scholarly journals Evaluation of four years continuous δ<sup>13</sup>C(CO<sub>2</sub>) data using a running Keeling approach

2016 ◽  
Author(s):  
Sanam Noreen Vardag ◽  
Samuel Hammer ◽  
Ingeborg Levin
Keyword(s):  
Fossil Fuel ◽  
Co2 Concentration ◽  
High Temporal Resolution ◽  
Data Set ◽  
Additional Information ◽  
Hourly Data ◽  
The Mean ◽  
Carbon Dioxide Co2 ◽  
End Members ◽  
Different Sources

Abstract. As different carbon dioxide (CO2) emitters have different carbon isotope ratios, measurements of atmospheric δ13C(CO2) and CO2 concentration contain information on the CO2 source mix in the catchment area of an atmospheric measurement site. Often, this information is illustratively presented as mean isotopic source signature. Recently an increasing number of continuous measurements of δ13C(CO2) and CO2 have become available, opening the door to quantification of CO2 shares from different sources at high temporal resolution. Here, we present a method to compute the CO2 source signature (δS) continuously without introducing biases and evaluate our result using model data. We find that biases in δS are smaller than 0.2 ‰ with uncertainties of about 1.2 ‰ for hourly data. Applying the method to a four year data set of CO2 and δ13C(CO2) measured in Heidelberg, Germany, yields a distinct seasonal cycle of δS. Disentangling this seasonal source signature into its source components is, however, only possible if the isotopic end members of these sources, i.e., the biosphere, δbio, and the fuel mix, δF, are known. From the mean source signature record in 2012, δbio could be reliably estimated only for summer to (−25 ± 1) ‰ and δF only for winter to (−32.5 ± 2.5) ‰. As the isotopic end members δbio and δF were shown to change over the season, no year-round estimation of the fossil fuel or biosphere share is possible from the measured mean source signature record without additional information from emission inventories or other tracer measurements, such as Δ14C(CO2).

scholarly journals Evaluation of 4 years of continuous <i>δ</i><sup>13</sup>C(CO<sub>2</sub>) data using a moving Keeling plot method

2016 ◽  
Vol 13 (14) ◽  
pp. 4237-4251 ◽  
Author(s):  
Sanam Noreen Vardag ◽  
Samuel Hammer ◽  
Ingeborg Levin
Keyword(s):  
Transport Model ◽  
Co2 Concentration ◽  
High Temporal Resolution ◽  
Model Data ◽  
Additional Information ◽  
Keeling Plot ◽  
Data Points ◽  
The Mean ◽  
Carbon Dioxide Co2 ◽  
End Members

Abstract. Different carbon dioxide (CO2) emitters can be distinguished by their carbon isotope ratios. Therefore measurements of atmospheric δ13C(CO2) and CO2 concentration contain information on the CO2 source mix in the catchment area of an atmospheric measurement site. This information may be illustratively presented as the mean isotopic source signature. Recently an increasing number of continuous measurements of δ13C(CO2) and CO2 have become available, opening the door to the quantification of CO2 shares from different sources at high temporal resolution. Here, we present a method to compute the CO2 source signature (δS) continuously and evaluate our result using model data from the Stochastic Time-Inverted Lagrangian Transport model. Only when we restrict the analysis to situations which fulfill the basic assumptions of the Keeling plot method does our approach provide correct results with minimal biases in δS. On average, this bias is 0.2 ‰ with an interquartile range of about 1.2 ‰ for hourly model data. As a consequence of applying the required strict filter criteria, 85 % of the data points – mainly daytime values – need to be discarded. Applying the method to a 4-year dataset of CO2 and δ13C(CO2) measured in Heidelberg, Germany, yields a distinct seasonal cycle of δS. Disentangling this seasonal source signature into shares of source components is, however, only possible if the isotopic end members of these sources – i.e., the biosphere, δbio, and the fuel mix, δF – are known. From the mean source signature record in 2012, δbio could be reliably estimated only for summer to (−25.0 ± 1.0) ‰ and δF only for winter to (−32.5 ± 2.5) ‰. As the isotopic end members δbio and δF were shown to change over the season, no year-round estimation of the fossil fuel or biosphere share is possible from the measured mean source signature record without additional information from emission inventories or other tracer measurements.

scholarly journals Assimilation of atmospheric CO2 observations from space can support national CO2 emission inventories

2021 ◽  
Author(s):  
Thomas Kaminski ◽  
Marko Scholze ◽  
Peter Rayner ◽  
Michael Voßbeck ◽  
Michael Buchwitz ◽  
...  
Keyword(s):  
Co2 Emission ◽  
Fossil Fuel ◽  
Greenhouse Gas Emission ◽  
Co2 Concentration ◽  
Atmospheric Co2 ◽  
Additional Information ◽  
Emission Estimate ◽  
Carbon Dioxide Co2 ◽  
Assimilation System ◽  
Fossil Fuel Emissions

Abstract The Paris Agreement establishes a transparency framework for anthropogenic carbon dioxide (CO2) emissions. It's core component are inventory-based national greenhouse gas emission reports, which are complemented by independent estimates derived from atmospheric CO2 measurements combined with inverse modelling. It is, however, not known whether such a Monitoring and Verification Support (MVS) capacity is capable of constraining estimates of fossil-fuel emissions to an extent that is sufficient to provide valuable additional information. The CO2 Monitoring Mission (CO2M), planned as a constellation of satellites measuring column-integrated atmospheric CO2 concentration (XCO2), is expected to become a key component of such an MVS capacity. Here we provide a novel assessment of the potential of a comprehensive data assimilation system using simulated XCO2 and other observations to constrain fossil fuel CO2 emission estimates for an exemplary 1-week period in 2008. We find that CO2M enables useful weekly estimates of country-scale fossil fuel emissions independent of national inventories. When extrapolated from the weekly to the annual scale, uncertainties in emissions are comparable to uncertainties in inventories, so that estimates from inventories and from the MVS capacity can be used for mutual verification. We further demonstrate an alternative, synergistic mode of operation, with the purpose of delivering a best fossil fuel emission estimate. In this mode, the assimilation system uses not only XCO2 and the other data streams of the previous (verification) mode, but also the inventory information. Finally, we identify further steps towards an operational MVS capacity.

scholarly journals From runoff to rainfall: inverse rainfall–runoff modelling in a high temporal resolution

2015 ◽  
Vol 19 (11) ◽  
pp. 4619-4639 ◽  
Author(s):  
M. Herrnegger ◽  
H. P. Nachtnebel ◽  
K. Schulz
Keyword(s):  
Daily Rainfall ◽  
Inverse Model ◽  
High Temporal Resolution ◽  
Rainfall Runoff ◽  
Time Step ◽  
Lumped Model ◽  
Additional Information ◽  
Mountainous Regions ◽  
Hourly Data ◽  
Areal Rainfall

Abstract. Rainfall exhibits a large spatio-temporal variability, especially in complex alpine terrain. Additionally, the density of the monitoring network in mountainous regions is low and measurements are subjected to major errors, which lead to significant uncertainties in areal rainfall estimates. In contrast, the most reliable hydrological information available refers to runoff, which in the presented work is used as input for an inverted HBV-type rainfall–runoff model that is embedded in a root finding algorithm. For every time step a rainfall value is determined, which results in a simulated runoff value closely matching the observed runoff. The inverse model is applied and tested to the Schliefau and Krems catchments, situated in the northern Austrian Alpine foothills. The correlations between inferred rainfall and station observations in the proximity of the catchments are of similar magnitude compared to the correlations between station observations and independent INCA (Integrated Nowcasting through Comprehensive Analysis) rainfall analyses provided by the Austrian Central Institute for Meteorology and Geodynamics (ZAMG). The cumulative precipitation sums also show similar dynamics. The application of the inverse model is a promising approach to obtain additional information on mean areal rainfall. This additional information is not solely limited to the simulated hourly data but also includes the aggregated daily rainfall rates, which show a significantly higher correlation to the observed values. Potential applications of the inverse model include gaining additional information on catchment rainfall for interpolation purposes, flood forecasting or the estimation of snowmelt contribution. The application is limited to (smaller) catchments, which can be represented with a lumped model setup, and to the estimation of liquid rainfall.

scholarly journals Diurnal and Seasonal Variations of Carbon Dioxide (CO2) Concentration in Urban, Suburban, and Rural Areas around Tokyo

Atmosphere ◽  
2018 ◽  
Vol 9 (10) ◽  
pp. 367 ◽  
Author(s):  
Ryoichi Imasu ◽  
Yuka Tanabe
Keyword(s):  
Carbon Dioxide ◽  
Seasonal Variations ◽  
Rural Areas ◽  
Urban Areas ◽  
Local Governments ◽  
Inversion Layer ◽  
Co2 Concentration ◽  
Early Spring ◽  
Hourly Data ◽  
Carbon Dioxide Co2

Site environments and instrumental characteristics of carbon dioxide (CO2) measurements operated by local governments in the Kanto Plain, the center of which is Tokyo, were summarized for this study. The observation sites were classified into environments of three types: urban, suburban, and woodland. Based on a few decades of accumulated hourly data, the diurnal and seasonal variations of CO2 concentrations were analyzed as a composite of anomalies from annual means recorded for each site. In urban areas, the highest concentrations appear before midnight in winter. The second peak corresponds to the morning rush hour and the strengthening of the inversion layer. Suburban areas can be characterized as having the highest concentration before dawn and the lowest concentration during the daytime in summer in association with the activation of respiration and photosynthesis of vegetation. In these areas, concentration peaks also appear during the morning rush hour. Woodland areas show background features, with the highest concentration in early spring, which are higher than the global background by about 5 ppmv.

scholarly journals High-frequency productivity estimates for a lake from free-water CO<sub>2</sub> concentration measurements

2018 ◽  
Vol 15 (7) ◽  
pp. 2021-2032 ◽  
Author(s):  
Maria Provenzale ◽  
Anne Ojala ◽  
Jouni Heiskanen ◽  
Kukka-Maaria Erkkilä ◽  
Ivan Mammarella ◽  
...  
Keyword(s):  
Temporal Resolution ◽  
Free Water ◽  
Co2 Concentration ◽  
Freshwater Ecosystems ◽  
High Temporal Resolution ◽  
Data Set ◽  
Fully Integrated ◽  
Global Budgets ◽  
Typical Summer ◽  
Good Agreement

Abstract. Lakes are important actors in biogeochemical cycles and a powerful natural source of CO2. However, they are not yet fully integrated in carbon global budgets, and the carbon cycle in the water is still poorly understood. In freshwater ecosystems, productivity studies have usually been carried out with traditional methods (bottle incubations, 14C technique), which are imprecise and have a poor temporal resolution. Consequently, our ability to quantify and predict the net ecosystem productivity (NEP) is limited: the estimates are prone to errors and the NEP cannot be parameterised from environmental variables. Here we expand the testing of a free-water method based on the direct measurement of the CO2 concentration in the water. The approach was first proposed in 2008, but was tested on a very short data set (3 days) under specific conditions (autumn turnover); despite showing promising results, this method has been neglected by the scientific community. We tested the method under different conditions (summer stratification, typical summer conditions for boreal dark-water lakes) and on a much longer data set (40 days), and quantitatively validated it comparing our data and productivity models. We were able to evaluate the NEP with a high temporal resolution (minutes) and found a very good agreement (R2≥0.71) with the models. We also estimated the parameters of the productivity–irradiance (PI) curves that allow the calculation of the NEP from irradiance and water temperature. Overall, our work shows that the approach is suitable for productivity studies under a wider range of conditions, and is an important step towards developing this method so that it becomes more widely used.

scholarly journals The Tropospheric 14CO2 Level in Mid-Latitudes of the Northern Hemisphere (1959–2003)

Radiocarbon ◽  
2004 ◽  
Vol 46 (3) ◽  
pp. 1261-1272 ◽  
Author(s):  
Ingeborg Levin ◽  
Bernd Kromer
Keyword(s):  
Northern Hemisphere ◽  
West Coast ◽  
Fossil Fuel ◽  
Background Level ◽  
Time Span ◽  
Data Set ◽  
European Mountain ◽  
The Mean

A comprehensive tropospheric 14CO2 data set of quasi-continuous observations covering the time span from 1959 to 2003 is presented. Samples were collected at 3 European mountain sites at height levels of 1205 m (Schauinsland), 1800 m (Vermunt), and 3450 m asl (Jungfraujoch), and analyzed in the Heidelberg Radiocarbon Laboratory. The data set from Jungfraujoch (1986–2003) is considered to represent the free tropospheric background level at mid-latitudes of the Northern Hemisphere, as it compares well with recent (yet unpublished) measurements made at the marine baseline station Mace Head (west coast of Ireland). The Vermunt and Schauinsland records are significantly influenced by regional European fossil fuel CO2 emissions. The respective Δ14CO2 depletions, on an annual mean basis, are, however, only 5 less than at Jungfraujoch. Vermunt and Schauinsland both represent the mean continental European troposphere.

Secondary Organic Carbon Estimations with Hourly Monitoring Data and the OC/EC Primary Ratio Method

2013 ◽  
Vol 295-298 ◽  
pp. 849-853
Author(s):  
Mei Fang Lu ◽  
Mei Chuan Huang ◽  
Chiau Yi Wen ◽  
Yi Hui Wu ◽  
Jim Jui Min Lin
Keyword(s):  
Organic Carbon ◽  
Pollution Source ◽  
Photochemical Reactions ◽  
Monitoring Data ◽  
Ratio Method ◽  
High Temporal Resolution ◽  
Data Set ◽  
Daily Data ◽  
Hourly Data ◽  
Secondary Organic Carbon

This study examined the hourly monitoring data from 2006 to 2009 collected by the Aerosol Supersite of the Environmental Protection Administration of Taiwan. The OC/EC primary ratio method has been applied to estimate the content of secondary organic carbon (SOC). Results of this study indicated that the monthly concentrations of PM2.5, OC, and EC all remained low in summer but went up in winter. Possible factors were climate-related and influences from continental high pressure systems. The content (24–36%) of SOC in summer was significantly higher than in other seasons, indicating that a great formation of organic carbon in summer. When considering the hourly trend, apparent peaks can be consistently observed in the morning, which may be due to an increase of mobile pollution source and photochemical reactions. (OC/EC)min ratio values were calculated based on both hourly and daily concentrations of OC and EC, then annual values (2006~2009) were 0.20~1.11 and 0.68~2.72 for hourly and daily data base respectively. Content of SOC in PM2.5 and OC were estimated to be 16~23 % and 75~93 % based on (OC/EC)min ratio from hourly data set, and were 11~18 % and 42~77 % based on (OC/EC)min ratio from daily data set. Results from this study, as well as those from other studies, demonstrated that the OC/EC ratio is dependent upon the sampling method as well as the method of analysis. Furthermore, the daily OC/EC ratio may change, and significant variations may be found even within 24 hours. Taken together, when conducting estimation of SOC, it is important to eliminate the consideration on background concentrations but to take a good advantage of the high temporal resolution of hourly monitoring data in order to estimate SOC using a corrective approach.

scholarly journals High-frequency productivity estimates for a lake from free-water CO<sub>2</sub> concentration measurements

2017 ◽  
Author(s):  
Maria Provenzale ◽  
Anne Ojala ◽  
Jouni Heiskanen ◽  
Kukka-Maaria Erkkilä ◽  
Ivan Mammarella ◽  
...  
Keyword(s):  
Temporal Resolution ◽  
High Frequency ◽  
Free Water ◽  
Co2 Concentration ◽  
Freshwater Ecosystems ◽  
High Temporal Resolution ◽  
Net Ecosystem Productivity ◽  
Data Set ◽  
Fully Integrated ◽  
Typical Summer

Abstract. Lakes are important actors in biogeochemical cycles and a powerful natural source of CO2. However, they are not yet fully integrated in carbon budgets, and the carbon cycle in the water is still poorly understood. In freshwater ecosystems, productivity studies have usually been carried out with traditional methods (bottle incubations, 14C technique), which are imprecise and have a poor temporal resolution. Consequently, our ability to quantify and predict the net ecosystem productivity (NEP) is limited: the estimates are prone to errors and the NEP cannot be parameterized from environmental variables. Here we expand the testing of a free-water method based on the direct measurement of the CO2 concentration in the water. The approach was proposed already in 2008, but was tested on a very short data set (3 days) under specific conditions (autumn turnover); despite showing promising results, it has not been used ever since. We tested the method under different conditions (summer stratification, typical summer conditions for boreal dark-water lakes) and on a much longer data set (40 days), and quantitatively validated it comparing our data and productivity models. We were able to evaluate the NEP with a high temporal resolution (minutes) and found an excellent agreement with the models. We also estimated the parameters of the productivity-irradiance (PI) curves that allow the calculation of the NEP from irradiance and water temperature. Overall, our work shows that the approach is suitable for productivity studies under a wider range of conditions, and is an important step towards developing it so that it becomes even more general.

scholarly journals The Synergistic Effect of PM2.5 and CO2 Concentrations on Occupant Satisfaction and Work Productivity in a Meeting Room

2021 ◽  
Vol 18 (8) ◽  
pp. 4109
Author(s):  
Jindong Wu ◽  
Jiantao Weng ◽  
Bing Xia ◽  
Yujie Zhao ◽  
Qiuji Song
Keyword(s):  
Air Quality ◽  
Synergistic Effect ◽  
Work Productivity ◽  
Co2 Concentration ◽  
Human Beings ◽  
Meeting Room ◽  
Negative Effect ◽  
Carbon Dioxide Co2 ◽  
Occupant Satisfaction ◽  
Pm2.5 Concentration

High indoor air quality is crucial for the health of human beings. The purpose of this work is to analyze the synergistic effect of particulate matter 2.5 (PM2.5) and carbon dioxide (CO2) concentration on occupant satisfaction and work productivity. This study carried out a real-scale experiments in a meeting room with exposures of up to one hour. Indoor environment parameters, including air temperature, relative humidity, illuminance, and noise level, were controlled at a reasonable level. Twenty-nine young participants were participated in the experiments. Four mental tasks were conducted to quantitatively evaluate the work productivity of occupants and a questionnaire was used to access participants’ satisfaction. The Spearman correlation analysis and two-way analysis of variance were applied. It was found that the overall performance declined by 1% for every 10 μg/m3 increase in PM2.5 concentration. Moreover, for every 10% increase in dissatisfaction with air quality, productivity performance decreased by 1.1% or more. It should be noted that a high CO2 concentration (800 ppm) has a stronger negative effect on occupant satisfaction towards air quality than PM2.5 concentration in a non-ventilated room. In order to obtain optimal occupant satisfaction and work productivity, low concentrations of PM2.5 (<50 μg/m3) and CO2 (<700 ppm) are recommended.

scholarly journals Relationship between large-scale ionospheric field-aligned currents and electron/ion precipitations: DMSP observations

2020 ◽  
Vol 72 (1) ◽  
Author(s):  
Chao Xiong ◽  
Claudia Stolle ◽  
Patrick Alken ◽  
Jan Rauberg
Keyword(s):  
Time Distribution ◽  
Large Scale ◽  
Particle Flux ◽  
Particle Energy ◽  
Lower Latitude ◽  
Particle Precipitation ◽  
Data Set ◽  
The Mean ◽  
Two Parameters ◽  
Meteorological Satellite

Abstract In this study, we have derived field-aligned currents (FACs) from magnetometers onboard the Defense Meteorological Satellite Project (DMSP) satellites. The magnetic latitude versus local time distribution of FACs from DMSP shows comparable dependences with previous findings on the intensity and orientation of interplanetary magnetic field (IMF) By and Bz components, which confirms the reliability of DMSP FAC data set. With simultaneous measurements of precipitating particles from DMSP, we further investigate the relation between large-scale FACs and precipitating particles. Our result shows that precipitation electron and ion fluxes both increase in magnitude and extend to lower latitude for enhanced southward IMF Bz, which is similar to the behavior of FACs. Under weak northward and southward Bz conditions, the locations of the R2 current maxima, at both dusk and dawn sides and in both hemispheres, are found to be close to the maxima of the particle energy fluxes; while for the same IMF conditions, R1 currents are displaced further to the respective particle flux peaks. Largest displacement (about 3.5°) is found between the downward R1 current and ion flux peak at the dawn side. Our results suggest that there exists systematic differences in locations of electron/ion precipitation and large-scale upward/downward FACs. As outlined by the statistical mean of these two parameters, the FAC peaks enclose the particle energy flux peaks in an auroral band at both dusk and dawn sides. Our comparisons also found that particle precipitation at dawn and dusk and in both hemispheres maximizes near the mean R2 current peaks. The particle precipitation flux maxima closer to the R1 current peaks are lower in magnitude. This is opposite to the known feature that R1 currents are on average stronger than R2 currents.

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