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154 results for “Heavy metals”
Organic micropollutants and heavy metals in stormwater runoff of five different catchment types in Berlin (Germany)
<p>This dataset includes concentrations of micropollutants (67), heavy metals (8) and standard parameters (9) for stormwater runoff taken from separated sewers of five catchments between 3 and 37 ha in Berlin (Germany). It also includes rain data of analyzed events as separate file. Samples were taken as part of the OgRe research project of Kompetenzzentrum Wasser Berlin (<a href="https://www.kompetenz-wasser.de/en/project/ogre/">www.kompetenz-wasser.de/en/project/ogre/</a>) in 2014 and 2015. Sampling and analytical methods are detailed in "Concentrations of micropollutants in urban stormwater runoff of different land uses" (<a href="https://doi.org/10.3390/w13091312">https://doi.org/10.3390/w13091312</a>). A dataset with concentrations of the urban stream Panke in Berlin during dry and wet weather (samples were taken as part of the same project) is available separately (<a href="https://zenodo.org/record/4633779">https://zenodo.org/record/4633779</a>).</p> <p><strong>Description of fields (concentrations):</strong></p> <ul> <li><strong>SampleID</strong>: unique sample identifier</li> <li><strong>SiteID</strong>: unique site identifier (catchment type) <ul> <li> 1 - OLD: area with typical five-storey perimeter blocks built between 1870 and 1930 (31 ha)</li> <li> 2 - NEW: newer area of 4-8-storey concrete slab buildings built between 1960 and 1980 (16 ha)</li> <li> 3 - STR: 1.3 km of a busy streeat with intersection with traffic lights and bus stops (3 ha)</li> <li> 4 - OFH: a residential area characterized by one-family houses and villas with gardens (17 ha)</li> <li> 5 - COM: a commercial and industrial area of high imperviousness with large flat-roof buildings and yards (37 ha)</li> <li> 6 - PNK: urban stream Panke (characterized by strong stormwater inputs from separate sewer discharges - available in separate dataset)</li> </ul> </li> <li><strong>LocalDateTime</strong>: start time of sampling (local)</li> <li><strong>DateTimeUTC</strong>: start time of sampling (UTC)</li> <li><strong>UTCOffset</strong>: UTC offset to local time in h</li> <li><strong>SampleType</strong>: either "composite" for volume proportional composite sample (all samples from storm sewers) or "single" for grab sample (all stream samples, separate dataset)</li> <li><strong>VariableName</strong>: name of analysed substance/parameter</li> <li><strong>UnitsAbbreviation</strong>: either "ug/L" (microgram per litre) or "mg/L" (milligram per litre)</li> <li><strong>CensorCode</strong>: either "lt" (less than) for concentration below detection limit (value is detection limit) or "nc" (not censored) for concentration above detection limit</li> <li><strong>DataValue</strong>: measured value (if censor code is lt, value indicates detection limit)</li> </ul> <p><strong>Description of fields (rain data):</strong></p> <ul> <li><strong>SampleID</strong>: sample identifier of matching sample (see above)</li> <li><strong>SiteID and SiteName</strong>: unique site identifier and name (catchment type) (see above)</li> <li><strong>tBeg_rain, tEnd_rain</strong>: begin and end of rain event in local time</li> <li><strong>depth.mm</strong>: rain depth of rain event in mm</li> <li><strong>duration_rain.h</strong>: duration of rain event in h</li> <li><strong>intensity_max_10min.mm_h</strong>: maximum rain intensitity of rain event in 10-min interval in mm/h</li> <li><strong>intensity_mean_event.mm_h</strong>: mean rain intensitity of rain event in mm/h</li> <li><strong>ADD.d</strong>: number of antecedent dry days in days</li> </ul> <p>Rain data was collected by rain gauge network of Berlin waterworks (>40 gauges) — gauge with best correlation between rain depth and event volume in storm sewer was chosen (distances to monitoring sites: 2–6 km).</p> <p>Two data files are provided in comma separated format:</p> <ul> <li>"OgRe_drain.csv" contains concentrations of all stormwater runoff samples taken in separate storm sewers</li> <li>"OgRe_rain.csv" contains rain data for all stormwater runoff samples</li> </ul>
Butterfly heavy metal content, wing size, egg count, and brain mass in the Minneapolis-St. Paul (MSP) Metropolitan Area
We collected 26 common species of butterflies across a gradient of lead pollution in the Twin Cities metropolitan area (Minneapolis and St. Paul, MN, USA). We measured their thorax lead concentrations and their body condition including wing area, number of eggs, and brain mass. We also quantified lead in the soil, host plant leaves, and air (through lichen bio-monitors) at sites where the butterflies were collected.
Heavy metals in mammal tissue over the last 100 years and their proximity to populated places in Minnesota
This dataset makes use of the University of Minnesota's Bell Museum of Natural History collection examining specimens of four mammal species (a mouse, shrew, bat and squirrel) to ask how tissue metal content has changed over a 94-year time period (1911-2005), and implications for measures of individual performance (body size and cranial capacity). The metal content of organisms is often elevated closer to cities, so these specimens were examined for spatial variation in metal exposure based on their proximity to human populations and the size of those populated areas at the time of collection. Analysis of mammal tissues focused on six heavy metals associated with human activity (Pb, Cd, Zn, Cu, Cr, Ni, Mn), to address whether these anthropogenic metal pollutants vary in concert with human activity.
Emissions from building materials - concentration of micropollutants and heavy metals in stormwater runoff of two new development areas in Berlin (Germany)
<p>This dataset includes concentrations of micropollutants (27) and heavy metals (7) for stormwater runoff from different sampling points at two test sites (A and B) in Berlin, Germany. Both sites are new development areas of similar size that were both constructed in 2017 (1 – 1.5 years prior to the start of the monitoring campaign). Composite samples of individual rain events were taken at three sampling points of each test site: façade runoff, roof runoff and corresponding stormwater runoff from the catchment area. Samples were taken as part of the research project BaSaR (<a href="http://www.kompetenz-wasser.de/en/forschung/projekte/basar/">www.kompetenz-wasser.de/en/forschung/projekte/basar/</a>) of Kompetenzzentrum Wasser Berlin, Ostschweizer Fachhochschule and Berliner Wasserbetriebe. More information including sampling and analytical methods are detailed in the corresponding journal paper "Emissions from building materials – a thread for the environment?", submitted to the MDPI-journal <em>Water</em>.</p> <p><strong>Description of fields:</strong></p> <ul> <li><strong>SiteID</strong>: site identifier <ul> <li>A: new development site with typical architecture for multi-storey apartment buildings with plastered and painted facades in northern part of Berlin (124 apartments)</li> <li>B: new development site with typical architecture for multi-storey apartment buildings with plastered and painted facades in southeastern part of Berlin (122 appartments)</li> </ul> </li> <li><strong>SamplingPoint</strong> <ul> <li>facade runoff: runoff from plastered facade collected with gutters during individual rain events</li> <li>roof runoff: roof runoff collected from one downpipe during individual rain events</li> <li>storm sewer: stormwater runoff sampled during individual rain events in a manhole receiving runoff from the entire catchment (A or B)</li> </ul> </li> <li><strong>LocalDateTime_StartRain</strong>: start time of sampled rain event (CET / CEST)</li> <li><strong>LocalDateTime_EndRain</strong>: end time of sampled rain event (CET / CEST)</li> <li><strong>CardinalDirection</strong>: only relevant for facade runoff <ul> <li>N: runoff from facade oriented to the north</li> <li>W: runoff from facade oriented to the west</li> </ul> </li> <li><strong>VariableName</strong>: name of analysed substance/parameter</li> <li><strong>CensorCode</strong>: either "lt" (less than) for concentration below detection limit (value is detection limit) or "nc" (not censored) for concentration above detection limit</li> <li><strong>UnitsAbbreviation</strong>: either "ug/L" (microgram per litre) or "mg/L" (milligram per litre)</li> <li><strong>DataValue</strong>: measured value (if censor code is lt, value indicates detection limit)</li> </ul> <p>One data file is provided in comma separated format:<br> "BaSaR_data.csv" contains concentrations of all samples.</p>
Non-genetically-based intraspecific differentiation for heavy metal tolerance in the copper moss Scopelophila cataractae
<p>We used next-generation sequencing to study DNA methylation and gene expression changes in plants from four clonal populations of the metallophyte moss <em>Scopelophila cataractae</em> experimentally exposed to either Cd or Cu. For this we performed reduced representation bisulfite DNA sequencing and RNA sequencing. </p>
Estimating heavy metal deposition in Germany using model calculations and biomonitoring data, link to research data and scientific software
<p>Research data and scientific software related to an investigation dealing with modelled data on Cd and Pb deposition (LOTOS-EUROS, EMEP/MSC-East) and monitoring data from the International Cooperative Programme on Effects of Air Pollution on Natural Vegetation and Crops (ICP Vegetation Moss Survey) and the German Environmental Specimen Bank (ESB) providing corresponding parameters on HM concentration in various biota. The study aimed at examining, whether an integrated use of model calculations and monitoring data can extend established methods for estimating and evaluating spatial patterns of atmospheric Pb and Cd deposition across Germany.</p>
Fig 1 in Different responses of epigeic beetles to heavy metal contamination depending on functional traits at the family level
Fig 1. Diagram of non-metric multidimensional scaling of beetle assemblages classified to three groups of contamination (square- almost uncontaminated sites, circle- moderately contaminated sites, diamond- highly contaminated sites)
Fig 2 in Different responses of epigeic beetles to heavy metal contamination depending on functional traits at the family level
Fig 2. Mean total density ± SE of the most frequently occurring groups of beetles in three classes of contaminations along the season (circle- almost uncontaminated sites, square- moderately contaminated sites, triangle- highly contaminated sites).
Fig. 2 in Accumulation Of Heavy Metals By Small Mammals The Background And Polluted Territories Of The Urals
Fig. 2. The dendrogram is obtained for element analysis (Cu+Zn+Cd) in small mammals from natural populations in the background zone (Bcg) and polluted territories (Imp). The results of cluster analysis confirmed the statistically significant differences in heavy metals total accumulation in three species of small mammals.
A field study of the molecular response of brown macroalgae to heavy metal exposure: an (epi)genetic approach
<p>We used next-generation sequencing to study DNA methylation changes and DNA sequence variation (SNPs) in thalli from four populations of the brown macroalgae <em>Fucus vesiculosus</em> reciprocally transplanted between two polluted and two unpolluted sites. For this, we performed reduced representation bisulfite DNA sequencing.</p>
Figure 2 in Spatial Distribution of the Content of Heavy Metals in the Belaya River Ecosystem
Figure 2. Normalized values of Pb (a) and Mn (b) by Fe in gauge stations I-III (gauges I–II-aerobic conditions; gauge III – anaerobic conditions).
Figure 1 in Bioaccumulation of heavy metals in the tissues of Schizothorax plagiostomus at River Swat
Figure 1. Sampling sites: Charbagh, Odigram, and Landakai of River Swat (Google map, 2017). 2.3. Fish identification
Figure 3 in Bioaccumulation of heavy metals in the tissues of Schizothorax plagiostomus at River Swat
Figure 3. Atomic absorption spectrophotometer used for the analysis of heavy metals i.e zinc, lead, chromium and nickel present in the extracted tissues of muscles and gills.
Figure 7 in Bioaccumulation of heavy metals in the tissues of Schizothorax plagiostomus at River Swat
Figure 7. Heavy metals concentrations (ppm) in muscle and gills of S. plagiostomus at Odigram, Charbagh, and Landakai site.
Figure 2 in Bioaccumulation of heavy metals in the tissues of Schizothorax plagiostomus at River Swat
Figure 2. The collected samples of the Schizothorax plagiostomus species from Charbagh, Odigram and Landakai of River Swat.
Fig. 1 in Heavy metals in bones from Harbour Porpoises Phocoena phocoena from the Western Black Sea Coast
Fig. 1. Map of the Western Black Sea showing the sampling sites along the Bulgarian Black Sea Coast.
Fig. 2 in Heavy metals in bones from Harbour Porpoises Phocoena phocoena from the Western Black Sea Coast
Fig. 2. (a) Correlation matrix between heavy metals and age in bone tissue of harbour porpoises (Phocoena phocoena) beached at Black Sea, Bulgaria (significant correlations highlighted in bold). (b) Zink (Zn) concentration in the bones of common harbour porpoises (mg/kg) as a function of age (years).
Figure 2. A in Estimation of heavy metal residues from the feathers of Falconidae, Accipitridae, and Strigidae in Punjab, Pakistan
Figure 2. A comparison of concentrations (µg/g) of 6 different metals estimated from the feathers of raptors in 3 different regions of Punjab Province. Values expressed as mean ± SE.
Figure 4 in Іnfluence of some heavy metals to the pulmonary and direct diffusive respiration of the great ramshorn Planorbarius corneus allospecies (Mollusca: Gastropoda: Planorbidae) from the Ukrainian river system
Figure 4. Photo of habitat Planorbarius corneus from Sula River (Romny, Sumy region) in 2021 (Photos: Yuliia V. Babych).
Figure 2 in Іnfluence of some heavy metals to the pulmonary and direct diffusive respiration of the great ramshorn Planorbarius corneus allospecies (Mollusca: Gastropoda: Planorbidae) from the Ukrainian river system
Figure 2. Map showing the type localities of Planorbarius corneus s. lato allospecies: black triangle – «western»; black square – «eastern».
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