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87 results for “chemical properties”
Data and Scripts for Schweiger et al. (2021) "Chemical properties of key metabolites determine the global distribution of lichens"
<p>Data and Scripts for Schweiger et al. (2021) "Chemical properties of key metabolites determine the global distribution of lichens".</p> <p>A detailed description of the individual files is provided in the "Schweiger-et-al-DataPublication-Index-Submissionfiles.txt" file.</p> <p>Summary of the study:</p> <p>In lichen symbioses, fungal secondary metabolites provide UV protection on which certain lichen algae such as trebouxioid green algae sensitively depend. These metabolites differ in their UV absorbance capability and solvability, and thus vary in their propensity of being leached from the lichen body by high precipitation and temperatures, with still unknown implications for the global distribution of lichens. In this global study, we show that the occurrence and chemical properties of fungal-derived metabolites are of eco-evolutionary significance for the global, latitudinal distribution of lichenized Trebouxiophyceae. This might represent an indirect environmental adaptation in which the mycobiont invests to protect the trebouxioid photobiont from harsh environmental conditions and, by doing this, secures its efficient source of photosynthetic carbon.</p>
Chemical, optical, and oxidizing properties of three kinds of water-soluble organic matter in PM2.5 from biomass and coal combustion in rural areas in Northwest China
<p>this data set is about the molecular carbon content, light absorption, infrared spectra, and oxidation activity in PM2.5</p>
Fig 2 in Monitoring and assessing the physico-chemical water properties and planktonic communities in tilapia nursing pond
Fig 2: Percentages of different phytoplankton communities during the study period (a, b c, are indicating the size category as small, medium and large)
Fig 1 in Monitoring and assessing the physico-chemical water properties and planktonic communities in tilapia nursing pond
Fig 1: Percentages of total phytoplankton and total zooplankton in all size categorized pond during the sampling period
Figure 2 in The influence of distance from crushed stone mining on surface-active arthropods and soil chemical properties
Figure 2. Principal coordinates analyses (PCO) of the composition of soil chemical properties across sampling points from A, Blue Rock and B, Ikwezi mining sites. Grey triangles = 5 m, circles = 30 m, squares = 50 m, and open triangles = 70 m from the mining activities.
Figure 1 in The influence of distance from crushed stone mining on surface-active arthropods and soil chemical properties
Figure 1. Study sites showing sampling points (5 m, 30 m, 50 m and 70 m) from the mining activities at Blue Rock and Ikwezi mining sites.
Figure 3 in The influence of distance from crushed stone mining on surface-active arthropods and soil chemical properties
Figure 3. Effect of distance from the mining sites on the mean values of zinc. A, Blue Rock and B, Ikwezi mining site.
Database of physical and chemical properties and thresholds relevant to shale gas
<p>Results of the data collection effort on the chemical, physical and toxicity properties as well as permitted concentration levels in drinking water of chemicals that are frequently used in the fracking process.</p>
Spatio-temporal change of selected soil physico-chemical properties in grevillea-banana agroforestry systems
<p>This is a data base containin raw data (soil and litter data) as well as the R scripts used for their analyses</p>
Physico-chemical properties of the top 120 m of two ice cores in Dronning Maud Land (East Antarctica)
<p>We provide in this dataset the complete records from the top 120 m of two ice cores drilled on two adjacent ice rises (Hammarryggen and Lokeryggen, ~100 km apart) located in coastal Dronning Maud Land, Antarctica. Density, water stable isotopes (δ<sup>18</sup>O, δD and d-excess), ions concentrations (Na<sup>+</sup>, K<sup>+</sup>, Mg<sup>+</sup>, Ca<sup>+</sup>, MSA, Cl<sup>-</sup>, SO<sub>4</sub><sup>2-</sup> and NO<sub>3</sub><sup>-</sup>), and continuous electrical conductivity measurement (ECM) records, as well as age models and resulting surface mass balance (SMB) are presented here. These ice cores are dated back to the end of the eighteenth century (CE 1793 ± 3 years for FK17and 1780 ± 5 years for TIR18) by manual and automatic multivariable layer counting and volcanic tie points validation. The SMB is calculated after correction for vertical strain rates.</p> <p>A detailed description of the measurement procedures, data treatments and uncertainties can be found in: Wauthy S., Tison, J.-L., Inoue, M., El Amri, S., Sun, S., Claeys, P., and Pattyn, F.: Physico-chemical properties of the top 120 m of two ice cores in Dronning Maud Land (East Antarctica): an open window on spatial and temporal regional variability of environmental proxies, submitted to Earth System Science Data (ESSD).</p> <p>These new records can be compared to those from other coastal ice cores in DML and to regional or global model results, and represent a great opportunity for further studies addressing the mechanisms behind SMB spatial and temporal variability in East Antarctica.</p> <p>The study was funded in the framework of the Mass2Ant project, contract n° BR/165/A2 by the Belgian Science Policy BELSPO.</p>
Valgarður: A Database of the Petrophysical, Mineralogical, and Chemical Properties of Icelandic Rocks
<p>PLEASE NOTE: There was an issue with some of the total porosity data in a previous version of the database (the decimal place was shifted). Please use this version of the database. Please contact samuelwarrenscott--at--gmail.com if there are any questions. </p> <p>The <em>Valgarður </em>database is a compilation of data describing the physical and geochemical properties of Icelandic rocks. The dataset comprises 1072 samples obtained from fossil and active geothermal systems, as well as relatively fresh volcanic rocks erupted in sub-aerial or sub-aqueous environments. The database includes petrophysical properties (effective and total porosity, grain density, permeability, electrical resistivity, acoustic velocities), as well as mineralogical and geochemical data obtained by point-counting, X-ray Fluorescence (XRF), quantitative X-ray Diffraction (XRD), and Cation Exchange Capacity (CEC) analyses. The motivation behind this database is threefold: (i) aid in the interpretation of geophysical data including uncertainty estimations, (ii) facilitate the parameterization of numerical reservoir models, and (iii) improve our understanding of the relationship between rock type, hydrothermal alteration and petrophysical properties.</p>
Soil chemistry dataset from the work "Modelling and prediction of major soil chemical properties with Random Forest: machine learning as tool to understand soil-environment relationships in Antarctica"
<p>Bases sum, H+Al (potential acidity), pH, phosphorous, remaining P (P-rem), sodium and total organic carbon distribution in Antarctic soils modeled and predicted through Machine Learning approaches, legacy soil data and environmental covariates. The quantile and prediction interval data represent the spatial uncertainty of the predictions.</p> <p>As soon as the work "Modelling and prediction of major soil chemical properties with Random Forest: machine learning as tool to understand soil-environment relationships in Antarctica" is published, the paper will be cited here. </p> <p>The .zip file contains the following folders:</p> <p>1) soil_chemistry_antarctica: data containing the soil chemical attributes distribution</p> <p>2) soil_chemistry_prediction_interval: uncertainty from the prediction interval 90% (Q95% - Q5%) of the soil attributes prediction</p> <p>4) soil_texture_quantile05: quantile 5% of the soil attributes prediction</p> <p>5) soil_texture_quantile95: quantile 95% of the soil attributes prediction</p>
Soil chemical and physical property data for Green Lakes Valley, 1982 - 1983.
The genesis and water chemistry of two soil catenas and mineralogy of eolian dust were studied to evaluate the capacity of these soils to buffer acid conditions. Field and laboratory analyses of 50 soil pits and three eolian dust traps indicated that the surface horizons are mainly eolian dust accumulation and the subsurface horizons differed in texture, organic carbon percentage, bulk density, pH, concentration of soluble and exchangeable ions, dissolved organic carbon, and distribution and concentration of clay materials. The chemistry and mineralogy of the eolian dust resemble those of the surface horizons. Calcite, which increases soil buffering capacity, was found in the eolian dust. The eolian calcite probably comes from western Colorado, where limestone exposures are common. This natural liming process may reduce effects of acid rain on the aquatic system.
Soil chemical and physical property data for Martinelli slope, mid-1980s.
Soil pits were excavated at the Martinelli slope within the Boulder City Watershed. Soil profiles were described in the field and samples were analyzed in the laboratory for various constituents.
Soil chemical and physical property data for Saddle nodal plots, 1986.
Samples were collected from various soil horizons during installation of tension soil solution samplers adjacent to nodal plots in the Saddle. Excavation was limited to minimize disturbance. Consequently, complete soil profile descriptions were not made. Samples were analyzed in the laboratory for various constituents.
Data from: Physical, chemical, and functional properties of neuronal membranes vary between species of Antarctic notothenioids differing in thermal tolerance
Disruption of neuronal function is likely to influence limits to thermal tolerance. We hypothesized that with acute warming the structure and function of neuronal membranes in the Antarctic notothenioid fish Chaenocephalus aceratus are more vulnerable to perturbation than membranes in the more thermotolerant notothenioid Notothenia coriiceps. Fluidity was quantified in synaptic membranes, mitochondrial membranes, and myelin from brains of both species of Antarctic fishes. Polar lipid compositions and cholesterol contents were analyzed in myelin; cholesterol was measured in synaptic membranes. Thermal profiles were determined for activities of two membrane-associated proteins, acetylcholinesterase (AChE) and Na+/K+-ATPase (NKA), from brains of animals maintained at ambient temperature or exposed to their critical thermal maxima (CTMAX). Synaptic membranes of C. aceratus were consistently more fluid than those of N. coriiceps (P < 0.0001). Although the fluidities of both myelin and mitochondrial membranes were similar among species, sensitivity of myelin fluidity to in vitro warming was greater in N. coriiceps than in C. aceratus (P < 0.001), which can be explained by lower cholesterol contents in myelin of N. coriiceps (P < 0.05). Activities of both enzymes, AChE and NKA, declined upon CTMAX exposure in C. aceratus, but not in N. coriiceps. We suggest that hyper-fluidization of synaptic membranes with warming in C. aceratus may explain the greater stenothermy in this species, and that thermal limits in notothenioids are more likely to be influenced by perturbations in synaptic membranes than in other membranes of the nervous system.
Database of topsoil chemical and physical properties in Croatia
<h3>Sources</h3><p>Data for database is collected from four main sources: </p><ul><li>Data published in book "Martinović, J. and Vranković, A. (Editors), 1997. Baza podataka o hrvatskim tlima, I. Državna uprava za zaštitu prirode i okoliša, Zagreb" labeled as "martinovic_1997" in the database.<ul><li>This source consists of 2199 pedological profiles sampled from 1963 to 1996, most of which include depth to bedrock information.</li></ul></li><li>Data from project: "Spatial variability of trace and toxic metals in agricultural soils of Croatia", Ministry of Science and Education and Croatian Waters. Project leader: prof.dr.sc. Marija Romić from Faculty of Agriculture, Zagreb, labeled as "agricultural_2013".<ul><li>Data are sampled from "database of properties and quality of agricultural soils of Croatia" on 8x8 km grid and consists only from top soil samples (0-30 cm). There are 811 samples in this database.</li></ul></li><li>Data from the the project: "Change in soil carbon stocks and calculation of trends in total nitrogen and organic carbon in soil and C: N ratio", from Ministry of Environmental Protection and Energy, carried on by Croatian Geological Institute (HGI), the Croatian Forestry Institute (HŠI) and the Agricultural Land Agency (APZ).<ul><li>This dataset consists of two subsets:<ul><li>"azo_2013" - 2519 samples of topsoil (0-25 cm), from 1994 to 2004 for making of Geochemistry Atlas of Croatia</li><li>"azo_2016" - 742 locations were revisited during 2015-2016 and new samples are taken and analyzed in horizons 0-10 cm, 10-20 cm, 20-30 cm.</li></ul></li></ul></li><li>Network of piezometers</li></ul><h3>Description of sources </h3><h4>Martinović, J. and Vranković, A. (Editors), 1997. Baza podataka o hrvatskim tlima (Database of Croatian Soils) </h4><p>The database contains data on soil profiles and covers the total area of the Republic of Croatia. Only data accepted by external control are entered in the Database, as well as those profiles for which there is a minimum data. External control of data reliability was performed by comparing the genetical-morphological characteristics of the soil determined by field research and the data of laboratory soil analyses. The profiles for which the field and laboratory analyses are found to differ are rejected. In addition to data on soil properties, basic data on pedogenetic factors are given. The soil profiles surveyed in the period 1963-1996 are entered in the database. The majority of data come from the Basic Pedological Map of Croatia (Osnovna pedološka karta Hrvatske - OPKH) project. The following are entered in the Database: 1347 profiles in volume I and 851 profiles in volume II, a total of 2198 pedological profiles</p><h4>Spatial variability of trace and toxic metals in agricultural soils of Croatia, Project Leader: Marija Romić </h4><p>The problem of exposure of agricultural soils to different anthropogenic inputs of toxic metals, but also of other potentially toxic substances, has acquired global dimensions in the last decades. Besides atmospheric deposition, environmental dispersion of chemicals used in agriculture is an important factor directly affecting the natural soil functions, or indirectly endangering the biosphere by bioaccumulation and inclusion into the food chain. Metal concentrations in soil can be generally predicted starting with the element abundance in the parent material. The extent to which pedogenesis affects heavy metals distribution varies according to the prevailing factors affecting soil processes. Because of the toxicity to plants and animals, it is important to determine their content, forms and distribution. Such hypotheses may be tested by total metal content determination, as well as other elements relevant for geochemical valorization of the agricultural soils of Croatia. Thus, the spatial variability and baseline of elements in soils will be determined by means of relevant statistical and geostatistical methods. The maps of toxic metal distribution will be produced and the suitability of soils for agriculture will be assessed. GIS is increasingly used in environmental assessment studies because of its ability to superimpose different spatial information and to combine them with the results of statistical analysis, enabling thus the detection of complex spatial relationships among different parameters. Geostatistics and multivariate statistics has been widely used in geochemical studies to identify pollution sources and to apportion natural vs. anthropogenic contribution, establishing a geochemical background as well. The main objectives of the investigation are: (i) to provide a geochemical database relevant to the agricultural soils in Croatia; (ii) to provide a detailed information about the natural variability of the geochemical background which is pertinent to administrative and legal issues as well as to safety food production and environmental protection; (iii) presenting the influence of human and other environmental activities on the soil quality mainly regarding the toxic and trace metal contents, and (iv) we are going to observe the influence of natural conditions on regional differences which have been widely neglected so far, and have not been taken into account while national regulations and guidelines on soil toxic metal contents have been established.</p><h4>Change in soil carbon stocks and calculation of trends in total nitrogen and organic carbon in soil and C: N ratio </h4><p>The project is funded by the Fund for Environmental Protection and Energy Efficiency within the Program "Upgrading and Development of the Environmental Information System and Improving the Monitoring and Reporting System on the State of the Environment in the Republic of Croatia", Component 2: Improving the Monitoring and Reporting System on the State of the Environment Croatia; improving the system of data collection and exchange and developing methodologies for their processing in accordance with the guidelines of the UNFCCC and the Kyoto Protocol defined by the IPCC (Intergovernmental Panel on Climate Change). </p><p>The project holder is the Ministry of Environmental Protection and Energy, and the executors are the Croatian Geological Institute, the Croatian Forestry Institute and the Agricultural Land Agency.</p><p>In the period 2014-2017, field and laboratory research of soil conditions was conducted at 725 representative locations. General data on the location of sampling were collected, which contain administrative, locational, geographical and other data (relief, climatic and meteorological data, detailed data on land use and vegetation cover, description of surface soil properties).</p><p>Field soil sampling for each LULUCF land use category was performed according to a modified methodology described in the EU DG JRC (Joint Research Center) "Protocol for soil sampling to confirm changes in organic carbon stocks in the EU" by Stolbovoy et al. 2007 (Soil sampling protocol to certify the changes of organic carbon stock in mineral soil of the European Union - EU JRC). The protocol modifications aimed to ensure reporting under the UNFCCC and Kyoto protocols, i.e., to ensure compliance with the IPCC methodology. Soil sampling on forest land (FL) according to the JRC protocol is planned at two depths of 0-10 cm and 10 - 20 cm and an organic layer (list), but due to reporting requirements under the UNFCCC and Kyoto protocol, sampling was carried out at a depth of 20 - 30 cm. Land under crops (CL) was sampled at two depths (0-20 cm and 20-30 cm) and grasslands (GL), wetlands (WL), settlements (SL) and other land (OL) were sampled at three depths 0- 10, 10-20 and 20-30 cm. Geochemical analyzes were performed at depths of 0–10 and 20–30 cm for forest soils (FL) and for meadows and pastures (GL) while for soils under crops (CL) composite samples of 0–30 cm and 0–20 cm were analyzed.</p><h4>Network of piezometers</h4><p>To get a more accurate depth to bedrock parameter, positions of 812 piezometers are considered as they have at least 4 meters of depth to bedrock.</p><h3>Description of database</h3><p>Column names and descriptions:</p><p>Metadata columns:</p><p><strong>site_key </strong>- unique identifier that identifies sample in source database <br><strong>source_db</strong> - label of source database <br><strong>source_sampled</strong> - label of organization/team who sampled and analyzed data <br><strong>site_obsdate</strong> - year of taking sample <br><strong>longitude_decimal_degrees</strong> - longitude in degrees in WGS84 geographical projection <br><strong>latitude_decimal_degrees</strong> - latitude in degrees in WGS84 geographical projection <br><strong>pedon_completeness_index</strong> - quality factor (0-100) <br><strong>taxgrtgroup</strong> - classification of sample according to WBR 2014/2016 classification </p><p>Soil properties columns:</p><p>column name - property - measurement units - description<br><strong>oc</strong> - Carbon, Organic - % wt - CMS analyte. Organic carbon is a measure of all organic forms of carbon in the soil, including organic carbon within minerals. <br><strong>n_tot_ncs</strong> - Nitrogen, Total NCS - % wt - Total nitrogen is a measure of all organic and inorganic nitrogen, including that found in nitrogen minerals.<br><strong>ca_mehlich3</strong> - Calcium, Mehlich3 Extractable - mg/kg - The calcium extracted by the Mehlich III solution. <br><strong>k_mehlich3</strong> - Potassium, Mehlich3 Extractable - mg/kg - The potassium extracted by the Mehlich III solution. <br><strong>mg_mehlich3</strong> - Magnesium, Mehlich3 Extractable - mg/kg - The magnesium extracted by the Mehlich III solution. <br><strong>p_mehlich3</strong> - Phosphorus, Mehlich3 Extractable - mg/kg - The phosphorus extracted by the Mehlich III solution. <br><strong>cec_sum</strong> - Cation Exchange Capacity, Summary cmol(+)/kg - The effective cation exchange capacity is calculated by BASE_SUM+AL_KCL. It is not calculated if soluble salts are present. It is reported as meq per 100 grams on a <2 mm base. CMS derived value default <br><strong>ec_satp</strong> - Electrical Conductivity , Saturation Extract - dS/m - The electrical conductivity of the saturation extract is used to estimate the concentration of salts in a sample, and provides inferences on cation concentration in solution and osmotic pressure. It is reported as mmhos per centimeter. <br><strong>caco3</strong> - Carbonates - % wt - Carbonate in the < 2mm fraction is measured by CO2 evolution after acid treatment. It is reported as gravimetric percent CaCO3 on a <2 mm base, even though carbonates of Mg, Na, K, and Fe may be present and react with the acid<br><strong>ph_h2o</strong> - pH, 1:1 Soil-Water Suspension - (NA) - The pH, 1:1 soil-water suspension is the pH of a sample measured in distilled water at a 1:1 soil:solution ratio. If wider ratios increase the pH, salts are indicated. <br><strong>ph_kcl</strong> - The pH, 1:1 soil-KCl suspension - (NA) - The pH, 1:1 soil-KCl suspension is the pH of a sample measured in 1.0N KCl at a 1:1 soil:solution ratio. If the pH in KCl < pH in water, Al+++ is indicated. <br><strong>total_clay</strong> - Clay, Total - % wt - Total clay is the soil separate with <0.002 mm particle diameter. Clay size carbonate is included. Total clay is reported as a weight percent of the <2 mm fraction. <br><strong>total_silt</strong> - Silt, Total - % wt - Total silt is the soil separate with 0.002 to 0.05 mm particle size. It is reported as a gravimetric percent on a <2 mm base. <br><strong>total_sand</strong> - Sand, Total - % wt - Total sand is the soil separate with 0.05 to 2.0 mm particle diameter. It is reported as a gravimetric percent on a <2 mm base. <br><strong>wpg2</strong> - Coarse fragments - % wt - The weight fraction of particles with >2 mm diameter is reported as a gravimetric percent on a whole soil base. <br><strong>db_od</strong> Bulk Density, <2mm Fraction, Ovendry - g/cc - Bulk density, oven dry (105 C) is the weight per unit volume of the <2 mm fraction, with volume measured on oven dry (105 C) natural fabric (clods). It is reported as grams per cubic centimeter on a <2 mm base. <br><strong>dbr</strong> - Depth to bedrock - cm - Depth to the R horizon or similar</p>
Aggregated database of forest soil chemical properties in the Czech Republic based on surveys from 2000-2020.
<p>The dataset includes data from forest soil surveys conducted in the period 2000–2020. It provides soil and site variables from 8,269 locations. Data are aggregated in three basic soil layers: upper organic soil horizon (FH, 6,876 locations), upper mineral layer 0–30 cm (M03, 8,051 locations) and deeper mineral soil layer (30–80 cm, M38, 2,260 locations).</p> <p>This dataset is linked to the following article published in Annals of Forest Science:</p> <p>Neudertová Hellebrandová, K., Fadrhonsová, V. & Šrámek, V. Aggregated database of forest soil chemical properties in the Czech Republic based on surveys from 2000 to 2020. Annals of Forest Science 81, 17 (2024). <a href="https://doi.org/10.1186/s13595-024-01225-y">https://doi.org/10.1186/s13595-024-01225-y</a></p>
Changes in community-weighted trait mean, functional diversity, soil chemical properties and temperature along an elevational gradient in Tenerife, Canary Islands
<p>This dataset comprises community-weighted trait means and functional diversity of leaf traits, chemical soil properties and temperature recorded in roadside (disturbed) and interior (less disturbed) plots, along an elevational gradient of 2,300 m in Tenerife, Canary Islands. The leaf traits measured were specific leaf area (SLA), nitrogen, nitrogen to phosphorus ratio, leaf dry matter content (LDMC) and carbon to phosphorus ratio. The soil chemical properties measured were pH, nitrogen, nitrogen to phosphorus ratio, carbon to phosphorus ratio, calcium, potassium, magnesium and cation exchange capacity. Also the scores of the three first axes derived from a PCA analysis including the soil chemical properties are included. The temperature variables consist of bioclimatic variables Bio10 (mean temperature of the warmest quarter) and Bio11 (mean temperature of the coldest quarter). This dataset has been used for the analysis presented in Ratier Backes et al. (2021).</p>
Data associated to the article "Effects of fluoride salt addition to the physico-chemical properties of the MgCl2-NaCl-KCl heat transfer fluid : a molecular dynamics study"
<p>Contains input file and data used to generate the figures of the article:</p> <p>Effects of fluoride salt addition to the physico-chemical properties of the MgCl<sub>2</sub>-NaCl-KCl heat transfer fluid : a molecular dynamics study</p> <p>Weiguang Zhou, Yanping Zhang, Mathieu Salanne</p> <p>https://chemrxiv.org/engage/chemrxiv/article-details/618e903a2bf8a950c7d98e5d</p> <p>The files <em>data.inpt</em> and <em>runtime.inpt </em>are used to simulate the system using the software MetalWalls</p> <p>The files <em>MgNaKCl.txt, MgNaKClF01.txt, MgNaKClF05.txt, MgNaKClF10.txt, MgNaKClF20.txt</em> contain the computed densities, viscosities and thermal conductivities at various temperatures for several compositions (provided in the header of the files)</p>
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