IPCC Research Articles

Intergovernmental Panel on Climate Change (IPCC) Tier 1 forest biomass estimates from Earth Observation

Aboveground biomass density (AGBD) estimates from Earth Observation (EO) can be presented with the consistency standards mandated by United Nations Framework Convention on Climate Change (UNFCCC). This article delivers AGBD estimates, in the format of Intergovernmental Panel on Climate Change (IPCC) Tier 1 values for natural forests, sourced from National Aeronautics and Space Administration’s (NASA’s) Global Ecosystem Dynamics Investigation (GEDI) and Ice, Cloud and land Elevation Satellite (ICESat-2), and European Space Agency’s (ESA’s) Climate Change Initiative (CCI). It also provides the underlying classification used by the IPCC as geospatial layers, delineating global forests by ecozones, continents and status (primary, young (≤20 years) and old secondary (>20 years)). The approaches leverage complementary strengths of various EO-derived datasets that are compiled in an open-science framework through the Multi-mission Algorithm and Analysis Platform (MAAP). This transparency and flexibility enables the adoption of any new incoming datasets in the framework in the future. The EO-based AGBD estimates are expected to be an independent contribution to the IPCC Emission Factors Database in support of UNFCCC processes, and the forest classification expected to support the generation of other policy-relevant datasets while reflecting ongoing shifts in global forests with climate change.

Performance Analysis of Neighborhood Component Analysis on Support Vector Machine in Greenhouse Gas Emission Classification

The heatwave phenomenon has hit several countries in various parts of the world, caused by climate change. Climate change leads to greenhouse gas emissions increasing beyond the limits set by the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report Global Warming Potentials. This final project uses a combination of Neighborhood Component Analysis (NCA) and Support Vector Machine (SVM) methods with linear, polynomial, Radial Basis Function (RBF), and sigmoid kernel functions. The purposes of this final project are to evaluate the performance of NCA on SVM and to determine the best kernel function in this combination. Based on the analysis, it was found that classification using a combination of NCA and SVM methods can reduce variables, with the best kernel function being the Polynomial kernel function. This is because the analysis using the Polynomial kernel function achieved the highest accuracy values for training data, testing accuracy, and F1-Score, which are 98,96%, 99,15%, and 98,98% respectively. Additionally, the training analysis time and testing analysis time were the shortest at 0,15 seconds and 0,04 seconds.

Transforming the feeding regime towards low-input increases the environmental impact of organic milk production on a case study farm in central germany

Abstract Purpose Despite the direct effect of the feeding regime on the environmental impacts of dairy farming systems, its level of intensity, particularly in organic systems, has rarely been investigated. This study compares the environmental impact of a high-input feeding regime with a grassland-based, low-input feeding regime scenario within an organic milk production system conducted on Gladbacherhof, the research farm of Justus Liebig University Giessen, in Central Germany. Methods An integrated Life Cycle Assessment (LCA) analysis was performed from a cradle-to-farm gate perspective to quantify five environmental impacts, namely Global Warming (GW), Non-Renewable Energy Use (NREU), Land Use (LU), Terrestrial Acidification (TA), and Freshwater Eutrophication (FE). All agronomic data of the Gladbacherhof research farm, averaged over the years 2010–2017, were included. When not directly measured on the farm, ecoinvent data were included. Results and discussion Contrary to our hypothesis, the results suggest that a grassland-based low-input system has a higher environmental impact as compared to a high-input system for each of the five impact categories when using fat and protein-corrected milk (FPCM) as the functional unit. A 50% reduction in concentrates and exclusion of maize silage from the feed ration in the modelled low-input production system lead to a 20% drop in milk yield. To balance the energy content in low-input feeding ration, longer grazing period and higher amount of hay, alfalfa, and grass silage are required. This in turn results in higher emissions from enteric fermentation, manure management, and feed production and hence in higher environmental impact, particularly for GW, TA, and FE. Conclusions This study is one of the few that directly explores the environmental impact of feeding intensity in an organic milk production system. Nevertheless, there is a lack of research on consolidated emission factors for several greenhouse gas (GHG) sources in organic livestock and cropping systems to perform more robust carbon footprint calculations that comply with the Intergovernmental Panel on Climate Change (IPCC) Tier 3 GHG reporting guidelines. To generalize the results at the regional or national scale, direct comparisons with a larger number of organic farms representative of high-input and low-input intensities are still essential.

Dynamics of Exposure and Sensitivity of Agricultural Sector to Climate Change in Yogyakarta Special Region as Observed by Geospatial Datasets

Abstract The impact of climate change on agricultural productivity is evident. Higher temperatures, more extreme rainfall, and shorter growing seasons are leading to decreased agricultural yields. To address this, it is crucial to map the exposure and sensitivity of the agricultural sector to climate change in the Yogyakarta Special Region. This is especially important given the region’s heavy reliance on agriculture, particularly in Sleman, Bantul, Kulon Progo, and Gunungkidul Regencies. Mapping these factors aligns with the Intergovernmental Panel on Climate Change (IPCC) assessments. Exposure and sensitivity are evaluated using biophysical indicators over three periods: 2020, 2030, and 2050, under two Representative Concentration Pathway (RCP) scenarios, 4.5 and 8.5. The findings reveal three levels of exposure and sensitivity in the region: low, moderate, and high. Exposure values are projected to rise under both RCP scenarios across the studied periods. In Gunungkidul, Saptosari, Purwosari, Tanjungsari, and Panggang consistently exhibit high exposure levels, while Pakem and Cangkringan in Sleman maintain low exposure levels. Gedangsari and Rongkop in Gunungkidul show highest sensitivity, whereas Temon in Kulon Progo and Pakem in Sleman show lowest sensitivity. Therefore, it is important to develop plans to reduce these impacts.

Variability of seasonal temperature from 1990 to 2020 within Oum Er Rbia hydraulic basin (Morocco): Study of trends and anomalies

Abstract The fifth report of the Intergovernmental Panel on Climate Change (IPCC) indicates that global temperatures have increased during the 20th century. In Morocco, numerous studies have unveiled that the nation has been contending with the effects of global warming for several decades, attributed to its geographical location. The studies have mainly focused on the evolution of rainfall and the recurrence of droughts. Nevertheless, temperature variations remain less addressed, especially at large spatial scales. This paper aims to study the seasonal temperature variability in the large hydraulic basin of Oum Er Rbia, focusing on its anomalies and trends as well as identifying their impacts on the basin’s territory. Indeed, the large basin of Oum Er Rbia occupies more than 48,.000 km2 and is characterized by an arid to semi-arid climate. Its water resources are important and play an essential role in the country’s socio-economic development. This basin is well-known for its agricultural activity. Although its water and economic potential are significant, the great basin is considered vulnerable to climatic variations, which strongly condition its development. Considering the significance of temperature trends within the framework of global warming, this current study delves into the topic of seasonal temperature variability within the expansive hydraulic basin of Oum Er Rbia. Based on statistical analysis using the temperature anomaly index and the Mann-Kendall trend test, this study reveals that strong interannual variability marked the evolution of seasonal temperatures during the period of 1990-2020, with a remarkable upward trend during the autumn and spring. When the temperature increase, the temperature increases in turn: thus, the negative impacts affect both water resources and the agriculture sector, which suffers from the combined effect of increased evapotranspiration and reduction of irrigation water.

Towards Defining Climate Adaptation Literacy in the Context of Urban Resilience

Abstract The climate crisis intensifies rapidly, straining the urban environment and society. Addressing climate change requires collaborative efforts, integrating physical resilience with knowledge empowerment. Formal and informal knowledge are vital for effective adaptation. In the updated Intergovernmental Panel on Climate Change (IPCC) AR6 Report an emphasis on knowledge and its role in reducing response risk was highlighted. At the urban scale, adaptation knowledge is essential, bridging social and technical systems. Here, community knowledge evolves from a passive component within a greater adaptation strategy to an active, integral element. This paper develops a unique definition of climate adaptation literacy for the urban built environment based on an extensive literature review on urban climate adaptation, guided by the PISA (Program for International Student Assessment) 2025 Framework. The results of this work highlight existing gaps in climate adaptation knowledge and present urban climate adaptation literacy as a means to measure the response risk. These insights aid the formulation of resilience policies and urban adaptation strategies and contribute to the safety, resilience, sustainability, and functionality of the material and non-material values of the urban environment

Study of the feature of the temperature regime of the Mykolaiv and region in the context of the issue of climate change

Climate change is one of the most important and acute environmental problems of our time. It includes a complex of changes, such as rising ambient temperatures, changes in precipitation patterns, rising sea levels, and more frequent extreme weather events. According to the Intergovernmental Panel on Climate Change (IPCC), the average global temperature has risen by about 1.1°C since the late nineteenth century. Projections point to a possible increase of 1.5°C by the middle of this century unless significant measures are taken to reduce greenhouse gas emissions. On the basis of the above, the paper analyzes trends in changes in atmospheric air temperature on the territory of risky agriculture in the South of Ukraine in the Mykolaiv region.The purpose of the study: to determine and substantiate the regularities of changes in the temperature regime of Mykolaiv and Mykolaiv region in the context of climate change.Research results. The values of temperature characteristics for the year and season in Mykolaiv and Mykolaiv region during 1991−2023 are analyzed. In Mykolaiv, about 60-67 days with a negative average daily air temperature and about 32 days with a negative maximum daily air temperature are recorded. The duration of the period with a negative minimum air temperature can be an average of 93 days per year: 64 in winter, 16 in spring and 14 in autumn. At the same time, on a large territory of the Mykolaiv region, autumn is warmer than spring. The average seasonal air temperature is 10.6°C, the average maximum temperature is 15.4°C, and the average minimum temperature is 6.4°C. In the Northern Black Sea region, both maximum and minimum temperatures in autumn are higher than in spring. The dynamics of changes in average annual temperatures in the city of Mykolaiv in the period from 1980 to 2023 are analyzed. A stable linear trend towards a gradual increase in average annual temperatures has been determined. The warmest year for this observation period is 2023, the coldest are 1985 and 1987. It is determined that the rate of increase in average temperature is 0.61°C for every ten years. Maximum temperatures are increasing at a rate of 0.0884°C per year and minimum temperatures are decreasing at a rate of 0.0136°C per year. Every year, the average annual temperature increases by approximately 0.021°С. The largest number of days accompanied by heat stress (up to 90%) is observed in July – August. Thus, changes in air temperature indicate a significant change in the temperature regime of the entire climate system of the region, and the consequences of climate change may be predominantly negative and will intensify in the future.

Cost and Benefit Analysis of Different Buildings Through Reuse of Treated Greywater

The fact that the impacts of climate change cannot be prevented in the short term has increased the importance of climate change adaptation activities, and many national and international studies have been initiated in this regard. Greywater reuse (GWR) activities have become important methods recommended by the Intergovernmental Panel on Climate Change (IPCC) for adaptation to climate change. This study selects GWR from 3 different real typologies, a hotel, a residential building, and an industrial plant planned in Izmir Province of Türkiye, to design greywater systems followed by cost-benefit analyses. The applicability of GWR systems in these typologies has been analyzed, and comparisons have been made. GWR systems at the project design stage eliminate the need for installation modifications. Therefore, it is concluded that new buildings should be designed to integrate these alternative water resource systems. Recovered water through the installation of GWR systems is recommended to be used as flushing water, and the excess for garden irrigation, car washing and cleaning. The payback periods were calculated as 12 years for the hotel and industrial plant and 6 years for the residential building. The water savings were calculated as 46% for the hotel, 44% for the residential building, and 29% for the industrial plant. The results put forth the feasibility of this alternative water resource.

Optimizing dietary habits for climate benefits in China: Greenhouse gas emissions and sustainable substitution strategies

The transition in dietary patterns will impact future food consumption and greenhouse gas emissions (GHGs). In this study, we employed the Intergovernmental Panel on Climate Change (IPCC) coefficient method to evaluate the GHGs associated with dietary consumption across 31 provinces in China from 1978 to 2022. Additionally, we simulated the greenhouse gas emission reduction potential and the spatio-temporal changes under five food substitution scenarios for the period 2022–2050. The results indicated that GHGs from animal-based foods increased the most, rising from 1673.1 Mt. CO2eq in 1978 to 6660.3 Mt. CO2eq in 2022, with pork being the largest source of emissions, accounting for approximately 44 %. The grain-based food substitution scenario resulted in the lowest GHG emissions, about 533.88 Mt. CO2eq. Conversely, the plant-based food substitution scenario had the highest emissions, reaching 635.49 Mt. CO2eq. This study provides a benchmark for improving regional dietary structures and formulating policies aimed at reducing GHGs through dietary consumption.

Recommendation of consensus definition of sea turtle fibropapillomatosis

AbstractSea turtle fibropapillomatosis (FP) is an emerging transboundary contagious disease that affected concomitantly two different marine hot spots in the Northern Atlantic Ocean and in the South China Sea at the beginning of the twentieth century. FP reached a panzootic status in the 1990s in green turtle (Chelonia mydas) populations, with increased risks of emergence and spread of the disease which have been correlated with climate induced terrestrial and oceanic physical and chemical changes. During 2023–2024, scientific experts performed a bibliographic review and recommend the consensus definition of sea turtle fibropapillomatosis. FP is an emerging transboundary viral terrestrial and aquatic contagious neoplastic syndrome involving cancerous molecular transmission pathways, which may affect all species of sea turtles at all life stages. The diagnosis of the most common verrucous form of FP is pathognomonic by visual examination of a sea turtle. We summarize the main clinical characteristics of FP, moderated by a degree of confidence of research findings adapted from the Intergovernmental Panel on Climate Change (IPCC) assessment reports. We recommend the implementation of a universal and transparent monitoring strategy of sea turtle fibropapillomatosis in sentinel bays, under the governance of the World Organisation for Animal Health.

Habitat availability decline for waterbirds in a sensitive wetland: Climate change impact on the Ebro Delta

The highly biodiverse, productive and vulnerable areas, such as coastal wetlands, are increasingly threatened by human-induced disturbances, resulting in habitat loss. This habitat loss is a critical driver of biodiversity decline and significantly impacts species distribution and behavior, increasing the risk of extinctions. To address these concerns, we developed a Species Distribution Model (SDM) using a decade-long dataset of waterbird functional group occurrences in the Ebro Delta, with a particular focus on the Ardeidae family, which represents the most prominent species in the wetland. This model aims to predict potential habitat loss under various climate change scenarios, specifically those outlined in the Intergovernmental Panel on Climate Change (IPCC) Representative Concentration Pathways (RCP) 4.5 and 8.5, across three distinct time periods.Our SDM revealed that habitat suitability for waterbirds was notably influenced by temperature variations, increased cumulative precipitation, and lower terrain elevation. Predictions indicate an increase in available habitat for these waterbird species over the study periods considering the specified climate scenarios. However, the incorporation of sea-level rise and flooded areas into the models unveiled a dramatic decline in available areas for waterbirds in the long-term, reaching up to 50 % (RCP 4.5) and 70 % (RCP 8.5) reduction.Our study highlights the urgent need for conservation efforts to mitigate the substantial reduction in available habitat for waterbirds. This need is especially crucial due to the Ebro Delta's importance as a vital coastal wetland for many thousands of waterbirds throughout their entire life cycle. Immediate and targeted conservation actions are imperative to safeguard the essential habitats for these species.

Low N2O emissions induced by root-derived residues compared to aboveground residues of red clover or grass mixed into soil

The default The Intergovernmental Panel on Climate Change (IPCC) guidelines assume a constant N2O emission factor (EFN2O) for both belowground crop residues (BGR) and aboveground residues (AGR), and that ∼70 % of total N2O emissions following renewal of temporary grasslands come from BGR. However, empirical evidence is lacking, which motivated this study. BGR-free and BGR-rich clay loam collected in grass or red clover leys were incubated alone or mixed with AGR and different doses of nitrate over 107 days. The average EFN2O of BGR was around 18 % of that of AGR, and remained low even when soil nitrate concentration was very high, whereas EFN2O of AGR varied largely and rocketed even with a small increase in soil nitrate. The decomposition of the carbon present in crop residues was critical for N2O emissions. Lower EFN2O of BGR relative to AGR were related to slower C decomposition, which was not predicted by the biochemical characteristics. It is also likely that BGR were less conducive than AGR to develop into hotspots for N2O emission because of the roots’ finer distribution and closer contact with soil particles. Differences in EFN2O among AGR were mostly linked to the availability of N, either derived from residue mineralization or present in the soil. In conclusion, N2O accountings based on present IPCC default methodology likely overestimate the contribution by crops’ BGR.

A dynamic multi-objective optimization model for inner-industry carbon responsibility allocation based on carbon tax and carbon offsets accounting

The setting of Intergovernmental Panel on Climate Change (IPCC) raises concerns on curbing the excessive carbon emissions, and European Union (EU) has been proactively attempting “green” initiatives striving to achieve carbon neutrality. The current Carbon Border Adjustment Mechanism (CBAM) only works on short-term carbon reduction without much “greenness” investment incentives so far, and few studies focus on the long-standing inner-industrial carbon reduction coordination. To address these issues, this paper creatively presents a dynamic multi-objective carbon responsibility allocation model (CRAM) for EU carbon market, allows the carbon trade with a taxation based on carbon offsets accounting, and considers the final targets of sustainable “greenness” investment incentives. To find the optimal results of the designed dynamic CRAM, an improved KT-NSGA-II algorithm is proposed to detect the Pareto frontiers of each successive periods. Data from EU Cement and Aluminium industries are then selected for empirical analysis to compare the proposed CRAM to conventional CBAM model. The findings demonstrate that the superiority of CRAM in carbon emissions reduction, economic benefits improvement and green invests encouragement. With the adjustment of the inner-industrial carbon allowance trade, total carbon emissions decreased by 28.03% and the “greenness” investment initiative increased by 39.24% in contrast to the CBAM. The sensitivity analysis of the model also provides suggestions on the settings of carbon quota and tax with different industrial production process, and proposes policy recommendations for CRAM implementation.

The Slow Pace of Green Transformation: Underlying Factors and Implications

Concerns about climate change are a hot topic in the current debate about a sustainable future, and despite more than 30 years of international conferences, including the Intergovernmental Panel on Climate Change (IPCC) and the United Nations Climate Change Conference (COP), the annual usage amount of fossil fuel-based energy sources has remained largely unchanged, and the green transition to a carbon-free energy system is progressing at a much slower pace than anticipated. This paper presents an original approach that consists in addressing the green transition’s dilemmas by analyzing the complex interplay of strongly interwoven forces hindering the rapid adoption of so-called green energy sources scrutinized from a three-fold perspective: socio-psychological; political–strategic and territorial; and technological. Moreover, these forces are ranked according to the magnitude of their impact on the anticipated transition to green, and it is estimated by logistic fit extrapolation that the total share of the contribution of low-carbon sources might reach a maximum of about 25% among all energy sources in 2050. A final original picture is presented, summarizing how all the involved forces are acting upon the expected transition as well as their consequences.

Perceptions of carbon dioxide emission reductions and future warming among climate experts

The Intergovernmental Panel on Climate Change (IPCC) employs emission scenarios to explore a range of future climate outcomes but refrains from assigning probabilities to individual scenarios. However, IPCC authors have their own views on the likelihood of different climate outcomes, which are valuable to understand because authors possess both expert insight and considerable influence. Here we report the results of a survey of 211 IPCC authors about the likelihood of four key climate outcomes. We found that most authors are skeptical that warming will be limited to the Paris targets of well below 2 °C, but are more optimistic that net zero CO2 emissions will be reached during the second half of this century. When asked about the beliefs of their peers, author responses showed strong correlations between personal and peer beliefs, suggesting that participants with extreme beliefs perceive their own estimates as closer to the community average than they actually are.

Decoding environmental impact with image-based CO2 emission analytics

As per the regulations of Intergovernmental Panel on Climate Change (IPCC), the country’s carbon emission data hold primacy. Nevertheless, establishing and utilizing a database pose a daunting challenge. This study presents the “Carbon Seer System,” a novel software prototype designed to inform and educate users about the carbon footprint during their production and in daily life. The development process involved a three-stage user interview process, ensuring system’s alignment with user needs and preferences. The system employs machine learning and visual recognition technology, including convolutional neural networks (CNNs), feature pyramid networks, and self-attention mechanisms, enabling users to analyze captured images for carbon emission factors. It automatically identifies the carbon emission factors of industrial products, energy producers, household producers, waste treatment, and transportation. A unique “group detection” method allows for the simultaneous analysis of multiple objects in a single image, enhancing user convenience. Additionally, the software features a carbon footprint tracker and a carbon sink dashboard, providing users with insights into their carbon emissions and the efforts needed for offsetting. The study concludes that the “Carbon Seer System” represents a significant step towards individual enablement at understanding and actively participating in a low-carbon lifestyle.

High-resolution carbon emission mapping and spatial-temporal analysis based on multi-source geographic data: A case study in Xi'an City, China

Cities, contributing over 70% of global emissions, are key areas for climate change mitigation. Heterogeneity within cities determines the need for spatialized urban emissions reduction policies. However, few studies have attempted to characterize the spatial distribution of carbon emissions at the urban scale. To address this issue, a novel mapping method was proposed, using Xi'an as an example to explore the spatial distribution of carbon emissions at the city scale. Firstly, multiple geospatial open-source data, such as point of interest (POI), road networks, and land use, were utilized to identify the locations of emission sources. High-resolution carbon emission distributions were then mapped by allocating emissions based on the Intergovernmental Panel on Climate Change (IPCC) methodology. The study employed Global Moran's I to analyze the changes in spatial heterogeneity at different resolutions. Additionally, the Local Indicators of Spatial Association index (LISA) and Standard Deviation Ellipses (SDE) were adopted to examine the spatiotemporal characteristics of carbon emissions in Xi'an. The results show that carbon emissions at Xi'an City rises from 45.112 million tons to 72.701 million tons between 2010 and 2021. The construction of multi-scale carbon emissions spatial distributions, with a resolution of up to 30 m, allowed for a more detailed characterization of carbon emissions, especially in urban fringe areas. In addition, the results indicate that urban carbon emissions exhibit the strongest spatial autocorrelation at a resolution of 350 m. The study can provide a reference for the development of regional carbon emission reduction policies and spatial planning. In addition, the proposed spatialized method of city carbon emissions depends on open-source data, which allows it to have the potential for application in other cities.

Estimating fossil carbon contributions from chemicals and microplastics in Sweden's urban wastewater systems: A model-based approach

The importance of including fossil carbon in greenhouse gas emission assessments from wastewater treatment plants (WWTPs) is highlighted in the 2019 Intergovernmental Panel for Climate Change (IPCC) guidelines revision and underpinned by an increasing number of experimental studies. The present study introduces a model-based approach to estimate fossil carbon flows within Sweden's urban wastewater system, employing data on chemical and polymeric material flows as a starting point. Our findings show that fossil carbon constitutes approximately 12–17 % of the total carbon emissions to sewer systems. This result aligns with experimental data, which shows fossil carbon contributions to WWTP influents ranging from 4 to 28 %. Our analysis further indicates that microplastics contribute about 13 % of the fossil carbon influx to Swedish WWTPs, while organic chemicals account for the remaining 83 %.

Carbon emissions from global impervious surface expansion between 1985 and 2020

Impervious surface expansion (ISE) refers to the phenomenon that natural surfaces are covered by artificial materials, such as cement, asphalt, bricks, etc., usually due to human activities. Over recent decades, the rapid growth of the global population, economic development, and continuous urbanization have contributed to extensive ISE, which caused significant losses in terrestrial ecosystem carbon pools. A global assessment effort is lacking because of limited comprehensive data on carbon pools and uncertainties surrounding the extent of ISE. In this study, we aimed to quantify the carbon emissions resulting from global ISE between 1985 and 2020, following the method provided by the Intergovernmental Panel on Climate Change (IPCC) Guidelines. We first divided global land into 87 fine geographical zones by overlaying continental boundary information with an ecological zone map. Then, multiple time-series impervious surface data products, land cover dynamic monitoring product, global biomass data, and topsoil organic carbon (TSOC) information were integrated to build a lookup table (LUT) of biomass and TSOC density for these fine geographical zones. Last, we employed the IPCC method to estimate carbon emissions from ISE between 1985 and 2020. Our findings indicated a global ISE encompassing a total area of 58.12 Mha, with cropland encroachment accounting for 67.30 %. Over the past 35 years, cumulative committed carbon emissions from global ISE reached 1.14 ± 0.38 PgC, with TSOC representing 54.55 % and biomass carbon contributing 45.45 %.

Methodological framework for assessing malaria risk associated with climate change in Côte d'Ivoire.

Malaria is the leading cause of morbidity among children under five years of age and pregnant women in Côte d'Ivoire. We assessed the geographical distribution of its risk in all climatic zones of the country based on the Fifth Assessment Report (AR5) of the United Nations Intergovernmental Panel on Climate Change (IPCC) approach to climate risk analysis. This methodology considers three main driving components affecting the risk: Hazard, exposure and vulnerability. Considering the malaria impact chain, various variables were identified for each of the risk factors and for each variable, a measurable indicator was identified. These indicators were then standardized, weighted through a participatory approach based on expert judgement and finally aggregated to calculate current and future risk. With regard to the four climatic zones in the country: Attieen (sub-equatorial regime) in the South, Baouleen (humid tropical) in the centre, Sudanese or equatorial (tropical transition regime) in the North and the mountainous (humid) in the West. Malaria risk among pregnant women and children under 5 was found to be higher in the mountainous and the Baouleen climate, with the hazard highest in the mountainous climate and Exposure very high in the Attieen climate. The most vulnerable districts were those in Baouleen, Attieen and the mountainous climates. By 2050, the IPCC representative concentration pathway (RCP) 4.5 and 8.5 scenarios predict an increase in risk in almost all climatic zones, compared to current levels, with the former considering a moderate scenario, with an emissions peak around 2040 followed by a decline and RCP 8.5 giving the highest baseline emissions scenario, in which emissions continue to rise. It is expected that the AR5 approach to climate risk analysis will be increasingly used in climate risk assessment studies so that it can be better assessed at a variety of scales.