Source Of Carbon Dioxide Research Articles

Extreme rainfall events eliminate the response of greenhouse gas fluxes to hydrological alterations and fertilization in a riparian ecosystem

Riparian ecosystems are essential carbon dioxide (CO2) sources, which considerably promotes climate warming. However, the other greenhouse gas fluxes (GHGs), such as methane (CH4) and nitrous oxide (N2O), in the riparian ecosystems have not been well studied, and it remains unclear whether and how these GHG fluxes respond to extreme weather, fertilization and hydrological alterations associated with reservoir management. Here, we assessed the impacts of hydrological alterations (i.e., flooding frequency) and fertilization (nitrogen and/or phosphorus) induced by human activities (hydroengineering construction and agricultural activities) on GHG fluxes, and further investigated the underlying mechanisms in two contrasting years (normal vs. extreme rainfall years) in a reservoir riparian zone dominated by grasses. The significant combined effects of extreme rainfall events and human activities (hydrological alterations and fertilization) on the GHGs were observed. Continuous flooding reduced CO2 emissions by 24% but increased CH4 emissions by ∼4 times in a normal rainfall year. In addition, nitrogen fertilization promoted CO2 emissions by 37%. However, these phenomena were not observed in the year with extreme rainfall events, which made the flooding levels homogeneous across the treatments. Furthermore, we found that CO2 fluxes were driven by the soil moisture, nutrient content, aboveground biomass, and root carbon content, while CH4 and N2O fluxes were merely driven by the soil properties (pH, moisture, and nutrient content). This study provides valuable insights into the crucial role of extreme rainfall events, hydrological alteration, and fertilization in regulating GHG fluxes in riparian ecosystems, as well as supports the integration of these changes in GHG emission models.

Validating the rhenium proxy for rock organic carbon oxidation using weathering profiles

Chemical weathering over geological timescales acts as a source or sink of atmospheric carbon dioxide (CO2), while influencing long-term redox cycling and atmospheric oxygen (O2) at Earth's surface. There is a growing recognition that the oxidative weathering of rock organic carbon (OCpetro) can release more CO2 than is locally drawn down by silicate weathering, and may vary due to changes in erosion and climate. The element rhenium (Re) has emerged as a proxy to track the oxidative weathering of OCpetro, yet uncertainties in its application remain namely that we lack a systematic assessment of the comparative mobility of Re and OCpetro during sedimentary rock weathering. Here we measure Re and OCpetro loss across gradients in rock weathering at 12 global sites, spanning a range of initial OCpetro values from ~0.2 % to >10 %. At nine sites we use titanium to account for volume changes during weathering and assess Re and OCpetro loss alongside major elements that reflect silicate (Na, Mg), carbonate (Ca, Mg) and sulfide (S) weathering. Across the dataset, Re loss is correlated with OCpetro loss but not with loss of any other major element. Across the weathering profiles, the average molar ratio of OCpetro to Re loss was 0.84 ± 0.15, with 8 out of 9 sites having a ratio >0.74. At one site (Marcellus Shale), the average ratio was lower at 0.58 ± 0.11. The excess loss of Re matches expectations that, typically, between ~0 and 20 % of the Re liberated by sedimentary rock weathering derives from silicate or sulfide phases, while some OCpetro may be physically or chemically protected from weathering. Overall, our measurements provide validation for the Re proxy of OCpetro oxidation and allow future work to further improve our knowledge of regional and global-scale rates of this important source of CO2 in the geochemical carbon cycle.

CO2 Emissions Associated with Groundwater Storage Depletion in South Korea: Estimation and Vulnerability Assessment Using Satellite Data and Data-Driven Models

Groundwater is crucial in mediating the interactions between the carbon and water cycles. Recently, groundwater storage depletion has been identified as a significant source of carbon dioxide (CO2) emissions. Here, we developed two data-driven models—XGBoost and convolutional neural network–long short-term memory (CNN-LSTM)—based on multi-satellite and reanalysis data to monitor CO2 emissions resulting from groundwater storage depletion in South Korea. The data-driven models developed in this study provided reasonably accurate predictions compared with in situ groundwater storage anomaly (GWSA) observations, identifying relatively high groundwater storage depletion levels in several regions over the past decade. For each administrative region exhibiting a decreasing groundwater storage trend, the corresponding CO2 emissions were quantified based on the predicted GWSA and respective bicarbonate concentrations. For 2008–2019, XGBoost and CNN-LSTM estimated CO2 emissions to be 0.216 and 0.202 MMTCO2/year, respectively. Furthermore, groundwater storage depletion vulnerability was assessed using the entropy weight method and technique for order of preference by similarity to ideal solution (TOPSIS) to identify hotspots with a heightened potential risk of CO2 emissions. Western South Korean regions were particularly classified as high or very high regions and susceptible to groundwater storage depletion-associated CO2 emissions. This study provides a foundation for developing countermeasures to mitigate accelerating groundwater storage depletion and the consequent rise in CO2 emissions.

Land use and urbanization indirectly control riverine CH4 and CO2 emissions by altering nutrient input

Urban rivers are recognized as significant sources of methane (CH4) and carbon dioxide (CO2) emissions. Despite this, the influence of land use and urbanization on carbon emissions across rural-urban rivers at the watershed scale has been insufficiently explored. This study utilized in-situ surveys of the Liao River in northern China to investigate the spatial and temporal variations of CH4 and CO2 emissions and their relationship with urbanization and its potential controlling factors. The findings revealed that CH4 emissions peaked in fall, whereas CO2 emissions were highest in summer. The average fluxes of CH4 and CO2 at the water-gas interface were 1387.22 ± 2474.98 µmol·m−2·d−1 and 52.78 ± 54.44 mmol·m−2·d−1, respectively. Water quality parameters accounted for 80.49 % of the total variation in CH4 and CO2 concentrations and fluxes. Structural equation modeling indicated that TN, TP, DTC, and conductivity had direct effects on riverine CH4 and CO2 emissions, with standardized direct effects of 0.50 and 0.49, respectively. Nutrient input emerged as the primary driver, increasing CH4 and CO2 concentrations and fluxes, particularly in urban-adjacent river sections likely receiving higher nutrient loads. This study underscores that land use and urbanization indirectly influence riverine CH4 and CO2 emissions by modifying nutrient inputs. Effective land use management and nutrient input control are recommended strategies to mitigate riverine CH4 and CO2 emissions.

Investigating carbon footprints of the Malawi University of Science and Technology

Background: Increasing greenhouse gasses concentration in the atmosphere is perturbing the environment to cause grievous global warming and associated consequences. Following the rule that only measurable is manageable, mensuration of greenhouse gas intensiveness of different products, bodies, and processes is going on worldwide, expressed as their carbon footprints (CF). Methods: The methodologies for carbon footprint calculations are still evolving and it is emerging as an important tool for greenhouse gas management. The purpose of this paper was to determine the CF of the Malawi University of Science and Technology (MUST) campus and identify the stressors. The greenhouse gasses (GHG) protocol separates emissions into three scopes which include scope 1 of direct emissions, scope 2 which is indirect emissions, and scope 3 of other indirect emissions. Findings: The estimation of CF from transportation measured 930670.2 kgCO2e, and from electricity measured 2824243.2 kgCO2e while from the use of charcoal fuel measured 30804 kgCO2e. Results showed that emissions generated by gen-sets and transportation produced the highest contribution of 669124.8 kgCO2e and 238991.4 kgCO2e respectively to the MUST campus in the year 2018-2019 as compared to previous years (2015-2017). Conclusion: The study strongly suggested that for the whole 5 years period the use of gen-sets in the campus was the main stressor and this was due to frequent blackouts. Second was transport and as the university grows, the demand for transportation will also increase hence more emissions from transport. Therefore the study recommends that the university should be more considerate of these carbon dioxide sources so as it is trying to meet its needs and demand from these activities, it should also consider reducing the carbon footprint of the campus. Novelty/Originality of this Study: In a pioneering effort for Malawian higher education institutions, this study quantifies the carbon footprint of the Malawi University of Science and Technology campus, paving the way for targeted greenhouse gas management strategies in academic settings.

Enhancing sustainability in concrete production: A novel compression casting technique for optimizing cement usage

Cement manufacturing is a major source of carbon dioxide (CO2) emissions. This study focuses on using the compression casting method to reduce the cement content in concrete manufacturing. No such work is present in the existing literature. For this purpose, five concrete mix designs of normal concrete (NC) and compression cast concrete (CCC), targeting compressive strengths of 50 MPa, 30 MPa, 25 MPa, 20 MPa, and 15 MPa, were considered. Moreover, considering the reduced cement content, five additional concrete mixes of NC and CCC were also prepared. All concrete specimens were tested in axial compression to study the stress-strain behavior. The findings reveal that CCC specimens exhibit higher stress-strain curves compared to NC specimens for the same mix design. The post-peak behavior of CCC specimens is observed to be more brittle than that of NC specimens. The reduction in density, compressive strength, and elastic modulus with the increase in the water-to-cement (w/c) ratio is more pronounced in NC specimens than in CCC specimens. The results indicate that the compression casting method allows for a reduction in cement content by approximately 25–50 % while achieving the desired compressive strengths, ranging from 30 to 50 MPa. A correlation is clearly demonstrated to determine the potential cement savings for specific concrete strengths. In summary, adopting compression casting technology effectively lowers cement requirements, leading to cost and carbon emission reductions in the construction sector and significantly enhancing the durability of concrete materials.

Study on the stability and properties of carbon neutral methanol in blends with diesel fuel

As the simplest liquid fuel, methanol can be sustainably produced from carbon dioxide and renewable energy sources. It is one of the most competitive green fuels. However, there are difficulties in being miscible with conventional fuels when it is used as a blended fuel. In this paper, the furan from biomass is used as the co-solvent of methanol blended fuel, which is expected to address the issue. In this study, not only surface tension, electrical conductivity, and particle size were used to characterize the macroscopic and microscopic structures of carbon neutral methanol blended fuels, and fuel properties including the density, lower calorific value and corrosivity of the mixed fuel have also been discussed. Results indicate that biomass furan reduces the surface tension and keeps the mixed fuel in a microemulsion state for more than 45 days. It increases the fuel density, reduces the unit calorific value cost, and slightly aggravates the corrosion. Carbon neutral methanol fuel, with the help of biomass furan, can be used together with traditional fossil fuels, providing a potential effective path for the efficient and convenient application of new carbon neutral fuels and biomass fuels.

Analysing type of plants for reducing noise pollution in climate change adaptation

Abstract The noisier a region or city is, the faster the rate of global warming. Noise is not a substance. However, most sources of carbon dioxide and other greenhouse gases are also sources of noise; for example, busy highways in cities can occasionally see as many as 100 cars per hour. Planting trees to mitigate noise pollution has been identified as one of the most sustainable methods to employ, since plants may function as a buffer and absorb sounds. Several plant species were chosen to assess noise absorption based on parameters such as leaf thickness, breadth, surface area, and length. The initial goal of this study is to estimate the noise absorption on the selected flora native to the Malaysian environment, where the noise was measured using an in-house developed impedance tube to discover the effective acoustic characteristics of leaves. The investigation was then carried on by assessing the data on the correlation coefficient parameter in order to determine the link between noise absorption and leaf features. Because of the freshness and perishability of the materials, measurements were repeated twice. Only 100% and 50% vegetation quantity size were measured for 10 sample species during the initial data collection. According to the findings, half of the leaves’ features were connected with noise absorption. This might be owing to the freshness state, which cannot be maintained for an extended period of time. To acquire a better value, the experiment was repeated within the permissible freshness time. The findings are as predicted, with the maximum noise absorption and features correlation at 100% plant density including twigs. When the vegetation amount is lowered to 50%, this will progressively diminish. The notion is confirmed by the fact that a tube packed with thicker samples absorbs more noise. The correlation study identifies that each leaf has its unique capacity for noise absorption dependent on its properties and freshness level.

Carbon Dioxide Driven Methane Consumption in Soil Ecosystem

Soil is an important source and sink of greenhouse gas carbon dioxide (CO2) and methane (CH4). During CH4 consumption CO2 is produced as an end product. It is generally assumed that CO2 would inhibit CH4 consumption due to feedback inhibition. To test the effect of CO2 on methanotrophy, experiments were conducted in microcosms with different initial concentration of CO2 and CH4. Changes in CH4 consumption potential and abundance of pmoA gene copies in relation to CO2 concentration were estimated. In general, CH4 consumption ceased in the absence of CO2. In presence of CO2, rate of CH4 consumption (ng CH4 consumed g−1 soil d−1) varied from 0.283 to 0.481 at 1000 ppm of CH4 and 2.958 to 4.994 at 10,000 ppm of CH4. Abundance of methanotrophs (pmoA gene copies g−1 soil) ranged from 4.5 × 105 to 107 × 105 g−1 soil. A follow up experiment was carried out to evaluate CH4 consumption in the presence or absence of CO2, which proved that CO2 is essential for CH4 consumption. Study concludes that CO2 is a precursor molecule for CH4 consumption in soil ecosystem and methanotrophs are capable of mitigating both the greenhouse gases, CH4 and CO2.

CloudRoots-Amazon22: Integrating Clouds with Photosynthesis by Crossing Scales

Abstract How are rain forest photosynthesis and turbulent fluxes influenced by clouds? To what extent are clouds affected by local processes driven by rain forest energy, water, and carbon fluxes? These interrelated questions were the main drivers of the intensive field experiment CloudRoots-Amazon22 which took place at the Amazon Tall Tower Observatory (ATTO)/Campina supersites in the Amazon rain forest during the dry season, in August 2022. CloudRoots-Amazon22 collected observational data to derive cause–effect relationships between processes occurring at the leaf level up to canopy scales in relation to the diurnal evolution of the clear-to-cloudy transition. First, we studied the impact of cloud and canopy radiation perturbations on the subdiurnal variability of stomatal conductance. Stoma opening is larger in the morning, modulated by the cloud optical thickness. Second, we combined 1-Hz frequency measurements of the stable isotopologues of carbon dioxide and water vapor with measurements of turbulence to determine carbon dioxide and water vapor sources and sinks within the canopy. Using scintillometer observations, we inferred 1-min sensible heat flux that responded within minutes to the cloud passages. Third, collocated profiles of state variables and greenhouse gases enabled us to determine the role of clouds in vertical transport. We then inferred, using canopy and upper-atmospheric observations and a parameterization, the cloud cover and cloud mass flux to establish causality between canopy and cloud processes. This shows the need for a comprehensive observational set to improve weather and climate model representations. Our findings contribute to advance our knowledge of the coupling between cloudy boundary layers and primary carbon productivity of the Amazon rain forest.

Climate change mitigation potential of restoration of boreal peatlands drained for forestry can be adjusted by site selection and restoration measures

Peatland restoration is seen as a key nature‐based solution to tackle climate change and biodiversity loss. In Europe, nearly 50% of peatlands have been drained during the last decades, which have shifted their soils to carbon dioxide (CO2) sources. Soils of forestry‐drained peatlands are known to vary from CO2 sources to small sinks depending on their fertility and wetness. When peatlands are restored, it can be expected that rates of CO2 and methane exchange will vary depending on site fertility and wetness. We generated seven restoration pathways with different starting and end points and assessed the climate impacts of them. The GHG emission coefficients were compiled from literature, and radiative forcing was calculated for a 500‐year time period since restoration. All seven restoration pathways improved carbon sink capacity; however, the climate impact differed from cooling to warming. The highest cooling impact occurred in a pathway leading from nutrient‐rich drained peatlands toward tree‐covered spruce or pine mires. Warming impacts occurred in a pathway leading from nutrient‐poor drained peatlands toward open peatlands. The results of this study can be used to help identify peatland sites and restoration targets to maximize climate change mitigation from restoration. In practice, however, restoration has to fulfill other targets, such as biodiversity safeguarding, improvement of hydrological conditions, and socio‐economic aspects. Fulfilling all targets simultaneously requires compromises on all targets.

A global surface CO2 flux dataset (2015–2022) inferred from OCO-2 retrievals using the GONGGA inversion system

Abstract. Accurate assessment of the size and distribution of carbon dioxide (CO2) sources and sinks is important for efforts to understand the carbon cycle and support policy decisions regarding climate mitigation actions. Satellite retrievals of the column-averaged dry-air mole fractions of CO2 (XCO2) have been widely used to infer spatial and temporal variations in carbon fluxes through atmospheric inversion techniques. In this study, we present a global spatially resolved terrestrial and ocean carbon flux dataset for 2015–2022. The dataset was generated by the Global ObservatioN-based system for monitoring Greenhouse GAses (GONGGA) atmospheric inversion system through the assimilation of Orbiting Carbon Observatory-2 (OCO-2) XCO2 retrievals. We describe the carbon budget, interannual variability, and seasonal cycle for the global scale and a set of TransCom regions. The 8-year mean net biosphere exchange and ocean carbon fluxes were −2.22 ± 0.75 and −2.32 ± 0.18 Pg C yr−1, absorbing approximately 23 % and 24 % of contemporary fossil fuel CO2 emissions, respectively. The annual mean global atmospheric CO2 growth rate was 5.17 ± 0.68 Pg C yr−1, which is consistent with the National Oceanic and Atmospheric Administration (NOAA) measurement (5.24 ± 0.59 Pg C yr−1). Europe has the largest terrestrial sink among the 11 TransCom land regions, followed by Boreal Asia and Temperate Asia. The dataset was evaluated by comparing posterior CO2 simulations with Total Carbon Column Observing Network (TCCON) retrievals as well as Observation Package (ObsPack) surface flask observations and aircraft observations. Compared with CO2 simulations using the unoptimized fluxes, the bias and root mean square error (RMSE) in posterior CO2 simulations were largely reduced across the full range of locations, confirming that the GONGGA system improves the estimates of spatial and temporal variations in carbon fluxes by assimilating OCO-2 XCO2 data. This dataset will improve the broader understanding of global carbon cycle dynamics and their response to climate change. The dataset can be accessed at https://doi.org/10.5281/zenodo.8368846 (Jin et al., 2023a).

Estimating high spatio-temporal resolution XCO2 using spatial features deep fusion model

The high temporal-spatial resolution estimation of XCO2 data is foundational for precision quantification of carbon dioxide sources and sinks at a regional scale. This study proposed an advanced XCO2 data estimation method, using spatial features deep fusion. Leveraging convolutional neural network (CNN) principles, SpatialFusionNet—a module was designed to amalgamate geographical features within a defined spatial range. This module captures and integrates the spatial characteristics of meteorological and surface environmental factors, enhancing its application to the XCO2 estimation model. Building upon machine learning methods including Extreme Gradient Boosting (XGBoost), Support Vector Machine (SVM), and Deep Neural Network (DNN), combined with the SpatialFusionNet module, the spatial features deep fusion models were constructed utilizing relationships among OCO-2 satellite XCO2 trajectory monitoring data in China, Copernicus Atmospheric Monitoring Service (CAMS) XCO2 reanalysis data, and meteorological factors, surface vegetation, and meteorological factors. Model performance improvements were significant, with SVM, DNN, and XGBoost showing respective RMSE reductions of 1.297 ppm, 0.480 ppm, and 0.200 ppm in ten-fold cross-validation based on OCO-2 trajectory samples. In data validation with TCCON Hefei station, the correlation between inversion data and ground-based data reached 0.85, affirming the method's high accuracy. Employing the spatial feature extraction module combined with DNN, the 2015 XCO2 annual spatial distribution of China, analyzing temporal-spatial distribution characteristics in China was generated. The DNN model, combining the SpatialFusionNet module, significantly contributes to the estimation of high temporal-spatial resolution XCO2 datasets, facilitating fine-scale quantification of regional carbon cycling.

Aircraft Taxi Path Optimization Considering Environmental Impacts Based on a Bilevel Spatial–Temporal Optimization Model

Aircraft taxiing emissions are the main source of carbon dioxide and other pollutant gas emissions during airport ground operations. It is crucial to optimize aircraft taxiing from both spatial and temporal perspectives to improve airport operation efficiency and reduce aviation emissions. In this paper, a bilevel spatial and temporal optimization model of aircraft taxiing is constructed. The upper-level model optimizes the aircraft taxiing path, and the lower-level model optimizes the taxiing start time of the aircraft. By the iterative optimization of the upper- and lower-level interactions, the aviation fuel consumption, flight waiting time, and number of taxiing conflicts are reduced. To improve the calculation accuracy, the depth-first search algorithm is utilized to generate the set of available paths for aircraft during the model solution process, and a model solution method based on the genetic algorithm is constructed. Simulation experiments using Tianjin Binhai International Airport as the research object show that adopting the waiting taxiing strategy can effectively avoid taxiing conflicts and reduce aviation fuel consumption by 753.18 kg and 188.84 kg compared to the available path sets generated using Dijkstra’s algorithm and those created manually based on experience, respectively. Conversely, adopting an immediate taxi-out strategy caused 54 taxiing conflicts and increased aviation fuel consumption by 49.44 kg. These results can provide safe and environmentally friendly taxiing strategies for the sustainable development of the air transportation industry.

Massive crustal carbon mobilization and emission driven by India underthrusting Asia

The active Himalayan-Tibetan orogen, where India underthrusts into Asia, is an important geological source of carbon dioxide (CO2) emission into Earth’s atmosphere. However, the extent to which Indian underthrusting could stimulate the mobilization of deeply-sourced carbon and its subsequent emission remains unknown. Here, we use a combination of field observations coupled with in-situ CO2 flux measurements and helium and carbon isotopic data, to study the controls on CO2 origins and fluxes in a 400-kilometre-long rift transecting northern Himalaya and southern Tibet. High diffuse CO2 fluxes sustained by pure crustal fluids are confined to rift segments in the northern Himalaya, while toward southern Tibet, CO2 fluxes become lower but mantle fluid inputs are identified. Such rift-related CO2 degassing profile suggests metamorphic decarbonation and release of carbon-bearing fluids enhanced by the underthrusting Indian lower crust, agreeing well with Himalayan metamorphism and orogen-parallel lithospheric extension. Deep CO2 fluxes from extensional tectonics in northern Himalaya and southern Tibet, primarily of crustal origins, are comparable to mantle CO2 fluxes from global mid-ocean ridges. Our findings demonstrate that geophysical and geo-tectonic responses to continental underthrusting could facilitate massive crustal carbon mobilization and emission, making active collisional orogens globally important carbon sources.

Optimization of superstructure network in the CCS/CCSU system for CO2 reduction from exhaust gas industry and gas field in Indonesia as archipelago state

Industrial exhaust gases and gas fields are two significant sources of carbon dioxide (CO2) emissions that contribute to the rising levels of CO2 in the atmosphere. Among the various emission reduction systems, the CCSU (Carbon Capture, Storage, and Utilization) system has garnered extensive attention and research. This research aims to obtain the superstructure network sequentially in the CCSU system using GAMS (General Algebraic Modeling System). A mathematical approach was developed to optimize the amount of CO2 stored and utilized by varying the time difference (dt) between the source and sink from 0 to 10 years. After calculating the economic potential (EP), it was found that the Carbon Capture and Storage (CCS) system for both sources has a negative impact. In contrast, the CCSU system enhances the economic potential (EP) by generating a positive value. This is possible as the captured CO2 can be sold to the utilization sink, thereby creating a revenue stream. The EP for CO2 reduction from gas fields is greater than that from the industry, 21.68 × 106 USD compared to 12.50 × 106 USD at dt min10 years. The CCSU system, when utilizing CO2 sources from gas fields, is more profitable compared to using industrial emissions.

Emissions reduction in LNG production facilities through emerging post-combustion carbon capture and storage technologies

The liquefied natural gas (LNG) sector relies extensively on gas turbines for on-site power generation and to drive refrigeration compressors. They provide an efficient and reliable energy source for LNG operations in remote locations. With upcoming changes to the Safeguard Mechanism in Australia, there is an increased focus on Scope 1 emissions, so management and targeted reduction are a priority to reduce liabilities. Despite technology advancements, gas turbines remain one of the largest sources of carbon dioxide (CO2) emissions in LNG production facilities. Also, in Australia, many facilities are not grid-connected, meaning that displacement of Scope 1 emissions through renewable electricity sourcing is a challenge. To develop deeper cuts in Scope 1 emissions, one solution is to deploy post-combustion carbon capture and storage (CCS) on existing gas turbines, with the potential to reduce associated emissions by over 90%. Globally, a number of LNG facilities are already deploying CCS to permanently store reservoir CO2 from the LNG processing trains. Several Australian LNG facilities are located in close proximity to potential CO2 storage reservoirs, meaning that a coordinated approach to both reservoir and post-combustion CO2 should be considered when sizing pipelines, shipping systems and storage wells to optimise and leverage the required investment. This paper outlines the technological, economic and policy aspects of integrating both reservoir post-combustion CCS on LNG facilities, including barriers and opportunities for deployment. It will discuss new developments and enablers for CCS to be more widely deployed at LNG production sites.

Empirical assessment of fuel-wood induced carbon footprint in Udu Local Government Area of Delta State, Nigeria

Most studies of carbon footprint (CFP) in relation to climate change focus on the generation of greenhouse gases (GHG) by human activities such as electricity, industrialization and transportation in urban areas with little attention on rural areas. Against this background, this study aims to identify sources of Carbon dioxide (CO2) emission, and estimate the amount of CFP generated through fuel-wood consumption in Udu LGA of Delta State, Nigeria. Data for the study were obtained from a sample of 200 households in four (4) rural settlements chosen randomly from 32 villages. Mixed survey technique which involved questionnaires, field observations and measurement were employed to collect data for the study. Data obtained were analysed using descriptive statistics, Pearson Correlation Analysis and calculation of CFP. The study reveals that the major source of CO2 emission was fuel wood (82.0%), which is used for various domestic and production activities with an average of 39.58kg consumed by each sampled household; thus, generating between 7.24314 MT daily. The amount of CFP also varies directly with the sizes of the sampled households. The study recommends that alternative sources of clean energy should be developed and utilized for sustainable development of the environment and mitigation of climate change phenomenon.

Production of greenhouse gases by logging residue in boreal clear-cut forests

AbstractForest deadwood is an important carbon reserve, estimated to contain 8% of the total forest carbon. This type of woody debris is recognized as a source of carbon dioxide (CO2), as the carbon is released back into the atmosphere by microbial decomposition. Production of methane (CH4) and nitrous oxide (N2O) has also been reported. In managed forests, logging residues form a major source of fine deadwood, but its role in the greenhouse gas exchange of forest ecosystems is poorly understood. We studied the greenhouse gas production of spruce and birch left-over fine woody debris and estimated the residence time of these residues at 18 spruce-dominated boreal forest sites in Central Finland. The study areas consisted of clear-cut forest stands, totally covering approximately 47 hectares, with logging residue ages varying between 0 and 10 years. The research was carried out over eight months from May to December 2019. We observed that CO2 dominated the greenhouse gas production of the logging residues, with the production being regulated by air temperature, tree species, residue age, and wood moisture. Emission of CO2 continued throughout the research period with a clear seasonal pattern. Production of CH4 and N2O was also observed, but not in climatically-relevant amounts. Deadwood half-life was estimated at 18 years for spruce and 9 years for birch. Our study demonstrates that logging residues form a mid-term carbon reserve and suggests that global warming could reduce the lifetime of the residues as a result of elevated and temperature-dependent CO2 release in the studied Myrtillus type forest stands.

Spatial modeling of micro‐scale carbon dioxide sources and sinks in urban environments: A novel approach to quantify urban impacts on global warming

AbstractUrban environments play a significant role in global carbon emissions and sequestration, necessitating a comprehensive understanding of their spatial distribution. This study presents a micro‐scale spatial modeling framework to elucidate the complex interplay between CO2 sources and sinks within urban settings. Utilizing advanced geospatial analysis, remote sensing data, and geographically weighted regression (GWR) modeling techniques, we provide a detailed characterization of emission patterns and identify the spatial distribution of carbon dioxide sequestration. Employing the bottom‐up method and geographic information system techniques, we quantified carbon dioxide emissions in Isfahan City, Iran, attributing 81.68% to stationary combustion sources (residential, commercial, industrial, and power plant sectors) and 18.32% to mobile combustion sources (road‐rail transportation, and non‐road transportation [agricultural machinery]). To model carbon sequestration, we calculated tree biomass using allometric equations and estimated carbon sequestration per tree unit. Subsequently, we employed GWR to map the spatial distribution of carbon deposition across the city. The results revealed an annual carbon sequestration capacity of 7,704 tons, equivalent to storing 28,275 tons of CO2. Our findings highlight the substantial contribution of urban areas to greenhouse gas emissions and the potential of urban green spaces to mitigate these emissions. The spatial modeling framework developed in this study provides a valuable tool for urban planners to optimize carbon management strategies and promote sustainable urban development. © 2024 Society of Chemical Industry and John Wiley & Sons, Ltd.