Atmospheric Greenhouse Gas Concentrations Research Articles

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.

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.

Reversal of Projected European Summer Precipitation Decline in a Stabilizing Climate

AbstractPrecipitation projections in transient climate change scenarios have been extensively studied over multiple climate model generations. Although these simulations have also been used to make projections at specific Global Warming Levels (GWLs), dedicated simulations are more appropriate to study changes in a stabilizing climate. Here, we analyze precipitation projections in six multi‐century experiments with fixed atmospheric concentrations of greenhouse gases, conducted with the UK Earth System Model and which span a range of GWLs between 1.5 and 5°C of warming. Regions are identified where the sign of precipitation trends in high‐emission transient projections is reversed in the stabilization experiments. For example, stabilization reverses a summertime precipitation decline across Europe. This precipitation recovery occurs concurrently with changes in the pattern of Atlantic sea surface temperature trends due to a slow recovery of the Atlantic Meridional Overturning Circulation in the stabilization experiments, along with changes in humidity and atmospheric circulation.

Parageobacillus thermoglucosidasius Strain Engineering Using a Theophylline Responsive RiboCas for Controlled Gene Expression.

The relentless increase in atmospheric greenhouse gas concentrations as a consequence of the exploitation of fossil resources compels the adoption of sustainable routes to chemical and fuel manufacture based on biological fermentation processes. The use of thermophilic chassis in such processes is an attractive proposition; however, their effective exploitation will require improved genome editing tools. In the case of the industrially relevant chassis Parageobacillus thermoglucosidasius, CRISPR/Cas9-based gene editing has been demonstrated. The constitutive promoter used, however, accentuates the deleterious nature of Cas9, causing decreased transformation and low editing efficiencies, together with an increased likelihood of off-target effects or alternative mutations. Here, we rectify this issue by controlling the expression of Cas9 through the use of a synthetic riboswitch that is dependent on the nonmetabolized, nontoxic, and cheap inducer, theophylline. We demonstrate that the riboswitches are dose-dependent, allowing for controlled expression of the target gene. Through their use, we were then able to address the deleterious nature of Cas9 and produce an inducible system, RiboCas93. The benefits of RiboCas93 were demonstrated by increased transformation efficiency of the editing vectors, improved efficiency in mutant generation (100%), and a reduction of Cas9 toxicity, as indicated by a reduction in the number of single nucleotide polymorphisms (SNPs) observed. This new system provides a quick and efficient way to produce mutants in P. thermoglucosidasius.

Opinion: Stratospheric ozone – depletion, recovery and new challenges

Abstract. We summarise current important and well-established open issues related to the depletion of stratospheric ozone and discuss some newly emerging challenges. The ozone layer is recovering from the effects of halogenated source gases due to the continued success of the Montreal Protocol despite recent renewed production of controlled substances and the impact of uncontrolled very short-lived substances. The increasing atmospheric concentrations of greenhouse gases, such as carbon dioxide, methane (CH4) and nitrous oxide (N2O), have large potential to perturb stratospheric ozone in different ways, but their future evolutions, and hence impacts, are uncertain. Ozone depletion through injection of smoke particles has been observed following recent Australian wildfires. Further perturbations to the ozone layer are currently occurring through the unexpected injection of massive amounts of water vapour from the Hunga Tonga–Hunga Ha'apai volcano in 2022. Open research questions emphasise the critical need to maintain, if not expand, the observational network and to address the impending “satellite data gap” in global, height-resolved observations of stratospheric trace gases and aerosols. We will, in effect, be largely blind to the stratospheric effects of similar wildfire and volcanic events in the near future. Complex Earth system models (ESMs) being developed for climate projections have the stratosphere as an important component. However, the huge computational requirement of these models must not result in an oversimplification of the many processes affecting the ozone layer. Regardless, a hierarchy of simpler process models will continue to be important for testing our evolving understanding of the ozone layer and for providing policy-relevant information.

Functional analysis of variance (ANOVA) for carbon flux estimates from remote sensing data

Abstract. The constellation of Earth-observing satellites has now produced atmospheric greenhouse gas concentration estimates covering a period of several years. Their global coverage is providing additional information on the global carbon cycle. These products can be combined with complex inversion systems to infer the magnitude of carbon sources and sinks around the globe. Multiple factors, including the atmospheric transport model and satellite product aggregation method, can impact such flux estimates. Analysis of variance (ANOVA) is a well-established statistical framework for estimating common signals while partitioning variability across factors in the analysis of experiments. Functional ANOVA extends this approach with a statistical model that incorporates spatiotemporal correlation for each ANOVA component. The approach is illustrated on inversion experiments with different satellite retrieval aggregation methods and identifies consistent significant patterns in flux increments that span large spatial scales. Functional ANOVA identifies these patterns while accounting for the uncertainty at small spatial scales that is attributed to differences in the aggregation method. Functional ANOVA is also applied to a recent flux model intercomparison project (MIP), and the relative magnitudes of inversion system effects and data source (satellite versus in situ) are similar but exhibit slightly different importance for fluxes over different continents. In all examples, the unexplained residual variability is locally sizable in magnitude but with limited spatial and temporal correlation. These common behaviors across flux inversion experiments demonstrate the diagnostic capability for functional ANOVA to simultaneously distinguish the spatiotemporal coherence of carbon cycle processes and algorithmic factors.

Advancements in greenhouse gas emission reduction methodology for fluorinated compounds and N2O in the semiconductor industry via abatement systems

Greenhouse gases (GHGs), particularly fluorinated compounds (FCs), nitrous oxide (N2O), and nitrogen trifluoride (NF3), contribute significantly to climate change, and the semiconductor industry is a notable emitter of these gases. This report introduces an innovative methodology for GHG emission reduction in the semiconductor industry by utilizing advanced abatement systems, referencing Clean Development Mechanism (CDM) published methods AM0078 and AM0111. The proposed methodology shows promising potential, with substantial reductions in FCs, N2O, and NF3 emissions, positioning the semiconductor industry as a key player in climate change mitigation efforts. The main results indicate that by applying the latest abatement systems, a significant reduction in the targeted GHGs can be achieved. The methodology’s verification process confirms the effectiveness of GHG reduction, ensuring that semiconductor manufacturing’s environmental impact is minimized. Our findings suggest that the implementation of this methodology could lead to industry-wide adoption, resulting in a substantial contribution towards stabilizing atmospheric GHG concentrations.

A Preliminary Methane Emission Study of Typical Coalbed Methane Production Areas Based on Multi-satellites Remote Sensing Data

The monitoring of methane emission is helpful for reducing the concentration of atmospheric greenhouse gases. A preliminary methane emission study of typical coalbed methane production areas based on multi-satellites remote sensing data was proposed. Methane monitoring for typical coalbed methane production areas in Shanxi Province, methane anomaly analysis, associated gas flaring identification as well as emission estimation were carried out, using Sentinel-5P TROPOMI (TROPOspheric Monitoring Instrument) CH4 data, Sentinel-2 false color images and VIIRS (Visible Infrared Imaging Radiometer Suite) active fire data. The research showed that typical coalbed methane production areas in Shanxi Province were featured with high CH4 concentration in the southeast and low concentration in the northwest. The maximum methane anomaly of about 80 ppb was discovered and the emission rate was estimated to be approximately 20 t/h-23 t/h for the identified associated gas flaring location. The estimation was consistent with the results from PRISMA data for the Shanxi coal mining region. The research demonstrated the capability of satellite observation to support the coalbed methane production emission source identification from space and indicated the method provided was favorable for methane anomaly analysis, emission identification as well as emission rate estimation for coalbed methane production areas.

A Synthesis of Global Coastal Ocean Greenhouse Gas Fluxes

AbstractThe coastal ocean contributes to regulating atmospheric greenhouse gas concentrations by taking up carbon dioxide (CO2) and releasing nitrous oxide (N2O) and methane (CH4). In this second phase of the Regional Carbon Cycle Assessment and Processes (RECCAP2), we quantify global coastal ocean fluxes of CO2, N2O and CH4 using an ensemble of global gap‐filled observation‐based products and ocean biogeochemical models. The global coastal ocean is a net sink of CO2 in both observational products and models, but the magnitude of the median net global coastal uptake is ∼60% larger in models (−0.72 vs. −0.44 PgC year−1, 1998–2018, coastal ocean extending to 300 km offshore or 1,000 m isobath with area of 77 million km2). We attribute most of this model‐product difference to the seasonality in sea surface CO2 partial pressure at mid‐ and high‐latitudes, where models simulate stronger winter CO2 uptake. The coastal ocean CO2 sink has increased in the past decades but the available time‐resolving observation‐based products and models show large discrepancies in the magnitude of this increase. The global coastal ocean is a major source of N2O (+0.70 PgCO2‐e year−1 in observational product and +0.54 PgCO2‐e year−1 in model median) and CH4 (+0.21 PgCO2‐e year−1 in observational product), which offsets a substantial proportion of the coastal CO2 uptake in the net radiative balance (30%–60% in CO2‐equivalents), highlighting the importance of considering the three greenhouse gases when examining the influence of the coastal ocean on climate.

An Explainable Evaluation Model for Building Thermal Comfort in China

The concentration of atmospheric greenhouse gases is being amplified by human activity. Building energy consumption, particularly for heating and cooling purposes, constitutes a significant proportion of overall energy demand. This research aims to establish a smart evaluation model to understand the thermal requirements of building occupants based on an open-access dataset. This model is beneficial for making reasonable adjustments to building thermal management, based on factors such as different regions and building user characteristics. Employing Bayesian-optimized LightGBM and SHAP (SHapley Additive exPlanations) methods, an explainable machine learning model was developed to evaluate the thermal comfort design of buildings in different areas and with different purpose. Our developed LightGBM model exhibited superior evaluation performance on the test set, outperforming other machine learning models, such as XGBoost and SVR (Support Vector Regression). The SHAP method further helps us to understand the interior evaluation mechanism of the model and the interactive effect among input features. An accurate thermal comfort design for buildings based on the evaluation model can benefit the carbon-neutral strategy.

Using machine learning to construct TOMCAT model and occultation measurement-based stratospheric methane (TCOM-CH4) and nitrous oxide (TCOM-N2O) profile data sets

Abstract. Monitoring the atmospheric concentrations of greenhouse gases (GHGs) is crucial to improve our understanding of their climate impact. However, there are no long-term profile data sets of important GHGs that can be used to gain a better insight into the processes controlling their variations in the atmosphere. In this study, we apply corrections to chemical transport model (CTM) output based on profile measurements from two solar occultation instruments: the HALogen Occultation Experiment (HALOE) and the Atmospheric Chemistry Experiment – Fourier Transform Spectrometer (ACE-FTS). The goal is to construct long-term (1991–2021), gap-free stratospheric profile data sets, hereafter referred to as TCOM, for two important GHGs. To estimate the corrections that need to be applied to the CTM profiles, we use the extreme gradient boosting (XGBoost) regression model. For methane (TCOM-CH4), we utilize both HALOE and ACE satellite profile measurements from 1992 to 2018 to train the XGBoost model, while profiles from 2019 to 2021 serve as an independent evaluation data set. As there are no nitrous oxide (N2O) profile measurements for earlier years, we derive XGBoost-derived correction terms to construct TCOM-N2O profiles using only ACE-FTS profiles from the 2004–2018 time period, with profiles from 2019–2021 used for the independent evaluation. Overall, both TCOM-CH4 and TCOM-N2O profiles exhibit excellent agreement with the available satellite-measurement-based data sets. We find that compared to evaluation profiles, biases in TCOM-CH4 and TCOM-N2O are generally less than 10 % and 50 %, respectively, throughout the stratosphere. The daily zonal mean profile data sets, covering altitude (15–60 km) and pressure (300–0.1 hPa) levels, are publicly available via the following links: https://doi.org/10.5281/zenodo.7293740 for TCOM-CH4 (Dhomse, 2022a) and https://doi.org/10.5281/zenodo.7386001 for TCOM-N2O (Dhomse, 2022b).

The Impact of Recent Climate Change on Plants

Climatic conditions play a key role in the basic plants processes (photosynthesis, respiration, growth and development), their seasonal cycle, and in determining the limits of their distribution. Climate has a great impact on plant individuals, populations and species, as well as on their communities, ecosystems and biomes. As a result, concerns have grown in recent decades about the possible effects of global climate change on flora. The paper gives an overview of the observed climate change, primarily changes in the atmospheric concentration of greenhouse gases, air temperature (global warming), precipitation regime and extreme weather and climate events. Then, the observed effects of recent climate change on the plants are analyzed, primarily the effects on the physiology, phenology and distribution of plant species, as well as the effects on plant communities and ecosystems. The results of numerous studies in the world proved that recent climate change has led to significant changes in the plants distribution ‒ range (shifts to higher latitudes and higher altitudes), physiology (improving the rate of photosynthesis and water use efficiency, decreasing stomatal conductivity and increasing net primary production) and the seasonal cycle ‒ phenology (earlier onset of growing season and earlier occurrence of phenophases in spring and summer and delay of autumn phenophases ending the growing season, and as a consequence of these changes prolongation of growing season in many regions) as well as that changed climatic conditions have already led to changes in plant communities (through changes in composition and altered interactions between species such as pollination, competition, predation, parasitism, mutualism, disease transmission, food chains, etc.) and local extinction of certain plant species.

Global terrestrial monsoon area variations since Last Glacial Maximum based on TraCE21ka and PMIP4-CMIP6 simulations

Global monsoon over land (GM_L) have significant variations in their dominated area (GMA_L). The quantitative assessment of changes in GMA_L is essential for understanding spatial environment impacts and the underlying driving mechanism of GM_L evolution. Simulation results of a suite of transient climate evolution simulation over the last 21,000 years (TraCE21ka) and five-model ensemble outputs of the Paleoclimate Modelling Intercomparison Project in their latest phase (fourth, PMIP4-CMIP6) are analyzed to study the changes in global, hemispheric and six sub-monsoon areas over the past 21 ka over land. Both datasets can reproduce large-scale characteristics of GMA_L variability, although there are differences in the magnitudes of their changes. Compared to 0 ka, TraCE21ka simulations reveal that GMA_L reduced by about 4.89 × 106 km2 (decreased by 10.89%) during the Last Glacial Maximum (LGM, 21–18 ka), and reached a maximum of 46.61 × 106 km2 (increased by 3.83%) during the middle Holocene (MH, 9–6 ka). In comparison, the results of PMIP4-CMIP6 yield a smaller change of GMA_L during the LGM (decreased by 3.72%) and a larger magnitude of GMA_L during the MH (increased by 4.73%). The analysis of GMA_L over the past 21 ka reveals the varying influences of external forcing, with insolation playing a dominant role. Rising atmospheric greenhouse gas concentrations (GHG) and ice sheet melting have induced a stepwise expansion in GMA_L during the last deglaciation, superimposed with several abrupt millennial-scale weakened monsoon events under meltwater fluxes (MWF) forcing. After that, insolation caused a gradually declining trend in GMA_L during the Holocene. The position of the Intertropical Convergence Zone (ITCZ) under orbital forcing, leading to an anti-phase reaction between Northern Hemisphere monsoon areas (NHMA_L) and Southern Hemisphere monsoon areas (SHMA_L), particularly after 9 ka. Among the six sub-monsoons, they show diverse variations and regional characteristics under different forcings. Although regional monsoons like Indonesia-Australia monsoon (IAM) exhibit nonlinear behavior due to internal variabilities, the overall response of global monsoons to external forcing is predominantly linear. In addition, changes in the hydrological processes can indicate the formation and expansion of monsoon domains. Moisture budget shows that thermodynamic effect has always dominated monsoon hydrological cycles over the past 21 ka. The differences in regional monsoon hydrological processes arise from the dynamic effect. Moreover, δ18O records have been used to test these numerical simulation results. Which, together with diverse thermodynamic and dynamic component configurations of terrestrial paleo-monsoon variations, would help to better understand the underlying mechanism of global monsoon and its influences in the future.

Effects of Vegetation Types and Soil Properties on Regional Soil Carbon and Nitrogen in Salinized Reservoir Wetland, Northeast China

This study investigated the spatial variability in soil organic carbon (SOC), total nitrogen (TN), soil microbial biomass carbon (SMBC), soil microbial biomass nitrogen (SMBN) and their possible relationships with other soil properties in the Hongqipao reservoir, which is dominated by different vegetation types. The results showed that there were high spatial variabilities in SOC, TN, SMBC and SMBN, and that the SOC, TN, SMBC and SMBN contents decreased with increasing soil depth in the Hongqipao reservoir. The SOC was significantly positively correlated with TN, SMBC, moisture content (MC) and negatively correlated with carbon to nitrogen ratio (C:N ratio) and bulk density (BD). Soil TN was significantly positively correlated with SMBC, SMBN, MC and negatively correlated with the C:N ratio, BD and pH. The SMBC was significantly positively correlated with SMBN, MC and negatively correlated with the C:N ratio, BD and pH. The SMBN was significantly negatively correlated with the C:N ratio and BD. All of the measures of soil properties in this study could explain the higher significant variability in the response variables (SOC, TN, SMBC and SMBN contents). The generalized additive model (GAM) showed that SOC and TN had different influencing factors in different soil depths. The structural equation model (SEM) showed that vegetation types had a significantly positive effect on TN and SMBN, and the soil depths had a significantly positive effect on SOC and a significantly negative effect on TN and SMBC. This study further suggests that vegetation types play a major role in determining the spatial characteristics of soil carbon and nitrogen, and any changes in the vegetation types in the reservoir may influence the distributions of soil carbon and nitrogen. This may affect the global carbon and nitrogen budgets and the atmospheric greenhouse gas concentration significantly.

Biomass residue to carbon dioxide removal: quantifying the global impact of biochar

The Climate Change Conference of Parties (COP) 21 in December 2015 established Nationally Determined Contributions toward reduction of greenhouse gas emissions. In the years since COP21, it has become increasingly evident that carbon dioxide removal (CDR) technologies must be deployed immediately to stabilize concentration of atmospheric greenhouse gases and avoid major climate change impacts. Biochar is a carbon-rich material formed by high-temperature conversion of biomass under reduced oxygen conditions, and its production is one of few established CDR methods that can be deployed at a scale large enough to counteract effects of climate change within the next decade. Here we provide a generalized framework for quantifying the potential contribution biochar can make toward achieving national carbon emissions reduction goals, assuming use of only sustainably supplied biomass, i.e., residues from existing agricultural, livestock, forestry and wastewater treatment operations. Our results illustrate the significant role biochar can play in world-wide CDR strategies, with carbon dioxide removal potential of 6.23 ± 0.24% of total GHG emissions in the 155 countries covered based on 2020 data over a 100-year timeframe, and more than 10% of national emissions in 28 countries. Concentrated regions of high biochar carbon dioxide removal potential relative to national emissions were identified in South America, northwestern Africa and eastern Europe.Graphical abstract

Assessment of the Influence of Instrument Parameters on the Detection Accuracy of Greenhouse-Gases Absorption Spectrometer-2 (GAS-2)

Satellite-based monitoring of atmospheric greenhouse gas (GHG) concentrations has emerged as a prominent and globally recognized field of research. With the imminent launch of the Greenhouse-Gases Absorption Spectrometer-2 (GAS-2) on the FengYun3-H (FY3-H) satellite in 2024, there is a promising prospect for substantial advancements in GHG detection capabilities. Crucially, the accurate acquisition of spectral information by GAS-2 is heavily reliant on its instrument parameters. However, the existing body of research predominantly emphasizes the examination of atmospheric parameters and their impact on GHG detection accuracy, thereby leaving a discernible gap in the comprehensive evaluation of instrument parameters specifically concerning the acquisition of atmospheric greenhouse gas concentration data by GAS-2. To address this knowledge gap, our study employs a radiation transfer model grounded in radiation transfer theory. This comprehensive investigation aims to quantitatively analyze the effects of various instrument parameters, encompassing crucial aspects such as spectral resolution, spectral sampling rate, signal-to-noise ratio, radiometric resolution, and spectral calibration accuracy (including instrument line shape function, central wavelength shift, and spectral resolution broadening). Based on our preliminary findings, it is evident that GAS-2 has the necessary spectral resolution, spectral sampling rate, and signal-to-noise ratio, slightly surpassing existing international instruments and enabling a significant detection accuracy level of 1 part per million (ppm). Moreover, it is essential to recognize the critical impact of instrument spectral calibration accuracy on overall detection precision. Among the five commonly used instrument line shape functions, the sinc function has the least impact on detection accuracy. Additionally, GAS-2’s radiance quantization depth is 14 bits, which is comparable to similar international payloads and maintains a root mean squared error below 0.1 ppm, thus ensuring a high level of precision. This study provides a comprehensive evaluation of the influence of GAS-2’s instrument parameters on detection accuracy, offering valuable insights for the future development of spectral calibration, the optimization of similar payload instrument parameters, and the overall improvement of instrument quantification capabilities.

Climate models underestimate the sensitivity of Arctic sea ice to carbon emissions

Arctic sea ice has steadily diminished as atmospheric greenhouse gas concentrations have increased. Using observed data from 1979 to 2019, we estimate a close contemporaneous linear relationship between Arctic sea ice area and cumulative carbon dioxide emissions. For comparison, we provide analogous regression estimates using simulated data from global climate models (drawn from the CMIP5 and CMIP6 model comparison exercises). The carbon sensitivity of Arctic sea ice area is considerably stronger in the observed data than in the climate models. Thus, for a given future emissions path, an ice-free Arctic is likely to occur much earlier than the climate models project. Furthermore, little progress has been made in recent global climate modeling (from CMIP5 to CMIP6) to more accurately match the observed carbon-climate response of Arctic sea ice.

Comparing the impacts of ozone-depleting substances and carbon dioxide on Arctic sea ice loss

The rapid decline of Arctic sea ice is widely believed to be a consequence of increasing atmospheric concentrations of greenhouse gases (GHGs). While carbon dioxide (CO2) is the dominant GHG contributor, recent work has highlighted a substantial role for ozone-depleting substances (ODS) in Arctic sea ice loss. However, a careful analysis of the mechanisms and relative impacts of CO2 versus ODS on Arctic sea ice loss has yet to be performed. This study performs this comparison over the period 1955–2005 when concentrations of ODS increased rapidly, by analyzing a suite of all-but-one-forcing ensembles of climate model integrations, designed to isolate the forced response to individual forcing agents in the context of internal climate variability. We show that ODS have played a significant role in year-round Arctic sea ice extent and volume trends over that period, accounting for 64% and 32% of extent and volume trends, respectively. These impacts represent 50% and 38% of the impact from CO2 forcing, respectively. We find that ODS act via similar physical processes to CO2, causing sea ice loss via increased summer melt, and not sea ice dynamics changes. These findings imply that the future trajectory of ODS emissions will play an important role in future Arctic sea ice evolution.

Review: The Energy Implications of Averting Climate Change Catastrophe

Conventional methods of climate change (CC) mitigation have not ‘bent the curve’ of steadily rising annual anthropic CO2 emissions or atmospheric concentrations of greenhouse gases. This study reviews the present position and likely future of such methods, using the recently published literature with a global context. It particularly looks at how fast they could be implemented, given the limited time available for avoiding catastrophic CC (CCC). This study then critically examines solar geoengineering, an approach often viewed as complementary to conventional mitigation. Next, this review introduces equity considerations and shows how these even further shorten the available time for effective action for CC mitigation. The main findings are as follows. Conventional mitigation approaches would be implemented too slowly to be of much help in avoiding CCC, partly because some suggested technologies are infeasible, while others are either of limited technical potential or, like wind and solar energy, cannot be introduced fast enough. Due to these problems, solar geoengineering is increasingly advocated for as a quick-acting and effective solution. However, it could have serious side effects, and, given that there would be winners and losers at the international level as well as at the more regional level, political opposition may make it very difficult to implement. The conclusion is that global energy consumption itself must be rapidly reduced to avoid catastrophic climate change, which requires strong policy support.

An Overview of Climate Change Mitigation, Mitigation Strategies, and Technologies to Reduce Atmospheric Greenhouse Gas Concentrations: A Review

An Overview of Climate Change Mitigation, Mitigation Strategies, and Technologies to Reduce Atmospheric Greenhouse Gas Concentrations: A Review