Not logged in
PANGAEA.
Data Publisher for Earth & Environmental Science

Riechelmann, Sylvia; Spötl, Christoph (2021): Mg, O, and H isotope composition and Mg concentration of monthly precipitation of northwest Germany from 2014 to 2017 [dataset]. PANGAEA, https://doi.org/10.1594/PANGAEA.937577

Always quote citation above when using data! You can download the citation in several formats below.

RIS CitationBibTeX CitationShow MapGoogle Earth

Abstract:
The data set consists of magnesium (Mg), oxygen (O), and hydrogen (H) isotope signatures and Mg concentrations of monthly collected precipitation and daily snow samples. Samples were collected between December 2014 and June 2017 in the village of Gevelsberg (NW Germany, 51.32°N, 7.32°E) at 206 m above sea level. Rainwater was collected daily using a funnel connected to a 5 liter PET canister. The collected water was transferred into a second canister to store the monthly sample. Snow samples were separately collected on the days of snowfall in ca. 5 m distance to the rainwater collection site using 500 ml PET bottles. The full snow thickness was sampled using a small scoop. All collected monthly and daily snow samples were filtered using 0.45µm cellulose-acetate filters (Sartorius) and stored in a fridge. Subsequent analysis of rain and snow samples include Mg concentration analysis using an ICP-OES (iCAP 6500 DUO, Thermo Fisher Scientific) and Magnesium isotope composition analysis using an MC-ICP-MS Neptune (Thermo Fisher Scientific) at the Ruhr-University Bochum, Germany. Oxygen and hydrogen isotope composition was determined using cavity ring-down spectrometry (L2140i, Picarro) at Innsbruck University, Austria.
Keyword(s):
Mg concentration; Mg isotopes; oxygen and hydrogen isotopes; precipitation; rain; Rainwater; snow
Supplement to:
Riechelmann, Sylvia; Spötl, Christoph; Immenhauser, Adrian (2021): Time series of δ26 Mg variability in precipitation of north‐west Germany. The Depositional Record, https://doi.org/10.1002/dep2.171
Project(s):
Marine Karbonat-Archive: Kontrollierende Faktoren der Karbonat-Fällung und diagenetische Alterationspfade (CHARON)
Funding:
Deutsche Forschungsgemeinschaft, Bonn (DFG), grant/award no. 189839832: Marine Karbonat-Archive: Kontrollierende Faktoren der Karbonat-Fällung und diagenetische Alterationspfade
Coverage:
Latitude: 51.320000 * Longitude: 7.320000
Date/Time Start: 2014-12-01T00:00:00 * Date/Time End: 2017-06-30T00:00:00
Minimum Elevation: 206.0 m * Maximum Elevation: 206.0 m
Event(s):
Gevelsberg_2014-2017 * Latitude: 51.320000 * Longitude: 7.320000 * Date/Time Start: 2014-12-01T00:00:00 * Date/Time End: 2017-06-30T00:00:00 * Elevation: 206.0 m * Location: Gevelsberg, Germany * Method/Device: Water sample, precipitation (WSP)
Parameter(s):
#NameShort NameUnitPrincipal InvestigatorMethod/DeviceComment
Sample code/labelSample labelRiechelmann, Sylvia
Sample typeSamp typeRiechelmann, Sylvia
DATE/TIMEDate/TimeRiechelmann, SylviaGeocode – Start date
DATE/TIMEDate/TimeRiechelmann, SylviaGeocode – End date
δ18O, waterδ18O H2O‰ SMOWRiechelmann, SylviaCavity ring-down spectrometer, Picarro, L2140iVSMOW
δ18O, water, standard deviationδ18O H2O std dev±Riechelmann, SylviaCavity ring-down spectrometer, Picarro, L2140i±1σ
δ Deuterium, waterδD H2O‰ SMOWRiechelmann, SylviaCavity ring-down spectrometer, Picarro, L2140iVSMOW
δ Deuterium, water, standard deviationδD H2O std dev±Riechelmann, SylviaCavity ring-down spectrometer, Picarro, L2140i±1σ
MagnesiumMg2+mg/lRiechelmann, SylviaICP-OES (iCAP 6500 DUO, Thermo Fisher Scientific)
10 Magnesium, standard deviationMg std dev±Riechelmann, SylviaICP-OES (iCAP 6500 DUO, Thermo Fisher Scientific)±1σ
11 δ26Mgδ26MgRiechelmann, SylviaMC-ICP-MS (Thermo Scientific, Neptune)DSM3
12 δ26Mg, standard deviationδ26Mg std dev±Riechelmann, SylviaMC-ICP-MS (Thermo Scientific, Neptune)±2σ
Status:
Curation Level: Enhanced curation (CurationLevelC)
Size:
372 data points

Data

Download dataset as tab-delimited text — use the following character encoding:


Sample label

Samp type

Date/Time
(Start date)

Date/Time
(End date)

δ18O H2O [‰ SMOW]
(VSMOW, Cavity ring-down spect...)

δ18O H2O std dev [±]
(±1σ, Cavity ring-down spectro...)

δD H2O [‰ SMOW]
(VSMOW, Cavity ring-down spect...)

δD H2O std dev [±]
(±1σ, Cavity ring-down spectro...)

Mg2+ [mg/l]
(ICP-OES (iCAP 6500 DUO, Therm...)
10 
Mg std dev [±]
(±1σ, ICP-OES (iCAP 6500 DUO, ...)
11 
δ26Mg []
(DSM3, MC-ICP-MS (Thermo Scien...)
12 
δ26Mg std dev [±]
(±2σ, MC-ICP-MS (Thermo Scient...)
RW 12/14Rainwater2014-12-012014-12-31-8.750.02-55.80.40.1000.003-1.120.03
RW 01/15Rainwater2015-01-012015-01-31-9.150.09-59.10.40.1400.002-0.910.02
RW 02/15Rainwater2015-02-012015-02-28-11.650.08-82.30.60.1500.003-2.030.04
RW 03/15Rainwater2015-03-012015-03-31-6.830.04-43.60.40.1600.002-2.290.03
RW 04/15Rainwater2015-04-012015-04-30-7.730.07-47.30.40.2000.002-1.830.03
RW 05/15Rainwater2015-05-012015-05-31-6.660.08-47.90.80.1800.002-1.360.03
RW 06/15Rainwater2015-06-012015-06-30-7.000.09-46.30.60.2000.004-2.190.08
RW 07/15Rainwater2015-07-012015-07-31-4.720.06-27.01.30.1700.003-1.280.03
RW 08/15Rainwater2015-08-012015-08-31-8.010.10-52.90.80.1900.003-1.850.03
RW 09/15Rainwater2015-09-012015-09-30-7.290.14-44.30.50.1500.002-1.320.05
RW 10/15Rainwater2015-10-012015-10-31-13.150.05-93.00.20.1700.002-1.620.03
RW 11/15Rainwater2015-11-012015-11-30-6.430.04-38.90.40.1400.004-1.600.03
RW 12/15Rainwater2015-12-012015-12-31-6.660.04-41.70.20.0900.001-1.470.04
RW 01/16Rainwater2016-01-012016-01-31-10.370.10-71.50.50.0800.002-1.270.02
RW 02/16Rainwater2016-02-012016-02-29-8.120.04-55.80.30.1000.001-1.170.01
RW 03/16Rainwater2016-03-012016-03-310.1300.002-1.140.06
RW 04/16Rainwater2016-04-012016-04-30-9.850.09-66.10.70.2000.004-1.130.04
RW 05/16Rainwater2016-05-012016-05-31-6.220.09-40.20.40.1500.004-1.430.06
RW 06/16Rainwater2016-06-012016-06-30-7.050.12-50.20.50.0700.002-1.280.05
RW 07/16Rainwater2016-07-012016-07-31-6.010.03-39.90.20.2200.004-1.580.06
RW 08/16Rainwater2016-08-012016-08-31-4.970.02-31.30.40.1000.004-1.640.03
RW 09/16Rainwater2016-09-012016-09-30-6.720.05-45.30.20.2500.002-1.720.06
RW 10/16Rainwater2016-10-012016-10-31-7.290.03-55.80.20.1500.002-1.660.05
RW 11/16Rainwater2016-11-012016-11-300.0800.002-2.160.03
RW 12/16Rainwater2016-12-012016-12-31-6.730.07-44.00.40.2300.002-1.480.02
RW 01/17Rainwater2017-01-012017-01-31-9.830.05-65.50.30.2500.003-1.400.03
RW 02/17Rainwater2017-02-012017-02-28-7.140.04-47.50.40.1000.001-1.730.04
RW 03/17Rainwater2017-03-012017-03-31-8.100.07-55.50.10.1300.003-2.340.07
RW 04/17Rainwater2017-04-012017-04-30-7.980.07-50.60.10.2300.003-2.850.02
RW 05/17Rainwater2017-05-012017-05-31-8.520.05-65.10.30.0900.002-2.010.03
RW 06/17Rainwater2017-06-012017-06-300.1300.003-2.040.03
Snow 24.01.2015Snow2015-01-24-12.500.08-87.40.70.0700.002-1.800.03
Snow 30.01.2015Snow2015-01-30-12.200.08-79.90.60.1800.002-1.150.02
Snow 23.02.2015Snow2015-02-23-15.780.02-119.41.00.0200.001-1.150.05
Snow 17.01.2016Snow2016-01-170.5500.004-1.260.02
Snow 15.02.2016Snow2016-02-15-12.690.02-89.90.00.1000.002-1.470.03
Snow 07.03.2016Snow2016-03-07-20.890.06-155.90.20.0040.002
Snow 02.01.2017Snow2017-01-02-11.690.06-80.10.10.1500.002-1.450.04
Snow 13.-16.01.17Snow2017-01-132017-01-16-7.950.06-52.00.30.4300.006-1.610.04