scholarly journals A Descriptive Time Series Analysis Applied to the Fit of Carbon-Dioxide (CO2)

2019 ◽  
Vol 21 ◽  
pp. 1-8
Author(s):  
Chijioke Joel Nweke ◽  
George Chinanu Mbaeyi ◽  
Kelechi Charity Ojide ◽  
Ogbonnia Elem-Uche ◽  
Onyekachi Stanley Nwebe
Keyword(s):  
Carbon Dioxide ◽  
Time Series ◽  
Coefficient Of Variation ◽  
Atmospheric Carbon Dioxide ◽  
Study Data ◽  
Multiplicative Model ◽  
Seasonal Component ◽  
Variation Approach ◽  
Level Of Significance ◽  
Series Technique

The study examined the use of population spectrum in determining the nature (deterministic and stochastic) of trend and seasonal component of given time series. It also adopts the use of coefficient of variation approach in the choice of appropriate model in descriptive time series technique. Illustrations were carried out using average monthly atmospheric Carbon dioxide (C02) from 2000-2017 with 2018 used for forecast. Spectrum analysis showed that the descriptive technique of time series is more appropriate for analysis of the study data. The coefficient of variation revealed that the multiplicative model was appropriate for the CO2 data while the forecast and the actual values showed no significant mean difference at 5% level of significance.

Stochastic analysis of time-series related to ocean acidification

2021 ◽  
Author(s):  
Georgios Vagenas ◽  
Theano Iliopoulou ◽  
Panayiotis Dimitriadis ◽  
Demetris Koutsoyiannis
Keyword(s):  
Carbon Dioxide ◽  
Time Series ◽  
Ocean Acidification ◽  
Atmospheric Carbon Dioxide ◽  
Anthropogenic Activities ◽  
Time Lag ◽  
Carbon Dioxide Concentration ◽  
Carbon Dioxide Partial Pressure ◽  
Chemical Transformations ◽  
Mauna Loa

<p>Since the pre-industrial era at the end of the 18<sup>th</sup> century, the atmospheric carbon dioxide concentration (CO<sub>2</sub>) has increased by 47.46% from the level of 280 ppmv (parts per million volume) to 412.89 ppmv (Mauna Loa – NOAA Station, November 2020). These increased concentrations caused by natural & anthropogenic activities, interact with the aquatic environment which acts as a safety valve. Nevertheless, the absorbed CO<sub>2 </sub>amounts undergo chemical transformations, resulting in increasing ionized concentrations that can significantly reduce the water’s pH, a process described as ocean acidification. Here, we use the HOT (Hawaii-Ocean-Time series) to perform time series analysis for temperature, carbon dioxide partial pressure and pH. More specifically, we analyze their temporal changes in month and annual time lag. Then, we proceed in comparisons with relevant studies on atmospheric data to evaluate the produced results. Finally, we make an effort to disentangle the results with simplified assumptions connected with the observed impact of ocean acidification on the aquatic ecosystems.</p>

A time series sequestration and storage model of atmospheric carbon dioxide

2014 ◽  
Vol 272 ◽  
pp. 59-67 ◽  
Author(s):  
G.L.A.F. Arce ◽  
J.A. Carvalho ◽  
L.F.C. Nascimento
Keyword(s):  
Carbon Dioxide ◽  
Time Series ◽  
Atmospheric Carbon Dioxide ◽  
Storage Model ◽  
Atmospheric Carbon ◽  
And Storage

scholarly journals Detecting causality signal in instrumental measurements and climate model simulations: global warming case study

2019 ◽  
Author(s):  
Mikhail Y. Verbitsky ◽  
Michael E. Mann ◽  
Byron A. Steinman ◽  
Dmitry M. Volobuev
Keyword(s):  
Carbon Dioxide ◽  
Time Series ◽  
Atmospheric Carbon Dioxide ◽  
Climate Model ◽  
Carbon Dioxide Concentration ◽  
Anthropogenic Forcing ◽  
Carbon Dioxide Concentrations ◽  
Climate Model Simulations ◽  
Earth’S Climate

Abstract. Detecting the direction and strength of the causality signal in observed time series is becoming a popular tool for exploration of distributed systems such as Earth's climate system. Here we suggest that in addition to reproducing observed time series of climate variables within required accuracy a model should also exhibit the causality relationship between variables found in nature. Specifically, we propose a novel framework for a comprehensive analysis of climate model responses to external natural and anthropogenic forcing based on the method of conditional dispersion. As an illustration, we assess the causal relationship between anthropogenic forcing (i.e., atmospheric carbon dioxide concentration) and surface temperature anomalies. We demonstrate a strong directional causality between global temperatures and carbon dioxide concentrations (meaning that carbon dioxide affects temperature stronger than temperature affects carbon dioxide) in both the observations and in (CMIP5) climate model simulated temperatures.

scholarly journals The water column distribution of carbonate system variables at the ESTOC site from 1995 to 2004

2010 ◽  
Vol 7 (2) ◽  
pp. 1995-2032 ◽  
Author(s):  
M. González-Dávila ◽  
J. M. Santana-Casiano ◽  
M. J. Rueda ◽  
O. Llinás
Keyword(s):  
Carbon Dioxide ◽  
Time Series ◽  
North Atlantic ◽  
Atmospheric Carbon Dioxide ◽  
Inorganic Carbon ◽  
Total Alkalinity ◽  
Carbonate System ◽  
Anthropogenic Co2 ◽  
Atmospheric Carbon ◽  
System Variables

Abstract. The accelerated rate of increase in the atmospheric carbon dioxide (CO2) and the substantial fraction of anthropogenic CO2 emissions absorbed by the oceans are affecting the anthropocenic properties of seawater. Long-term time series are a powerful tool for investigating any change in ocean bio-geochemistry and its effects on the carbon cycle. We have evaluated the ESTOC (European Station for Time series in the Ocean at the Canary islands) observations of measured pH (total scale at 25 °C) and total alkalinity plus computed total dissolved inorganic carbon CO2 concentration (CT) from 1995 to 2004 for surface and deep waters, by following all changes in response to increasing atmospheric carbon dioxide. The experimental values for the partial surface pressure of CO2 from 1995 to 2008 were also taken into consideration. The data were treated to better understand the fundamental processes controlling vertical distributions in the Eastern North Atlantic Ocean and the accumulation of anthropogenic CO2, CANT. CT at constant salinity, NCT, increased at a rate of 1 μmol kg−1 yr−1 in the first 200 m, linked to an fCO2 increase of 1.7±0.7 μatm yr−1 in both the atmosphere and the ocean. Consequently, the ESTOC site has also become more acidic, −0.0018±0.0003 units yr−1 over the first 100 m, whereas the carbonate ion concentrations and CaCO3 saturation states have also decreased over time. The rate of change is to be observed over the first 1000 m, where at 300, 600, and 1000 m the NCT increases at a rate of 0.69, 0.61 and 0.48 μmol kg−1 yr−1, respectively. The vertical distribution of the carbonate system variables are affected by the water mass structure and, to a different extent, controlled by the production/decomposition of organic matter, the formation/dissolution of carbonates, and differences in their respective pre-formed values. At 3000 m, 30% of the inorganic carbon production is related to the dissolution of calcium carbonate, with a total of 35% at the bottom. The total column inventory of anthropogenic CO2 for the decade was 66±3 mol m−2. A model fitting indicated that the column inventory of CANT increased from 61.7 mol m−2 in the year 1994 to 70.2 mol m−2 in 2004. The ESTOC site is presented by way of a reference site to follow CANT changes in the North Atlantic Sub-tropical gyre.

scholarly journals Detecting causality signal in instrumental measurements and climate model simulations: global warming case study

2019 ◽  
Vol 12 (9) ◽  
pp. 4053-4060 ◽  
Author(s):  
Mikhail Y. Verbitsky ◽  
Michael E. Mann ◽  
Byron A. Steinman ◽  
Dmitry M. Volobuev
Keyword(s):  
Carbon Dioxide ◽  
Time Series ◽  
Atmospheric Carbon Dioxide ◽  
Climate Model ◽  
Carbon Dioxide Concentration ◽  
Coupled Model ◽  
Anthropogenic Forcing ◽  
Carbon Dioxide Concentrations ◽  
Climate Model Simulations ◽  
Earth’S Climate

Abstract. Detecting the direction and strength of the causality signal in observed time series is becoming a popular tool for exploration of distributed systems such as Earth's climate system. Here, we suggest that in addition to reproducing observed time series of climate variables within required accuracy a model should also exhibit the causality relationship between variables found in nature. Specifically, we propose a novel framework for a comprehensive analysis of climate model responses to external natural and anthropogenic forcing based on the method of conditional dispersion. As an illustration, we assess the causal relationship between anthropogenic forcing (i.e., atmospheric carbon dioxide concentration) and surface temperature anomalies. We demonstrate a strong directional causality between global temperatures and carbon dioxide concentrations (meaning that carbon dioxide affects temperature more than temperature affects carbon dioxide) in both the observations and in (Coupled Model Intercomparison Project phase 5; CMIP5) climate model simulated temperatures.

scholarly journals The water column distribution of carbonate system variables at the ESTOC site from 1995 to 2004

2010 ◽  
Vol 7 (10) ◽  
pp. 3067-3081 ◽  
Author(s):  
M. González-Dávila ◽  
J. M. Santana-Casiano ◽  
M. J. Rueda ◽  
O. Llinás
Keyword(s):  
Carbon Dioxide ◽  
Time Series ◽  
Mixed Layer ◽  
Atmospheric Carbon Dioxide ◽  
Inorganic Carbon ◽  
Dissolved Inorganic Carbon ◽  
Total Alkalinity ◽  
Anthropogenic Co2 ◽  
Rate Of Increase ◽  
Atmospheric Carbon

Abstract. The accelerated rate of increase in atmospheric carbon dioxide and the substantial fraction of anthropogenic CO2 emissions absorbed by the oceans are affecting the anthropocenic signatures of seawater. Long-term time series are a powerful tool for investigating any change in ocean bio-geochemistry and its effects on the carbon cycle. We have evaluated the ESTOC (European Station for Time series in the Ocean at the Canary islands) observations of measured pH (total scale at 25 °C) and total alkalinity plus computed total dissolved inorganic carbon concentration (CT) from 1995 to 2004 for surface and deep waters, by following all changes in response to increasing atmospheric carbon dioxide. The observed values for the surface partial pressure of CO2 from 1995 to 2008 were also taken into consideration. The data were treated to better understand the fundamental processes controlling vertical distributions in the Eastern North Atlantic Ocean and the accumulation of anthropogenic CO2, CANT. CT at constant salinity, NCT, increased at a rate of 0.85 μmol kg−1 yr−1 in the mixed layer, linked to an fCO2 increase of 1.7±0.7 μatm yr−1 in both the atmosphere and the ocean. Consequently, the mixed layer at ESTOC site has also become more acidic, −0.0017±0.0003 units yr−1, whereas the carbonate ion concentrations and CaCO3 saturation states have also decreased over time. NCT increases at a rate of 0.53, 0.49 and 0.40 μmol kg−1 yr−1 at 300, 600, and 1000 m, respectively. The general processes controlling the vertical variations of alkalinity and the inorganic carbon distribution were computed by considering the pre-formed values, the production/decomposition of organic matter and the formation/dissolution of carbonates. At 3000 m, 30% of the inorganic carbon production is related to the dissolution of calcium carbonate, increasing to 35% at 3685 m. The total column inventory of anthropogenic CO2 for the decade was 66±3 mol m−2. A model fitting indicated that the column inventory of CANT increased from 61.7 mol m−2 in the year 1994 to 70.2 mol m−2 in 2004. The ESTOC site is presented as a reference site to follow CANT changes in the Northeast Atlantic Sub-tropical gyre.

Communication: Photoinduced Carbon Dioxide Binding with Surface-Functionalized Silicon Quantum Dots

2018 ◽  
Author(s):  
Oscar A. Douglas-Gallardo ◽  
Cristián Gabriel Sánchez ◽  
Esteban Vöhringer-Martinez
Keyword(s):  
Carbon Dioxide ◽  
Quantum Dots ◽  
Atmospheric Carbon Dioxide ◽  
Density Functional ◽  
Tight Binding ◽  
Carbon Dioxide Concentration ◽  
Research Area ◽  
Silicon Quantum Dots ◽  
Dependent Model ◽  
Photoinduced Charge

<div> <div> <div> <p>Nowadays, the search of efficient methods able to reduce the high atmospheric carbon dioxide concentration has turned into a very dynamic research area. Several environmental problems have been closely associated with the high atmospheric level of this greenhouse gas. Here, a novel system based on the use of surface-functionalized silicon quantum dots (sf -SiQDs) is theoretically proposed as a versatile device to bind carbon dioxide. Within this approach, carbon dioxide trapping is modulated by a photoinduced charge redistribution between the capping molecule and the silicon quantum dots (SiQDs). Chemical and electronic properties of the proposed SiQDs have been studied with Density Functional Theory (DFT) and Density Functional Tight-Binding (DFTB) approach along with a Time-Dependent model based on the DFTB (TD-DFTB) framework. To the best of our knowledge, this is the first report that proposes and explores the potential application of a versatile and friendly device based on the use of sf -SiQDs for photochemically activated carbon dioxide fixation. </p> </div> </div> </div>

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