Detailed Information on Publication Record
2023
A temporally and spatially explicit, data-driven estimation of airborne ragweed pollen concentrations across Europe
MAKRA, Laszlo, Istvan MATYASOVSZKY, Gabor TUSNADY, Lewis H ZISKA, Jeremy J HESS et. al.Basic information
Original name
A temporally and spatially explicit, data-driven estimation of airborne ragweed pollen concentrations across Europe
Authors
MAKRA, Laszlo, Istvan MATYASOVSZKY, Gabor TUSNADY, Lewis H ZISKA, Jeremy J HESS, Laszlo G NYUL, Daniel S CHAPMAN, Luca COVIELLO, Andrea GOBBI, Giuseppe JURMAN, Cesare FURLANELLO, Mauro BRUNATO, Athanasios DAMIALIS, Athanasios CHARALAMPOPOULOS, Heinz MUELLER-SCHARER, Norbert SCHNEIDER, Bence SZABO, Zoltan SUMEGHY, Anna PALDY, Donat MAGYAR, Karl-Christian BERGMANN, aron Jozsef DEAK, Edit MIKO, Michel THIBAUDON, Gilles OLIVER, Roberto ALBERTINI, Maira BONINI, Branko SIKOPARIJA, Predrag RADISIC, Mirjana Mitrovic JOSIPOVIC, Regula GEHRIG, Elena SEVEROVA, Valentina SHALABODA, Barbara STJEPANOVIC, Nicoleta IANOVICI, Uwe BERGER, Andreja Kofol SELIGER, Ondřej RYBNÍČEK (203 Czech Republic, belonging to the institution), Dorota MYSZKOWSKA, Katarzyna DABROWSKA-ZAPART, Barbara MAJKOWSKA-WOJCIECHOWSKA, Elzbieta WERYSZKO-CHMIELEWSKA, Lukasz GREWLING, Piotr RAPIEJKO, Malgorzata MALKIEWICZ, Ingrida SAULIENE, Olexander PRYKHODO, Anna MALEEVA, Victoria RODINKOVA, Olena PALAMARCHUK, Jana SCEVKOVA and James M BULLOCK
Edition
Science of the Total Environment, AMSTERDAM, Elsevier, 2023, 0048-9697
Other information
Language
English
Type of outcome
Článek v odborném periodiku
Field of Study
30225 Allergy
Country of publisher
Netherlands
Confidentiality degree
není předmětem státního či obchodního tajemství
References:
Impact factor
Impact factor: 9.800 in 2022
RIV identification code
RIV/00216224:14110/23:00133787
Organization unit
Faculty of Medicine
UT WoS
001160018800001
Keywords in English
Ambrosia; Aerobiology; Flowering phenology; Artificial intelligence; Climate change; Data reconstruction; Health risk; Invasive species
Tags
International impact, Reviewed
Změněno: 15/3/2024 14:12, Mgr. Tereza Miškechová
Abstract
V originále
Ongoing and future climate change driven expansion of aeroallergen-producing plant species comprise a major human health problem across Europe and elsewhere. There is an urgent need to produce accurate, temporally dynamic maps at the continental level, especially in the context of climate uncertainty. This study aimed to restore missing daily ragweed pollen data sets for Europe, to produce phenological maps of ragweed pollen, resulting in the most complete and detailed high-resolution ragweed pollen concentration maps to date. To achieve this, we have developed two statistical procedures, a Gaussian method (GM) and deep learning (DL) for restoring missing daily ragweed pollen data sets, based on the plant's reproductive and growth (phenological, pollen production and frost-related) characteristics. DL model performances were consistently better for estimating seasonal pollen integrals than those of the GM approach. These are the first published modelled maps using altitude correction and flowering phenology to recover missing pollen information. We created a web page (http://euragweedpollen.gmf.u-szeged.hu/), including daily ragweed pollen concentration data sets of the stations examined and their restored daily data, allowing one to upload newly measured or recovered daily data. Generation of these maps provides a means to track pollen impacts in the context of climatic shifts, identify geographical regions with high pollen exposure, determine areas of future vulnerability, apply spatially-explicit mitigation measures and prioritize management interventions.