IPCC Research Articles

Global Downscaled Projections for Climate Impacts Research (GDPCIR): preserving quantile trends for modeling future climate impacts

Abstract. Global climate models (GCMs) are important tools for understanding the climate system and how it is projected to evolve under scenario-driven emissions pathways. Their output is widely used in climate impacts research for modeling the current and future effects of climate change. However, climate model output remains coarse in relation to the high-resolution climate data needed for climate impacts studies, and it also exhibits biases relative to observational data. Treatment of the distribution tails is a key challenge in existing bias-adjusted and downscaled climate datasets available at a global scale; many of these datasets used quantile mapping techniques that were known to dampen or amplify trends in the tails. In this study, we apply the Quantile Delta Mapping (QDM) method (Cannon et al., 2015) for bias adjustment. After bias adjustment, we apply a new spatial downscaling method called Quantile-Preserving Localized-Analog Downscaling (QPLAD), which is designed to preserve trends in the distribution tails. Both methods are integrated into a transparent and reproducible software pipeline, which we apply to global, daily GCM surface variable outputs (maximum and minimum temperature and total precipitation) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) experiments (O'Neill et al., 2016) for the historical experiment and four future emissions scenarios ranging from aggressive mitigation to no mitigation, namely SSP1–2.6, SSP2–4.5, SSP3–7.0, and SSP5–8.5 (Riahi et al., 2017). We use the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5 (Hersbach et al., 2020) temperature and precipitation reanalysis as the reference dataset over the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6) reference period of 1995–2014. We produce bias-adjusted and downscaled data over the historical period (1950–2014) and the future emissions pathways (2015–2100) for 25 GCMs in total. The output dataset is the Global Downscaled Projections for Climate Impacts Research (GDPCIR), a global, daily, 0.25∘ horizontal-resolution product which is publicly available and hosted on Microsoft AI for Earth's Planetary Computer (https://planetarycomputer.microsoft.com/dataset/group/cil-gdpcir/, last access: 23 October 2023).

Carbon Dioxide Uptake Estimation for Spanish Cement-Based Materials.

The Intergovernmental Panel on Climate Change (IPCC), which is the United Nations body for assessing the science related to climate change, has recently recognized the natural carbonation process as a way of carbon offsetting with mortar and concrete. Accordingly, this activity could be recognized as a carbon removal process for which certification should be granted. The aim of the certification of carbon removal is to promote the development of adequate and efficient new carbon removal processes. Therefore, the main objective of this study is to provide reliable results on carbon dioxide uptake by cement-based materials in Spain. Yearly, greenhouse gas emissions are reported to the United Nations Framework Convention on Climate Change (UNFCCC) by each country, and the natural carbonation should be added up to the carbon accounting. Therefore, natural carbonation should be included in the IPCC Guidelines for National Greenhouse Gas Inventories, and such accounting information should be made available promptly to the national regulatory authorities. This paper provides the results of carbon dioxide uptake by Spanish cement-based materials from 1990 to 2020 by using an easy method of estimating the net carbon dioxide emissions (simplified method) considering the carbon dioxide released by the calcination during clinker production (process emissions). The outcome of this study reveals that there was 93,556,000 tons of carbon dioxide uptake by the mortar and concrete manufactured in Spain from 1990 to 2020.

Degradation increases peat greenhouse gas emissions in undrained tropical peat swamp forests

AbstractTropical peat swamp degradation can modify net peat greenhouse gas (GHG) emissions even without drainage. However, current Intergovernmental Panel on Climate Change (IPCC) guidelines do not provide default emission factors (EF) for anthropogenically-degraded undrained organic soils. We reviewed published field measurements of peat GHG fluxes in undrained undegraded and degraded peat swamp forests in Southeast Asia (SEA) and Latin America and the Caribbean (LAC). Degradation without drainage shifted the peat from a net CO2 sink to a source in both SEA (− 2.9 ± 1.8 to 4.1 ± 2.0 Mg CO2–C ha−1 yr−1) and LAC (− 4.3 ± 1.8 to 1.4 ± 2.2 Mg CO2–C ha−1 yr−1). It raised peat CH4 emissions (kg C ha−1 yr−1) in SEA (22.1 ± 13.6 to 32.7 ± 7.8) but decreased them in LAC (218.3 ± 54.2 to 165.0 ± 4.5). Degradation increased peat N2O emissions (kg N ha−1 yr−1) in SEA forests (0.9 ± 0.5 to 4.8 ± 2.3) (limited N2O data). It shifted peat from a net GHG sink to a source in SEA (− 7.9 ± 6.9 to 20.7 ± 7.4 Mg CO2-equivalent ha−1 yr−1) and increased peat GHG emissions in LAC (9.8 ± 9.0 to 24.3 ± 8.2 Mg CO2-equivalent ha−1 yr−1). The large observed increase in net peat GHG emissions in undrained degraded forests compared to undegraded conditions calls for their inclusion as a new class in the IPCC guidelines. As current default IPCC EF for tropical organic soils are based only on data collected in SEA ombrotrophic peatlands, expanded geographic representation and refinement of peat GHG EF by nutrient status are also needed.

Investigation the implications of climate change on crop water requirements in Western Nile Delta, Egypt

Investigation the implications of climate change on crop water requirements in Western Nile Delta, Egypt

Sea level rise estimation and projection from long-term multi-mission satellite altimetry and tidal data in the Southeast Asia region

ABSTRACT The Southeast Asian (SEA) region represents a complex coastal geographical location. Most countries in SEA are encircled by the ocean, with lowlands coastal areas. The advantages of long-term satellite altimetry and tide gauge measurements have enabled climate-related research, particularly sea level rise, to be examined extensively in spatial and temporal scales. In this study, sea level anomaly (SLA) derived from 26 years of multi-mission satellite altimeter data plus approximately 28 years of tidal data have been utilized. Then, the projection for every 10 years starting from 2030 until 2100 has been analysed using machine learning regression. The projections are then evaluated based on the global model of the Intergovernmental Panel on Climate Change (IPCC). The findings presented that sea level rise trends around SEA with overall means of 4.70 ± 0.37 mm yr−1 for the satellite altimeter and 3.41 ± 0.24 mm yr−1 for the coastal tide gauge. Sea level projection from coastal tide gauge and satellite altimeter are expected to rise up to 34.87 and 33.71 cm, respectively, in 2100. These outcomes prove that the altimetry data from Radar Altimeter Database System (RADS) and the redundant tidal data are capable in measuring the sea level in SEA. These results are also expected to be valuable for multidisciplinary environmental studies in SEA, such as coastal flooding, coastal erosion, and other effect of global warming. Thus, it would make a meaningful contribution towards Sustainable Development Goal (SDG) 13, climate action, by providing the sea level rate and prediction information.

A comparison of Tier 1, 2, and 3 methods for quantifying nitrous oxide emissions from soils amended with biosolids

Municipal biosolids are a nitrogen (N)-rich agricultural fertilizer which may emit nitrous oxide (N2O) after rainfall events. Due to sparse empirical data, there is a lack of biosolids-specific N2O emission factors to determine how land-applied biosolids contribute to the national greenhouse gas inventory. This study estimated N2O emissions from biosolids-amended land in Canada using Tier 1, Tier 2 (Canadian), and Tier 3 (Denitrification and Decomposition model [DNDC]) methodologies recommended by the Intergovernmental Panel on Climate Change (IPCC). Field data was from replicated plots at 8 site-years between 2017 and 2019 in the provinces of Quebec, Nova Scotia and Alberta, Canada, representing three distinct ecozones. Municipal biosolids were the major N source for the crop, applied as mesophilic anaerobically digested biosolids, composted biosolids, or alkaline-stabilized biosolids alone or combined with an equal amount of urea-N fertilizer to meet the crop N requirements. Fluxes of N2O were measured during the growing season with manual chambers and compared to N2O emissions estimated using the IPCC methods. In all site-years, the mean emission of N2O in the growing season was greater with digested biosolids than other biosolids sources or urea fertilizer alone. The emissions of N2O in the growing season were similar with composted or alkaline-stabilized biosolids, and no greater than the unfertilized control. The best estimates of N2O emissions, relative to measured values, were with the Tier 3 > adapted Tier 2 with biosolids-specific correction factors > standard Tier 2 = Tier 1 methods of the IPCC, according to the root mean square error statistic. The Tier 3 IPCC method was the best estimator of N2O emissions in the Canadian ecozones evaluated in this study. These results will be used to improve methods for estimating N2O emissions from agricultural soils amended with biosolids and to generate more accurate GHG inventories.

Climate (in)Justice in Action? A Commentary on COP28 and Emerging Accounting Mechanisms

ABSTRACT With the concept of ‘just transition’ entering the mainstream of intergovernmental climate negotiations, social and environmental accounting scholars have a new and critical role in the global pursuit of climate justice. At its core, accounting mechanisms are being called upon to navigate a paradox inherent to the just transition: pursuing scalability through standardisation and simultaneously prioritising a tailored approach to national and sub-national contexts. While we venture potential conceptual approaches to grapple with this paradox, our priority for this article is to outline what we hope is a starting point for an agenda on accounting for climate justice. It, therefore, looks to provoke debate on an array of research questions and interventions, from the role of COPs (Conferences of the Parties to the United Nations Framework Convention on Climate Change) in giving birth to new accounting mechanisms, to the need to engage with the Intergovernmental Panel on Climate Change (IPCC) to highlight the relevance of accounting research in operationalising climate justice. Irrespective of how our community responds, notions of climate justice are already being made manifest in the international accounting mechanisms that aim to guide a just transition. We therefore call for action from the social and environmental accounting community.

Exploring temperature and precipitation changes under future climate change scenarios for black and white rhinoceros populations in Southern Africa

ABSTRACT Climate change is a potential human-induced threat to rhino populations and their habitat. Information on the effects of climate change on rhinoceros species can help manage and develop conservation plans to adapt to these changes. In this study, two climate change scenarios were used to predict temperature and precipitation changes in national parks in southern Africa and the effect those changes would have on black (Diceros bicornis) and white (Ceratotherium simum) rhinoceros populations. The study used the Intergovernmental Panel on Climate Change (IPCC) Representative Concentration Pathways (RCPs) 4.5 and 8.5, atmospheric CO2 concentrations of 650 and 1370 ppm, for the years 2055 and 2085 to explore the temperature and precipitation changes. All spatial information was processed using Geographic Information Systems and statistical analysis. Results show the changing climate will have significant negative impacts on the probability of occurrence of both species. Temperature changes will affect these probabilities more than precipitation changes. All study parks will have zero probability of occurrence for the species throughout their ranges should conditions reach those represented by the RCP 8.5 scenario late in the century. Conservation activities for the rhinoceros should take into consideration the potential for temperature and precipitation changes modelled in this study.

CONSTRUCTION OF LOW-CARBON DEVELOPMENT INDEX SYSTEM IN THE ELECTRIC POWER CONSTRUCTION INDUSTRY

Climate change has become a global challenge, and China plays a crucial role in addressing this issue, particularly with significant challenges in carbon reduction tasks. The impact of global climate change on human production and life is increasingly prominent, and countries worldwide are committed to carbon neutrality through agreements such as the Paris Agreement. China accounted for approximately 29% of global carbon dioxide emissions in 2019, making achieving carbon peak and carbon neutrality a key factor in global competition. The Chinese government has repeatedly declared its goals of carbon peak and carbon neutrality, demonstrating a strong determination. Establishing a carbon accounting system is fundamental to achieving these targets. China refers to the guidelines of the United Nations Intergovernmental Panel on Climate Change (IPCC) and the MRV system to ensure detectable, reportable, and verifiable emissions, guaranteeing the accuracy of the data. This will facilitate the smooth operation of the national carbon trading market and stimulate carbon reduction efforts. Regarding carbon accounting, the article mentions two critical aspects: methodological guidance based on the IPCC's inventory guidelines and ensuring a detectable, reportable, and verifiable system. This provides the foundation for unified carbon emission data and the operation of the national carbon trading market. Building on the establishment of the carbon accounting system, the article further discusses the construction of a low-carbon development index system for power grid development. This involves establishing a carbon emission accounting and evaluation system for transmission and transformation projects, quantitatively monitoring and assessing projects through methods such as carbon emission accounting and input-output analysis. Additionally, a comprehensive index evaluation method is employed to construct a green construction evaluation system, providing a low-carbon green score for power grid construction. This work contributes to China's better achievement of carbon reduction goals and promotes sustainable development.

Inaction in Urban Climate Policy Undermines Health.

This paper investigates the critical intersection of urban climate policy and public health, emphasizing the pressing need for integrated strategies to address the intertwined challenges of climate change and health in urban settings. Despite cities being central to global emissions and energy consumption, a significant gap exists in the incorporation of health considerations into urban climate strategies, as evidenced by the analysis of urban content in Nationally Determined Contributions (NDCs). The paper highlights the Coalition for High Ambition Multilevel Partnerships (CHAMP) initiative and the forthcoming Intergovernmental Panel on Climate Change (IPCC) Special Report as pivotal moments for integrating climate and health agendas. However, it also points out the underwhelming response from cities in adopting comprehensive climate strategies, which undermines potential public health benefits. With substantial investments required to bridge the gap in health-focused climate resilience, the paper calls for a redefined approach to urban climate policy. This approach should prioritize health outcomes, leverage opportunities like the 15-Minute City concept, and foster the development of infrastructures that support both climate resilience and public health. The upcoming NDC revision cycle is identified as a critical opportunity for embedding health imperatives into urban climate strategies, emphasizing the need for a holistic perspective that views urban areas as ecosystems where climate and health are intricately connected. This comprehensive view aims to promote policies that are mutually reinforcing, thus contributing to healthier, more livable cities.

Migração forçada de El Salvador, Guatemala e Honduras para os Estados Unidos: identificando refugiados ambientais na multicausalidade

Abstract This article discusses natural disasters as the main factor that have led to forced migration processes in El Salvador, Guatemala, and Honduras to the United States between 2018 and 2023. These three countries have similarities in that their contexts of poverty and violence that force people to flee from them. They are also considered by the Intergovernmental Panel on Climate Change (IPCC) to be some of the most vulnerable places in Latin America to climate change. We analyzed data on internal displacement and asylum-seekers from these countries; statistics on the apprehension of migrants at the Southwest land border of the United States; data on natural disasters. This article aims to show that disasters can influence internal and international forced migration. By identifying potential environmental refugees in Central American migrations, we hope to draw attention to the need for legal protection for these people in situations of vulnerability.

Study on carbon emission driving factors and carbon peak forecasting in power sector of Shanxi province.

The realisation of the low-carbon transition of the energy system in resource-intensive regions, as embodied by Shanxi Province, depends on a thorough understanding of the factors impacting the power sector's carbon emissions and an accurate prediction of the peak trend. Because of this, the power industry's carbon emissions in Shanxi province are measured in this article from 1995 to 2020 using data from the Intergovernmental Panel on Climate Change (IPCC). To obtain a deeper understanding of the factors impacting carbon emissions in the power sector, factor decomposition is performed using the Logarithmic Mean Divisia Index (LMDI). Second, in order to precisely mine the relationship between variables and carbon emissions, the Sparrow Search Algorithm (SSA) aids in the optimisation of the Long Short-Term Memory (LSTM). In order to implement SSA-LSTM-based carbon peak prediction in the power industry, four development scenarios are finally built up. The findings indicate that: (1) There has been a fluctuating upward trend in Shanxi Province's total carbon emissions from the power industry between 1995 and 2020, with a cumulative growth of 372.10 percent. (2) The intensity of power consumption is the main factor restricting the rise of carbon emissions, contributing -65.19%, while the per capita secondary industry contribution factor, contributing 158.79%, is the main driver of the growth in emissions. (3) While the baseline scenario and the rapid development scenario fail to peak by 2030, the low carbon scenario and the green development scenario peak at 243,991,100 tonnes and 258,828,800 tonnes, respectively, in 2025 and 2028. (4) Based on the peak performance and the decomposition results, resource-intensive cities like Shanxi's power industry should concentrate on upgrading and strengthening the industrial structure, getting rid of obsolete production capacity, and encouraging the faster development of each factor in order to help the power sector reach peak carbon performance.

Greenhouse gas emissions trends and drivers insights from the domestic aviation in Thailand

Domestic aviation is a swiftly expanding contributor to global greenhouse gas (GHG) emissions. Presently, economic volatility and the Coronavirus disease (COVID-19) crisis have resulted in the decline of domestic aviation, but domestic aviation is rapidly recovering in many countries. However, from a GHG emissions viewpoint, the domestic aviation sector is largely unenforced even though the International Civil Aviation Organization's (ICAO) Carbon Offsetting and Reduction Scheme for International Aviation (CORSIA) provision for international aviation is currently in place. Accordingly, the knowledge base on emissions and their drivers from domestic aviation is weak, especially in developing countries, thus hindering an evidence-based policy debate. In this context, we have estimated and analyzed the pre-COVID-19 GHG emissions and their trends from commercial domestic aviation in Thailand; and provided insights on the role of key drivers that influence GHG emissions that are expected to be useful not only for Thailand but also for other developing countries. Emissions are estimated following Intergovernmental Panel on Climate Change (IPCC) Tier-II. Specifically, activity-based landing/take-off (LTO) cycle and cruise. This is compared to the Tier-I method, and key drivers were analyzed using an index decomposition method. The total annual average GHG emissions for all LTO cycles and cruises of commercial domestic aviation for 2015–2020 was 2254 Th. tonnes of CO2-eq. During the LTO cycle of the aircraft, GHG emissions were at an average of 983 Th. tonnes of CO2-eq. Additionally, during the cruise stage, emissions averaged 1270 Th. tonnes of CO2-eq. The choice of accounting methods (i.e., IPCC Tier II vs. Tier I) seems to have had only nominal implications. Our analysis showed that, in the 2008–2020 period, the aviation activity effect and economic growth were the key decisive factors in this sector's GHG emissions growth. It was followed by the fuel energy intensity levels and the population effect in descending order of impact. These findings have significant ramifications for present and future policies aimed at decreasing GHG emissions, aiding Thailand in achieving its climate targets by 2050, and enhancing energy efficiency as the domestic aviation market adapts.

Defining severe risks related to mobility from climate change

While migration is often conceptualized as an adaptive response to climate hazards, migration can also present severe risks to people on the move. In this paper, we attempt to operationalize the Representative Key Risks (RKR) framework of the Sixth Assessment Report of Working Group II of the Intergovernmental Panel on Climate Change (IPCC) for human mobility. First, we provide a framework for understanding how mobility risks emerge by engaging with the concept of habitability. We argue that uninhabitability occurs where the physical environment loses suitability and where there is a loss of agency in local populations. The severity of the risk from the loss of habitability is then represented by the high potential for human suffering. When climate hazards affect physical suitability and agency, the forms of migration that occur undermine human wellbeing and the right to self-determination: forced displacement, community relocation/resettlement, and involuntary immobility. Second, we show how such forms of mobility are more or less likely along different Shared Socioeconomic Pathways (SSPs). This paper asserts a central concern around human suffering to recentre scenario discourse on where, and how, adaptation, changes to development patterns, and government policies can reduce this suffering. Proactive governance at local, national, and international levels that attends to people’s adaptation and mobility needs can avert the more frequent emergence of severe risks related to mobility in a changing climate.

Impact of climate warming on soil microbial communities during the restoration of the inner Mongolian desert steppe.

Grazer exclosure is widely regarded as an effective measure for restoring degraded grasslands, having positive effects on soil microbial diversity. The Intergovernmental Panel on Climate Change (IPCC) predicts that global surface temperatures will increase by 1.5-4.5°C by the end of the 21st century, which may affect restoration practices for degraded grasslands. This inevitability highlights the urgent need to study the effect of temperature on grassland soil microbial communities, given their critical ecological functions. Here, we assessed the effects of heavy grazing (control), grazer exclosure, and grazer exclosure plus warming by 1.5°C on soil microbial community diversity and network properties as well as their relationships to soil physicochemical properties. Our results showed that grazer closure increased soil microbial richness relative to heavy grazing controls. Specifically, bacterial richness increased by 7.9%, fungal richness increased by 20.2%, and the number of fungal network nodes and edges increased without altering network complexity and stability. By contrast, grazer exclosure plus warming decreased bacterial richness by 9.2% and network complexity by 12.4% compared to heavy grazing controls, while increasing fungal network complexity by 25.8%. Grazer exclosure without warming increased soil ammonium nitrogen content, while warming increased soil nitrate nitrogen content. Soil pH and organic carbon were not affected by either exclosure strategy, but nitrate nitrogen was the dominant soil factor explaining changes in bacterial communities. Our findings show that grazer exclosure increases soil microbial diversity which are effective soil restoration measures for degraded desert steppe, but this effect is weakened under warming conditions. Thus, global climate change should be considered when formulating restoration measures for degraded grasslands.

Assessment of Temporal Trend in Surface Air Temperatures across Some Selected Eco-Climatic Zones in Nigeria

Temporal trends in surface air temperatures across some selected eco-climatic zones in Nigeria from 1981 to 2018 were assessed using the Merra-2 reanalysis dataset. A total of 15 stations spread across the eco-climatic zones in Nigeria were used for this study. The Mann-Kendall (M-K) trend test was used to detect direction, significance, coefficients of time trends, while the linear regression and the Sen’s slope trend tests were used to estimate the trend magnitudes. The M-K trend test showed that the surface air maximum temperature of 14 stations had monotonic increasing trends, of which 13 stations were statistically significant at the 0.01 significance level, and 1 station was statistically significant at the 0.05 significance level. However, the M-K trend test also showed that surface air minimum temperature for all the 15 stations (representing 100%), showed monotonic upward trends, statistically significant at the 0.01 significance level. The Sen's slope and linear trend tests showed higher trend magnitudes at most stations, particularly stations in the Guinea-wooded, Sudan and Sahel savannas. The estimated mean trend magnitudes of maximum and minimum air surface temperatures increased by approximately 0.035°C/year and 0.036°C/year, respectively. The estimated mean air surface temperature increased by approximately 0.036°C/year and approximately 1.4°C for Nigeria over the 38-year period. The study then presents a linear trend projection of mean air surface temperature increase in Nigeria of approximately 4.3°C by 2100. This is 0.2°C below maximum levels and within the range of approximately 1.5 to 4.5°C that global air surface temperature is projected to rise by 2100 in the Intergovernmental Panel on Climate Change (IPCC) 2007 report. The M-K and linear trend tests were fully consistent with the standardized time series anomaly plots. Mean annual values of the air surface temperatures showed latitudinal dependence. The manifestation of significant long-term trends at high confidence levels in the air surface temperatures over the period, provides a clear evidence that the climate of Nigeria is witnessing a possible human-induced radiative forcing and a strong tendency for the occurrences of climate-related extreme events and their resulting adverse implications.

Estimating the GHGs and the MAC of Agricultural Production Systems in China

As the second largest source of greenhouse gas (GHG) emissions, the agricultural system has an arduous task of reducing emissions. There is an urgent need to think about how to achieve the goal of peaking carbon emissions in agricultural production at the lowest cost. This paper applied the Intergovernmental Panel on Climate Change (IPCC) factor method to calculate the GHG emissions of China’s agricultural production systems and deconstruct it into the crop farming and animal husbandry sectors. Input–output indicators based on parametric directional distance functions were constructed to assess the green production efficiency (GPE) of different agricultural sectors and scientifically quantify the marginal abatement costs (MACs) of different GHGs. The results showed the following: (a) During 2000 to 2020, GHG emissions from China’s agricultural production systems averaged 87.73 million tons of CO 2 -eq and showed a fluctuating downward trend. CH 4 emissions accounted for the largest average proportion of 55%, mainly animal enteric fermentation and rice methane emissions. (b) The average level of agricultural GPE in China is 0.79, and 0.76 for crop farming is slightly higher than 0.67 for animal husbandry. (c) The average MAC is 1,861.71 yuan/ton CO 2 -eq, and it is increasing year by year. The shadow price is positively correlated with the efficiency level. The “high-efficiency–low-cost” areas are key areas for agricultural emission reduction, such as Henan and Shandong provinces. Formulate emission reduction strategies according to the characteristics of regional GHG emissions to promote the realization of the “dual carbon” goal of agriculture.

Scenarios for combating global warming: China's critical role as a leader in the energy transition

<p>China is now the world leader with green capital actually creating renewable energy technologies. We address the possibility of whether China can emerge a new ecological civilization, as well as become the global leader to reach climate security. In particular, China has the potential to implement a solar energy infrastructure in the deserts of the Middle East as part of the Belt and Road Initiative, mainly in the form of concentrated solar power. The creation of this renewable energy capacity could supply electricity to much of the world, as well as power the direct air capture (DAC) of carbon dioxide with a permanent burial in the crust, in particular, using the ultramafic deposits in Oman. This realization would increase the chances of not breaching the International Panel on Climate Change (IPCC) warming target of 1.5 ℃, of course only if coupled with the termination of utilizing fossil fuels as early as possible and their replacement with renewable energy supplies globally. In this context, our pioneering model establishes that coupling a DAC-driven drawdown of atmospheric carbon dioxide with a rapid increase in the renewable energy capacity is more than capable of producing enough clean energy to eliminate energy insecurity globally (to all 8–10 billion humans) and to provide energy for the drawdown for the rest of the 21st century, thereby reducing atmospheric carbon dioxide to safe levels. This contingency will likely only be realized with a shift to demilitarization of the global economy. Likewise, this potential emergence of China as the global leader for climate security would likely inspire the push for a global Green New Deal to make this goal possible.</p>

Net global warming potential index rather than soil carbon stock change could provide better understanding of the carbon balance in soil systems.

This study was conducted to determine the soil organic carbon (SOC) stock change factor for green manure crops that was developed by the Intergovernmental Panel on Climate Change (IPCC) Tier 2 method and compare this with the net global warming potential (GWP) index that is used to evaluate the contribution of green manuring to global warming. Four treatments were barley (Hordeum vulgare L.; B), hairy vetch (Vicia villosa R.; HV), a barley/hairy vetch mixture (BHV) and a conventional treatment (C). The aboveground biomass of green manure crops was incorporated into the soil on 25 May 2018, 26 April 2019, 29 April 2020, 30 April 2021 and 2 May 2022. Maize (Zea mays L.) was transplanted as the subsequent crop after the incorporation of green manures. SOC stock decreased with green manures, even though carbon input with green manures, including B, HV and BHV, was greater than that with C. The mean value of the SOC stock change factor for green manure crops, including B, HV and BHV was 0.627 and was significantly lower than that of the C. However, the net GWP also decreased with the incorporation of green manure crops, and the mean value of the relative net GWP index across B, HV and BHV was 0.853. These conflicting results were caused by different estimation methods between annual SOC change (△SOC) and net GWP. The estimation of SOC stock change using △SOC suggested by the IPCC method may overestimate the contribution of green manure crops to global warming. The net GWP method with comprehensive input and output of carbon in the soil system could provide a better understanding of the carbon balance in soil systems. In the current study, the comparison of △SOC and net GWP was conducted for at one site of upland soil for 5years. Therefore, further research on estimating the effect of green manure crops on net GWP in various types of soil for longer years should be conducted.

Estimating Nitrous Oxide (N2O) emissions from managed soils at higher spatial resolution in the Republic of Ireland

This paper aims to define a high spatial resolution model for estimating nitrous oxide (N2O) emissions from agricultural soils in Ireland. In 2020, N2O emissions from the management of agricultural soils represented 10% of the total national agricultural Greenhouse Gas (GHG) emissions. The high spatial resolution model employed here takes account of environmental factors that influence N2O emissions at a more disaggregated spatial scale than the Intergovernmental Panel on Climate Change (IPCC) national inventory-reporting framework. Activity data from the EU Farm Accountancy Data Network (for Ireland) is used in conjunction with biophysical and climatic data in a geographic information system (GIS) framework to estimate N2O emissions at a sub-national level. Results indicate that N2O emissions are 5% lower by applying this high spatial resolution modelling approach at the farm level compared to the baseline model (Tier 2). Nevertheless, 25% of the farms in the sample analysed had an overestimation in their N2O emissions of 20%, and another 25% of the farm sample had an average underestimation in their N2O emissions by 19%, a consequence of the variation of environmental factors among farms. Using a data panel regression, results confirm that the environmental factors examined are statistically significant within the model proposed, and with a simulation, we assessed the switching of 20% of CAN fertiliser for protected urea. According to the high spatial model, this mitigation measure can reduce N2O emissions from inorganic fertilisers by up to 15%. However, the reduction is conditioned by local factors and environmental conditions.