMO LINK
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Latest publications (2019 and beyond)
- Ancellet, G., Penner, I. E., Pelon, J., Mariage, V., Zabukovec, A., Raut, J. C., Kokhanenko, G., and Balin, Y. S.: Aerosol monitoring in Siberia using an 808 nm automatic compact lidar, Atmos. Meas. Tech., 12, 147–168, https://doi.org/10.5194/amt-12-147-2019, 2019.
- Barbaro, E., K. Koziol, M. P. Björkman, C. P. Vega, C. Zdanowicz, T. Martma, J. C. Gallet, D. Kępski, C. Larose, B. Luks, F. Tolle, T. V. Schuler, A. Uszczyk and A. Spolaor (2021). "Measurement report: Spatial variations in ionic chemistry and water-stable isotopes in the snowpack on glaciers across Svalbard during the 2015–2016 snow accumulation season." Atmos. Chem. Phys. 21(4): 3163-3180.
- Barreira, L. M. F., Ylisirniö, A., Pullinen, I., Buchholz, A., Li, Z., Lipp, H., Junninen, H., Noe, S. M., Krasnova, A., Krasnov, D., Kask, K., Talts, E., Niinemets, Ü., Ruiz-Jimenez, J., and Schobesberger, S.: The importance of sesquiterpene oxidation products for secondary organic aerosol formation in a spring-time hemi-boreal forest, Atmos. Chem. Phys. Discuss. [preprint], https://doi.org/10.5194/acp-2021-8, in review, 2021.
- Beck, L.; Sarnela, N.; Junninen, H.; Hoppe, C.J.M.; Garmash, O.; Bianchi, F.; Riva, M.; Rose, C.; Peräkylä, O.; Wimmer, D.; Kausiala, O.; Jokinen, T.; Ahonen, L.; Mikkilä, J.; Hakala, J.; Wolf, K. K. E.; Cappelletti, D.; Mazzola, M.; Traversi, R.; Petroselli, C.; Viola, A.P.; Vitale, V. Lange, R.; Massling, A.; Nøjgaard, J.K.; Krejci, R.; Karlsson, L.; Ziegler, P.; Jang, S.M; Lee, K.; Vakkari, V.; Lampilahti, J.; Thakur, R.C.; Leino, K.; Kangasluoma, J.; Duplissy, E.-M.; Siivola, E.; Kontkanen, J.; Marbouti, M.; He, X.-C.; Tham, Y.J.; Saiz-Lopez, A.; Petäjä, T.; Ehn, M.; Worsnop, D.R.; Skov, H.; Kulmala, M.; Kerminen, V.-M.; and Sipilä, M. (2021) Differing Mechanisms of New Particle Formation at Two Arctic Sites GRL. Vol 48, e2020GL091334, http://dx.doi.org/10.1029/2020GL091334.
- Carotenuto, Federico, Lorenzo Brilli, Beniamino Gioli, Giovanni Gualtieri, Carolina Vagnoli, Mauro Mazzola, Angelo Pietro Viola, Vito Vitale, Mirko Severi, Rita Traversi, Alessandro Zaldei (2020), "Long-Term Performance Assessment of Low-Cost Atmospheric Sensors in the Arctic Environment", Sensors, pp. 1919, Vol 20 (7).
- Chuxian Li, Jeroen E. Sonke, Gaël Le Roux, Natalia Piotrowska, Nathalie Van der Putten, Stephen J. Roberts, Tim Daley, Roland Gehrels, Maxime Enrico, Dmitri Mauquoy, François De Vleeschouwer (2019) Unequal anthropogenic enrichment of mercury in Earth’s northern and southern hemispheres. ACS Earth & Space Chemistry. https://pubs.acs.org/doi/abs/10.1021/acsearthspacechem.0c00220
- Cornford, S. L., Seroussi, H., Asay-Davis, X. S., Gudmundsson, G. H., Arthern, R., Borstad, C., Christmann, J., Dias dos Santos, T., Feldmann, J., Goldberg, D., Hoffman, M. J., Humbert, A., Kleiner, T., Leguy, G., Lipscomb, W. H., Merino, N., Durand, G., Morlighem, M., Pollard, D., Rückamp, M., Williams, C. R., and Yu, H.: Results of the third Marine Ice Sheet Model Intercomparison Project (MISMIP+), The Cryosphere, 14, 2283–2301, https://doi.org/10.5194/tc-14-2283-2020, 2020
- Dall'Osto, M., Beddows, D. C. S., Tunved, P., Harrison, R. M., Lupi, A., Vitale, V., Becagli, S., Traversi, R., Park, K.-T., Yoon, Y. J., Massling, A., Skov, H., Lange, R., Strom, J., and Krejci, R.: Simultaneous measurements of aerosol size distributions at three sites in the European high Arctic, Atmos. Chem. Phys., 19, 7377–7395, https://doi.org/10.5194/acp-19-7377-2019, 2019.
- Edwards, T.L., Nowicki, S., Marzeion, B. [...] Humbert, A., Kleiner, T. Rückamp, M. [...] et al. (2021) Projected land ice contributions to twenty-first-century sea level rise. Nature 593, 74–82. https://doi.org/10.1038/s41586-021-03302-y
- Feltracco, M., Barbaro, E., Spolaor, A., Vecchiato, M., Callegaro, A., Burgay, F., Vardè, M., Maffezzoli, N., Dallo, F., Scoto, F., Zangrando, R., Barbante, C., and Gambaro, A.: Year-round measurements of size-segregated low molecular weight organic acids in Arctic aerosol, Sci Total Environ, 763, 142954, 2021. Feltracco, M., E. Barbaro, S. Tedeschi, A. Spolaor, C. Turetta, M. Vecchiato, E. Morabito, R. Zangrando, C. Barbante and A. Gambaro (2020). "Interannual variability of sugars in Arctic aerosol: Biomass burning and biogenic inputs." Science of The Total Environment 706: 136089.
- Goelzer, H., Nowicki, S., Payne, A., Larour, E., Seroussi, H., Lipscomb, W. H., Gregory, J., Abe-Ouchi, A., Shepherd, A., Simon, E., Agosta, C., Alexander, P., Aschwanden, A., Barthel, A., Calov, R., Chambers, C., Choi, Y., Cuzzone, J., Dumas, C., Edwards, T., Felikson, D., Fettweis, X., Golledge, N. R., Greve, R., Humbert, A., Huybrechts, P., Le clec'h, S., Lee, V., Leguy, G., Little, C., Lowry, D. P., Morlighem, M., Nias, I., Quiquet, A., Rückamp, M., Schlegel, N.-J., Slater, D. A., Smith, R. S., Straneo, F., Tarasov, L., van de Wal, R., and van den Broeke, M.: The future sea-level contribution of the Greenland ice sheet: a multi-model ensemble study of ISMIP6, The Cryosphere, 14, 3071–3096, https://doi.org/10.5194/tc-14-3071-2020, 2020
- Gryning, S.E. Batchvarova, E. Floors, R. Münkel, C. Skov, H. and Sørensen, L.L. (2021) Observed and modelled cloud cover up to 6 km height at Station Nord in High Arctic. Int. J. Climatol. Vol. 41, p1584–1598. https://doi.org/10.1002/joc.6894.
- Hochreuther, P.; Neckel, N.; Reimann, N.; Humbert, A.; Braun, M. Fully Automated Detection of Supraglacial Lake Area for Northeast Greenland Using Sentinel-2 Time-Series. Remote Sens. 2021, 13, 205
- Hofstede, C., Beyer, S., Corr, H., Eisen, O., Hattermann, T., Helm, V., Neckel, N., Smith, E. C., Steinhage, D., Zeising, O., and Humbert, A. (2021) Evidence for a grounding line fan at the onset of a basal channel under the ice shelf of Support Force Glacier, Antarctica, revealed by reflection seismics, The Cryosphere, 15, 1517–1535, https://doi.org/10.5194/tc-15-1517-2021
- Humbert, A., Schröder, L., Schultz, T., Müller, R., Neckel, N., Helm, V., Zindler, R., Eleftheriadis, K., Salzano, R., Salvatori, R., Dark Glacier surface of Greenland’s largest floating tongue governed by high local deposition of dust (2020) Remote Sensing, 12 (22), art. no. 3793, pp. 1-17. DOI: 10.3390/rs12223793
- Ianniello, A.; Salzano, R.; Salvatori, R.; Esposito, G.; Spataro, F.; Montagnoli, M.; Mabilia, R.; Pasini, A. Nitrogen Oxides (NOx) in the Arctic Troposphere at Ny-Ålesund (Svalbard Islands): Effects of Anthropogenic Pollution Sources. Atmosphere 2021, 12, 901. https://doi.org/10.3390/atmos12070901
- Im, U., Tsigaridis, K. Faluvegi, G. Langen, P.L. French, J.P. Mahmood, R. Manu, T. von Salzen, K Thomas, D. C. Whaley, C. H. Klimont, Z. Skov, H. and Brandt, J. (2021) Present and future aerosol impacts on Arctic climate change in the GISS-E2.1 Earth system model, ACP. vol. 21, 10413–10438, https://doi.org/10.5194/acp-2020-1296.
- J.-C. Gallet, M.P. Björkman, C.P. Borstad A.J. Hodson, H.-W. Jacobi, C. Larose, B. Luks, A. Spolaor, T.V. Schuler, C. Zdanowicz. Snow research in Svalbard, in SEES Report 2018 - An annual report on the State of Environmental Science, Orr et al (eds) 2019: SESS report 2018, Longyearbyen, Svalbard Integrated Arctic Earth Observing System.
- Jawak SD, Andersen BN, Pohjola VA, Godøy Ø, Hübner C, Jennings I, Ignatiuk D, Holmén K, Sivertsen A, Hann R, Tømmervik H, Kääb A, Błaszczyk M, Salzano R, Luks B, Høgda KA, Storvold R, Nilsen L, Salvatori R, Krishnan KP, Chatterjee S, Lorentzen DA, Erlandsson R, Rune Lauknes T, Malnes E, Karlsen SR, Enomoto H, Fjæraa AM, Zhang J, Marty S, Nygård KO, Lihavainen H. SIOS’s Earth Observation (EO), Remote Sensing (RS), and Operational Activities in Response to COVID-19. Remote Sensing. 2021; 13(4):712. https://doi.org/10.3390/rs13040712
- Kern, M., Cullen, R., Berruti, B., Bouffard, J., Casal, T., Drinkwater, M. R., Gabriele, A., Lecuyot, A., Ludwig, M., Midthassel, R., Navas Traver, I., Parrinello, T., Ressler, G., Andersson, E., Martin-Puig, C., Andersen, O., Bartsch, A., Farrell, S., Fleury, S., Gascoin, S., Guillot, A., Humbert, A., Rinne, E., Shepherd, A., van den Broeke, M. R., and Yackel, J.: The Copernicus Polar Ice and Snow Topography Altimeter (CRISTAL) high-priority candidate mission, The Cryosphere, 14, 2235–2251, https://doi.org/10.5194/tc-14-2235-2020, 2020
- Kitz, F., Spielmann, F. M., Hammerle, A., Kolle, O., Migliavacca, M., Moreno, G., et al. (2020). Soil COS exchange: A comparison of three European ecosystems. Global Biogeochemical Cycles, 34, e2019GB006202. https://doi.org/10.1029/2019GB006202
- Kokhanovsky, Alexander, Claudio Tomasi, Alexander Smirnov, Andreas Herber, Roland Neuber, André Ehrlich, Angelo Lupi, Boyan H Petkov, Mauro Mazzola, Christoph Ritter, Carlos Toledano, Thomas Carlund, Vito Vitale, Brent Holben, Tymon Zielinski, Simon Bélanger, Pierre Larouche, Stefan Kinne, Vladimir Radionov, Manfred Wendisch, Jason L Tackett, David M Winker (2020), "Remote Sensing of Arctic Atmospheric Aerosols", In In: Kokhanovsky A., Tomasi C. (eds) Physics and Chemistry of the Arctic Atmosphere. Springer Polar Sciences. Springer, pp. 505-589
- Kulmala, M., Ezhova, E., Kalliokoski, T., Noe, S., Vesala, T., Lohila, A., Liski, J., Makkonen, R., Bäck, J., Petäjä, T., & Kerminen, V-M. (2020). CarbonSink+: Accounting for multiple climate feedbacks from forests. Boreal Environment Research, 25, 145-159. Lampert, A. A., B.; Bärfuss, K.; Bretschneider, L.; Sandgaard, J.; Michaelis, J.; Lobitz, L.; Asmussen, M.; Damm, E.; Käthner, R.; Krüger, T.; Lüpkes, C.; Nowak, S.; Peuker, A.; Rausch, T.; Reiser, F.; Scholtz, A.; Sotomayor Zakharov, D.; Gaus, D.; Bansmer, S.; Wehner, B.; Pätzold, F. (2020). "Unmanned Aerial Systems for Investigating the Polar Atmospheric Boundary Layer—Technical Challenges and Examples of Applications." Atmosphere 11: 416.
- Lange, R., Dall´Osto, M., Wex, H., Skov, H., & Massling, A. ( 2019). Large summer contribution of organic biogenic aerosols to Arctic cloud condensation nuclei. Geophysical Research Letters, 46. https://doi.org/10.1029/2019GL084142
- Lim, A. G., Jiskra, M., Sonke, J. E., Loiko, S. V., Kosykh, N. and Pokrovsky, O. S.: A revised northern soil Hg pool, based on western Siberia permafrost peat Hg and carbon observations, Biogeosciences, 2020, 1–35, doi:10.5194/bg-2019-483
- Manousakas, M., Popovicheva, O., Evangeliou, N., Diapouli, E., Sitnikov, N., Shonija, N., Eleftheriadis, K., Aerosol carbonaceous, elemental and ionic composition variability and origin at the Siberian High Arctic, Cape Baranova (2020) Tellus, Series B: Chemical and Physical Meteorology, 72 (1), pp. 1-14. DOI: 10.1080/16000889.2020.1803708
- Mason, S. L., Hogan, R. J.,Westbrook, C. D., Kneifel, S., Moisseev, D., and von Terzi, L.: The importance of particle size distribution and internal structure for triple-frequency radar retrievals of the morphology of snow, Atmos. Meas. Tech., 12, 4993–5018, https://doi.org/10.5194/amt-12-4993-2019, 2019.
- Moroni, Beatrice, Christoph Ritter, S Crocchianti, Krystof Markowicz, Mauro Mazzola, Silvia Becagli, Rita Traversi, Radovan Krejci, Peter Tunved, David Cappelletti (2020), "Individual particle characteristics, optical properties and evolution of an extreme long‐range transported biomass burning event in the European Arctic (Ny‐Ålesund, Svalbard Islands)", Journal of Geophysical Research: Atmospheres, pp. e2019JD031535, Vol. 125 (5).
- Moschos, V. Dzepina, K. Bhattu, D. Lamkaddam, H. Casotto, R. Daellenbach, K. R. Canonaco, F. Aas, W. Becagli, S. Calzolai, G. Eleftheriadis, K. Moffett, C. E. Schnelle-Kreis, J. Severi, M. Sharma, S. Skov, H. Vestenius, M. Zhang, W. Hakola, H. Hellén, H. Huang, L Jaffrezo, J.-L. Massling, A. Nøjgaard, J. K. Petäjä, T. Popovicheva, O. Sheesley, R. J. Traversi, R. Yttri, K. E. Schmale, J. Prévôt, A. S. H. Baltensperger, U. El Haddad, I. Equal abundance of summertime natural and wintertime anthropogenic Arctic organic aerosols. In Press, Nature, Geoscience, May 2021.
- Moschos, V.; Gysel-Beer, M.; Modini, R. L.; Corbin, J. C.; Massabó, D.; Costa, C.; Danelli, S. G.; Vlachou, A.; Daellenbach, K. R.; Szidat, S.; Prati, P.; Prévôt, A. S. H.; Baltensperger, U.; El Haddad, I. Source-specific light absorption by carbonaceous components in the complex aerosol matrix from yearly filter-based measurements. Atmos. Chem. Phys. Discuss. (in review), https://acp.copernicus.org/preprints/acp-2020-1293/acp-2020-1293.pdf.
- Neckel N, Zeising O, Steinhage D, Helm V and Humbert A (2020) Seasonal Observations at 79°N Glacier (Greenland) From Remote Sensing and in situ Measurements. Front. Earth Sci. 8:142. doi: 10.3389/feart.2020.00142
- Nielsen, I. E., Skov, H., Massling, A., Eriksson, A. C., Dall’Osto, M., Junninen, H., Sarnela, N., Lange, R., Collier, S., Zhan, Q., Cappa, C. D., Nøjgaard, J. K. (2019) Biogenic and anthropogenic sources of Arctic aerosols, accepted by Atmos. Chem. and Phys.
- Nigul, K.; Padari, A.; Kiviste, A.; Noe, S.M.; Korjus, H.; Laarmann, D.; Frelich, L.E.; Jõgiste, K.; Stanturf, J.A.; Paluots, T.; Põldveer, E.; Kängsepp, V.; Jürgenson, H.; Metslaid, M.; Kangur, A. The Possibility of Using the Chapman–Richards and Näslund Functions to Model Height–Diameter Relationships in Hemiboreal Old-Growth Forest in Estonia. Forests 2021, 12, 184. https://doi.org/10.3390/f12020184
- Noe SM and Niinemets Ü (2020) Impact of Gall-Forming Insects on Global BVOC Emissions and Climate: A Perspective. Front. For. Glob. Change 3:9. doi: 10.3389/ffgc.2020.00009
- Pernov, J. B., Bossi, R., Lebourgeois, T., Nøjgaard, J. K., Holzinger, R., Hjorth, J. L., and Skov, H.: Atmospheric VOC measurements at a High Arctic site: characteristics and source apportionment, Atmos. Chem. Phys., 21, 2895–2916, https://doi.org/10.5194/acp-21-2895-2021, 2021.
- Pernov, J. B., Jensen, B., Massling, A., Thomas, D. C., and Skov, H.: Dynamics of gaseous oxidized mercury at Villum Research Station during the High Arctic summer, Atmos. Chem. Phys. Discuss. [preprint], https://doi.org/10.5194/acp-2020-1287, in review, 2021.
- Petäjä T., Duplissy E.M., Tabakova K., Schmale J., Altstädter B., Ancellet G.,Arshinov M., Balin Y., Baltensperger U., Bange J, Beamish A., Belan B., Berchet A., Bossi R., Cairns W. R. L., Ebinghaus R., Haddad I. E. , Ferreira-Araujo B., Franck A., Huang L., Hyvärinen A., Humbert1 A., Kalogridis A.C., Konstantinov P., Lampert A., MacLeod M., Magand O., Mahura A., Marelle L., Masloboev V., Moisseev D.,, Moschos V., Neckel N., Onishi T., Osterwalder O., Ovaska A., Paasonen P., Panchenko M., Pankratov M., Pernov J.B., Platis A., Popovicheva O., Raut J.C., Riandet A., Sachs T., Salvatori R., Salzano R., Schröder L., Schön M., Shevchenko V., Skov H., Sonke J.E., Spolaor A., Stathopoulos V., Strahlendorff M., Thomas J.L., Vitale V., Vratolis S., Barbante C., Chabrillat S., Dommergue A., Eleftheriadis K., Heilimo J., Law K.S., Massling A., Noe S.M., Pari J.D., Prévôt A., Riipinen I., Wehner B., Xie Z., and Lappalainen H.K, 2020. Overview – Integrative and Comprehensive Understanding on Polar Environments (iCUPE): the concept and initial results ,Environments (iCUPE), DOI: 10.5194/acp-20-8551-2020
- Petäjä, T., Ganzei, K. S., Lappalainen, H. K., Tabakova, K., Makkonen, R., Räisänen, J., Chalov, S., Kulmala, M., Zilitinkevich, S., Baklanov, P. Y., Shakirov, R. B., Mishina, N. V., Egidarev, E. G., & Kondrat'ev, I. I. (2021). Research agenda for the Russian Far East and utilization of multi-platform comprehensive environmental observations. International Journal of Digital Earth, 14(3), 311-337. https://doi.org/10.1080/17538947.2020.1826589
- Popovicheva, O., Diapouli, E., Makshtas, A., Shonija, N., Manousakas, M., Saraga, D., Uttal, T., Eleftheriadis, K. , East Siberian Arctic background and black carbon polluted aerosols at HMO Tiksi, (2019) Science of the Total Environment, 655, pp. 924-938. DOI: 10.1016/j.scitotenv.2018.11.165
- Popovicheva, O., Diapouli, E., Makshtas, A., Shonija, N., Manousakas, M., Saraga, D., Uttal, T., Eleftheriadis, K., East Siberian Arctic background and black carbon polluted aerosols at HMO Tiksi, (2019), Science of The Total Environment, 655, Pages 924-938, DOI: 10.1016/j.scitotenv.2018.11.165.
- Rinaldi, M., Hiranuma, N., Santachiara, G., Mazzola, M., Mansour, K., Paglione, M., Rodriguez, C. A., Traversi, R., Becagli, S., Cappelletti, D. M., and Belosi, F. (2020): Condensation and immersion freezing Ice Nucleating Particle measurements at Ny-Ålesund (Svalbard) during 2018: evidence of multiple source contribution, Atmos. Chem. Phys. Discuss. [preprint], https://doi.org/10.5194/acp-2020-605, in review, 2020.
- Rückamp, M., Goelzer, H., and Humbert, A.: Sensitivity of Greenland ice sheet projections to spatial resolution in higher-order simulations: the Alfred Wegener Institute (AWI) contribution to ISMIP6 Greenland using the Ice-sheet and Sea-level System Model (ISSM), The Cryosphere, 14, 3309–3327, https://doi.org/10.5194/tc-14-3309-2020, 2020
- Rückamp, M., Humbert, A., Kleiner, T., Morlighem, M., and Seroussi, H.: Extended enthalpy formulations in the Ice-sheet and Sea-level System Model (ISSM) version 4.17: discontinuous conductivity and anisotropic streamline upwind Petrov–Galerkin (SUPG) method, Geosci. Model Dev., 13, 4491–4501, https://doi.org/10.5194/gmd-13-4491-2020, 2020
- Saiz-Lopez, A., Travnikov, O., Sonke, J. E., Thackray, C. P., Jacob, D. J., Carmona-García, J., Francés-Monerris, A., Roca-Sanjuán, D., Acuña, A. U., Dávalos, J. Z., Cuevas, C. A., Jiskra, M., Wang, F., Bieser, J., Plane, J. M. C. and Francisco, J. S.: Photochemistry of oxidized Hg(I) and Hg(II) species suggests missing mercury oxidation in the troposphere, Proceedings of the National Academy of Sciences, https://doi.org/10.1073/pnas.1922486117, 2020.
- Salzano, R., Aalstad K., Boldrini E., Gallet J.C., KępskiD., Luks B., Nilsen, Salvatori R., Westermann S, 2021, Terrestrial Photography ApplicationS on Snow covEr in Svalbard (PASSES), SESS report 2020-The State of Environmental Science in Svalbard– an annual report, DOI: https://doi.org/10.5281/zenodo.4294084
- Salzano, R., Killie M.A, Luks B., Malnes E.,2021, A multi-scale approach to snow cover observations and models (Snow Cover), SESS report 2020-The State of Environmental Science in Svalbard– an annual report, https://doi.org/10.5281/zenodo.4294092
- Salzano, R., Lanconelli C, Esposito G, Giusto M, Montagnoli M, Salvatori R. On the Seasonality of the Snow Optical Behaviour at Ny Ålesund (Svalbard Islands, Norway). Geosciences. 2021; 11(3):112. https://doi.org/10.3390/geosciences11030112
- Salzano, R.; Salvatori, R.; Valt, M.; Giuliani, G.; Chatenoux, B.; Ioppi, L. Automated Classification of Terrestrial Images: The Contribution to the Remote Sensing of Snow Cover. Geosciences, 2019, 9, 97.
- Schacht, J., Heinold, B., Quaas, J., Cherian, R., Backman, J., Massling, A., Herber, A., Sinha, P. R., Kondo, Y., Weinzierl, B., Zanatta, M., Ehrlich, A., Tegen, I. (2019) The importance of the representation of air pollution emissions for the modeled distribution and radiative effects of black carbon in the Arctic, accepted by Atmos. Chem. and Phys..
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- Schröder, L.; Neckel, N.; Zindler, R.; Humbert, A. Perennial Supraglacial Lakes in Northeast Greenland Observed by Polarimetric SAR. Remote Sens. /doi.org/10.3390/rs12172798, 2020, 12, 2798
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