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Two decades of fire activity over the PEEX domain:a look from space,with contribution from models and ground-based measurements

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Big Earth Data 2024年第2期8卷 350-396页

作者： Larisa Sogacheva Timo H.Virtanen Anu-Maija Sundström Pekka Kolmonen mikhail sofiev Hanna K.Lappalainen Antti Arola Finnish Meteorological Institute Climate Research ProgrammeHelsinkiFinland Finnish Meteorological Institute Space and Earth Observation CentreHelsinkiFinland Institute for Atmospheric and Earth System Research/Physics Faculty of ScienceUniversity of HelsinkiHelsinkiFinland

It has been suggested that forest fires will become more frequent/intense with changing climate,which would increase aerosol/gas emissions into the atmosphere.A better under-standing of the relations between meteorological conditions,fires,and fire emissions will help estimate the climate response via forest *** this study,we use ERA5 meteor-ological products,including temperature,precipitation,and soil moisture,to explain the frequency of forest fires and the amount of radiant energy released per time unit by burning vegetation(fire radiative power,FRP).We explore the relation-ships between satellite-retrieved fire products and aerosol properties(aerosol optical depth,AOD),carbon monoxide(CO),formaldehyde(HCHO),and nitrogen dioxide(NO_(2))con-centrations over the PEEX domain,which covers different vegetation zones(***/grasslands,forest,arctic tun-dra)of Pan-Eurasia and *** analyse the concentrations of black carbon and absorbing organic carbon using groundbased AErosol RObotic *** analysis covers the months of May to August from 2002 to *** show posi-tive temperature trends in the Northern zone(>65°N)in June and August(1.56°C and 0.64°C,respectively);all statistically significant trends for precipitation and soil moisture are *** can explain increased fire activity in Siberia over the recent years(2019-2022).Over the whole PEEX domain,FC and FRP trends remain insignificant or negative;a decrease in AOD may address those negative *** show that intrasummer variations exist for cropland/grassland fires,which occur most often in May and August,while Siberian forest fires occur more often in July and *** show that CO concentration has been gradually decreasing in the last two decades in May and *** trends are negative in May,June,and over summer for all regions,in July in Europe,China,the Southern zone(<55°N),and the PEEX *** trends are not significant in all ***_(2)trends are positive in May and

关键词： PEEX wild fires satellite trend enhancement ratios

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Towards seamless environmental prediction-development of Pan-Eurasian EXperiment(PEEX)modelling platform

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Big Earth Data 2024年第2期8卷 189-230页

作者： Alexander Mahura Alexander Baklanov Risto Makkonen Michael Boy Tuukka Petäjä Hanna KLappalainen Roman Nuterman Veli-Matti Kerminen Stephen R.Arnold Markus Jochum Anatoly Shvidenko Igor Esau mikhail sofiev Andreas Stohl Tuula Aalto Jianhui Bai Chuchu Chen Yafang Cheng Oxana Drofa Mei Huang Leena Järvi Harri Kokkola Rostislav Kouznetsov Tingting Li Piero Malguzzi Sarah Monks Mads Bruun Poulsen Steffen M.Noe Yuliia Palamarchuk Benjamin Foreback Petri Clusiu Till Andreas Soya Rasmussen Jun She Jens Havskov Sørensen Dominick Spracklen Hang Su Juha Tonttila Siwen Wang Jiandong Wang Tobias Wolf-Grosse Yongqiang Yu Qing Zhang Wei Zhang Wen Zhang Xunhua Zheng Siqi Li Yong Li Putian Zhou Markku Kulmala Faculty of Science Institute for Atmospheric and Earth System Research(INAR)/PhysicsUniversity of Helsinki(UHEL)HelsinkiFinland Science and Innovation Department World Meteorological Organization(WMO)GenevaSwitzerland Niels Bohr Institute University of CopenhagenCopenhagenDenmark Climate System Research Finnish Meteorological Institute(CSR-FMI)HelsinkiFinland School of Engineering Sciences Lappeenranta University of TechnologyLappeenrantaFinland Institute for Climate and Atmospheric Science School of Earth and EnvironmentUniversity of LeedsLeedsUK Biodiversity and Natural Resources Program International Institute for Applied Systems Analysis(IIASA)LaxenburgAustria Department of Physics and Technology UiT-The Arctic University of NorwayTromsoNorway Nansen Environmental and Remote Sensing Center(NERSC) BergenNorway Atmospheric Composition Finnish Meteorological Institute(AC-FMI)HelsinkiFinland Norwegian Institute for Air Research(NILU) KjellerNorway LAGEO Institute of Atmospheric PhysicsChinese Academy of Sciences(IAP-CAS)BeijingChina Max Planck Institute for Chemistry(MPI-Chem) MainzGermany Institute of Atmospheric Sciences and Climate National Research Council of Italy(CNR-15SAC)BolognaItaly Institute of Geographic Sciences and Natural Resources Research(IGSNRR) Chinese Academy of Sciences(CAS)BeijingChina Faculty of Science Helsinki Institute of Sustainability Science(HELSUS)University of Helsinki(UHEL)HelsinkiFinland Atmospheric Research Centre of Eastern Finland Finnish Meteorological Institute(ARCEF-FMI)KuopioFinland Institute of Atmospheric Physics Chinese Academy of Sciences(IAP-CAS)BeijingChina Department of Plant Physiology Estonian University of Life Sciences(EULS)Institute of Agricultural and Environmental Sciences(IAES)TartuEstonia Danish Meteorological Institute(DMI) CopenhagenDenmark State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry LAPC) Institute of Atmospheric Physics(IAP)Chinese Academy of Sciences(CAS)BeijingChina Uni

The Pan-Eurasian Experiment Modelling Platform(PEEX-MP)is one of the key blocks of the PEEX Research *** PEEX MP has more than 30 models and is directed towards seamless envir-onmental *** main focus area is the Arctic-boreal regions and *** models used in PEEX-MP cover several main components of the Earth’s system,such as the atmosphere,hydrosphere,pedosphere and biosphere,and resolve the physicalchemicalbiological processes at different spatial and temporal scales and *** paper introduces and discusses PEEX MP multi-scale modelling concept for the Earth system,online integrated,forward/inverse,and socioeconomical modelling,and other approaches with a particular focus on applications in the PEEX geographical *** employed high-performance com-puting facilities,capabilities,and PEEX dataflow for modelling results are *** virtual research platforms(PEEXView,Virtual Research Environment,Web-based Atlas)for handling PEEX modelling and observational results are *** over-all approach allows us to understand better physical-chemicalbiological processes,Earth’s system interactions and feedbacks and to provide valuable information for assessment studies on evaluating risks,impact,consequences,*** population,envir-onment and climate in the PEEX *** work was also one of the last projects of *** Zilitinkevich,who passed away on 15 February *** the finalization took time,the paper was actually submitted in 2023 and we could not argue that the final paper text was agreed with him.

关键词： Multi-scale and-processes modelling concept seamless coupling high-performance computing data infrastructure virtual research platforms

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A demonstration project of Global Alliance against Chronic Respiratory Diseases:Prediction of interactions between air pollution and allergen exposure—the Mobile Airways Sentinel NetworK-Impact of air POLLution on Asthma and Rhinitis approach

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Chinese Medical Journal 2020年第13期133卷 1561-1567页

作者： mikhail sofiev Yuliia Palamarchuk Annabelle Bedard Xavier Basagana Josep M.Anto Rostislav Kouznetsov Rodrigo Delgado Urzua Karl Christian Bergmann Joao A.Fonseca Govert De Vries Michiel Van Erd Isabella Annesi-Maesano Daniel Laune Jean Louis Pepin Ingrid Jullian-Desayes Stephane Zeng Wienczyslawa Czarlewski Jean Bousquet Finnish Meteorological Institute(FMI) Helsinki 00560Finland Barcelona Institute for Global Health Centre for Research in Environmental Epidemiology(CREAL)Barcelona 08003Spain Centro de Investigacion Biomedica en Red de Epidemiologia y Salud Publica(CIBER)Epidemiologia y Salud Publica(CIBERESP) Barcelona 08003Spain Universitat Pompeu Fabra(UPF) Barcelona 08003Spain Institut Hospital del Mar d'lnvestigacions Mediques(IMIM) Barcelona 08003Spain Charite-Universitatsmedizin Berlin Corporate Member of Freie Universitat BerlinHumboldt-Uniersitat zu Berlin and Berlin Institute of HealthComprehensive Allergy-CentreDepartment of Dermatology and AllergyBerlin 10117Germany Center for Health Technology and Services Research(CINTESIS) Center for Research in Health Technology and Information SystemsFaculdade de Medicina da Universidade do Portoand MedidaLda Porto s/n 4200-450Portugal Peercode BV Geldermalsen 4191 NWThe Netherlands Epidemiology of Allergic and Respiratory Diseases Department Institute Pierre Louis of Epidemiology and Public HealthINSERM and Sorbonne UniversiteMedical School Saint AntoineParis 75571France KYomed Innovation Montpellier 34184France Universite Grenoble Alpes Laboratoire HP2GrenobleINSERMU1042 and CHU de GrenobleGrenoble 38000France Bull DSAS Echirolles 38130France Medical Consulting Czarlewski Levalloisand MASK-airMontpellier 92300France University Hospital Montpellier Montpellier 34000France Contre les Maladies Chroniques pour un Vieillissement Actif en Languedoc Roussillon-France MontpellierFrance Charite Universitatsmedizin BerlinHumboldt-Universitat zu Berlinand Berlin Institute of HealthComprehensive Allergy CenterDepartment of Dermatology and AllergyBerlin 10117Germany

This review analyzes the state and recent progress in the field of information support for pollen allergy *** decades,information available for the patients and allergologists consisted of pollen counts,which are vital but *** technology paves the way to substantial increase in amount and diversity of the *** paper reviews old and newly suggested methods to predict pollen and air pollutant concentrations in the air and proposes an allergy risk concept,which combines the pollen and pollution information and transforms it into a qualitative risk *** new index is available in an app(Mobile Airways Sentinel NetworK-air)that was developed in the frame of the European Union grant Impact of Air POLLution on sleep,Asthma and Rhinitis(a project of European Institute of Innovation and Technology-Health).On-going transformation of the pollen allergy information support is based on new technological solutions for pollen and air quality monitoring and *** new information-technology and artificial-intelligence-based solutions help to convert this information into easy-to-use services for both medical practitioners and allergy sufferers.

关键词： Pollen allergy Pollen season Google trends Pollen dispersion modeling System for Integrated modeLling of Atmospheric coMposition model Pollen index Air quality index

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