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71 results for “CO2 concentration”
Summer high frequency measurements of dissolved O2 and CO2 concentrations and water temperature at the surface of 11 northern lakes
This dataset includes high frequency paired measurements of dissolved O2 and CO2 concentrations at the surface (0.5 to 2 m depth) of 11 lakes in the Northern Hemisphere. Measurements were taken every 2 hours in summer (July and August) of various years depending on lakes (between 2011 and 2014). The dataset is used to test a conceptual framework on the controls of coupling and decoupling of these two gases. In all lakes dissolved CO2 was measured with infrared analyzer coupled with a diffusion membrane and dissolved O2 with optodes. All gas measurements are paired with water temperature provided by one of the gas probe (usually from the O2 probe).
High-frequency wind (u, w, v, Ts) and gas concentration measurements of CO2 and H2O over an agricultural field in Braunschweig, Germany
<p>This dataset contains high-frequency eddy covariance (EC) measurements over a flat agricultural field at the Thünen Institute in Braunschweig, Germany (52.30° N, 10.45° E).</p> <p>The data collection period spanned <strong>77 days </strong>in the year 2020 split into three files</p> <p> </p> <table> <tbody> <tr> <td>BS2020_06.rds</td> <td>June 11 to July 15</td> </tr> <tr> <td>BS2020_10.rds</td> <td>October 1 to November 10</td> </tr> <tr> <td>BS_2020_07_subset.rds</td> <td>July 11 to July 25</td> </tr> </tbody> </table> <p> </p> <p>Included in the dataset are 3D wind velocity data, recorded using a uSonic-3 Class A sonic anemometer from Metek GmbH. Additionally, the dataset provides gas concentration measurements for carbon dioxide (CO2) and water vapor (H2O), captured using an LI-7500A open-path infra-red gas analyzer from LI-COR Biosciences GmbH, Germany.</p> <p>Variables in the dataset</p> <table> <tbody> <tr> <th>Variable Name</th> <th>Description</th> <th>Units</th> </tr> </tbody> <tbody> <tr> <td>time</td> <td>Unique time stamp (POSIXct format)</td> <td>Seconds since Unix epoch</td> </tr> <tr> <td>CO2</td> <td>Wet molar density of carbon dioxide</td> <td>µmol m⁻³</td> </tr> <tr> <td>H2O</td> <td>Wet molar density of water vapor</td> <td>mmol m⁻³</td> </tr> <tr> <td>Ts</td> <td>Sonic temperature</td> <td>Kelvin</td> </tr> <tr> <td>u, v, w</td> <td>3D wind velocity components</td> <td>m s⁻¹</td> </tr> </tbody> </table> <p> </p> <p> </p> <div> <div> <div> <p>The dataset is in RDS format (version 3), compatible with R version 3.5.0 or higher.</p> <p>RDS is a binary file format native to the R programming environment</p> </div> </div> </div>
CO2 concentrations and emissions from subtropical headwater streams, São Carlos, Brazil, 2018
The data were collected in the municipalities of São Carlos, Itirapina, and Brotas in the state of São Paulo, southeastern Brazil. Six sandy/rocky-bottom headwater streams (1st to 2nd order) were selected based on the main land use in the catchment. Three streams drained sugarcane plantations, and three streams drained native vegetation catchments (Cerrado vegetation). The catchment drainage areas were determined using digital elevation models. Land use was classified based on satellite images from LANDSAT using ArcGIS software. The data were collected to study the impact of different land uses (sugarcane plantations vs. native vegetation) on the headwater streams. These streams have previously been studied for methane dynamics, indicating a focus on understanding environmental and ecological impacts. Three samples were collected from each stream during spring, summer, and winter using the headspace extraction technique. Due to access issues, samples from one stream were not collected in spring and summer 2018. Syringes filled with ultrapure nitrogen were used to collect stream water samples, which were then shaken to equilibrate gases. The gas was analyzed using a Shimadzu GC-2014 gas chromatograph equipped with various detectors. Concentrations were compared with standards to calculate CO2 levels, and CO2 emissions were calculated based on gas transfer velocity and dissolved concentrations.
Input data for running forward simulations of CO2 atmospheric concentrations over Europe for the year 2019.
<p>This dataset provides input data (fluxes, background concentrations, and observations) for running forward simulations of CO2 atmospheric concentrations over Europe for the year 2019 using chemical transport models (CTMs). While some components of the dataset are available in other repositories, this compilation serves to 1) streamline the data collection process for other users and 2) bypass the need to perform data aggregation.</p> <p>Here is a description of each dataset:</p> <p><strong>cams73_latest_co2_conc_surface_inst_2019*.nc</strong></p> <p>CO2 mole fractions from the CAMS global inversion-optimised product v20r2 (Chevallier et al., 2010).</p> <p>The data are provided at a resolution of 3.75° in longitude and 1.9° in latitude, with a 3-hourly temporal resolution. </p> <p><strong>monitor_CO2_CIF_2019.nc</strong></p> <div> <div> <div> <div> <div> <div> <p>Observed CO2 atmospheric mixing ratios in Europe, compiled in version V8 of the ICOS GlobalView Obspack (ICOS RI et al., 2023), include continuous measurements from 58 stations across Europe, incorporating both ICOS and non-ICOS facilities.</p> <p>The original dataset has been aggregated and adapted to match the format of the monitor files used in the Community Inversion Framework (CIF; Berchet et al., 2021).</p> </div> </div> </div> </div> </div> </div> <p><strong>EDGARv4.3_BP2021_CO2_EU2_2019.nc</strong></p> <p>Anthropogenic CO2 fluxes (European, hourly) obtained from EDGAR-v4.2 and BP.</p> <p>The anthropogenic CO2 emissions are based on the spatial distribution from the EDGAR-v4.2 inventory, national and annual budgets from British Petroleum (BP) statistics, and hourly temporal profiles derived using the COFFEE approach (Steinbach et al., 2011, available on the ICOS Carbon Portal). This data is provided at a 0.1° × 0.1° horizontal resolution and hourly temporal resolution.</p> <p><strong>FG2.TRENDY11.ORC3.S3.3H_NBP_resp_2019.nc</strong></p> <p>NBP CO2 fluxes (global, 3-hourly) obtained from ORCHIDEE simulations. </p> <p>The ORCHIDEE-TRENDY simulation is conducted as part of the TRENDY model intercomparison project (e.g., Sitch et al., 2015; Friedlingstein et al., 2022). This simulation uses inputs provided by the project, including the CRUERA atmospheric climate forcing (global, 6-hourly, 0.5-degree resolution), LUH2 land-use change dataset, global atmospheric CO2 concentration data, and nitrogen fertilizer input datasets. All TRENDY simulations adhere to a standardized protocol: a model spin-up phase using recycled forcing data from 1901-1920, with other inputs from 1700, continues until the model's carbon pools reach equilibrium (340 years of spin-up for ORCHIDEE). This is followed by a transient simulation from 1700-1900, varying CO2 and land-use data while recycling climate forcing, and a historical simulation from 1901-2020 with all data inputs varied.</p> <p><strong>FR2.ORC3v7267.CRUERA3.NBP_3H.2019.nc</strong></p> <p>NBP CO2 fluxes (Europe, 3-hourly) obtained from ORCHIDEE simulations. </p> <p>The ORCHIDEE-VERIFY simulation is performed as part of the VERIFY project over the European region. This simulation is driven by the CRUERA dataset, which is derived from the ERA5-Land dataset (originally global, 1-hourly, at 0.1-degree resolution), transformed to the VERIFY region of interest (35°N to 73°N, 25°W to 45°E, 3-hourly, at 0.125-degree resolution), and re-aligned with the CRU observation dataset (for air temperature, shortwave radiation, humidity, and precipitation). The Hilda+ dataset is used for land use, and the EMEP model outputs are used for nitrogen inputs. The VERIFY simulation follows the general protocol used in the TRENDY project.</p> <p><strong>FR2.ORC3v7267.CRUERA3.hetero_resp_3H.2019.nc</strong></p> <p>Heterotrophic respiration CO2 fluxes (Europe, 3-hourly) obtained from ORCHIDEE simulations as described in the previous section.</p> <p><strong>Becker_coastal_fluxes_RF_v2021_2_2019.nc</strong></p> <p>Ocean CO2 fluxes (Europe, daily). </p> <p>The ocean fluxes come from a hybrid product combining the University of Bergen coastal ocean flux estimate and the Rödenbeck global ocean estimate (Rödenbeck et al., 2014). This data is provided at a 0.125° × 0.125° horizontal resolution and at a daily temporal resolution.</p> <p> </p> <p><em><strong>References</strong></em> </p> <p> </p> <p>Berchet, A., Sollum, E., Pison, I., Thompson, R. L., Thanwerdas, J., Fortems-Cheiney, A., Peet, J. C. A. v., Potier, E., Chevallier, F., Broquet, G., and Berchet, A.: The Community Inversion Framework: codes and documentation, https://doi.org/10.5281/zenodo.6304912, 2022</p> <p>Chevallier, F., Ciais, P., Conway, T. J., Aalto, T., Anderson, B. E., Bousquet, P., Brunke, E. G., Ciattaglia, L., Esaki, Y., Fröhlich, M., Gomez, A., Gomez-Pelaez, A. J., Haszpra, L., Krummel, P. B., Langenfelds, R. L., Leuenberger, M., Machida, T., Maignan, F., Matsueda, H., Morguí, J. A., Mukai, H., Nakazawa, T., Peylin, P., Ramonet, M., Rivier, L., Sawa, Y., Schmidt, M., Steele, L. P., Vay, S. A., Vermeulen, A. T., Wofsy, S., and Worthy, D.: CO2 surface fluxes at grid point scale estimated from a global 21 year reanalysis of atmospheric measurements, Journal of Geophysical Research: Atmospheres, 115, https://doi.org/10.1029/2010JD013887, 2010</p> <p>Friedlingstein, P., O’Sullivan, M., Jones, M. W., Andrew, R. M., Gregor, L., Hauck, J., Le Quéré, C., Luijkx, I. T., Olsen, A., Peters, G. P.,Peters, W., Pongratz, J., Schwingshackl, C., Sitch, S., Canadell, J. G., Ciais, P., Jackson, R. B., Alin, S. R., Alkama, R., Arneth, A., Arora,V. K., Bates, N. R., Becker, M., Bellouin, N., Bittig, H. C., Bopp, L., Chevallier, F., Chini, L. P., Cronin, M., Evans, W., Falk, S., Feely, R. A., Gasser, T., Gehlen, M., Gkritzalis, T., Gloege, L., Grassi, G., Gruber, N., Gürses, O., Harris, I., Hefner, M., Houghton, R. A.,Hurtt, G. C., Iida, Y., Ilyina, T., Jain, A. K., Jersild, A., Kadono, K., Kato, E., Kennedy, D., Klein Goldewijk, K., Knauer, J., Korsbakken,J. I., Landschützer, P., Lefèvre, N., Lindsay, K., Liu, J., Liu, Z., Marland, G., Mayot, N., McGrath, M. J., Metzl, N., Monacci, N. M.,Munro, D. R., Nakaoka, S.-I., Niwa, Y., O’Brien, K., Ono, T., Palmer, P. I., Pan, N., Pierrot, D., Pocock, K., Poulter, B., Resplandy, L.,Robertson, E., Rödenbeck, C., Rodriguez, C., Rosan, T. M., Schwinger, J., Séférian, R., Shutler, J. D., Skjelvan, I., Steinhoff, T., Sun, Q., Sutton, A. J., Sweeney, C., Takao, S., Tanhua, T., Tans, P. P., Tian, X., Tian, H., Tilbrook, B., Tsujino, H., Tubiello, F., van der Werf,G. R., Walker, A. P., Wanninkhof, R., Whitehead, C., Willstrand Wranne, A., Wright, R., Yuan, W., Yue, C., Yue, X., Zaehle, S., Zeng, J., and Zheng, B.: Global Carbon Budget 2022, Earth System Science Data, 14, 4811–4900, https://doi.org/10.5194/essd-14-4811-2022,https://essd.copernicus.org/articles/14/4811/2022/, publisher: Copernicus GmbH, 2022</p> <p>ICOS RI, Bergamaschi, P., Colomb, A., De Mazière, M., Emmenegger, L., Kubistin, D., Lehner, I., Lehtinen, K., Lund Myhre, C., Marek, M., Platt, S. M., Plaß-Dülmer, C., Schmidt, M., Apadula, F., Arnold, S., Blanc, P.-E., Brunner, D., Chen, H., Chmura, L., Conil, S., Couret, C., Cristofanelli, P., Delmotte, M., Forster, G., Frumau, A., Gheusi, F., Hammer, S., Haszpra, L., Heliasz, M., Henne, S., Hoheisel, A., Kneuer, T., Laurila, T., Leskinen, A., Leuenberger, M., Levin, I., Lindauer, M., Lopez, M., Lunder, C., Mammarella, I., Manca, G., Manning, A., Marklund, P., Martin, D., Meinhardt, F., Müller-Williams, J., Necki, J., O’Doherty, S., Ottosson-Löfvenius, M., Philippon, C., Piacentino, S., Pitt, J., Ramonet, M., Rivas-Soriano, P., Scheeren, B., Schumacher, M., Sha, M. K., Spain, G., Steinbacher, M., Sørensen, L. L., Vermeulen, A., Vítková, G., Xueref-Remy, I., di Sarra, A., Conen, F., Kazan, V., Roulet, Y.-A., Biermann, T., Heltai, D., Hensen, A., Hermansen, O., Komínková, K., Laurent, O., Levula, J., Pichon, J.-M., Smith, P., Stanley, K., Trisolino, P., ICOS Carbon Portal, ICOS Atmosphere Thematic Centre, ICOS Flask And Calibration Laboratory, and ICOS Central Radiocarbon Laboratory: European Obspack compilation of atmospheric carbon dioxide data from ICOS and non-ICOS European stations for the period 1972-2023;<br>obspack_co2_466_GLOBALVIEWplus_v8.0_2023-04-26, https://doi.org/10.18160/CEC4-CAGK, 2023</p> <p>Rödenbeck, C., Bakker, D. C. E., Metzl, N., Olsen, A., Sabine, C., Cassar, N., Reum, F., Keeling, R. F., and Heimann, M.: Interannual sea–air CO2 flux variability from an observation-driven ocean mixed-layer scheme, Biogeosciences, 11, 4599–4613, https://doi.org/10.5194/bg-11-4599-2014, 2014</p> <p>Sitch, S., Friedlingstein, P., Gruber, N., Jones, S. D., Murray-Tortarolo, G., Ahlström, A., Doney, S. C., Graven, H., Heinze, C., Huntingford,C., Levis, S., Levy, P. E., Lomas, M., Poulter, B., Viovy, N., Zaehle, S., Zeng, N., Arneth, A., Bonan, G., Bopp, L., Canadell, J. G.,Chevallier, F., Ciais, P., Ellis, R., Gloor, M., Peylin, P., Piao, S. L., Le Quéré, C., Smith, B., Zhu, Z., and Myneni, R.: Recent trends and drivers of regional sources and sinks of carbon dioxide, Biogeosciences, 12, 653–679, https://doi.org/10.5194/bg-12-653-2015, https://bg.copernicus.org/articles/12/653/2015/, publisher: Copernicus GmbH, 2015.</p> <p>Steinbach, J., Gerbig, C., Rödenbeck, C., Karstens, U., Minejima, C., and Mukai, H.: The CO2 release and Oxygen uptake from Fossil Fuel Emission Estimate (COFFEE) dataset: effects from varying oxidative ratios, Atmospheric Chemistry and Physics, 11, 6855–6870,1160 https://doi.org/10.5194/acp-11-6855-2011, 2011</p> <p> </p> <p> </p> <p> </p>
Data-set of the partial pressure of CO2, dissolved concentrations of CH4, N2O, NO3-, NO2- and NH4+, specific conductivity and water temperature in the rivers and streams of the Napo River basin in Ecuador (2018, 2019, 2020, 2021)
<p>Data-set consists of two files:</p> <p>- data_ghgs.xlsx : Time-stamped and georeferenced data-set of the partial pressure of CO2 (pCO2 in ppm), dissolved CH4 concentration (CH4 in nmol/L), dissolved N2O concentration (N2O in nmol/L), specific (Sp.) conductivity (in µS/cm), water temperature (in °C), dissolved nitrate concentration (NO3- in µmol/L), dissolved nitrite concentration (NO2- in µmol/L), and dissolved ammonia concentration (NH4+ in µmol/L) in the rivers and streams of the Napo River basin in Ecuador (October 2018 and 2019, January 2019 and 2020, April 2019 and 2021, July 2019 and 2020). Gas measurements were made by headspace equilibration directly in the field with a infra-red gas analyser for CO2 and in the lab with a gas chromatograph for CH4 and N2O. NO3-, NO2- and NH4+ were measured with standard colometric procedures. Sampling and analytical protocols are provided here <a href="https://doi.org/10.5194/bg-16-3801-2019">https://doi.org/10.5194/bg-16-3801-2019</a></p> <p>- RiverATLAS.xlsx: hydro-environmental data for the sampled streams extracted from RiverATLAS (https://www.nature.com/articles/s41597-019-0300-6). Data codes and units are available here: https://data.hydrosheds.org/file/technical-documentation/HydroATLAS_TechDoc_v10_1.pdf</p> <p>First column of each of the two files provides station ID allowing to merge both data-sets.</p>
Profiles of 0-50 cm soil CO2 and N2O concentrations collected in the CPCRW from 1998-2002
This table contains concentrations (ppmv) of CO2 and N2O measured at 5, 10, 20, 30, 40, and 50 cm depths below the soil surface in closed-canopy black spruce and mixed hardwood sites (@ 3 replicate sites) in the Caribou Poker Creeks Research Watershed. Samples were taken at weekly or bi-weekly intervals from two profiles in each site during growing seasons from June 1, 1999 through September 17, 2002. This period brackets the Frostfire burn of July 1999; because the fire missed the planned burn sites in mixed hardwoods, the mixed hardwood plots were moved (reflected in the site numbering in the database).
McMurdo Dry Valleys Lake Bonney Autonomous Lake Profiler and Samplers (ALPS): Dissolved CO2 Concentrations
Knowledge of the McMurdo Dry Valley (MDV) lakes is limited by winter access, a period which is most relevant in understanding the habitability of other icy worlds and critical to understanding the overall function of these lakes. Owing to the lack of winter access, data that normally require human presence are incomplete. Our goal was to conduct the first year-round investigation of the biogeophysics of these unique lakes. An important part of the McMurdo Long Term Ecological Research (LTER) is evaluating carbon and nitrogen budgets in perennial ice-covered lakes. This data set addresses this core area of research and quantifies the dissolved CO 2 concentrations found at specific depths in McMurdo Dry Valley lakes.
Elevated atmospheric concentrations of CO2 increase endogenous immune function in a specialist herbivore
<p>1. Animals rely on a balance of endogenous and exogenous sources of immunity to mitigate parasite attack. Understanding how environmental context affects that balance is increasingly urgent under rapid environmental change. In herbivores, immunity is determined, in part, by phytochemistry which is plastic in response to environmental conditions. Monarch butterflies, <i>Danaus plexippus,</i> consistently experience infection by a virulent parasite, <i>Ophryocystis elektroscirrha</i>, and some medicinal milkweed (<i>Asclepias</i>) species, with high concentrations of toxic steroids (cardenolides), provide a potent source of exogenous immunity. 2. We investigated plant-mediated influences of elevated CO<sub>2</sub> (eCO<sub>2</sub>) on endogenous immune responses of monarch larvae to infection by <i>O. elektroscirrha</i>. Recently, transcriptomics have revealed that infection by <i>O. elektroscirrha </i>does not alter monarch immune gene regulation in larvae, corroborating that monarchs rely more on exogenous than endogenous immunity. However, monarchs feeding on medicinal milkweed grown under eCO<sub>2</sub> lose tolerance to the parasite, associated with changes in phytochemistry. Whether changes in milkweed phytochemistry induced by eCO<sub>2</sub> alter the balance between exogenous and endogenous sources of immunity remains unknown. 3. We fed monarchs two species of milkweed; <i>A. curassavica</i> (medicinal) and <i>A. incarnata </i>(non-medicinal) grown under ambient CO<sub>2</sub> (aCO2) or eCO<sub>2</sub>. We then measured endogenous immune responses (phenoloxidase activity, hemocyte concentration, and melanization strength), along with foliar chemistry, to assess mechanisms of monarch immunity under future atmospheric conditions. 4. The melanization response of late-instar larvae was reduced on medicinal milkweed in comparison to non-medicinal milkweed. Moreover, the endogenous immune responses of early-instar larvae to infection by <i>O. elektroscirrha</i> were generally lower in larvae reared on foliage from aCO<sub>2</sub> plants and higher in larvae reared on foliage from eCO<sub>2</sub> plants. When grown under eCO<sub>2</sub>, milkweed plants exhibited lower cardenolide concentrations, lower phytochemical diversity, and lower nutritional quality (higher C:N ratios). Together, these results suggest that the loss of exogenous immunity from foliage under eCO<sub>2</sub> results in increased endogenous immune function. 5. Animal populations face multiple threats induced by anthropogenic environmental change. Our results suggest that shifts in the balance between exogenous and endogenous sources of immunity to parasite attack may represent an underappreciated consequence of environmental change. </p>
The response of the ozone layer to quadrupled CO2 concentrations: implications for climate
<p>The quantification of the climate impacts exerted by stratospheric ozone changes in abrupt 4 × CO2 forcing experiments is an important step in assessing the role of the ozone layer in the climate system. Here, we build on our previous work on the change of the ozone layer under 4 × CO2 and examine the effects of ozone changes on the climate response to 4 × CO2, using the Whole Atmosphere Community Climate Model. We show that the global-mean radiative perturbation induced by the ozone changes under 4 × CO2 is small, due to nearly total cancellation between high and low latitudes, and between longwave and shortwave fluxes. Consistent with the small global-mean radiative perturbation, the effect of ozone changes on the global-mean surface temperature response to 4 × CO2 is negligible. However, changes in the ozone layer due to 4 × CO2 have a considerable impact on the tropospheric circulation. During boreal winter, we find significant ozone-induced tropospheric circulation responses in both hemispheres. In particular, ozone changes cause an equatorward shift of the North Atlantic jet, cooling over Eurasia, and drying over northern Europe. The ozone signals generally oppose the direct effects of increased CO2 levels and are robust across the range of ozone changes imposed in this study. Our results demonstrate that stratospheric ozone changes play a considerable role in shaping the atmospheric circulation response to CO2 forcing in both hemispheres and should be accounted for in climate sensitivity studies.</p>
Simulated atmospheric CO2 concentration at Point Barrow, Alaska
<p>This dataset is provided in order to enable the reproduction of findings from a series of experiments with the CASA-TOMCAT model setup (Chipperfield, 2006). </p> <p>The Carnegie Ames Stanford Approach (CASA) is a land-surface model that was used to produce fluxes of net ecosystem exchange (NEE) and fires. Our simulations held various input parameters constant in CASA (described below). We then forced the TOMCAT atmospheric chemistry model with these data to produce an estimate of atmospheric CO2 at the Barrow Observatory in Alaska. Further information on the details of the model setup is described in the 'Model_setup.txt' file.</p> <p>Enclosed in this directory are the simulated CO2 at Barrow observatory, Alaska (71.3N, 156.6E) for a number of experiments which are described below. Half of the text files have variable meteorology and are described as 'atmos_vary' in the title, the remaining half have constant (periodical) meteorology, in which atmospheric transport is retained at 1992 values (and described as 'atmos_const').</p> <p>Within each file is the time and date of each measurement of atmospheric CO2 in ppm. In order to obtain the required simulated atmospheric value, add the background, ocean, and fossil fuel (FF) tracer values to the relevant NEE and fire value from the simulation of interest.</p> <p>The simulations are as follows (with their abbreviation given in parentheses): </p> <p>Constant, periodical temperature scalar (temp)<br> Constant, periodical temperature and moisture scalars (temppre)<br> Constant, periodical fraction of photosynthetically active radiation (fpar)<br> Constant, periodical solar radiation (solrad)<br> All the above variables held constant, periodical (all)<br> Control run in which everything varies (ctrl)</p>
High-spatiotemporal resolution mapping of spatiotemporally continuous atmospheric CO2 concentrations over the global continent
<p>This dataset contains global continental-scale carbon dioxide inversion results for four periods in 2015 with a spatial resolution of 0.01°.</p>
Effects of elevated temperature and CO2 concentration on floral development and sex differentiation in Morus alba L.
<p>The effects of global warming on floral development have been reported in many plants, but knowledge of floral development regarding gender and sex differentiation under elevated temperature, CO<sub>2</sub> concentration and their combination remains limited. So here we analysed flowering phase, sex ratio, floral morphology and biomass, total carbon and nitrogen data in male and female inflorescences (flowers) of <em>Morus alba </em>L. to determine whether and how they differ.</p> <p>This excel file contains the raw data for each data table and figure within a manuscript submitted to Annals of Forest Science.</p> <p> </p> <p> </p> <p> </p> <p> </p>
Co2 concentration, temperature and humidity in primary classrooms during the Covid-19 Safety Measures in Spain
<p>Co2 concentration, temperature and humidity in primary classrooms during the Covid-19 Safety Measures in Spain. The data presented were collected between 1 May 2020 and 23 June 2021 using a low-cost CO<sub>2</sub> sensor called SCD30 (https://bit.ly/3dDWXu1). This sensor can messure CO<sub>2</sub>, temperature and air humidity. Six nodes were built and deployed in six classrooms in two different schools in two different periods. In the first school, located in Vilafamés (Castellón, Spain), a total of 38,891 observations were carried out. Altogether 34,570 measurements were captured in the second school located in Vall d’Alba (Castellón, Spain).</p>
Data for "Impact of prior terrestrial carbon flux on atmospheric CO2 concentration simulation"
<p>Data for "Impact of prior terrestrial carbon flux on atmospheric CO2 concentration simulation"</p>
Isotopic evidence for increased carbon and nitrogen exchanges between peatland plants and their symbiotic microbes with rising atmospheric CO2 concentrations since 15000 cal. yr BP
<p>Whether nitrogen (N) availability will limit plant growth and removal of atmospheric CO<sub>2</sub> this century is controversial. Studies have suggested that N could progressively limit plant growth, as trees and soils accumulate N in slowly cycling biomass pools in response to increases in carbon sequestration. However, a question remains over the longer-term (decadal to century) feedbacks between climate, CO<sub>2</sub> and plant N uptake. The symbiosis between plants and microbes can help plants with mycorrhizal N uptake or biological N2 fixation – the pathway through which N can be rapidly brought into ecosystems and thereby partially or completely alleviate N limitation on plant productivity. Here we present results for plant N isotope composition (δ<sup>15</sup>N) in a peat core that dates to 15000 cal. yr BP to ascertain ecosystem-level N cycling responses to rising atmospheric CO<sub>2</sub> concentrations in the past. We found that an increase in atmospheric CO<sub>2</sub> concentration happened with a decrease in δ<sup>15</sup>N values of both <em>Sphagnum</em> moss and Ericaceae over this time period when constrained for climatic factors. A modern experiment demonstrated that δ<sup>15</sup>N of <em>Sphagnum</em> mosses decreased with increasing N2 fixation rates. These findings suggested that N2 fixation in <em>Sphagnum</em> moss by symbiosis with cyanobacteria and N uptake in Ericaceae by symbiosis with mycorrhizal fungi both likely increased with rising atmospheric CO<sub>2</sub> concentrations, highlighting a longer-term feedback mechanism whereby N constraints on terrestrial carbon storage can be overcome. </p>
A structured evaluation of regression models for predicting CO2 concentration from plasma emission spectra, dataset
<p>Dataset for publication: <a href="https://doi.org/10.1016/j.sab.2022.106467">https://doi.org/10.1016/j.sab.2022.106467</a>.</p> <p>The recorded spectra are stored as comma separated values, the set includes a meta data-file (.mat-file), and a column descriptions (columns.pdf).</p>
Data From: Laisk measurements in the non-steady-state: tests in plants exposed to warming and variable CO2 concentrations
<p>Light respiration (<em>R</em><sub>L</sub>) is an important component of plant carbon balance and a key parameter in photosynthesis models. <em>R</em><sub>L</sub><em> </em>is often measured using the Laisk method, a gas exchange technique that is traditionally employed under steady-state conditions. However, a non-steady-state dynamic assimilation technique (DAT) may allow for more rapid Laisk measurements. In two studies, we examined the efficacy of DAT for estimating <em>R</em><sub>L</sub> and the parameter <em>C</em><sub>i</sub>*<em> </em>(the intercellular CO<sub>2</sub> concentration where rubisco's oxygenation velocity is twice its carboxylation velocity), which is also derived from the Laisk technique. In the first study, we compared DAT and steady-state <em>R</em><sub>L</sub> and <em>C</em><sub>i</sub>* estimates in paper birch (<em>Betula papyrifera</em>) growing under control and elevated temperature and CO<sub>2</sub> concentrations. In the second, we compared DAT-estimated <em>R</em><sub>L</sub> and <em>C</em><sub>i</sub>* in hybrid poplar (<em>Populus nigra L. x P. maximowiczii</em> A. Henry 'NM6') exposed to high or low CO<sub>2</sub> concentration pre-treatments. The DAT and steady-state methods provided similar <em>R</em><sub>L</sub> estimates in <em>B</em>. <em>papyrifera</em>, and we found little acclimation of <em>R</em><sub>L</sub> to temperature or CO<sub>2</sub>; however, <em>C</em><sub>i</sub>* was higher when measured with DAT compared to steady-state methods. These <em>C</em><sub>i</sub>* differences were amplified by the high or low CO<sub>2</sub> pre-treatments. We propose that changes in the export of glycine from photorespiration may explain these apparent differences in <em>C</em><sub>i</sub>*.</p>
Data From: Laisk measurements in the non-steady-state: tests in plants exposed to warming and variable CO2 concentrations
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Elevated atmospheric concentrations of CO2 increase endogenous immune function in a specialist herbivore
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Isotopic evidence for increased carbon and nitrogen exchanges between peatland plants and their symbiotic microbes with rising atmospheric CO2 concentrations since 15000 cal. yr BP
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