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Überwachung Luftqualität Transformation Areal Rosental: Flüchtige Schadstoffe
Bedingt durch die frühere Nutzung des Rosental Areals – auch bekannt als die Wiege der Basler Chemie - ist der Untergrund mit Schadstoffen belastet. Während der Tiefbauarbeiten im Rahmen der «Transformation [Rosental Mitte](https://rosentalmitte.ch/)» überwacht das [Lufthygieneamt beider Basel (LHA)](https://www.baselland.ch/politik-und-behorden/direktionen/bau-und-umweltschutzdirektion/lufthygiene) die Immissionen mittels Messungen der Luft [(Dashboard)](https://data.bs.ch/pages/rosental-dashboard/). Änderungsprotokoll:23.4.2024: Die Messstation ROSEN 3 wurde verschoben. Alte geografische Breiten- und Längengrade 47.567827676637364, 7.603804744961502. Neue Breiten- und Lägengrade 47.567997530870265, 7.60479830196066.
Coronavirus (COVID-19): Massentests an Schulen der Sekundarstufe II
Dieser Datensatz zeigt die Resultate der SARS-CoV-2-Tests, welche an Schüler:innen und Lehrpersonen in baselstädtischen Schulen der Sekundarstufe II durchgeführt wurden. An dieser Schulstufe werden Einzeltests durchgeführt. Weitere Informationen zum Coronavirus in Basel-Stadt: [https://www.bs.ch/gd/md/gesundheitsschutz/uebertragbarekrankheiten/grippe-corona-und-co](https://www.bs.ch/gd/md/gesundheitsschutz/uebertragbarekrankheiten/grippe-corona-und-co)Dieser Datensatz wird seit Ende Februar 2022 nicht mehr aktualisiert. Seit Mitte März 2022 werden die Daten zu Tests in Basler Schulen in einem neuen Datensatz veröffentlich: [https://data.bs.ch/explore/dataset/100183/](https://data.bs.ch/explore/dataset/100183/)
U-Abos nach Alter und Wohnsitz
Der Datensatz enthält Informationen zu Umweltschutz-Abonnements (U-Abos) im Tarifverbund Nordwestschweiz (TNW). Er zeigt die Anzahl der U-Abos sowie den Bevölkerungsanteil mit U-Abo nach Wohnsitz, Kategorie, Altersgruppe und Jahr. Der Bevölkerungsanteil mit U-Abo wurde berechnet auf Basis der ständigen Wohnbevölkerung laut Bundesamt für Statistik (BFS).Erhebungsmethode:Die Daten werden jährlich vom Tarifverbund Nordwestschweiz (TNW) bereitgestellt. Sie basieren auf den Verkaufszahlen der Abonnements.
Empfohlene Schwimmbereiche im Rhein
Der Datensatz enthält die empfohlenen Schwimmbereiche im Rhein.
Smarte Strasse: Luftqualität Vergleichsmessungen
Das [Lufthygieneamt beider Basel](https://www.baselland.ch/politik-und-behorden/direktionen/bau-und-umweltschutzdirektion/lufthygiene) (LHA) testet im Projekt «Smarte Strasse» kosteneffiziente Mikrosensoren auf ihre Genauigkeit und Zuverlässigkeit. Der installierte Sensor vom Typ «Nubo» der Firma Sensirion AG ist in der Lage, die Konzentration verschiedener Schadstoffe in der Luft in Echtzeit zu ermitteln. Gemessen werden die Gehalte der Gase Stickstoffdioxid (NO2) und Ozon (O3), sowie die feinere Fraktion des Feinstaubs «PM2.5». Dieser Datensatz enthält die Daten von drei «Nubo»- Sensoren, welche an den permanenten Messstationen des LHA am St. Johanns-Platz, an der Feldbergstrasse und auf der Autobahn A2 in der Hard installiert und gegen die Referenzmessgeräte des LHA verglichen werden.Genaue Standorte dieser Sensoren: Feldbergstrasse: 2611747 / 1268491, [Kartenansicht](https://map.geo.admin.ch/?X=268491&Y=611747&zoom=9&lang=de&topic=ech&bgLayer=ch.swisstopo.pixelkarte-farbe&crosshair=bowl&layers=ch.swisstopo.zeitreihen,ch.bfs.gebaeude_wohnungs_register,ch.bav.haltestellen-oev,ch.swisstopo.swisstlm3d-wanderwege,ch.astra.wanderland-sperrungen_umleitungen&layers_opacity=1,1,1,0.8,0.8&layers_visibility=false,false,false,false,false&layers_timestamp=18641231,,,,)St. Johanns-Platz: 2610790 / 1268370, [Kartenansicht](https://map.geo.admin.ch/?X=268370&Y=610790&zoom=9&lang=de&topic=ech&bgLayer=ch.swisstopo.pixelkarte-farbe&crosshair=bowl&layers=ch.swisstopo.zeitreihen,ch.bfs.gebaeude_wohnungs_register,ch.bav.haltestellen-oev,ch.swisstopo.swisstlm3d-wanderwege,ch.astra.wanderland-sperrungen_umleitungen&layers_opacity=1,1,1,0.8,0.8&layers_visibility=false,false,false,false,false&layers_timestamp=18641231,,,,)A2 Hard: 2615839 / 1265282, [Kartenansicht](https://map.geo.admin.ch/?X=265282&Y=615839&zoom=9&lang=de&topic=ech&bgLayer=ch.swisstopo.pixelkarte-farbe&crosshair=bowl&layers=ch.swisstopo.zeitreihen,ch.bfs.gebaeude_wohnungs_register,ch.bav.haltestellen-oev,ch.swisstopo.swisstlm3d-wanderwege,ch.astra.wanderland-sperrungen_umleitungen&layers_opacity=1,1,1,0.8,0.8&layers_visibility=false,false,false,false,false&layers_timestamp=18641231,,,,)Weitere Informationen zur Luftqualität in der Region Basel sind auf [www.luftqualitaet.ch](https://www.luftqualitaet.ch) verfügbar. Hintergrundinformationen zu Ozon und Feinstaub auf den Webseiten [www.ozon-info.ch](https://ozon-info.ch/) und [www.feinstaub.ch](https://feinstaub.ch/). Angaben zu den gesundheitlichen Auswirkungen der Luftverschmutzung auf der Webseite [https://www.swisstph.ch/de/projects/ludok/healtheffects/](https://www.swisstph.ch/de/projects/ludok/healtheffects/).Weitere Informationen und Daten rund um das Projekt «Smarte Strasse» finden Sie unter den folgenden Links:Die Luftqualitäts-Daten der Sensoren an der smarten Strasse finden Sie hier: [https://data.bs.ch/explore/dataset/100093/](https://data.bs.ch/explore/dataset/100093/) Die Maximalwerte (O3) und Mittelwerte (NO2, PM 2.5) des Vortages sind zudem unter folgendem Datensatz zu finden: [https://data.bs.ch/explore/dataset/100174/](https://data.bs.ch/explore/dataset/100174/)Weitere Informationen zum Projekt «Smarte Strasse»: [https://www.bs.ch/medienmitteilungen/pd/2022-pilotprojekt-smarte-strasse-neue-technologien-im-test-fuer-die-stadt-von-morgen](https://www.bs.ch/medienmitteilungen/pd/2022-pilotprojekt-smarte-strasse-neue-technologien-im-test-fuer-die-stadt-von-morgen) Genaue Standorte aller Sensoren: [https://data.bs.ch/explore/dataset/100114/](https://data.bs.ch/explore/dataset/100114/) Weitere Datensätze rund um das Thema «Smarte Strasse»: [https://data.bs.ch/explore/?refine.tags=smarte+strasse](https://data.bs.ch/explore/?refine.tags=smarte+strasse) Hinweis: Die Luft-Sensoren an der Gundeldingerstrasse wurden am 29.6.23 abmontiert. Seit Anfang/Mitte Juni wurden keine Daten mehr erhoben.
Haltestellen des öffentlichen Verkehrs
Der Datensatz zeigt die Haltestellen des öffentlichen Verkehrs im Kanton Basel-Stadt sowie teilweise in der trinationalen Agglomeration. Es wird nach Transportunternehmen, Art und Typ der Haltestelle unterschieden.
Assessing ecosystem state with environmental DNA of aquatic insects
Data associated to the publication "Environmental DNA sequences from aquatic insects indicate freshwater ecosystem state" Authors: Flurin Leugger, Martina Lüthi, Meret Jucker, Virginie Marques, Sarah Thurnheer, Zacharias Kontarakis and Loïc Pellissier Contact: flurinleugger@gmail.com loic.pellissier@usys.ethz.ch Project description: In this project, we aimed to compare kick-sampling-derived taxa lists and ecosystem state classifications (IBCH: Indece biologique Suisse) with eDNA metabarcoding and CRISPR-Dx. Additionally, we calculated the association with environmental variables and ecosystem state. We retrieved the kick-sampling-derived data from Haberthür et al. (2021) and Keck et al. (2023). We collected eDNA samples in 36 sites in the Rhine catchment in Switzerland (lowland) which are used for the national monitoring of freshwater in Summer 2024. We extracted the samples in the clean lab at ETH using the protocol described in Leugger et al. (2025). We used the 16S Ins primer (Elbrecht et al. 2016) for metabarcoding and for CRISPR analysis. To select indicator eDNA metabarcoding sequences, we applied a machine learning approach combining LASSO and rpart decision trees. For CRISPR-Dx, we used the rules of Leski et al. (2023) to in silicon predict detections based on the metabarcoding sequences and used the same machine learning approach as for the indicator metabarcoding eDNA sequences (see publication for more details). The data for the environmental variables is from the SWECO25 database (https://zenodo.org/communities/sweco25/records?q=&l=list&p=1&s=10&sort=newest; Külling et al. 2024). Folders: catchments\: Catchments in Switzerland, downloaded from https://data.geo.admin.ch/browser/index.html#/collections/ch.bafu.wasser-einzugsgebietsgliederung/items/wasser-einzugsgebietsgliederung?.language=en&.asset=asset-wasser-einzugsgebietsgliederung_2056-gpkg-zip The subfolder upstream_catchments includes the catchment for each buffer size tested. comparison_classification_methods\: File with the ecosystem state classification based on kick-sampling, indicator eDNA metabarcoding sequences (using the rpart decision tree) and CRISPR-Dx (using predicted, lab and retrained rpart trees). eDNA\: Folder metabarcoding\: Raw and cleaned metabarcoding data (ASVs) per environmental extract (EVE), including taxa information from Ecotag reference data base. Additionally, the rpart trees for indicator sequences only from Ephemeroptera and all EPT are provided. Columns which might not be self explanatory taxon: identified taxon rank: rank of identified taxon nb_reads: read numbers EVS and metabarcoding: key columns to link with metadata files ASV_cleaned_by_site.csv: Read count by site (after cleaning) ASV_raw_by_site.csv: Read count by site (before cleaning), column 'NC' is for the negative controls sequence_count_per_site.csv: Comparison of reads per site before and after cleaning/filtering. 'NC' refers again to Negative Controls. Folder CRISPR\: crispr_by_site.csv: Lab-based detection of the guide per site. Maximum number of detections is 6, as each site had two environmental extracts (EVE), and the PCR replicates were combined in 3 pools each. GRN refers to lab internal numbering of CRISPR-Dx assays. detection_matrix_Ephemeroptera_28_site.csv: Predicted detection based on eDNA metabarcoding sequences and the model of Leski et al 2023 per site. rpart_model_Ephemeroptera.rds: best performing rpart model for ecosystem state classification using the predicted CRISPR-Dx detections rpart_model_retrained.rds: best performing rpart model for ecosystem state classification using the actual lab-based CRISPR-Dx detections (thus "retrained" based on actual detections). IBCH\: IBCH_classification_filtered_and_extended.csv: includes IBCH_cat (ecosystem category from kick-sampling with IBCH 2019 categorization). IBCH_taxa_kick-sampling.csv: contains taxa detect per site (site_code as column name to link with metadata or eDNA data) kicknet_Trend_IBCH_sites.csv: taxa detected by site, raw data metadata\: Folder containing files with overview of site names, extract number and coordinates. Columns named "metabarcoding" (and "EVS") are keys to link rows from the different tables. SWECO25\: Folder containing raster stack from SWECO25 data (Külling et al. 2024) used in the article and a table with the extracted variable value per site/catchment with the different upstream buffer sizes tested. site_code: Code for the sampling site, see also metadata to link to EVS Temperature_avg: annual mean temperature in upstream catchment [°C] Precip_annual: annual precipitation [mm] Population_density: mean population density in 25m cells Traffic_noise: noise levels EVI, NDVI and LAI: each standard deviation (sd) and average (avg) value per upstream catchment Natural rivers: proportion of upstream river length which is classified as natural Little-disturbed_rivers: proportion of upstream river length which is classified as little disturbed Heavily-disturbed_rivers: proportion of upstream river length which is classified as heavily disturbed unnatural_rivers: proportion of upstream river length which is classified as unnatural culverted_rivers: proportion of upstream river length which is culverted Forest_edges: proportion of forest edges in upstream catchment Forest: proportion of forest in upstream catchment Crops: proportion of crops in upstream catchment Built_environment: proportion of built environment in upstream catchment buffer: buffer width for upstream catchment area [m] catchment_area_m2: upstream catchment area in square meters References: Elbrecht, V., Taberlet, P., Dejean, T., Valentini, A., Usseglio-Polatera, P., Beisel, J. N., Coissac, E., Boyer, F., & Leese, F. (2016). Testing the potential of a ribosomal 16S marker for DNA metabarcoding of insects. PeerJ, 2016(4). https://doi.org/10.7717/peerj.1966 Haberthür, M. (2021). Ergebnisse der 3. Erhebung NAWA-Trend Los 2, Makrozoobenthos. https://www.google.com/url?sa=t&source=web&rct=j&opi=89978449&url=https://www.bafu.admin.ch/dam/bafu/de/dokumente/wasser/externe-studien-berichte/nawa_trend_biologie_2019-teil_makrozoobenthos.pdf.download.pdf/nawa_trend_biologie_2019-teil_makrozoobenthos.pdf&ved=2ahUKEwjI5crG-IaPAxUF_gIHHQisBZEQFnoECBgQAQ&usg=AOvVaw1QL3GRZdTllPsHLQ6hQtlP Külling, N., Adde, A., Fopp, F., Schweiger, A. K., Broennimann, O., Rey, P. L., Giuliani, G., Goicolea, T., Petitpierre, B., Zimmermann, N. E., Pellissier, L., Altermatt, F., Lehmann, A., & Guisan, A. (2024). SWECO25: a cross-thematic raster database for ecological research in Switzerland. Scientific Data, 11(1). https://doi.org/10.1038/s41597-023-02899-1 Leski, T. A., Spangler, J. R., Wang, Z., Schultzhaus, Z., Taitt, C. R., Dean, S. N., & Stenger, D. A. (2023). Machine learning for design of degenerate Cas13a crRNAs using lassa virus as a model of highly variable RNA target. Scientific Reports, 13(1), 6506. https://doi.org/10.1038/s41598-023-33494-4 Leugger, F., Lüthi, M., Schmidlin, M., Kontarakis, Z., & Pellissier, L. (2025). Rapid field-based detection of a threatened and elusive species with environmental DNA and CRISPR-Dx. Global Ecology and Conservation, 59, e03518. https://doi.org/10.1016/j.gecco.2025.e03518
Phenotypic and Growth Stage Development Data of a Quercus robur Mycorrhization Experiment
In this experiment, we investigated the inoculation-effects of two ectomycorrhizal fungi (EMF) species with contrasting evolutionary histories, ecological properties, host-preferences, and habitat-ranges on phenotypic responses and growth dynamics of pedunculate oak (*Quercus robur*), an ecologically and economically important temperate forest tree species. We set up the mycorrhization experiment using 96 plants of a genetically uniform *Q. robur* clone (DF159) and applied four treatments: A control treatment; an inoculation-treatment with the cosmopolitan Ascomycete *Cenococcum geophilum*, which is commonly found in oak forests; an inoculation-treatment with the Basidiomycete *Piloderma croceum*, which has not yet been found in natural oak forests but has been shown in previous experiments to support oak growth; and a co-inoculation treatment. We then assessed growth stage development of the trees over eight experimental weeks and measured various phenotypic traits during a destructive sampling.
Terrestrial laser scans on Hammarryggen Ice Rise, Dronning Maud Land, East Antarctica
Surface topography maps (spatial extent: 400 m x 400 m) obtained at approximately 300 m from the top of the Hammarryggen Ice Rise in Dronning Maud Land, East Antarctica, using a Riegl VZ-6000 Terrestrial Laser Scanner (TLS). Scans were obtained on 5 days in the 2018-2019 Austral summer: on December 21 and 27, and January 2, 4 and 11. By using reflectors installed on bamboo poles, scans were registered with respect to the reflectors, such that the difference between two successive scans reveals the spatial patterns of erosion and deposition of snow. On each scan day, we used multiple scan positions to create one combined point cloud. After applying an octree filter on the point cloud, a 3D surface was obtained. For each day, the dataset contains a 1 mm and a 10 cm octree filter resolution file, only including points in a 400 m x 400 m area centered around the scan positions. Notes: * All files in the dataset are in the same coordinate system. However, this coordinate system is arbitrary (i.e., not related to any global coordinate system). * From the installed reflectors, 4 reflectors could be used over the full period. The scan accuracy is generally higher within the area enclosed by the reflectors. * The scans from January 2 were found to have exhibited small tilt during the scan and are of lesser accuracy. * By walking along fixed corridors, disturbance of the snow was limited.
Daily data of solute and stable water isotopes in stream water and precipitation in the Alp catchment, Central Switzerland
This dataset contain measurements of solute and stable water isotopes in stream water and precipitation in the Alp catchment and two of its tributaries (between 2015 -2018) . The river Alp is a snow-dominated catchment situated in Central Switzerland characterized by an elevation range from 840 to 1898 m a.s.l. The dataset provides solutes (major anions and cations, trace metals) and stable water isotopes and water fluxes (precipitation rates, discharge) at daily intervals from several sampling locations. An updated version of the isotope dataset is available here: https://www.doi.org/10.16904/envidat.242