Carbon Dioxide Emissions and Concentrations on the Rise as Kyoto Era Fades

Characteristics of the large-scale circulation during episodes with high and low concentrations of carbon dioxide and air pollutants at an arctic monitoring site in winter

One of the major global issues threatening the survival of mankind is the effects of global warming exacerbated by the increasing production of carbon dioxide emissions. The global atmospheric carbon dioxide (CO₂) concentration has increased by 50 per cent since pre-industrial times, rising from 277 ppm in 1750 to 416 ppm in June 2023. In the US, this end-use sector accounted for more than 36% of CO2 emissions from the combustion of fossil fuel in 2020 for meeting energy demands related to heating and cooling. In Trinidad and Tobago, the electricity usage by the residential and commercial sector accounts for 40% of the power generated of which more than 50% is used for air-conditioning. This research investigates the potential reduction in atmospheric carbon dioxide using coconut fibre as a building thermal insulation via its carbon sequestration properties. Thermal conductivity measurements were conducted in accordance with ASTM C-518-04, standard test method for steady-state thermal transmission properties by means of the heat flow meter apparatus. Coconut Fiber test specimens, 254 mm square, and of thickness, 25.4, 38 and 50.4 mm, respectively, were made. Experiments were conducted at mean test temperatures of 15.6oC and 21.8oC, for the density range 40kg/m3 to 90 kg/m3. For presently used building thermal insulation the environmental payback period shows that insulation materials are environmentally efficient, if they are used for between seven to ten years. This time is required to achieve an equivalent carbon environmental neutrality between production carbon dioxide equivalents (CO2e) and saved CO2e. Research on coconut fiber indicates that it meets the criteria for use as building thermal insulation. The analysis for coconut fiber batt insulation shows carbon sequestration and with building insulation application will continue to decrease the carbon footprint through energy savings. Coconut palm as a monoculture crop provides 51.14 t/hectare per year of above ground carbon stock. This translates to 188.6 Tons of CO2e per hectare. The results indicate that at the installation stage for a 1 m2 area, fiberglass insulation batt has +5 kg CO2e compared to carbon sequestration of 16.1 and 18.6 kg CO2e of coconut fiber insulation for RSI 2.29 and RSI 2.64, respectively. In the case of Trinidad and Tobago, where building insulation is grossly inadequate, if any at all, effective insulation has the potential to reduce the electrical demand for cooling in the residential and commercial sector by 35 to 50%. This translates to 7 to 10 % reduction in the overall electrical demand which is in line with the Kyoto Protocol and Paris Agreement where it was agreed to reduce the overall carbon emissions by 15% by 2030.

To quantify the greenhouse gas emissions from rivers and lakes, environmental conditions, water qualities, carbon dioxide and methane emissions were determined in the up-, mid- and down-stream areas of Kaoping River and Chenching Lake. Atmospheric carbon dioxide concentrations were 292-430, 295-453, 328-476 and 302- 449 ppm, respectively, and atmospheric methane concentrations were 1.70-2.09, 1.71-3.10, 1.70-2.86 and 1.18- 3.60 ppm, respectively. By using the headspace method with brown color bottle, carbon dioxide concentrations were determined as 198-5,437, 1,077-8,584, 3,977-10,839 and 1,537-9,902 ppm, respectively, and methane concentrations fell into the range of 2.8-231.0, 38.9-881.2, 75.3-983.1 and 31.5-4,321.5 ppm, respectively. By using the static-chamber method, carbon dioxide emission rates were -51.3-209.3, -9.6-232.4, -25.7-265.8 and -155.9-217.1 mg m^(-2) h^(-1), respectively, and methane emission rates were 0.05-1.52, 0.05-4.50, 0.26-6.12 and 0.02- 2.68 mg m^(-2) h^(-1), respectively. There is a positive correlation between methane concentration with the headspace method and emission rate with the static-chamber method. Methane emission was very significantly negativelycorrelated with dissolved oxygen (DO), significantly negatively-covrelatived with redox potential (Eh), and very significantly positively-correlated with methane concentration, carbon dioxide concentration using the head-space method, total alkalinity (ALK), and conductivity (CD) in the tested river. Carbon dioxide emission in the tested river had positive correlation with methane concentration by the head-space method. Methane emission in the test lake had very significantly positive correlation with alkalinity (ALK), significantly positive correlation with redox potential (Eh), biological oxygen demand (BOD) and chemical oxygen demand (COD). The annual carbon flows from Kaoping River into ocean from 2003 to 2007 were estimated between 3.7 × 10^5 and 1.7 × 10^6 tons.

In the atmosphere, the amount of carbon dioxide and other greenhouse gases are rising in gradually increasing pace since the Industrial Revolution. The rising concentration of atmospheric carbon dioxide (CO2) contributes to global warming, and the changes affect to both the precipitation and the evaporation quantity. Moreover, the concentration of carbon dioxide directly affects the productivity and physiology of plants. The effect of temperature changes on plants is still controversial, although studies have been widely conducted. The C4-type plants react better in this respect than the C3-type plants. However, the C3-type plants respond more richer for the increase of atmospheric carbon dioxide and climate change.

The increase in carbon dioxide in the atmosphere is one of the main causes of global warming. Remote sensing technology has become an important means of monitoring the distribution of carbon dioxide gas. By remotely monitoring the temporal and spatial distributions of atmospheric carbon dioxide, people can further deepen their understanding of the global carbon process. The GOSAT (Greenhouse Gases Observing SATellite) CO2 L4B concentration data from 2010 to 2015 were validated using local station atmospheric data. The spatial and temporal distributions of the carbon dioxide concentration and its variation characteristics were analyzed. Based on the total primary productivity data and human emissions of carbon dioxide data, the influencing factors of spatial variations in carbon dioxide were analyzed. The results show that: (1) The correlation coefficient between GOSATL4B data and ground-measured data is above 0.95, which indicates that the remotely acquired data have high precision and stability. (2) The spatial distribution characteristics of carbon dioxide at different atmospheric pressure heights are quite different. The variation in the long-term series mean of carbon dioxide concentration levels at 17 vertical heights was studied. The fluctuations in concentration changes at different height levels vary, and the closer to the surface, the greater the fluctuation is. The near-surface carbon dioxide concentration (975 hPa) has the largest fluctuation. When the atmospheric pressure is low (for example, 150 or 100 hPa), the high carbon dioxide concentration region is banded and concentrated near the equator. The trends in carbon dioxide concentration over land and sea surfaces are similar, and the common pattern is that the concentration of carbon dioxide has been increasing. (3) The near-surface carbon dioxide concentration (975 hPa) has clearly different spatial characteristics. There are four high-value centers across the globe: East Asia, western Europe, the US East Coast, and Central Africa. The concentration of carbon dioxide in the Northern Hemisphere near the ground is higher than that in the Southern Hemisphere. The fluctuation in the Southern Hemisphere is relatively small, and the trend is opposite that in the Northern Hemisphere. (4) The concentration of carbon dioxide showed a significant growth trend during the study period. By studying the change characteristics of the monthly global average at the 975 hPa level (approximately 300 m above sea level) from January 2010 to October 2015, it can be seen that the global CO2 concentration has been above 400 ppm for most of the year, and it is increasing each year. (5) Compared with the Southern Hemisphere, the cyclical changes in carbon dioxide concentration in the Northern Hemisphere are obvious and large, while the trend in the Southern Hemisphere is relatively stable, and the change is small. There are opposite trends in the cyclical changes in the carbon dioxide concentration in the Northern and Southern Hemispheres. When the carbon concentration in the Northern Hemisphere resides over the annual high-value area, the Southern Hemisphere has a low-value area of carbon dioxide concentration every year. In addition, the change in carbon dioxide concentration during the year is obvious with seasonal changes. This should be related to changes in vegetation phenology and different seasons in the Northern and Southern Hemispheres. (6) Four countries in East Asia (Korea, Mongolia, Japan and China) from 2010 to 2014 were selected to analyze the relationship between GPP (gross primary production) and near-surface carbon dioxide concentration. These two factors have a significant inverse correlation. When carbon dioxide is at a minimum, the GPP is at its peak, and when carbon dioxide reaches its peak, the GPP reaches a minimum. The above relationship fully indicates that terrestrial ecosystems play an important role as carbon sink contributors in the carbon cycle. (7) The relationship between atmospheric carbon dioxide and carbon dioxide data from human activities from the Global Atmospheric Research Emissions Database was analyzed. The former is significantly and positively correlated with carbon dioxide emissions caused by human activities, indicating that human activities are an important factor in the increase in carbon dioxide.

Isoprenoids (isoprene and monoterpenes) are the most dominant class of biogenic volatile organic compounds (BVOCs) and have been shown to significantly affect global tropospheric chemistry and composition, climate, and the global carbon cycle. In this study we assess the sensitivity of biogenic isoprene and monoterpene emissions to combined and isolated fluctuations in observed global climate and atmospheric carbon dioxide (CO2) concentration during the period 1971–1990. We integrate surface emission algorithms within the framework of a dynamic global ecosystem model, the Integrated Biospheric Simulator (IBIS), to simulate biogenic fluxes of isoprenoids as a component of the climate‐vegetation dynamics. IBIS predicts global land surface isoprene emissions of 454 Tg C and monoterpenes of 72 Tg C annually and captures the spatial and temporal patterns well. The combined fluctuations in climate and atmospheric CO2 during 1971–1990 caused significant interannual and seasonal variability in global biogenic isoprenoid fluxes that was somewhat related to the El Niño‐Southern Oscillation. Furthermore, an increasing trend in the simulated emissions was seen during this period that is attributed partly to the warming trend and partly to CO2 fertilization effect. The isolated effect of increasing CO2 during this period was to steadily increase emissions as a result of increases in foliar biomass. These fluctuations in biogenic emissions could have significant impacts on regional and global atmospheric chemistry and the global carbon budget.

Models are an essential component of any assessment of ecosystem response to changes in global climate and elevated atmospheric carbon dioxide concentration. The problem with these models is that their long-term predictions are impossible to test unambiguously except by allowing enough time for the full ecosystem response to develop. Unfortunately, when one must assess potentially devastating changes in the global environment, time becomes a luxury. Therefore, confidence in these models has to be built through the accumulation of fairly weak corrobatin evidence rather than through a few crucial and unambiguous tests. The criteria employed to judge the value of these models are thus likely to differ greatly from those used to judge finer scale models, which are more amenable to the scientific tradition of hypothesis formulation and testing. This article looks at four categories of tests which could potentially be used to evaluate ERCC (ecosystem response to climate and carbon dioxide concentration) models and illustrates why they cannot be considered crucial tests. The the synthesis role of ERCC models are is discussed and why they are vital to any assessment of long-term responses of ecosystems to changes in global climate and carbon dioxide concentration. 49 refs., 2 figs.

<p>Here we present a 4200-year-old high-resolution peat core reconstruction from southern Patagonia. Our detailed carbon isotope (δ13C) record and testate amoeba-inferred water table depth reconstruction point to a progressive wetting of the peatland surface from 4200 to 1500 cal. yr BP, followed by a dry event at 1200-800 cal. yr BP and drier conditions since then. Superimposed on this trend are centennial-scale dips in δ13C values and water table depths that we associate with warm/dry spells. We interpret these shifts, which are akin to positive phases of the Southern Annual Mode (SAM), as reflecting century-scale changes in the Southern Westerly Wind belt during the late Holocene. Other records from southern South America and Tasmania have revealed synchronous changes in local vegetation and fire activity, strengthening our hypothesis. We know that millennial-scale shifts in the Westerly winds influence ocean upwelling in the Southern Ocean, with effects on global atmospheric carbon dioxide (CO2) concentrations. Our study, along with a few others, may help elucidate whether centennial-scale SAM-like shifts could also modulate the global carbon cycle via CO2 degassing from the deep ocean. This is important because instrumental and reanalysis records indicate strengthening and poleward contraction indicate a positive phase of the SAM since the late twentieth century.</p>

Current terrestrial ecosystem models are usually driven with global average annual atmospheric carbon dioxide (CO2) concentration data at the global scale. However, high‐precision CO2 measurement from eddy flux towers showed that seasonal, spatial surface atmospheric CO2 concentration differences were as large as 35 ppmv and the site‐level tests indicated that the CO2 variation exhibited different effects on plant photosynthesis. Here we used a process‐based ecosystem model driven with two spatially and temporally explicit CO2 data sets to analyze the atmospheric CO2 fertilization effects on the global carbon dynamics of terrestrial ecosystems from 2003 to 2010. Our results demonstrated that CO2 seasonal variation had a negative effect on plant carbon assimilation, while CO2 spatial variation exhibited a positive impact. When both CO2 seasonal and spatial effects were considered, global gross primary production and net ecosystem production were 1.7 Pg C·yr−1 and 0.08 Pg C·yr−1 higher than the simulation using uniformly distributed CO2 data set and the difference was significant in tropical and temperate evergreen broadleaf forest regions. This study suggests that the CO2 observation network should be expanded so that the realistic CO2 variation can be incorporated into the land surface models to adequately account for CO2 fertilization effects on global terrestrial ecosystem carbon dynamics.

Global atmospheric carbon dioxide (CO 2 ) concentrations have increased rapidly in recent years, raising concerns about air‐sea CO 2 exchange. The Arabian Sea, being a major CO 2 source with uncertain coastal fluxes, necessitates assessing its governing mechanisms and key drivers. To address this issue, nine basin‐scale observations were conducted in the eastern Arabian Sea (EAS) between January 2018 and January 2019. Surface p CO 2 (289–1,310 μatm) exhibited the lowest mean in the early spring (428 ± 30 μatm) and the highest in the late summer monsoon (606 ± 97 μatm). Strong upwelling coupled with cyclonic eddies elevates surface p CO 2 in the south and central EAS during the summer monsoon (SM), while moderate upwelling and strong winds drive CO 2 enrichment in the north. Coastal stratification and benthic production lower p CO 2 during non‐monsoons. Annually, mixing accounted for 36%–52% of p CO 2 variability, followed by air‐sea exchange (5%–34%), biological processes (10%–29%) and temperature (3%–26%); freshwater influence was significant only in the south (12%) during the peak SM. Consistently higher surface p CO 2 than the atmosphere makes the EAS a perennial source (4.7 ± 8.4 mmolC m −2 d −1 ), with maximum efflux during the peak SM (15.9 ± 19.5 mmolC m −2 d −1 ). The SM contributes 66% of annual emissions (9.9 TgC y −1 ) as upwelled CO 2 exceeds biological uptake. The north EAS, though productive in winter and summer, emits the most (6.5 TgC y −1 ), with substantial input from turbid macro‐tidal nearshore regions (2.1 TgC y −1 ), making it a hotspot for CO 2 emissions. Although no clear p CO 2 trend emerged over two decades, climate cycles and monsoon intensity strongly modulate interannual variability.

Annual CO2 emissions (in 1000 Mt) %

Radley Horton,1,a Daniel Bader,1,a Yochanan Kushnir,2 Christopher Little,3 Reginald Blake,4 and Cynthia Rosenzweig5 1Columbia University Center for Climate Systems Research, New York, NY. 2Ocean and Climate Physics Department, Lamont-Doherty Earth Observatory, Columbia University, Palisades, NY. 3Atmospheric and Environmental Research, Lexington, MA. 4Physics Department, New York City College of Technology, CUNY, Brooklyn, NY. 5Climate Impacts Group, NASA Goddard Institute for Space Studies; Center for Climate Systems Research, Columbia University Earth Institute, New York, NY

As the global carbon dioxide concentration rises, we need to understand the combination of direct stress effects of this gas and the anticipated effects of climatic change, including drought, on the physiology and growth of all crops [1]. The current increase in the atmospheric carbon dioxide concentration along with predictions of possible future increases in global air temperatures have stimulated interest in the effects of CO2 and temperature on the growth and yield of food crops [2] 2 has been documented continuously since 1958 by Keeling et al. [3], and currently the concentration of CO2 in air is about 360 μL L . The concentration could increase to about 670–760 μL L 1 by the year 2075 mainly because of the burning of fossil fuels [4,5]. General circulation models predict that global warming will result from rising CO2 and other greenhouse gases [6–11]. The stress effects of rising CO2 and elevated temperatures on tropical plants have received less attention than the effects on temperate species [12]. Because both CO2 and temperature have large effects on plants, especially those with the C3 photosynthetic pathway, it is important to quantify the effects of these climatic variables on C3 food crops [10]. Concern over the well-documented increase in the concentration of carbon dioxide in the earth’s atmosphere has stimulated research on the response of plants to this aspect of global change. Much of this research has focused on the response of photosynthetic carbon dioxide fixation, because the process is often dramatically and directly affected by the carbon dioxide concentration, and it is of fundamental importance both to plant growth and to ecosystem carbon storage. The concentration of carbon dioxide in the atmo-

Global warming, driven by greenhouse gas emissions from human activities, poses significant environmental challenges. Accurate greenhouse gas measurement data are crucial for effective emission reduction policies and international cooperation. The spaceborne integrated path differential absorption lidar offers high precision for monitoring global atmospheric carbon dioxide (CO2) concentrations on both days and nights. However, its accuracy can be compromised by water vapor interference. We evaluated the impact of water vapor on CO2 detection, focusing on measurements from an aerosol and carbon dioxide detection lidar onboard the atmospheric environment monitoring satellite. The bias due to water vapor absorption was negligible. However, water vapor broadened the absorption spectrum, causing molecular interference, which could introduce considerable CO2 column concentrations (XCO2) bias. In areas with high water vapor, the bias could exceed 1 ppm. Globally, the annual average bias of XCO2 due to water vapor broadening effects was 0.42 ppm. The analysis highlights the importance to account for water vapor spectrum broadening effects, not only in spaceborne lidar measurements such as ACDL but also in other atmospheric measurement techniques to improve CO2 measurement accuracy and enhance our understanding of global climate change and the carbon cycles.

Carbon emissions threaten marine species