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>

scholarly journals Technical Note: Long-term memory effect in the atmospheric CO<sub>2</sub> concentration at Mauna Loa

2006 ◽  
Vol 6 (6) ◽  
pp. 11957-11970 ◽  
Author(s):  
C. Varotsos ◽  
M.-N. Assimakopoulos ◽  
M. Efstathiou
Keyword(s):  
Carbon Dioxide ◽  
Time Series ◽  
Power Law ◽  
Carbon Dioxide Concentration ◽  
Global Climate Models ◽  
Fluctuation Analysis ◽  
Original Time Series ◽  
Mauna Loa ◽  
Carbon Dioxide Concentrations ◽  
Original Time

Abstract. The monthly mean values of the atmospheric carbon dioxide concentration derived from in-situ air samples collected at Mauna Loa Observatory, Hawaii, during 1958–2004 (the longest continuous record available in the world) are analyzed by employing the detrended fluctuation analysis to detect scaling behavior in this time series. The main result is that the fluctuations of carbon dioxide concentrations exhibit long-range power-law correlations (long memory) with lag times ranging from four months to eleven years, which correspond to 1/f noise. This result indicates that random perturbations in the carbon dioxide concentrations give rise to noise, characterized by a frequency spectrum following a power-law with exponent that approaches to one; the latter shows that the correlation times grow strongly. This feature is pointing out that a correctly rescaled subset of the original time series of the carbon dioxide concentrations resembles the original time series. Finally, the power-law relationship derived from the real measurements of the carbon dioxide concentrations could also serve as a tool to improve the confidence of the atmospheric chemistry-transport and global climate models.

scholarly journals Investigating the effect of carbon dioxide on the acidity of the Ocean

2021 ◽  
Vol 6 (6) ◽  
pp. 212-214
Author(s):  
AA El-Meligi
Keyword(s):  
Carbon Dioxide ◽  
Ocean Acidification ◽  
Data Center ◽  
Carbonic Acid ◽  
Carbon Dioxide Concentration ◽  
Research Institutions ◽  
Animal Life ◽  
Mauna Loa ◽  
Carbonate Ions ◽  
Snow And Ice

There is a significant effect of carbon dioxide on the acidification of the ocean. This research focuses on the acidification of the ocean and its effect on the animal life in the ocean. Also, it focuses on the effect of carbon dioxide concentration in the atmosphere on the ocean acidification. The data are collected from the research institutions and laboratories, such as National Snow and Ice Data Center (NSIDC), Japan, National Oceanic and Atmospheric Administration (NOAA), USA, Mauna Loa Observatory in Hawaii, and other sources of research about acidification of ocean. The results show that the acidity increases with increasing the amount of carbon dioxide in the atmosphere. This is because ocean absorbs nearly 50% of carbon dioxide from the atmosphere. Carbonate ions (CO32-) will be used in forming carbonic acid, which will increase the acidity of the water. Increasing the acidity of water will affect building of the animal Skeleton. It is recommended to reduce the amount of carbon dioxide in the atmosphere; therefore the acidity will be decreased in the ocean.

scholarly journals Comparative Analysis of Atmospheric Carbon Dioxide Concentration and Temperature between Forest and Non-Forested Domains in Oyo State, Nigeria

2021 ◽  
Vol 25 (3) ◽  
pp. 445-449
Author(s):  
B.M. Awosusi ◽  
I.S. Adamu ◽  
A.R. Orunkoyi ◽  
D.O. Atiba ◽  
A.A. Obe ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Atmospheric Carbon Dioxide ◽  
Anthropogenic Activities ◽  
Carbon Dioxide Concentration ◽  
High Rate ◽  
Afternoon Session ◽  
Forest Reserve ◽  
Positive Correlation ◽  
Routine Monitoring ◽  
Reduce Carbon Dioxide

This study was carried out to assess the concentration levels of CO2 and temperature and also to correlate their values among selected locations in Oyo State, Nigeria. CO2 and temperature readings were taken using a portable CO2 meter, and a GPS was use to capture co-ordinates of sample points, this was done twice a day. Data were collected from 7am to 11am for morning session while afternoon session data were collected between 1pm and  5pm making a total of 8 hours monitoring. There were negative correlation between CO2 and temperature in all the forests while we have positive correlation between CO2 and temperature in non-forested domains, this,  by implication, means that presence of trees in the forest reserve help to reduce Carbon dioxide during the day since trees  manufacture their food using CO2 in the presence of sunlight. Also, the positive correlation between CO2 and temperature in the towns is due to high rate of human anthropogenic activities during the day. The values of CO2 obtained in this study were higher when  compared with IPCC limit of 435 ppm (parts per million) of CO2 emission. Routine monitoring of carbon dioxide and public education is recommended. Keywords: Carbon dioxide, Temperature, Forest, Non-Forest, Forest Reserve

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 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 Technical Note: Long-term memory effect in the atmospheric CO<sub>2</sub> concentration at Mauna Loa

2007 ◽  
Vol 7 (3) ◽  
pp. 629-634 ◽  
Author(s):  
C. Varotsos ◽  
M.-N. Assimakopoulos ◽  
M. Efstathiou
Keyword(s):  
Carbon Dioxide ◽  
Time Series ◽  
Power Law ◽  
Carbon Dioxide Concentration ◽  
Global Climate Models ◽  
Fluctuation Analysis ◽  
Original Time Series ◽  
Mauna Loa ◽  
Carbon Dioxide Concentrations ◽  
Original Time

Abstract. The monthly mean values of the atmospheric carbon dioxide concentration derived from in-situ air samples collected at Mauna Loa Observatory, Hawaii, USA during 1958–2004 (the longest continuous record available in the world) are analyzed by employing the detrended fluctuation analysis to detect scaling behavior in this time series. The main result is that the fluctuations of carbon dioxide concentrations exhibit long-range power-law correlations (long memory) with lag times ranging from four months to eleven years, which correspond to 1/f noise. This result indicates that random perturbations in the carbon dioxide concentrations give rise to noise, characterized by a frequency spectrum following a power-law with exponent that approaches to one; the latter shows that the correlation times grow strongly. This feature is pointing out that a correctly rescaled subset of the original time series of the carbon dioxide concentrations resembles the original time series. Finally, the power-law relationship derived from the real measurements of the carbon dioxide concentrations could also serve as a tool to improve the confidence of the atmospheric chemistry-transport and global climate models.

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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