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TURDATA: a database of low-cost air quality and remote sensing measurements for the validation of micro-scale models in the real Prague urban environments
<p><strong>README</strong></p> <p>TURDATA is a supplementary data set for the TURBAN project Prague observation campaign described in the manuscript Bauerová et al. 2024 (submitted for publication). The measurement campaign was focused on air pollution and meteorological measurement, including vertical profiles in selected part of Prague city centre called here as Legerova domain. Within this area, one professional meteorological station (MS) Prague Karlov and one reference traffic air quality monitoring (AQM) station Prague 2-Legerova (classified as traffic hotspot) are located. To gain high spatial and temporal resolution data, the supplementary measurement network was established, which consisted of:</p> <p>- 20 combined low-cost sensor (LCS) stations for monitoring of PM<sub>10</sub>, PM<sub>2.5</sub>, NO<sub>2</sub> and O<sub>3</sub> concentrations (using Plantower PMS7003 particle counters and Envea Cairsense electrochemical sensors) placed in different sites and different height levels AGL (higher = H, lower = L),</p> <p>- 1 mobile telescopic meteorological mast for measuring temperature, relative humidity, wind velocity and direction and air pressure (using 2D ultrasonic anemometer Gill WindSonic 60 and weather station Gill MetConnect THP),</p> <p>- 1 MTP-5-He microwave radiometer (MWR; Attex) for temperature vertical profile,</p> <p>- 1 StreamLine XR Doppler LIDAR (HALO Photonics) for wind vertical profile. </p> <p>The main Legerova campaign lasted from 30 May 2022 to 28 March 2023 with some exceptions (see <em>TURDATA_metadata.xlsx</em> with all details). Because LCSs are known for their highly variable measurement quality, before their deployment the Legerova campaign, a sufficiently long-term initial field comparative measurement of all LCSs at RM Prague 4-Libuš was carried out (lasting from 16/12/2021 to 30/5/2022). The results showed that most of the LCSs were in raw measurement differently zero-shifted against each other and against gaseous reference or aerosol optical equivalent monitors (RMs or EMs). Therefore, the Multivariate Adaptive Regression Splines (MARS) method was applied to calculate corrected LCS concentrations based on initial field comparative measurement complemented by meteorological data from MS Prague Libuš. To check the quality of raw and MARS corrected LCS concentrations at the end of the measurement campaign, the final comparative field measurement of all LCSs at Prague 4-Libuš RM station was performed.</p> <p>Therefore, in case of LCSs measurement (both raw and corrected) the important columns of location (measurement placement: RM_Prague_4-Libus and Legerova_domain) and measurement_program (Initial_comparative_measurement, Legerova_campaign and Final_comparative_measurement) were added.</p> <p>In case of PM<sub>10</sub> and PM<sub>2.5</sub> measurement the maximum raw and MARS-corrected concentrations were influenced by temporary pollution episode on 26 July 2022 around 4 a.m. and 9 p.m. (both UTC) caused by aerosol pollution transported from large forest fire in Hřensko (the northern part of the Czech Republic). </p> <p> </p> <p>TURDATA includes the following files:</p> <p>1. <strong>TURDATA_metadata_and_photos.zip</strong> containing:</p> <p>- "<em>TURDATA_metadata.xlsx</em>" with the important list of metadata about devices placement, locations parameters and measurement periods</p> <p>- Folder "<em>Photos_from_Legerova_campaign</em>" with photos from Legerova measurement campaign</p> <p>2. <strong>AQ_LCSs_raw_measurement_TURDATA.zip</strong> containing:</p> <p>- "<em>NO2_RAW_LCSs_TURDATA.xlsx</em>" with complete data set of NO<sub>2</sub> raw measured concentrations by all LCSs</p> <p>- "<em>O3_RAW_LCSs_TURDATA.xlsx</em>" with complete data set of O<sub>3</sub> raw measured concentrations by all LCSs</p> <p>- "<em>PM10_RAW_LCSs_TURDATA.xlsx</em>" with complete data set of PM<sub>10</sub> raw measured concentrations by all LCSs</p> <p>- "<em>PM2_5_RAW_LCSs_TURDATA.xlsx</em>" with complete data set of PM<sub>2.5</sub> raw measured concentrations by all LCSs</p> <p>- "<em>AQ_LCSs_raw_measurement_TURDATA_readme.txt</em>" with all necessary information for correct data use</p> <p>3. <strong>AQ_data_RM_stations_Prague_TURDATA.zip</strong> containing:</p> <p>- "<em>AQ_data_Prague_RM_stations_TURDATA_12-2021_06-2023.xlsx</em>" with air quality data measured by reference AQM stations in Prague</p> <p>- "<em>AQ_data_RM_stations_Prague_TURDATA_readme.txt</em>" with all necessary information for correct data use</p> <p>4. <strong>Meteo_data_Prague_MS_TURDATA.zip</strong> containing:</p> <p>- "<em>Meteo_data_Prague_MS_TURDATA_12-2021_06-2023.xlsx</em>" with meteorological data measured by professional meteorological stations in Prague</p> <p>- "<em>Meteo_data_Prague_MS_TURDATA_readme.txt</em>" with all necessary information for correct data use</p> <p>5. <strong>AQ_LCSs_MARS-corrected_measurement_TURDATA.zip</strong> containing:</p> <p>- "<em>NO2_COR_LCSs_TURDATA.xlsx</em>" with complete data set of NO<sub>2</sub> MARS-corrected concentrations for all LCSs</p> <p>- "<em>O3_COR_LCSs_TURDATA.xlsx</em>" with complete data set of O<sub>3</sub> MARS-corrected concentrations for all LCSs</p> <p>- "<em>PM10_COR_LCSs_TURDATA.xlsx</em>" with complete data set of PM<sub>10</sub> MARS-corrected concentrations for all LCSs</p> <p>- "<em>PM2_5_COR_LCSs_TURDATA.xlsx</em>" with complete data set of PM<sub>2.5</sub> MARS-corrected concentrations for all LCSs</p> <p>- "<em>AQ_LCSs_MARS-corrected_measurement_TURDATA_readme.txt</em>" with all necessary information for correct data use and brief description of MARS correction method</p> <p>6. <strong>Meteo-mast_PVK_measurement_TURDATA.zip</strong> containing:</p> <p>- "<em>Meteo-mast_PVK_TURDATA_06-2022_06_2023.xlsx</em>“ with non-referential meteorological data measured by mobile meteo-mast</p> <p>- "<em>Meteo-mast_data_PVK_TURDATA_readme.txt</em>" with all necessary information for correct data use</p> <p>7. <strong>MWR_temperature_profile_TURDATA.zip</strong> containing:</p> <p>- "<em>MWR_5min_temperature_TURDATA_02-2022_03-2023.xlsx</em>" with raw temperature vertical profile measurement from microwave radiometer</p> <p>- "<em>MWR_1hour_temperature_TURDATA.xlsx</em>" with 1-hour averaged temperature vertical profile from microwave radiometer</p> <p>- "<em>MWR_1hour_TMP_gradient_TURDATA.xlsx</em>" with 1hour temperature gradient calculated from raw temperature profiles measured by microwave radiometer</p> <p>- "<em>MWR_temperature_profile_TURDATA_readme.txt</em>" with all necessary information for correct data use</p> <p>8. <strong>LIDAR_wind_profile_TURDATA.zip</strong> contains:</p> <p>- Individual folders "yyyymm“ -> "yyyymmdd"</p> <p>- Each daily folder "yyyymmdd" contains files:</p> <p>a) "<em>Processed_Wind_Profile_188_yyyymmdd_hhmmss.hpl</em>" with processed WV and WS data</p> <p>b) "<em>Wind_Profile_188_yyyymmdd_hhmmss.hpl</em>" with non-processed Doppler wind profile data</p> <p>- "<em>LIDAR_wind_profile_TURADATA_readme.txt</em>" with all necessary information for correct data use</p>
Worldwide Unified Wildland-Urban Interface (WUWUI) database
<p>This is the Worldwide Unified Wildland-Urban Interface (WUWUI) database developed by the study entitled "Global Expansion of Wildland-Urban Interface (WUI) and WUI fires: Insights from a Multiyear Worldwide Unified Database (WUWUI)" published on Environmental Research Letters (<strong>DOI</strong> 10.1088/1748-9326/ad31da).</p> <p>Please use the latest version.</p>
Concrete habitat: Impervious surface in nest vicinity is associated with avian fitness decline in two urban adapters
<p>The conversion of natural habitats to impervious surfaces in cities affects biotic and abiotic attributes of urban ecosystems. Detailed information on the gradual influence of impervious surfaces on reproductive success, however, is lacking. Using five years of nestbox-breeding great tit and blue tit breeding data collected across various habitat types within and outside a Central-Eastern European capital city, we quantified the impact of impervious surfaces on avian reproductive success. Impervious surfaces strongly and negatively covaried with the number of fledged young in both species: a 50% increase in impervious surface resulted in 2.93 (95% CI: -4.27; -1.58) fewer blue tit offspring fledging the nest, and 3.51 (95% CI: -4.79; -2.23) fewer great tit offspring fledging the nest, thus halving the reproductive output of two widespread urban species. These results provide benchmark values of avian productivity for ecologists and urban policy makers, and for the management of urban areas.</p>
Fig. 3 in Role of urban forests as a source of diversity of carabids (Coleoptera: Carabidae) in urbanised areas
Fig. 3. DCA ordination diagram of ecological groups of Carabidae (Eu – eurytopic species, Fo – forest-related sp., OA – open-area-related sp., Pb – peatbog-related sp., H – hygrophilic sp., Mh – mesohygrophilic sp., M – mesophilic sp., Mxe – mesoxerophilic sp., Xe – xerophilic sp., Ph – phytophages, Hz – hemizoophages, Lz – large zoophages, Mz – medium zoophages, Sz – small zoophages, Au – autumn breeders, Sp – spring breeders, ab – abundance, r – richness, "- trap in the site A, %- trap in the site B, %- trap in the site C).
Fig. 2 in Role of urban forests as a source of diversity of carabids (Coleoptera: Carabidae) in urbanised areas
Fig. 2. RDA ordination diagram of the relationship between species dominance of Carabidae and environmental variables (presence of deciduous and coniferous trees, soil cover, anthropopressure, humidity)
Urban Riparian Wetland Water Quality Dataset_Stormwater Capture in Beaver-mediated Wetlands along Walnut Creek, Raleigh, North Carolina, USA
<p><span>This is the initial release of a </span><strong><span>water quality</span></strong><span> dataset pertaining to the <strong>riparian floodplain wetlands</strong> alongside Walnut Creek in Raleigh, North Carolina USA. Walnut Creek is the main drainage channel in an <strong>urbanized watershed</strong> (HUC-12: 030202011101) in central North Carolina. There are several riparian floodplain wetlands along the creek which are largely supplied by <strong>urban stormwater</strong> runoff including directed <strong>storm sewer flows</strong> and regular <strong>overbank flooding</strong> events. In many of these wetlands local water retention and residence time in the surface ponds is mediated by the damming activity of <strong>North American beavers (</strong><em><strong>Castor canadensis</strong></em><strong>)</strong>. This dataset contains data specific to the water quality values of <strong>Walnut Creek</strong>, its tributary <strong>Little Rock Creek</strong>, and the surface ponds and groundwater at the <strong>Walnut Creek Wetland Park</strong> which is actively influenced by resident beavers. The period of this dataset is from <strong>January </strong></span><strong><span>5</span><span>, 2023 through </span></strong><strong><span>October 28</span><span>, 2023</span></strong><span>. </span></p> <p><span>This dataset includes a variety of common <strong>water quality parameters</strong> measured in situ by use of a <strong>YSI Pro water quality meter</strong>, as well as <strong>dissolved nutrient values</strong> determined by <strong>laboratory analysis</strong> of collected water samples.<span> </span>YSI data was collected on a <strong>weekly</strong> basis and water samples were collected for laboratory analysis on a <strong>monthly</strong> basis. Additional measurements and collection took place during <strong>six large rainfall events</strong> to allow comparison between baseflow and stormflow conditions across the site.<span> </span>This dataset aims to provide a comprehensive look at the water quality of Walnut Creek in comparison with the surface ponds and groundwater in the Walnut Creek Wetland Park, which are all ultimately sourced from <strong>urban stormwater runoff</strong>. </span></p> <p><span>This water quality dataset is intended to accompany the <u>separate</u> <strong>hydrology dataset</strong> published on Zenodo at URL: <a href="https://doi.org/10.5281/zenodo.10709630">https://doi.org/10.5281/zenodo.10709630</a>. Together, these datasets are meant to support an improved understanding of the water availability and water quality found in connection with beaver-mediated stormwater capture in an urbanized watershed in the North Carolina Piedmont.</span></p> <p><span> </span><span>This dataset resulted from research supported with a Graduate Student Research Grant awarded by the <strong>North Carolina Water Resources Research Institute (WRRI)</strong>, under Project Number 23-10-W: "Stormwater Diversion, Storage, and Treatment by Beaver-enhanced Floodplain Wetlands in Piedmont Urban Watersheds". </span></p> <p><span>This material is based upon work supported by the <strong>National Science Foundation (NSF)</strong> Graduate Research Fellowship Program (GRFP) under Grant No. (DGE 2137100). Any opinion, findings, and conclusions or recommendations expressed in this material are those of the authors(s) and do not necessarily reflect the views of the National Science Foundation.</span></p> <p><span>Special thanks to <strong>Raleigh Parks</strong> and <strong>Walnut Creek Wetland Park</strong> for making this work possible.</span></p> <p><span>Laboratory analysis support for evaluation of dissolved nutrients (nitrate+nitrite, TKN, total phosphorus, and total organic carbon) was provided by the <strong>NC State Environmental and Agricultural Testing Services (EATS)</strong> laboratory, Department of Crop and Soil Sciences.</span></p> <p><span> </span><span>Additional laboratory analysis support for evaluation of dissolved nutrients (TKN and total phosphorus) was provided by the <strong>NC State Environmental Analysis Laboratory (EAL)</strong>, Department of Biological and Agricultural Engineering (BAE).</span></p> <p><span> </span><span>Usage of and technical support for the YSI Pro water quality meter used in this study was made possible by the <strong>Osburn Lab</strong>, Department of Marine, Earth and Atmospheric Sciences (MEAS), NC State University.</span></p>
Fig. 1 in Species Diversity And Ecology Of Amphibians And Reptiles In Urbanized Landscapes Of The City Of Minsk
Fig. 1 Location of the largest habitats and stable populations of amphibians and reptiles in the urbanized areas of the Minsk city.
Figure 10 in Ecological Features And Anthropogenic Transformation Of Wetlands As Part Of Urban Floras Of Ukraine
Figure 10. Distribution of plant communities by soil aeration and nitrogen content in soil (legend explanation is given in figure 9).
Figure 9 in Ecological Features And Anthropogenic Transformation Of Wetlands As Part Of Urban Floras Of Ukraine
Figure 9. Distribution of plant communities by variability of damping and total salt regime, where 1: Typhetum angustifoliae Pignatti 1953; 2: Typhetum latifoliae Nowiñski 1930; 3: Phragmitetum australis Savič 1926; 4: Sparganietum erecti Roll 1938; 5: CariciRumicion hydrolapathi Passarge 1964; 6: Senecionion fluviatilis Tx. ex Moor 1958; 7: ChelidonioAcerion negundi L. Ishbirdina et A. Ishbirdin 1991.
Figure 6 in Ecological Features And Anthropogenic Transformation Of Wetlands As Part Of Urban Floras Of Ukraine
Figure 6. Proportion of number of native and adventive plant species in wetland flora in studied territories.
Figure 7 in Ecological Features And Anthropogenic Transformation Of Wetlands As Part Of Urban Floras Of Ukraine
Figure 7. Proportion of number of wetlands plant species by the degree of urbanization in studied territories
Figure 2 in Ecological Features And Anthropogenic Transformation Of Wetlands As Part Of Urban Floras Of Ukraine
Figure 2. Proportion of number of plant species within families of wetland flora in studied territories.
Figure 3 in Ecological Features And Anthropogenic Transformation Of Wetlands As Part Of Urban Floras Of Ukraine
Figure 3. Proportion of number of plant species within soil water regime ecogroups in studied territories.
Figure 4 in Ecological Features And Anthropogenic Transformation Of Wetlands As Part Of Urban Floras Of Ukraine
Figure 4. Proportion of number of plant species within total salt regime ecogroups in studied territories.
Figure 1 in Ecological Features And Anthropogenic Transformation Of Wetlands As Part Of Urban Floras Of Ukraine
Figure 1. The location of the studied cities in Ukraine. (The map from Nations online: https://www. nationsonline.org/oneworld/map/ukrainepoliticalmap.htm).
Deciphering anthropogenic and biogenic contributions to selected NMVOC emissions in an urban area
<p>This netcdf data file is related to a study published in ACP by Peron et al., 2024. Selected concentration, fluxes of NMVOC as well as meteorological data are reported for the urban area of Innsbruck, Austria. For a complete site description we also refer to Ward et al., 2022: https://doi.org/10.5194/acp-22-6559-2022 and Karl et al., 2020: https://doi.org/10.1175/BAMS-D-19-0270.1</p>
Fig. 5 in Effects of urbanization on the diversity of testate amoebae (Protist, Rhizopoda) in a stream of the southwestern Amazon basin (Igarapé São Francisco in Acre state, Brazil)
Fig. 5. Variation in the mean species richness (A) and density (B) of testate amoebae recorded among the different sampling points on the São Francisco stream in Acre state, northern Brazil.
Fig. 4 in Effects of urbanization on the diversity of testate amoebae (Protist, Rhizopoda) in a stream of the southwestern Amazon basin (Igarapé São Francisco in Acre state, Brazil)
Fig. 4. The most abundant species of testate amoeba recorded in the present study: (A) Netzelia corona, (B) Arcella vulgaris, (C) Arcella brasiliensis, (D) Arcella discoide, (E) Centropyxis aculeata. Examples of the species of testate amoeba recorded in the state of Acre for the first time: (F) Difflugia distenda, (G) Difflugia sinuata, (H) Arcella gandalfi.
Fig. 2 in Effects of urbanization on the diversity of testate amoebae (Protist, Rhizopoda) in a stream of the southwestern Amazon basin (Igarapé São Francisco in Acre state, Brazil)
Fig. 2. Phytophysiognomy of sampling points in the São Francisco stream in the state of Acre, Brazil according to the degree of urbanization.
Fig. 1 in Effects of urbanization on the diversity of testate amoebae (Protist, Rhizopoda) in a stream of the southwestern Amazon basin (Igarapé São Francisco in Acre state, Brazil)
Fig. 1. Location of sampling points on the São Francisco stream in the municipalities of Rio Branco and Bujari, in Acre state, northern Brazil.
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.