Greenhouse Gas Concentrations Research Articles

A Preliminary Case Study on the Compounding Effects of Local Emissions and Upstream Wildfires on Urban Air Pollution

Interactions between urban and wildfire pollution emissions are active areas of research, with numerous aircraft field campaigns and satellite analyses of wildfire pollution being conducted in recent years. Several studies have found that elevated ozone and particulate pollution levels are both generally associated with wildfire smoke in urban areas. We measured pollutant concentrations at two Utah Division of Air Quality regulatory air quality observation sites and a local hot spot (a COVID-19 testing site) within a 48 h period of increasing wildfire smoke impacts that occurred in Salt Lake City, UT (USA) between 20 and 22 August 2020. The wildfire plume, which passed through the study area during an elevated ozone period during the summer, resulted in increased criteria pollutant and greenhouse gas concentrations. Methane (CH4) and fine particulate matter (PM2.5) increased at comparable rates, and increased NOx led to more ozone. The nitrogen oxide/ozone (NOx/O3) cycle was clearly demonstrated throughout the study period, with NOx titration reducing nighttime ozone. These findings help to illustrate how the compounding effects of urban emissions and exceptional pollution events, such as wildfires, may pose substantial health risks. This preliminary case study supports conducting an expanded, longer-term study on the interactions of variable intensity wildfire smoke plumes on urban air pollution exposure, in addition to the subsequent need to inform health and risk policy in these complex systems.

Tunable optical parametric oscillator based on ZnGeP2 crystal for greenhouse gas remote sensing systems

This work is devoted to the development of a compact source of coherent radiation with frequency-energy characteristics and a spectral generation range that allows remote determination of background concentrations of greenhouse gases in the atmosphere. The aim of this work was to create a frequency parametric converter based on ZGP, pumped by Ho:YAG laser radiation. For use as a source in a mobile lidar for remote determination of the concentration of greenhouse gases in the atmosphere. In the course of the research, a layout of an Optical parametric oscillator OPO based on a ZGP crystal with Ho:YAG laser radiation pumping was developed. The system’s continuous failure-free operation time was 1.5 h at a pulse repetition rate of 10 kHz and a pulse energy of the generated radiation of 0.08 mJ. The tuning range of the OPO was from 3.3 to 5 μm when using a Lyot filter. The losses from the average generation power when the Lyot filter was introduced into the resonator were 30%. At the same time, it was possible to achieve a linewidth of the generated radiation of 0.7 nm. The divergence of the generated radiation did not exceed 1.5 mrad.The absorption spectrum of gases CO2, CH4, N2O, CO in a gas cell was simulated for the entire generation range of the ZnGeP2-based OPO. As a result of the simulation, the most intense absorption lines of gases CO2, CH4, N2O, CO in the OPO tuning range were revealed, the central wavelengths of the absorption lines and their spectral width were determined.

Flipping of temperature and precipitation trends over the Indian subcontinent due to diametrically opposing influence of GHGs and aerosols

Despite significant development in the Earth system models (ESMs) and releases of several coupled model intercomparison projects (CMIPs), the evolving patterns of Indian summer monsoon rainfall and its future trajectory is still uncertain, with low confidence in its direction. This could be because of differential impacts from increasing greenhouse gas (GHG) and aerosol concentrations. We found that the observed pre-2000 (1951–2000) declining monsoon was likely attributed to the increasing aerosol concentrations. On the contrary, the reported revival of post-2000 monsoon rainfall is due to GHG dominance. These are spatiotemporally consistent with individual CMIP Phase 6 (CMIP6) ESM simulations with GHG and aerosols separately. Similar results were obtained for temperature in India, which showed no to low warming signal in pre-2000 due to aerosol-driven cooling. The dominance of GHG impacts has increased India’s warming trend in post-2000. This research highlights a notable trend in temperature and precipitation across the Indian subcontinent during the past two decades, emphasizing the dynamic character of climate change explained by contrasting anthropogenic influences, including GHGs and aerosols.

Economics of enhanced methane oxidation relative to carbon dioxide removal

Mitigating short-term global warming is imperative, and a key strategy involves reducing atmospheric methane (CH4) due to its high radiative forcing and short lifespan. This objective can be achieved through methods such as oxidising methane at its source or implementing enhanced oxidation techniques to reduce atmospheric CH4 concentrations. In this study, we use a range of metrics to analyse both the impact and value of enhanced CH4 oxidation relative to carbon dioxide (CO2) removal on global temperature. We apply these metrics to a select group of model studies of thermal-catalytic, photocatalytic, biological and capture-based oxidation processes under different greenhouse gas (GHG) concentrations. Using a target cost of €220-1000/tCO2 for CO2 removal, our findings indicate that metrics valuing enhanced oxidation techniques based on their contribution to mitigating the long-term level of warming show these techniques are uncompetitive with CO2 removal. However, when using metrics that value enhanced oxidation of CH4 based on its impact on the immediate rate of warming, photocatalytic methods may be competitive with CO2 removal, whereas biofiltration, thermal-catalytic oxidation and capture-based units remain uncompetitive. We conclude that if the policy goal is to target the immediate rate of warming, it may be more valuable to incentivise CO2 removal and enhanced oxidation of methane under separate GHG targets.

Elevation-dependent warming: observations, models, and energetic mechanisms

Abstract. Observational data and numerical models suggest that, under climate change, elevated land surfaces warm faster than non-elevated ones. Proposed drivers of this “elevation-dependent warming” (EDW) include surface albedo and water vapour feedbacks, the temperature dependence of longwave emission, and aerosols. Yet the relative importance of each proposed mechanism both regionally and at large scales is unclear, highlighting an incomplete physical understanding of EDW. Here we expand on previous regional studies and use gridded observations, atmospheric reanalysis, and a range of climate model simulations to investigate EDW over the historical period across the tropics and subtropics (40° S to 40° N). Observations, reanalysis, and fully coupled models exhibit annual mean warming trends (1959–2014), binned by surface elevation, which are larger over elevated surfaces and broadly consistent across datasets. EDW varies by season, with stronger observed signals in local winter and autumn. Analysis of large ensembles of single-forcing simulations (1959–2005) suggests historical EDW is likely a forced response of the climate system rather than an artefact of internal variability and is primarily driven by increasing greenhouse gas concentrations. To gain quantitative insight into the mechanisms contributing to large-scale EDW, a forcing–feedback framework based on top-of-atmosphere energy balance is applied to the fully coupled models. This framework identifies the Planck and surface albedo feedbacks as being robust drivers of EDW (i.e. enhancing warming over elevated surfaces), with energy transport by the atmospheric circulation also playing an important role. In contrast, water vapour and cloud feedbacks along with weaker radiative forcing in elevated regions oppose EDW. Implications of the results for understanding future EDW are discussed.

Estimated greenhouse gas emissions in the Mbalmayo thermal power plant between 2016-2020 using the genetic-Gaussian algorithm coupling.

The greenhouse gas (GHG) emissions inventories in our context result from the production of electricity from fuel oil at the Mbalmayo thermal power plant between 2016 and 2020. Our study area is located in the Central Cameroon region. The empirical method of the second level of industrialisation was applied to estimate GHG emissions and the application of the genetic algorithm-Gaussian (GA-Gaussian) coupling method was used to optimise the estimation of GHG emissions. Our work is of an experimental nature and aims to estimate the quantities of GHG produced by the Mbalmayo thermal power plant during its operation. The search for the best objective function using genetic algorithms is designed to bring us closer to the best concentration, and the Gaussian model is used to estimate the concentration level. The results obtained show that the average monthly emissions in kilograms (kg) of GHGs from the Mbalmayo thermal power plant are: 526 kg for carbon dioxide (CO2), 971.41 kg for methane (CH4) and 309.41 kg for nitrous oxide (N2O), for an average monthly production of 6058.12 kWh of energy. Evaluation of the stack height shows that increasing the stack height helps to reduce local GHG concentrations. According to the Cameroonian standards published in 2021, the limit concentrations of GHGs remain below 30 mg/m3 for CO2 and 200 μg/m3 for N2O, while for CH4 we reach the limit value of 60 μg/m3. These results will enable the authorities to take appropriate measures to reduce GHG concentrations.

Opinion: A research roadmap for exploring atmospheric methane removal via iron salt aerosol

Abstract. The escalating climate crisis requires rapid action to reduce the concentrations of atmospheric greenhouse gases and lower global surface temperatures. Methane will play a critical role in near-term warming due to its high radiative forcing and short atmospheric lifetime. Methane emissions have accelerated in recent years, and there is significant risk and uncertainty associated with the future growth in natural emissions. The largest natural sink of methane occurs through oxidation reactions with atmospheric hydroxyl and chlorine radicals. Enhanced atmospheric oxidation could be a potential approach to remove atmospheric methane. One method proposes the addition of iron salt aerosol (ISA) to the atmosphere, mimicking a natural process proposed to occur when mineral dust mixes with chloride from sea spray to form iron chlorides, which are photolyzed by sunlight to produce chlorine radicals. Under the right conditions, lofting ISA into the atmosphere could potentially reduce atmospheric methane concentrations and lower global surface temperatures. Recognizing that potential atmospheric methane removal must only be considered an additive measure – in addition to, not replacing, crucial anthropogenic greenhouse gas emission reductions and carbon dioxide removal – roadmaps can be a valuable tool to organize and streamline interdisciplinary and multifaceted research to efficiently move towards understanding whether an approach may be viable and socially acceptable or if it is nonviable and further research should be deprioritized. Here we present a 5-year research roadmap to explore whether ISA enhancement of the chlorine radical sink could be a viable and socially acceptable atmospheric methane removal approach.

Event attribution of a midlatitude windstorm using ensemble weather forecasts

The widespread destruction incurred by midlatitude storms every year makes it an imperative to study how storms change with climate. The impact of climate change on midlatitude windstorms, however, is hard to evaluate due to the small signals in variables such as wind speed, as well as the high resolutions required to represent the dynamic processes in the storms. Here, we assess how storm Eunice, which hit the UK in February 2022, was impacted by anthropogenic climate change using the ECMWF ensemble prediction system. This system was demonstrably able to predict the storm, significantly increasing our confidence in its ability to model the key physical processes and their response to climate change. Using modified greenhouse gas concentrations and changed initial conditions for ocean temperatures, we create two counterfactual scenarios of storm Eunice in addition to the forecast for the current climate. We compare the intensity and severity of the storm between the pre-industrial, current, and future climates. Our results robustly indicate that Eunice has become more intense with climate change and similar storms will continue to intensify with further anthropogenic forcing. These results are consistent across forecast lead times, increasing our confidence in them. Analysis of storm composites shows that this process is caused by increased vorticity production through increased humidity in the warm conveyor belt of the storm. This is consistent with previous studies on extreme windstorms. Our approach of combining forecasts at different lead times for event attribution enables combining event specificity and a focus on dynamic changes with the assessment of changing risks from windstorms. Further work is needed to develop methods to adjust the initial conditions of the atmosphere for the use in attribution studies using weather forecasts but we show that this approach is viable for reliable and fast attribution systems.

The Role of Diabatic Heating in the Midlatitude Atmospheric Circulation Response to Climate Change

Abstract Climate models generally predict a poleward shift of the midlatitude circulation in response to climate change induced by increased greenhouse gas concentration, but the intermodel spread of the eddy-driven jet shift is large and poorly understood. Recent studies point to the significance of midlatitude midtropospheric diabatic heating for the intermodel spread in the jet latitude. To examine the role of diabatic heating in the jet response to climate change, a series of simulations are performed using an idealized aquaplanet model. It is found that both increased CO2 concentration and increased saturation vapor pressure induce a similar warming response, leading to a poleward and upward shift of the midlatitude circulation. An exception to this poleward shift is found for a certain range of temperatures, where the eddy-driven jet shifts equatorward, while the latitude of the eddy heat flux remains essentially unchanged. This equatorward jet shift is explained by the connection between the zonal-mean momentum and heat budgets: increased diabatic heating in the midlatitude midtroposphere balances the cooling by the Ferrel cell ascending branch, enabling an equatorward shift of the Ferrel cell streamfunction and eddy-driven jet, while the latitude of the eddy heat flux remains unchanged. The equatorward jet shift and the strengthening of the midlatitude diabatic heating are found to be sensitive to the model resolution. The implications of these results for a potential reduction in the jet shift uncertainty through the improvement of convective parameterizations are discussed. Significance Statement The latitude of the eddy-driven jet displays considerable variation in climate models, and the factors influencing this variability are poorly understood. This work connects the strength of midlatitude diabatic heating to the structure of the midlatitude circulation and the eddy-driven jet latitude. The direction of the eddy-driven jet shift in response to climate change is found to depend on the diabatic heating response, which in turn depends on the parameterized convective heating. These results highlight the role of convective parameterizations in the representation of the midlatitude circulation in climate models. Additionally, the results imply that the eddy-driven jet shift cannot be explained solely based on the storm-track response to climate change, in contrast with previously suggested explanations.

Maximizing the capacity and benefit of CO2 storage in depleted oil reservoirs

Sequestering CO2 in depleted oil reservoirs provides one of the most appealing measures to reduce greenhouse gases (GHG) concentration in the atmosphere. The remaining liquids after enhanced oil recovery (EOR) processes, including residual oil and remaining water, lead to the main challenges to this approach. How to effectively evacuate a depleted oil reservoir by recovering not only residual oil but also remaining water is a critical consideration for this type of CO2 sequestration. This paper presents conceptual investigations concerning the methods which effectively evacuate depleted oil reservoirs from both the displacement efficiency and the sweep efficiency points of view. To improve the displacement efficiency, surfactant slug and solvent slug injection was examined using a core scale numerical model. Investigations regarding improving sweep efficiency, such as horizontal well pattern infilling and foam injection, were carried out based on a typical row well pattern. Simulation results showed that surfactant slug which modified the relative permeability and capillary pressure remarkably reduced both residual oil saturation and remaining water saturation. A CO2 slug injected before surfactant slug can help improve the oil recovery. Solvent enriched CO2 slug also remarkably reduced the residual oil saturation to as low as 2%. Horizontal well pattern infilling had great advantage for thick or inclined reservoirs, and foam slug injection greatly improved CO2 storage capacity in thin reservoirs by improving the sweep efficiency. Maximum mobility reduction (MRF) is the most important parameter to maximize the storage capacity and the benefit. The variation of CO2 storage capacity along with CO2 slug size. Larger foam slug size will play a better storage performance. The conceptual simulation investigations confirmed that depleted oil reservoirs can be effectively evacuated for CO2 storage. Depleted oil reservoirs with maximum evacuation are the best candidates for CO2 sequestrations.

Advancing hydrogen storage predictions in metal-organic frameworks: A comparative study of LightGBM and random forest models with data enhancement

The escalating consumption of fossil fuels has given rise to a substantial upsurge in greenhouse gas concentrations and global temperatures, which, in turn, has triggered severe climate-related consequences. The critical imperative to reduce CO2 emissions and combat global warming has spurred extensive investigations into clean energy alternatives, with hydrogen emerging as a compelling zero-emission energy source. As a pivotal component of clean energy strategies, hydrogen requires designing compact, lightweight, and efficient storage systems. This study focuses on the development and evaluation of machine learning models for predicting the efficiency of Metal-Organic Frameworks (MOFs) in hydrogen storage, a key aspect of advancing clean energy technologies. MOFs, a class of nanoporous materials, show remarkable potential for hydrogen storage due to their high surface area and porosity. However, selecting the most suitable MOF for this application from a vast array of possible structures is a daunting task. In this context, machine learning algorithms offer an efficient alternative for predicting MOF suitability by considering their structural and chemical properties. We used ensemble learning methods, specifically Light Gradient Boosting Machine (LightGBM) and Random Forest (RF), to predict hydrogen uptake of MOFs based on a dataset of 219 experimentally tested samples. Two modeling scenarios were considered: one using the entire dataset, and the other involving strategic data pre-processing, including outlier removal and feature engineering. The results demonstrate that the measures taken to refine the dataset significantly enhance the predictive performance of the developed models, reducing prediction errors and improving overall goodness of fit. Specifically, the Mean Absolute Error (MAE) values for both the LightGBM and random forest models were reduced from 0.48 and 0.94, respectively, to 0.16 for both models, and the coefficients of determination (R2) increased substantially from 0.84 and 0.72 to 0.95, in both cases. Moreover, feature importance analysis unveiled that pressure-related features make the most significant contributions to the formation of tree ensembles during the model training process. A parametric sensitivity analysis was conducted revealing that H2 uptake in MOFs is most sensitive to changes in adsorption enthalpy, followed by surface area and temperature, while showing lower sensitivity to variations in pressure, consistent with established literature. These results underscore the pivotal role of data enhancement methods in refining machine learning models and can be instrumental in accelerating the development and optimization of MOF materials for clean energy applications.

The Climate Change Conundrum: A Case for Course Correction in the Global Regulatory Approach$

The Conference of Parties (COP) of the multilateral environmental agreements (MEAs) provides a platform at a specific periodicity (one, two or three years) to review work of the Convention in question. The UN Framework Convention on Climate Change (UNFCCC) is a ‘universal’ convention with 198 parties. The 28th annual meeting of the COP (UNFCCC) was held in Dubai (UAE) during 30 November - 13 December 2023. The UN provides ‘secretariat’ support to the UNFCCC, hence the usage of prefix ‘United Nations’. It is called a ‘framework convention’ since it was adopted with a bare skeleton on 09 May 1992. It required ‘fleshing out’ of the UNFCCC with required elements to make it work for the “‘ultimate objective” of “stabilization of greenhouse gas concentrations in the atmosphere at a level that would prevent dangerous anthropogenic interference with the climate system” (Article 2). It led to the adoption of the (“related legal instruments”) 1997 Kyoto Protocol and 2015 Paris Agreement. The climate change regime now comprises these three legal instruments that seek to address the global climate problematique. Whereas COP27 (Sharm El-Shaik; 06–21 November 2022) was known for adoption of the decision on “loss and damage” funding for vulnerable countries hit hard by climate disasters, COP28 unveiled the first global climate ‘stocktake’. This took place on the heels of UNEP Emissions Gap Report (20 November 2023) that issued warming that “world is heading for a temperature rise far above the Paris Agreement goals unless countries deliver more than they have promised”. The UNEP report called for the GHG emissions (by 2030) to “fall by 28 per cent for the Paris Agreement 2°C pathway and 42 per cent for the 1.5°C pathway”. Thus, there is a big chasm between what is laid down in the climate change regulatory framework, what is scientifically ordained and what is actually given effect on the ground by the states Parties. After 30 years (1994–2024), the resultant ‘conundrum’ presents a challenge at this juncture of planetary crisis. It calls for the state Parties to the global climate change regime to engage in a major course correction in the current global climate change regulatory approaches for securing our planetary future.

An uncertain future change in aridity over the tropics

An ensemble of climate models from phase six of the Coupled Model Intercomparison Project shows that temperature and potential evapotranspiration (PET) are projected to increase globally towards the end of the 21st century. However, climate models show a spatially heterogeneous change in precipitation over the tropics. Consequently, future changes in aridity (a measure of water availability) are complex and location-dependent. We assess future changes in aridity using three climate models and several single-forcing experiments. Near-term (2021–2040) changes in aridity are small, and we focus instead on its long-term (2081–2100) changes. We show that the increase in greenhouse gases (GHG) primarily explains the spatial pattern, magnitude and ensemble spread of the long-term future changes in aridity. On this timescale, the effects of changes in emissions of anthropogenic aerosols are moderate compared to the effects of increases in atmospheric GHG concentrations. Model diversity in the responses to GHG concentration is large over northern Africa and North and South America. We suggest the large uncertainty is due to differences between models in simulating the effects of an increase in GHG concentrations on surface air temperature over the North Atlantic Ocean, on the interhemispheric temperature gradient, and on PET over North and South America.

Multiple stressors alter greenhouse gas concentrations in streams through local and distal processes.

Streams are significant contributors of greenhouse gases (GHG) to the atmosphere, and the increasing number of stressors degrading freshwaters may exacerbate this process, posing a threat to climatic stability. However, it is unclear whether the influence of multiple stressors on GHG concentrations in streams results from increases of in-situ metabolism (i.e., local processes) or from changes in upstream and terrestrial GHG production (i.e., distal processes). Here, we hypothesize that the mechanisms controlling multiple stressor effects vary between carbon dioxide (CO2) and methane (CH4), with the latter being more influenced by changes in local stream metabolism, and the former mainly responding to distal processes. To test this hypothesis, we measured stream metabolism and the concentrations of CO2 (pCO2) and CH4 (pCH4) in 50 stream sites that encompass gradients of nutrient enrichment, oxygen depletion, thermal stress, riparian degradation and discharge. Our results indicate that these stressors had additive effects on stream metabolism and GHG concentrations, with stressor interactions explaining limited variance. Nutrient enrichment was associated with higher stream heterotrophy and pCO2, whereas pCH4 increased with oxygen depletion and water temperature. Discharge was positively linked to primary production, respiration and heterotrophy but correlated negatively with pCO2. Our models indicate that CO2-equivalent concentrations can more than double in streams that experience high nutrient enrichment and oxygen depletion, compared to those with oligotrophic and oxic conditions. Structural equation models revealed that the effects of nutrient enrichment and discharge on pCO2 were related to distal processes rather than local metabolism. In contrast, pCH4 responses to nutrient enrichment, discharge and temperature were related to both local metabolism and distal processes. Collectively, our study illustrates potential climatic feedbacks resulting from freshwater degradation and provides insight into the processes mediating stressor impacts on the production of GHG in streams.

Multi-centennial evolution of the climate response and deep-ocean heat uptake in a set of abrupt stabilization scenarios with EC-Earth3

Abstract. Understanding long-term committed climate change due to anthropogenic forcing is key to informing climate policies, yet these timescales are still underexplored. We present here a set of 1000-year-long abrupt stabilization simulations performed with EC-Earth3. Each simulation follows a sudden stabilization of the external forcing at the level specified by CMIP6 for historical (1990) or SSP5-8.5 scenario (2025, 2050, 2065, 2080, 2100) conditions, with a final temperature increase ranging between 1.4 and 9.6 K with respect to the pre-industrial baseline. Remarkably, the simulation stabilized at a greenhouse gas (GHG) level close to the present day (2025) exceeds the Paris Agreement goals of 1.5 and 2° warming above pre-industrial in the long term, and only the 1990 simulation leads to a stabilized climate below 1.5° warming. We first focus on the evolution of the climate response at multi-centennial timescales and its dependence on the level of forcing. We note a decrease in the magnitude of the climate feedback parameter at longer timescales. Conversely, simulations with higher forcing exhibit a larger feedback parameter (in magnitude). Subsequently, the evolution of surface warming patterns over multi-centennial timescales is studied. While the response is generally consistent across simulations, some variations, particularly in the South Pacific and at high latitudes, suggest a certain level of state or forcing dependence. The patterns of precipitation change also evolve during the stabilization runs: the drying trends found in the subtropical oceans and in Mediterranean-like hotspots in the SSP5-8.5 scenario tend to be reduced or even reversed. We finally focus on the rate of heat storage in the global ocean, which is the main driver of the climate response at multi-centennial timescales. We find that the rate of warming of the deep ocean is almost independent from the amplitude of the forcing so that most of the additional heat remains in the upper layers at high forcing. This might be due – at least partly – to a decreased ventilation of the deep ocean, caused by changes in the Meridional Overturning Circulation (MOC). These results highlight the importance of studying multi-centennial timescales of climate change to better understand the response of the deep ocean, which will play a crucial role in determining the final state of the climate system once GHG concentrations are stabilized.

Behaviours of methane metabolism and community dynamics of methane anaerobic oxidation microbes on carbonate rocks with long-term cultivation in cold seep environment

The anaerobic oxidation of methane (AOM) and sulfate reduction processes in cold seep environments can control methane emission sources and thus mitigate the pressure of increasing global greenhouse gas concentrations. The surfaces of carbonate rocks in cold seep host an abundance of microorganisms that participate in AOM reactions. Investigating the metabolism and conversion of methane by these microbes is instrumental in advancing the exploration and utilization of deep-sea methane energy. Previous studies primarily focused on in-situ investigations of microbial communities on carbonate rocks in cold seep environments, while the dynamic balance of carbonate mineralization caused by microbial community changes and the characteristics of methane consumption in carbonate samples remains unclear. In this study, we used methane as the sole carbon source, enriched and cultured carbonate samples under high pressure, and monitored the community dynamics regularly. The results demonstrated that methane consumption and metabolic pathways played a crucial role in influencing community succession and carbonate mineralization. AOM processes, coupled with sulfate reduction and nitrate reduction, which are dominated by ANME-2c, facilitate the precipitation of calcium carbonate. Conversely, the acetate production process, dominated by ANME-1, may hinder the efficiency of calcium carbonate mineralization. Additionally, the impact of bacterial groups in the enrichment process, through the production of extracellular enzymes, organic acid pathways, and the expression of carbonic anhydrase pathways on carbonate mineralization, should not be disregarded. These findings highlight the significance of diverse pathway methane metabolism in the dynamics of methane consumption, deep-sea microbial communities, carbonate kinetics, and marine biological carbon sequestration processes.

Estimating Greenhouse Gas Emissions from Household Activities: A Case in Bogor Indonesia

Climate change is a result of global warming. Global warming is caused by an increase in the concentration of greenhouse gases (GHGs) in the atmosphere. One of the largest GHG-contributing sectors is the energy sector, which includes households with various activities. Household activities include using LPG, electricity, gasoline, waste generation, and farming and livestock activities to meet the household's needs. The level of GHG emissions produced in households is influenced by income, years of study, and knowledge of emissions. The objectives of this study are to estimate the amount of GHG emissions generated from household activities, analyze the factors that influence GHG emissions, and estimate the value of the carbon economy. The analytical methods used are quantitative descriptive analysis, IPCC (2006) method, multiple linear regression, and economic value analysis. The results showed that: (1) CO2-eq emissions generated in Sinarsari Village for 100 respondents amounted to 32,011.68 kg CO2-eq/month, and the amount of GHG emissions in one village scope amounted to 853,431.36 kg CO2-eq/month. (2) Income, length of study, and emission knowledge dummy influence GHG emissions. 3) Carbon economic value based on carbon pricing is Rp287,415,199.70/month.

Divergent drivers of the spatial variation in greenhouse gas concentrations and fluxes along the Rhine River and the Mittelland Canal in Germany

Lotic ecosystems are sources of greenhouse gases (GHGs) to the atmosphere, but their emissions are uncertain due to longitudinal GHG heterogeneities associated with point source pollution from anthropogenic activities. In this study, we quantified summer concentrations and fluxes of carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), and dinitrogen (N2), as well as several water quality parameters along the Rhine River and the Mittelland Canal, two critical inland waterways in Germany. Our main objectives were to compare GHG concentrations and fluxes along the two ecosystems and to determine the main driving factors responsible for their longitudinal GHG heterogeneities. The results indicated that the two ecosystems were sources of GHG fluxes to the atmosphere, with the Mittelland Canal being a hotspot for CH4 and N2O fluxes. We also found significant longitudinal GHG flux discontinuities along the mainstems of both ecosystems, which were mainly driven by divergent drivers. Along the Mittelland Canal, peak CO2 and CH4 fluxes coincided with point pollution sources such as a joining river tributary or the presence of harbors, while harbors and in-situ biogeochemical processes such as methanogenesis and respiration mainly explained CH4 and CO2 hotspots along the Rhine River. In contrast to CO2 and CH4 fluxes, N2O longitudinal trends along the two lotic ecosystems were better predicted by in-situ parameters such as chlorophyll-a concentrations and N2 fluxes. Based on a positive relationship with N2 fluxes, we hypothesized that in-situ denitrification was driving N2O hotspots in the Canal, while a negative relationship with N2 in the Rhine River suggested that coupled biological N2 fixation and nitrification accounted for N2O hotspots. These findings stress the need to include N2 flux estimates in GHG studies, as it can potentially improve our understanding of whether nitrogen is fixed through N2 fixation or lost through denitrification.

Assessing Greenhouse Gas Monitoring Capabilities Using SolAtmos End-to-End Simulator: Application to the Uvsq-Sat NG Mission

Monitoring atmospheric concentrations of greenhouse gases (GHGs) like carbon dioxide and methane in near real time and with good spatial resolution is crucial for enhancing our understanding of the sources and sinks of these gases. A novel approach can be proposed using a constellation of small satellites equipped with miniaturized spectrometers having a spectral resolution of a few nanometers. The objective of this study is to describe expected results that can be obtained with a single satellite named Uvsq-Sat NG. The SolAtmos end-to-end simulator and its three tools (IRIS, OptiSpectra, and GHGRetrieval) were developed to evaluate the performance of the spectrometer of the Uvsq-Sat NG mission, which focuses on measuring the main GHGs. The IRIS tool was implemented to provide Top-Of-Atmosphere (TOA) spectral radiances. Four scenes were analyzed (pine forest, deciduous forest, ocean, snow) combined with different aerosol types (continental, desert, maritime, urban). Simulated radiance spectra were calculated based on the wavelength ranges of the Uvsq-Sat NG, which spans from 1200 to 2000 nm. The OptiSpectra tool was used to determine optimal observational settings for the spectrometer, including Signal-to-Noise Ratio (SNR) and integration time. Data derived from IRIS and OptiSpectra served as input for our GHGRetrieval simulation tool, developed to provide greenhouse gas concentrations. The Levenberg–Marquardt algorithm was applied iteratively to fine-tune gas concentrations and model inputs, aligning observed transmittance functions with simulated ones under given environmental conditions. To estimate gas concentrations (CO2, CH4, O2, H2O) and their uncertainties, the Monte Carlo method was used. Based on this analysis, this study demonstrates that a miniaturized spectrometer onboard Uvsq-Sat NG is capable of observing different scenes by adjusting its integration time according to the wavelength. The expected precision for each measurement is of the order of a few ppm for carbon dioxide and less than 25 ppb for methane.

Nanofluids and Nanocomposite Membranes for Enhanced CO2 Capture: A Comprehensive Review

Abstract The increasing concentration of greenhouse gasses in Earth's atmosphere is a critical concern, of which 75% of carbon dioxide (CO2) emissions are from the combustion of fossil fuels. This rapid increase in emissions led to irredeemable damages to ecosystems, such as climate change and acid rain. As a result, industries and academia have focused on developing innovative and cost-effective technologies for CO2 capture and storage (CCS). Physical/chemical absorption using amine and membrane-based technologies is generally used in CCS systems. However, the inherent technical and cost-effective limitations of these techniques directed their attention toward applying nanotechnologies for CCS systems. Here, the researchers have focused on infusing nanoparticles (NPs) into existing CCS technologies. The NPs could either be suspended in a base fluid to create nanofluids (NFs) or infused with membrane base materials to create nanocomposite membranes for enhanced carbon capture capabilities. This review paper investigates the manufacturing methods, characterization techniques, and various mechanisms to analyze the impact of nanoparticles-infused nanofluids and nanocomposite membranes for CO2 capture. Finally, the paper summarizes the factors associated with the two technologies and then outlines the drawbacks and benefits of incorporating NPs for CCS applications.