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Luftqualitätsdaten (Datenstrom B) - Beurteilungsgebiete 2024 (Datensatz)

Datenstrom B umfasst alle Informationen zu den Beurteilungsgebieten – wie Name, Gebietscode, Abgrenzung, Einwohnerzahl, Historie, Schadstoffe und Schutzziele, Fristverlängerung.

Luftqualitätsdaten (Datenstrom D) - Beurteilungsmethoden 2024 (INSPIRE View/WMS)

Datenstrom D umfasst alle Informationen zu den Beurteilungsmethoden.

Luftqualitätsdaten (Datenstrom E1a) - Validierte Einzelwerte 2019 (Datensatz)

Datenstrom E1a umfasst gemessene (Link zu Datenstrom D) Einzelwerte von gasförmigen Schadstoffen (z. B. Ozon, Stickstoffdixoid, Schwefeldioxid, Kohlenmonoxid), von partikelförmigen Schadstoffen (z.B. Feinstaub, Ruß, Gesamtstaub) und Staubinhaltsstoffen (z.B. Schwermetalle, PAK in PM10, PM2.5, TSP) sowie der Gesamtdeposition (BULK), der nassen Deposition und meteorologische Messgrößen (z.B. Temperatur, Windgeschwindigkeit, Luftdruck), für die eine Datenbereitstellungspflicht besteht. Der Bericht umfasst zudem die Datenqualitätsziele (Messunsicherheit, Mindestzeiterfassung (time coverage) erfüllt ja/nein, Mindestdatenerfassung (data capture) erfüllt ja/nein) und Informationen zu Konzentrationswerten die natürlichen Quellen und der Ausbringung von Streusand und –salz zuzurechnen sind (Konzentrationswerte ohne etwaige Korrekturabzüge).

Global optimized REVEALS reconstruction of past vegetation cover for taxonomically harmonized pollen data sets

This data set presents the reconstructed vegetation cover for 3083 sites based on harmonized pollen data from the data set LegacyPollen 2.0 (https://doi.pangaea.de/10.1594/PANGAEA.965907) and optimized RPP values. 1115 sites are located in North America, 1435 in Europe, and 533 in Asia. Sugita's REVEALS model (2007) was applied to all pollen records using REVEALSinR from the DISQOVER package (Theuerkauf et al. 2016). Pollen counts were translated into vegetation cover by taking into account taxon-specific pollen productivity and fall speed. Additionally, relevant source areas of pollen were also calculated using the aforementioned taxon-specific parameters and a gaussian plume model for deposition and dispersal. In this optimized reconstruction, relative pollen productivity estimates for the ten most common taxa were first optimized by using reconstructed tree cover from modern pollen samples and LANDSAT remotely sensed tree cover (Townshend 2016) for North America, Europe, and Asia. Values for non-optimized taxa for relative pollen productivity and fall speed were taken from the synthesis from Wiezcorek and Herzschuh (2020). The average values from all Northern Hemisphere values were used where taxon-specific continental values were not available. We present tables with optimized reconstructed vegetation cover for all Europe, North America and Asia. As further details we list a table with the taxon-specific parameters used and a list of parameters adjusted in the default version of REVEALSinR.

REVEALS reconstruction of past vegetation cover with optimized RPP values for European samples

This data set presents the reconstructed vegetation cover for 1451 European sites based on harmonized pollen data from the data set LegacyPollen 2.0 and optimized RPP values. Sugita's REVEALS model (2007) was applied to all pollen records using REVEALSinR from the DISQOVER package (Theuerkauf et al. 2016). Pollen counts were translated into vegetation cover by taking into account taxon-specific pollen productivity and fall speed. Additionally, relevant source areas of pollen were also calculated using the aforementioned taxon-specific parameters and a gaussian plume model for deposition and dispersal and forest cover was reconstructed. In this optimized reconstruction, relative pollen productivity estimates for the ten most common taxa were first optimized by using reconstructed tree cover from modern pollen samples and LANDSAT remotely sensed tree cover (Sexton et al. 2013) for Europe. Values for non-optimized taxa for relative pollen productivity and fall speed were taken from the synthesis from Wiezcorek and Herzschuh (2020). The average values from all Northern Hemisphere values were used where taxon-specific continental values were not available. We present tables with optimized reconstructed vegetation cover for all records in Europe. As further details we list a table with the taxon-specific parameters used and a list of parameters adjusted in the default version of REVEALSinR.

REVEALS reconstruction of past vegetation cover with optimized RPP values for Asian samples

This data set presents the reconstructed vegetation cover for 706 Asian sites based on harmonized pollen data from the data set LegacyPollen 2.0 and optimized RPP values. Sugita's REVEALS model (2007) was applied to all pollen records using REVEALSinR from the DISQOVER package (Theuerkauf et al. 2016). Pollen counts were translated into vegetation cover by taking into account taxon-specific pollen productivity and fall speed. Additionally, relevant source areas of pollen were also calculated using the aforementioned taxon-specific parameters and a gaussian plume model for deposition and dispersal and forest cover was reconstructed. In this optimized reconstruction, relative pollen productivity estimates for the ten most common taxa were first optimized by using reconstructed tree cover from modern pollen samples and LANDSAT remotely sensed tree cover (Sexton et al. 2013) for Asia. Values for non-optimized taxa for relative pollen productivity and fall speed were taken from the synthesis from Wiezcorek and Herzschuh (2020). The average values from all Northern Hemisphere values were used where taxon-specific continental values were not available. We present tables with optimized reconstructed vegetation cover for records in Asia. As further details we list a table with the taxon-specific parameters used and a list of parameters adjusted in the default version of REVEALSinR.

Luftqualitätsdaten (Datenstrom D) - Beurteilungsmethoden 2022 (INSPIRE View/WMS)

Datenstrom D umfasst alle Informationen zu den Beurteilungsmethoden.

Luftqualitätsdaten (Datenstrom B) - Beurteilungsgebiete 2022 (INSPIRE View/WMS)

Datenstrom B umfasst alle Informationen zu den Beurteilungsgebieten – wie Name, Gebietscode, Abgrenzung, Einwohnerzahl, Historie, Schadstoffe und Schutzziele, Fristverlängerung.

Luftqualitätsdaten (Datenstrom G) - Erreichung der Umweltziele 2024 (INSPIRE View/WMS)

Datenstrom G bildet die formale gebietsbezogene Beurteilung der Luftqualität in Bezug auf Grenz- und Zielwerte ab, ggf. unter Berücksichtigung gewährter Fristverlängerung und bereinigt um Beiträge aus natürlichen Quellen und der Ausbringung von Streusand und –salz im Winterdienst.

Luftqualitätsdaten (Datenstrom D) - Beurteilungsmethoden 2024 (INSPIRE Download/WFS)

Datenstrom D umfasst alle Informationen zu den Beurteilungsmethoden.

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