Climate

15 pages, 1756 KiB

Open AccessArticle

The Relationship of Climate Change and Malaria Incidence in the Gambella Region, Ethiopia

by Geteneh Moges Assefa, Muluken Desalegn Muluneh and Zewdie Aderaw Alemu

Climate 2025, 13(5), 104; https://doi.org/10.3390/cli13050104 - 17 May 2025

Background: This study investigates the relationship between climate variables and malaria incidence in Ethiopia’s Gambella region, a hotspot for malaria transmission. Methods: Utilizing 30 years of satellite-derived climate data and 10 years of malaria incidence records from the Ethiopian Public Health Institute, this [...] Read more.

Background: This study investigates the relationship between climate variables and malaria incidence in Ethiopia’s Gambella region, a hotspot for malaria transmission. Methods: Utilizing 30 years of satellite-derived climate data and 10 years of malaria incidence records from the Ethiopian Public Health Institute, this research analyzed trends and correlations. Climate variables, including rainfall, temperature, and relative humidity, were extracted using GPS data and global climate models from NASA. Autoregressive modeling was employed to assess the impact of these variables on malaria incidence at different time lags (lag 0, 1, and 2). Results: The analysis revealed significant upward trends in rainfall, relative humidity, and temperature over the 30-year period, coinciding with a rise in malaria cases over the past decade. Rainfall exhibited delayed effects on malaria incidence, while relative humidity demonstrated both immediate and persistent impacts. Relative humidity at lag 0 had the strongest influence (IRR = 1.002, 95% CI: 1.001–1.003), whereas temperature showed minimal effects (IRR = 1.000, 95% CI: 1.000–1.001). Conclusions: These findings underscore the critical role of climate variables in driving malaria transmission and highlight the urgent need for climate adaptation strategies, early warning systems, and strengthened health infrastructure. Leveraging climate data for predictive modeling and expanding targeted interventions, such as insecticide-treated nets (ITNs), is essential to mitigate climate-driven malaria risks and protect vulnerable communities in Gambella and similar regions Full article

► Show Figures

Figure 1

14 pages, 2466 KiB

Open AccessArticle

Recent Increasing Trend in Fire Activity over Southern India Inferred from Two Decades of MODIS Satellite Measurements

by S. Vijaya Kumar, S. Ravindra Babu, M. Roja Raman, K. Sunilkumar, N. Narasimha Rao and M. Ravisankar

Climate 2025, 13(5), 103; https://doi.org/10.3390/cli13050103 - 16 May 2025

Abstract

With rising global temperatures attributed to climate change, an increase in fire occurrences worldwide is anticipated. Therefore, a detailed examination of changing fire patterns is essential to improve our understanding of effective control strategies. This study analyzes the long-term trends of fire activity [...] Read more.

With rising global temperatures attributed to climate change, an increase in fire occurrences worldwide is anticipated. Therefore, a detailed examination of changing fire patterns is essential to improve our understanding of effective control strategies. This study analyzes the long-term trends of fire activity in Southern India (8–20° N, 73–85° E), utilizing MODIS active fire count data from January 2003 to December 2023. The climatological monthly mean results show that Southern India experiences heightened fire activity from December to May, reaching a peak in March. Yearly variations indicate that the highest fire counts occurred in 2021, followed by 2023, 2012, and 2018. The three most significant fire years in recent history reflect an upward trend in fire activity over the past decade, confirming insights from annual trend analysis. The correlation between inter-annual fire anomalies and different meteorological factors reveals a notable negative relationship with precipitation and soil moisture and a positive relationship with surface air temperature (SAT). Soil moisture demonstrates a stronger correlation (−0.45) than precipitation and SAT. In summary, long-term trends show a noteworthy annual increase of 3%. Additionally, monthly trends reveal interesting rising patterns in October, November, December, and January with higher significance levels. Our research supports regional climate action initiatives and policies addressing fire incidents in Southern India in light of the ongoing warming crisis. Full article

(This article belongs to the Section Climate and Environment)

► Show Figures

Figure 1

16 pages, 1579 KiB

Open AccessSystematic Review

Green Banking Practices, Opportunities, and Challenges for Banks: A Systematic Review

by Martin Kamau Muchiri, Szilvia Kesmarki Erdei-Gally and Maria Fekete-Farkas

Climate 2025, 13(5), 102; https://doi.org/10.3390/cli13050102 - 14 May 2025

Abstract

Green banking has become a concept of interest, particularly with the focus on the role played by banks in pursuing Sustainable Development Goal 13 on climate action. This study is distinguished from previous ones in that it aimed at investigating the multi-regional view [...] Read more.

Green banking has become a concept of interest, particularly with the focus on the role played by banks in pursuing Sustainable Development Goal 13 on climate action. This study is distinguished from previous ones in that it aimed at investigating the multi-regional view on green banking practices/activities around the world with a special emphasis on the opportunities and challenges that various banks encounter in different geographical areas. A systematic review approach was adopted based on the Web of Science and Scopus databases, in which 159 articles were retrieved and 62 articles synthesized through a thematic analysis. The research process was demonstrated through a Prisma 2020 flowchart. Key multiregional green banking activities identified include digital banking, green loan or sukuk products for Islam-dominated economies, green services and investments, and financing of green infrastructure. In essence, the implementation of green banking is either directly through active green lending and greening their operations or indirectly through enhancing conditions. The key challenges identified include regulatory handles, social economic and culture hinderances, transition risk and the high cost of compliance, greenwashing concerns, and weak investor confidence. The most prevalent opportunities included green banking as a strategic competitive advantage, emerging market niche, and as a strategy for long-term climate risk management. Full article

► Show Figures

Figure 1

14 pages, 1534 KiB

Open AccessArticle

Influences of Climate Factors and Tree Characteristics on Carbon Storage in Longan Orchards, Thailand

by Yaowatat Boongla, Wanlapa Outong, Thaneeya Chetiyanukornkul and Supachai Changphuek

Climate 2025, 13(5), 101; https://doi.org/10.3390/cli13050101 - 13 May 2025

Abstract

This research aimed to investigate the above-ground biomass and carbon storage in the above-ground biomass of longan trees located in Lumphun and Surin Provinces. The species, tree height, and diameter at ground level were measured at the study site. The diameter-based above-ground biomass [...] Read more.

This research aimed to investigate the above-ground biomass and carbon storage in the above-ground biomass of longan trees located in Lumphun and Surin Provinces. The species, tree height, and diameter at ground level were measured at the study site. The diameter-based above-ground biomass (AGB) was calculated using the allometric equation for the longan tree plantation, along with carbon storage. It was then multiplied by 0.5 to estimate the carbon storage (CS) in the AGB. In Lamphun Province, longan trees of the Edo species totaled 319 per 2.5 ha, with an average biomass of 180.06 kg, resulting in an estimated carbon storage of 1.04 Mg C/ha. In Surin Province, longan trees of the Paungtong species totaled 227 per 1.6 ha, with an average biomass of 149.63 kg and an estimated carbon storage of 0.86 Mg C/ha. Our findings show that tree characteristics such as longan tree diameter, height, and age are associated with biomass and carbon storage, and that climate variation may affect the health of longan trees and plantation productivity. Thus, this study serves as a useful guide for understanding the carbon storage of longan trees and improving longan management. Full article

► Show Figures

Graphical abstract

51 pages, 11577 KiB

Open AccessArticle

Projected Impacts of Climate and Land Use Change on Endemic Plant Distributions in a Mediterranean Island Hotspot: The Case of Evvia (Aegean, Greece)

by Konstantinos Kougioumoutzis, Ioannis P. Kokkoris, Panayiotis Trigas, Arne Strid and Panayotis Dimopoulos

Climate 2025, 13(5), 100; https://doi.org/10.3390/cli13050100 - 13 May 2025

Abstract

Anthropogenic climate and land use change pose major threats to island floras worldwide, yet few studies have integrated these drivers in a single vulnerability assessment. Here, we examine the endemic flora of Evvia, the second-largest Aegean island in Greece and an important biodiversity [...] Read more.

Anthropogenic climate and land use change pose major threats to island floras worldwide, yet few studies have integrated these drivers in a single vulnerability assessment. Here, we examine the endemic flora of Evvia, the second-largest Aegean island in Greece and an important biodiversity hotspot, as a model system to address how these disturbances may reshape species distributions, community composition, and phylogenetic diversity patterns. We used species distribution models under the Ensemble of Small Models and the ENphylo framework, specifically designed to overcome parameter uncertainty in rare species with inherently limited occurrence records. By integrating climate projections and dynamic land use data, we forecasted potential range shifts, habitat fragmentation, and biodiversity patterns for 114 endemic taxa through the year 2100. We addressed transferability uncertainty, a key challenge in projecting distributions under novel conditions, using the Shape framework extrapolation analysis, thus ensuring robust model projections. Our findings reveal pronounced projected range contractions and increased habitat fragmentation for all studied taxa, with more severe impacts on single-island endemics. Our models demonstrated high concordance with established IUCN Red List assessments, validating their ecological relevance despite the sample size limitations of single-island endemics. Current biodiversity hotspots, primarily located in mountainous regions, are expected to shift towards lowland areas, probably becoming extinction hotspots due to projected species losses, especially for Evvia’s single-island endemics. Emerging hotspot analysis identified new biodiversity centres in lowland zones, while high-altitude areas showed sporadic hotspot patterns. Temporal beta diversity analysis indicated higher species turnover of distantly related taxa at higher elevations, with closely related species clustering at lower altitudes. This pattern suggests a homogenisation of plant communities in lowland areas. The assessment of protected area effectiveness revealed that while 94.6% of current biodiversity hotspots are within protected zones, this coverage is projected to decline by 2100. Our analysis identified conservation gaps, highlighting areas requiring urgent protection to preserve future biodiversity. Our study reveals valuable information regarding the vulnerability of island endemic floras to global change, offering a framework applicable to other insular systems. Our findings demonstrate that adaptive conservation strategies should account for projected biodiversity shifts and serve as a warning for other insular biodiversity hotspots, urging immediate actions to maintain the unique evolutionary heritage of islands. Full article

(This article belongs to the Section Climate and Environment)

► Show Figures

Figure 1

27 pages, 3102 KiB

Open AccessArticle

Sustainability Assessment and Resource Utilization of Agro-Processing Waste in Biogas Energy Production

by Viktor Koval, Dzintra Atstāja, Liliya Filipishyna, Viktoriia Udovychenko, Halyna Kryshtal and Yaroslav Gontaruk

Climate 2025, 13(5), 99; https://doi.org/10.3390/cli13050099 - 11 May 2025

Abstract

Biogas production from agricultural waste reduces methane emissions and addresses climate change challenges by converting livestock and organic waste into energy. This study analyzed biogas production in agricultural enterprises under the European Green Deal, the advantages of biogas as an energy source, and [...] Read more.

Biogas production from agricultural waste reduces methane emissions and addresses climate change challenges by converting livestock and organic waste into energy. This study analyzed biogas production in agricultural enterprises under the European Green Deal, the advantages of biogas as an energy source, and the use of digestate in agriculture. The raw material for biogas production from agro-industrial wastes in Ukraine has been investigated, showing that the country’s biogas production potential amounts to 34.59 billion m³, including 0.65 billion m³ from processing plant wastes. The main types of biomass that can be used for biogas production in Ukraine are crop residues (71.4%), manure (26.6%), and food industry waste (2.0%). The implementation of biogas production projects will reduce greenhouse gas emissions by 3.98 billion tons of CO₂ and increase profits through electricity sales. This study examines the barriers and prospects for the development of electricity generation from biogas in Ukraine in the context of the integration of Ukraine’s energy system into the EU energy space. Directions for developing the biogas industry, focusing on electricity production within the framework of European decarbonization initiatives, will enhance the energy security of Ukraine and the EU. Estimating the energy production from agricultural waste allows for determining biogas output from organic waste. A regional biogas cluster model was developed based on the agro-industrial complex, which combines the production of biogas, electricity, water, and biofertilizers with increased efficiency and regional sustainable development. Full article

► Show Figures

Figure 1

24 pages, 1725 KiB

Open AccessArticle

How Do Climate Concerns and Value Orientation Among Bankers Influence Agricultural Financing and Development?

by Khatun Mst Asma, Md Rony Masud and Koji Kotani

Climate 2025, 13(5), 98; https://doi.org/10.3390/cli13050098 - 9 May 2025

Abstract

Agricultural financing is crucial for economic development and sustainability. However, little is known about how bankers’ concerns about climate change influence their decision-making for agricultural financing and development and how these concerns are related to possible future performance. This study investigates a research [...] Read more.

Agricultural financing is crucial for economic development and sustainability. However, little is known about how bankers’ concerns about climate change influence their decision-making for agricultural financing and development and how these concerns are related to possible future performance. This study investigates a research question “how do bankers’ climate concerns and value orientation influence agricultural financing and development?” and the hypotheses “bankers’ climate concerns are negatively related to agricultural financing and development, whereas their value orientation for future generations is positively associated with these endeavors”. We conduct questionnaire surveys and collect data on climate concerns, prosocial attitude for future generations and sociodemographic & bank related information from 596 bankers at three areas in Bangladesh. The results reveal three main findings. First, bankers who have high levels of climate concerns tend to be less optimistic about agricultural financing and development. Second, bankers who live in high climate-change areas tend to have more severe climate concerns and darker prospectives in agricultural financing and development than those in low climate-change areas. Third, bankers who have a high value orientation for future generations are likely to be positive about future agricultural financing and development. Overall, our findings suggest that future agricultural financing and development shall be discouraged as climate change becomes severe, hitting low-land areas, such as Bangladesh, through the lens of bankers’ perceptions, unless the bankers possess high concerns for future generations. To counter such negative possibilities, a new agricultural financing scheme, such as “agricultural green banking”, shall be necessary to implement. Full article

(This article belongs to the Section Climate and Economics)

► Show Figures

Figure 1

12 pages, 4286 KiB

Open AccessArticle

El Niño Magnitude and Western Pacific Warm Pool Displacement. Part II: Future Changes Under Global Warming

by Zhuoxin Gu and De-Zheng Sun

Climate 2025, 13(5), 97; https://doi.org/10.3390/cli13050097 - 9 May 2025

Abstract

Observations reveal a strong correlation between the magnitude of El Niño and the displacement of the eastern edge of the western Pacific warm pool (WPWP). In Part I, this relationship was examined in the Coupled Model Intercomparison Project Phase 6 (CMIP6) models using [...] Read more.

Observations reveal a strong correlation between the magnitude of El Niño and the displacement of the eastern edge of the western Pacific warm pool (WPWP). In Part I, this relationship was examined in the Coupled Model Intercomparison Project Phase 6 (CMIP6) models using their historical simulations, and it was found to be comparable to that in the observations. The present study extends the analysis to future projections under two Shared Socioeconomic Pathway (SSP) scenarios—SSP245 and SSP585—to assess whether this strong relationship persists under global warming. It is found that El Niño magnitude and WPWP boundary displacement in most models under global warming are as strongly correlated as in the observations and their historical simulations. Moreover, most models project that stronger El Niño events will be accompanied by a greater eastward displacement of the WPWP boundary. For models with a positive response, the ensemble projects an increase in El Niño magnitude of 0.21 ± 0.03 °C (0.20 ± 0.03 °C) under the SSP245 (SSP585) scenario, accompanied by an eastward displacement of the WPWP by 11.7 ± 1.3° (11.1 ± 1.0°) in longitude. These results further support the notion that El Niño is a consequence of the eastward extension of the WPWP. Full article

(This article belongs to the Special Issue The Dynamics and Impacts of Ocean-Atmosphere Coupling on Regional and Global Climate)

► Show Figures

Figure 1

27 pages, 11799 KiB

Open AccessArticle

Developing Low-Carbon Pathways for the Transport Sector in Ethiopia

by Obiora A. Nnene, Dereje Senshaw, Mark Zuidgeest, Owen Mwaura and Yizengaw Yitayih

Climate 2025, 13(5), 96; https://doi.org/10.3390/cli13050096 - 6 May 2025

Abstract

This paper discusses the development of baseline and mitigation scenarios to guide the creation of a long-term plan supporting low-carbon transport in Ethiopia. Developing this method involved comprehensively reviewing policy documents, collecting historical activity data, and modelling the baseline and mitigation scenarios. The [...] Read more.

This paper discusses the development of baseline and mitigation scenarios to guide the creation of a long-term plan supporting low-carbon transport in Ethiopia. Developing this method involved comprehensively reviewing policy documents, collecting historical activity data, and modelling the baseline and mitigation scenarios. The paper emphasises the importance of stakeholder engagement, which is instrumental in validating the model inputs, policy targets, and results at each stage, ensuring the credibility and robustness of our findings. The scenario development and analysis are based on the IPCC guidelines, informed by the policies of the Government of Ethiopia, and implemented with the Low-Energy Analysis Platform (LEAP). Three net-zero scenarios are assessed for the time horizon between 2020 to 2050. The so-called maximum ambition, NDC-aligned, and late action scenarios reflect the energy requirements and emissions contribution for varying levels of government ambition towards low-carbon interventions in the transport sector. In the baseline scenario, the total amount of carbon emissions is estimated at 4.81 million tonnes of CO₂e in 2020, which is projected to increase to over 15 million tonnes by 2050. Under the mitigation scenarios, significant reductions are projected, with specific interventions like electrification in road freight reducing emissions by 9.68 MtCO₂e and expanding rail transport reducing 9.95 MtCO₂e by 2050 compared to the baseline. Other strategies identified for mitigating transport sector emissions, like improving energy efficiency, encouraging mass transit and non-motorised transport, show good potential for achieving a greener future. With the transport sector in Ethiopia identified as a major contributor to GHG emissions and climate change, this paper underscores the government’s efforts to ensure the long-term sustainability of its transport sector. Full article

(This article belongs to the Special Issue Climate Change and Transport)

► Show Figures

Figure 1

38 pages, 2567 KiB

Open AccessArticle

Improving Daily CMIP6 Precipitation in Southern Africa Through Bias Correction—Part 1: Spatiotemporal Characteristics

by Amarech Alebie Addisuu, Gizaw Mengistu Tsidu and Lenyeletse Vincent Basupi

Climate 2025, 13(5), 95; https://doi.org/10.3390/cli13050095 - 4 May 2025

Cited by 1

Abstract

Impact models used in water, ecology, and agriculture require accurate climatic data to simulate observed impacts. Some of these models emphasize the distribution of precipitation within a month or season rather than the overall amount. To meet this requirement, a study applied three [...] Read more.

Impact models used in water, ecology, and agriculture require accurate climatic data to simulate observed impacts. Some of these models emphasize the distribution of precipitation within a month or season rather than the overall amount. To meet this requirement, a study applied three bias correction techniques—scaled distribution mapping (SDM), quantile distribution mapping (QDM), and QDM with a separate treatment for precipitation below and above the 95th percentile threshold (QDM95)—to daily precipitation data from eleven Coupled Model Intercomparison Project Phase 6 (CMIP6) models, using the Climate Hazards Group Infrared Precipitation with Station version 2 (CHIRPS) as a reference. This study evaluated the performance of all bias-corrected CMIP6 models over Southern Africa from 1982 to 2014 in replicating the spatial and temporal patterns of precipitation across the region against three observational datasets, CHIRPS, the Climatic Research Unit (CRU), and the Global Precipitation Climatology Centre (GPCC), using standard statistical metrics. The results indicate that all bias-corrected precipitation generally performs better than native model precipitation in replicating the observed December–February (DJF) mean and seasonal cycle. The probability density function (PDF) of the bias-corrected regional precipitation indicates that bias correction enhances model performance, particularly for precipitation in the range of 3–35 mm/day. However, both corrected and uncorrected models underestimate higher extremes. The pattern correlations of the bias-corrected precipitation with CHIRPS, the GPCC, and the CRU, as compared to the correlations of native precipitation with the three datasets, have improved from 0.76–0.89 to 0.97–0.99, 0.73–0.87 to 0.94–0.97, and 0.74–0.89 to 0.97–0.99, respectively. Additionally, the Taylor skill scores of the models for replicating the CHIRPS, GPCC, and CRU precipitation spatial patterns over Southern Africa have improved from 0.57–0.80 to 0.79–0.95, 0.55–0.76 to 0.80–0.91, and 0.54–0.75 to 0.81–0.91, respectively. Overall, among the three bias correction techniques, QDM consistently demonstrated better performance than both QDM95 and SDM across various metrics. The implementation of distribution-based bias correction resulted in a significant reduction in bias and improved the spatial consistency between models and observations over the region. Full article

► Show Figures

Figure 1

22 pages, 2060 KiB

Open AccessArticle

Extreme Weather Shocks and Crime: Empirical Evidence from China and Policy Recommendations

by Huaxing Lin and Ping Jiang

Climate 2025, 13(5), 94; https://doi.org/10.3390/cli13050094 - 3 May 2025

Abstract

Rising global temperatures and increasing extreme weather events pose challenges to social stability and public security. This study examines the relationship between extreme weather and crime in China using fixed-effects quasi-Poisson and negative binomial regression models, along with a generalized additive model to [...] Read more.

Rising global temperatures and increasing extreme weather events pose challenges to social stability and public security. This study examines the relationship between extreme weather and crime in China using fixed-effects quasi-Poisson and negative binomial regression models, along with a generalized additive model to explore nonlinear effects. The results show that extreme heat significantly increases crime, following an “S” shaped pattern. This intense heat heightens emotional instability and impulsivity, leading to a crime surge. While moderate heat reduces crime, extreme cold and heavy rainfall have no significant effects. These findings highlight the need for stratified policy interventions. Based on empirical evidence, this study proposes three key recommendations: (1) developing a weather warning and public security risk coordination system, (2) promoting community-based crime prevention through mutual assistance networks and infrastructure improvements, and (3) enhancing psychological interventions to mitigate mental health challenges linked to extreme weather. Integrating meteorological data, law enforcement, and interventions to help potential perpetrators can strengthen urban resilience and public safety against climate-induced crime risks. Full article

► Show Figures

Figure 1

30 pages, 2710 KiB

Open AccessArticle

Improving Daily CMIP6 Precipitation in Southern Africa Through Bias Correction— Part 2: Representation of Extreme Precipitation

by Amarech Alebie Addisuu, Gizaw Mengistu Tsidu and Lenyeletse Vincent Basupi

Climate 2025, 13(5), 93; https://doi.org/10.3390/cli13050093 - 2 May 2025

Abstract

Accurate simulation of extreme precipitation events is crucial for managing climate-vulnerable sectors in Southern Africa, as such events directly impact agriculture, water resources, and disaster preparedness. However, global climate models frequently struggle to capture these phenomena, which limits their practical applicability. This study [...] Read more.

Accurate simulation of extreme precipitation events is crucial for managing climate-vulnerable sectors in Southern Africa, as such events directly impact agriculture, water resources, and disaster preparedness. However, global climate models frequently struggle to capture these phenomena, which limits their practical applicability. This study investigates the effectiveness of three bias correction techniques—scaled distribution mapping (SDM), quantile distribution mapping (QDM), and QDM with a focus on precipitation above and below the 95th percentile (QDM95)—and the daily precipitation outputs from 11 Coupled Model Intercomparison Project Phase 6 (CMIP6) models. The Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) dataset was served as a reference. The bias-corrected and native models were evaluated against three observational datasets—the CHIRPS, Multi-Source Weighted Ensemble Precipitation (MSWEP), and Global Precipitation Climatology Center (GPCC) datasets—for the period of 1982–2014, focusing on the December-January-February season. The ability of the models to generate eight extreme precipitation indices developed by the Expert Team on Climate Change Detection and Indices (ETCCDI) was evaluated. The results show that the native and bias-corrected models captured similar spatial patterns of extreme precipitation, but there were significant changes in the amount of extreme precipitation episodes. While bias correction generally improved the spatial representation of extreme precipitation, its effectiveness varied depending on the reference dataset used, particularly for the maximum one-day precipitation (Rx1day), consecutive wet days (CWD), consecutive dry days (CDD), extremely wet days (R95p), and simple daily intensity index (SDII). In contrast, the total rain days (RR1), heavy precipitation days (R10mm), and extremely heavy precipitation days (R20mm) showed consistent improvement across all observations. All three bias correction techniques enhanced the accuracy of the models across all extreme indices, as demonstrated by higher pattern correlation coefficients, improved Taylor skill scores (TSSs), reduced root mean square errors, and fewer biases. The ranking of models using the comprehensive rating index (CRI) indicates that no single model consistently outperformed the others across all bias-corrected techniques relative to the CHIRPS, GPCC, and MSWEP datasets. Among the three bias correction methods, SDM and QDM95 outperformed QDM for a variety of criteria. Among the bias-corrected strategies, the best-performing models were EC-Earth3-Veg, EC-Earth3, MRI-ESM2, and the multi-model ensemble (MME). These findings demonstrate the efficiency of bias correction in improving the modeling of precipitation extremes in Southern Africa, ultimately boosting climate impact assessments. Full article

► Show Figures

Figure 1

21 pages, 10225 KiB

Open AccessArticle

Exploring Socio-Spatial Inequalities in Flood Response Using Flood Simulation and Social Media Data: A Case Study of 2020 Flood in Nanjing, China

by Yi Chen, Yang Zhang, Dekai Tao, Wenjie Zhang, Jingxian You, Yuan Li, Yong Lei and Yao Meng

Climate 2025, 13(5), 92; https://doi.org/10.3390/cli13050092 - 30 Apr 2025

Abstract

Identifying socio-spatial inequalities in flood resilience is crucial for effective disaster risk management. This study integrates flood susceptibility simulations and Weibo activity data to construct a flood susceptibility index and incorporates socio-spatial differentiation to represent residents’ coping capacities. By combining flood risk awareness [...] Read more.

Identifying socio-spatial inequalities in flood resilience is crucial for effective disaster risk management. This study integrates flood susceptibility simulations and Weibo activity data to construct a flood susceptibility index and incorporates socio-spatial differentiation to represent residents’ coping capacities. By combining flood risk awareness and coping capacity, we develop a comprehensive flood response capability model to examine the spatial patterns of flood resilience inequality. The findings reveal that (1) high flood risk awareness is concentrated near the Yangtze River and major lakes based on social media data and simulations; (2) coping capacity to floods exhibits a central–periphery pattern, with higher resilience in urban centers and gradually decreases gradually to the suburban and exurban areas; (3) communities are classified into four types based on the combination of flood risk awareness and coping capacities. Multiple linear regression analysis indicates that both natural and social factors significantly influence flood response capacity. This research provides critical insights into the spatial patterns of flood resilience, offering valuable guidance for formulating targeted adaptation strategies. Full article

► Show Figures

Figure 1

23 pages, 5566 KiB

Open AccessArticle

The Impact of Beach Wrack on Greenhouse Gas Emissions from Coastal Soils

by Olga Nesterova, Mariia Bovsun, Andrei Egorin, Andrey Yatsuk, Dmitry Kravchenko, Irina Lisina, Igor Stepochkin and Anastasia Brikmans

Climate 2025, 13(5), 91; https://doi.org/10.3390/cli13050091 - 30 Apr 2025

Abstract

The existing management strategies of macrophyte beach wrack are not always environmentally sound. In this study, we tried to assess the impact of the presence or absence of macrophyte beach wrack on the CO₂ flux and the possibility of creating an environmentally [...] Read more.

The existing management strategies of macrophyte beach wrack are not always environmentally sound. In this study, we tried to assess the impact of the presence or absence of macrophyte beach wrack on the CO₂ flux and the possibility of creating an environmentally sound recycling of macrophyte beach wrack based on their removal from the beach and processing into biochar. The study was conducted on the coast of the Sea of Japan in the bay of Kievka. The Picarro G4301 portable laser gas analyzer was used to measure CO₂ fluxes in areas with and without macrophyte beach wrack. The CO₂ flux was 23 times higher at plots with macrophyte beach wrack, compared with plots without macrophyte beach wrack. In the plots after manual removal of the macrophyte beach wrack, on average, there was a 1.6-fold decrease in flow values compared to the plots with the macrophyte beach wrack. Considering the frequency of emissions in the study area, which is associated with frequent cyclones and storms, it is possible to organize the systematic cleaning of macrophyte beach wrack for the production of biochar. Creating projects based on the conversion of macrophyte beach wrack into biochar can have both environmental and economic benefits. The environmental benefits include the reduction of CO₂ flux at plots after manual removal of macrophyte beach wrack; the long-term storage of carbon from macrophyte beach wrack biomass in the form of biochar; and the reduction of CO₂ flux from soils (carbon sequestration) with the correct technology of introducing biochar into the soil. However, for a more accurate assessment, monitoring seasonal measurements and economic calculations of the entire technological chain of production, risks, and footprint are necessary. Full article

(This article belongs to the Special Issue Coastal Hazards under Climate Change)

► Show Figures

Figure 1

27 pages, 800 KiB

Open AccessArticle

Socio-Economic Determinants of Climate Change Adaptation Strategies Among Smallholder Farmers in Mbombela: A Binary Logistic Regression Analysis

by Thando Dyanty, Isaac Azikiwe Agholor, Tapelo Blessing Nkambule, Andries Agrippa Nkuna, Mzwakhe Nkosi, Shalia Matilda Ndlovu, Jabulani Johannes Mokoena, Pretty Nombulelo Nkosi, Nombuso Precious Nkosi and Thulasizwe Hopewell Makhubu

Climate 2025, 13(5), 90; https://doi.org/10.3390/cli13050090 - 29 Apr 2025

Abstract

Climate change poses significant challenges to smallholder farmers, particularly in sub-Saharan Africa, where agriculture is highly vulnerable to changing climatic conditions. This study examines the socioeconomic determinants influencing the adoption of strategies for adapting to climate change among smallholder farmers in Mbombela, South [...] Read more.

Climate change poses significant challenges to smallholder farmers, particularly in sub-Saharan Africa, where agriculture is highly vulnerable to changing climatic conditions. This study examines the socioeconomic determinants influencing the adoption of strategies for adapting to climate change among smallholder farmers in Mbombela, South Africa. A quantitative research approach was employed, using structured questionnaires to collect data from 308 randomly selected smallholder farmers. Furthermore, the study utilised binary logistic regression to analyse the relationship between socioeconomic factors and the adoption of adaptation strategies. The results revealed that gender, age, income sources, access to climate information, and cooperative membership significantly influenced farmers’ adoption of adaptation strategies. Findings further showed that female farmers, older farmers, and those relying solely on farming income were less likely to adopt adaptation strategies, while younger farmers and those with diversified income sources were more likely to embrace adaptation strategies. Moreover, the study found that access to climate information and cooperative membership were negatively associated with the adoption of adaptation strategies. This negative association may be attributed to inefficiencies in current information dissemination, where climate-related information may not be tailored to the specific needs of farmers, or to cooperative structures that may not effectively facilitate knowledge sharing or collective action. The study concludes that targeted interventions, such as gender-sensitive policies, livelihood diversification, improved extension services, and strengthened cooperative structures, are essential to enhance smallholder farmers’ adaptive capacity. Full article

(This article belongs to the Section Climate Adaptation and Mitigation)

► Show Figures

Figure 1

22 pages, 4743 KiB

Open AccessArticle

Spatiotemporal Analysis of Urban Heat Islands in Kisangani City Using MODIS Imagery: Exploring Interactions with Urban–Rural Gradient, Building Volume Density, and Vegetation Effects

by Julien Bwazani Balandi, Trésor Mbavumoja Selemani, Jean-Pierre Pitchou Meniko To Hulu, Kouagou Raoul Sambieni, Yannick Useni Sikuzani, Jean-François Bastin, Prisca Tshomba Wola, Jacques Elangilangi Molo, Joël Mobunda Tiko, Bill Mahougnon Agassounon and Jan Bogaert

Climate 2025, 13(5), 89; https://doi.org/10.3390/cli13050089 - 29 Apr 2025

Abstract

The urban heat island (UHI) effect has emerged in the literature as a major challenge to urban well-being, primarily driven by increasing urbanization. To address this challenge, this study investigates the spatiotemporal pattern of the UHI in the fast-growing city of Kisangani and [...] Read more.

The urban heat island (UHI) effect has emerged in the literature as a major challenge to urban well-being, primarily driven by increasing urbanization. To address this challenge, this study investigates the spatiotemporal pattern of the UHI in the fast-growing city of Kisangani and within its urban–rural gradient from 2000 to 2024 using land surface temperature (LST) data from the MODIS 11A2 V6.1 product. Inferential and descriptive statistics were applied to examine the patterns of UHI and the relationships between the LST, building volume density (BVD), and vegetation density expressed by the Normalized Difference Vegetation Index (NDVI). The results showed that the spatial extent of the moderate UHI gradually increased from 16 km² to 38 km², while the high UHI increased from 9 km² to 19 km². Furthermore, although high UHI values (0.2 < UHI ≤ 0.3) are observed in urban areas and significant differences in UHI variations are detected across urban, peri-urban, and rural zones, the results indicate that the mean UHI in Kisangani’s urban areas remains below 0.2. Therefore, based on average UHI variations, Kisangani’s urban zones exhibit moderate disparities in LST compared to rural areas. Moreover, the LST variations significantly correlate with the building volume and vegetation densities. However, the influence of vegetation density as a predictor of LST gradually decreases while the influence of building volume density increases over time, suggesting the need to implement a synergistic development pathway to manage the interactions between urbanization, landscape change, and ecosystem service provision. This integrated approach may represent a crucial solution for mitigating the UHI effect in regions categorized as high-temperature zones. Full article

(This article belongs to the Special Issue Climate Change—Achieving the UN Sustainable Development Goals in Urban Contexts)

► Show Figures

Figure 1

36 pages, 375 KiB

Open AccessReview

Barriers, Opportunities, and Best Practices for Corporate Climate Transition Plans: A Literature Review

by Daniel Kouloukoui, Nathalie de Marcellis-Warin and Thierry Warin

Climate 2025, 13(5), 88; https://doi.org/10.3390/cli13050088 - 29 Apr 2025

Abstract

Corporate climate transition is one of the greatest challenges and opportunities of the 21st century, shaping the future of business sustainability and aligning economic growth with global environmental goals. This article aims to identify the main barriers, opportunities, and best practices associated with [...] Read more.

Corporate climate transition is one of the greatest challenges and opportunities of the 21st century, shaping the future of business sustainability and aligning economic growth with global environmental goals. This article aims to identify the main barriers, opportunities, and best practices associated with the implementation of corporate climate transition plans. Based on a review of studies from leading databases—Scopus, Web of Science, ScienceDirect, and Google Scholar—the research categorizes barriers into economic, financial, political, regulatory, cultural, organizational, and technological dimensions. Opportunities are grouped into areas like sustainable finance, technological innovation, and resilience building. Best practices are organized into clusters, notably governance, energy efficiency, social equity, and just transition frameworks. In addition to advancing academic understanding, this study offers practical implications for key stakeholders. Financial institutions can use these findings to develop climate-aligned financial products tailored to corporate realities. Policymakers can improve regulatory frameworks to foster sustainable business practices and remove legislative barriers. Companies are empowered to refine their climate strategies, address operational constraints, and explore new sustainability-driven opportunities. By integrating scientific insights with real-world applicability, this review contributes to a more holistic understanding of corporate climate transition, bridging academic research with actionable pathways for businesses, financial actors, and public decision-makers. Full article

(This article belongs to the Section Climate Adaptation and Mitigation)

24 pages, 4408 KiB

Open AccessArticle

Impacts of Urban Morphology on Micrometeorological Parameters and Cyclonic Phenomena in Northern Colombian Caribbean

by Raúl Pérez-Arévalo, Juan E. Jiménez-Caldera, José Luis Serrano-Montes, Jesús Rodrigo-Comino, Juan Carlos Ortiz Royero and Andrés Caballero-Calvo

Climate 2025, 13(5), 87; https://doi.org/10.3390/cli13050087 - 29 Apr 2025

Abstract

The rapid urbanization processes across the world can be considered one of the most influential factors in climate change, particularly in metropolitan areas. In South America, the growing population and recurrent non-sustainable or controlled urban land management plans are even increasing the negative [...] Read more.

The rapid urbanization processes across the world can be considered one of the most influential factors in climate change, particularly in metropolitan areas. In South America, the growing population and recurrent non-sustainable or controlled urban land management plans are even increasing the negative consequences of urban heat islands. As a representative case study, Soledad in northern Colombia is an area with recurrent strong wind events, which have caused significant damage to property and human lives, conditioning urban plans. This research aimed to assess the micrometeorological conditions in areas of Soledad, where cyclonic events are highly frequent, to gather essential data on urban planning to understand microclimate changes. We conducted in situ measurements of air temperature, surface temperature, wind speed, relative humidity, and atmospheric pressure across different Local Climate Zones (LCZs). Data were analyzed to assess the impact of urban form, vegetation, and sky openness on microclimatic variations. Our results demonstrated that urban morphology, vegetation cover, and sky openness significantly influenced local microclimates, with lower Sky View Factor (SVF) and higher Leaf Area Index (LAI) values contributing to reduced temperatures and improved airflow. Areas with denser urban canyons exhibited higher temperatures and lower wind speeds, emphasizing the need for strategic urban planning to mitigate heat stress and enhance ventilation. Full article

► Show Figures

Figure 1

15 pages, 3465 KiB

Open AccessArticle

Wind and Humidity Nexus over Uganda in the Context of Past and Future Climate Volatility

by Ronald Ssembajwe, Amina Twah, Rhoda Nakabugo, Sharif Katende, Catherine Mulinde, Saul D. Ddumba, Yazidhi Bamutaze and Mihai Voda

Climate 2025, 13(5), 86; https://doi.org/10.3390/cli13050086 - 29 Apr 2025

Abstract

Wind and humidity are two very vital climate variables that have received little attention by researchers regarding Uganda. This study sought to close this knowledge gap by exposing the dynamics and relationship of windspeed and humidity in Uganda from 1980 to 2023 as [...] Read more.

Wind and humidity are two very vital climate variables that have received little attention by researchers regarding Uganda. This study sought to close this knowledge gap by exposing the dynamics and relationship of windspeed and humidity in Uganda from 1980 to 2023 as well as predicting the future trends from 2025 to 2040. Using high-resolution gridded windspeed and relative humidity (RH) data for the past and seven downscaled and bias-adjusted global climate models within the coupled model intercomparison project phase 6 framework under two shared socioeconomic pathways (SSPs), SPP245 and SSP585, we employed variability, trend, and correlational analyses to expose the wind–humidity nexus at a monthly scale. The results showed a domination of winds of the calm to gentle breeze category across the country, with a maximum magnitude of 6 knots centered over eastern Lake Victoria and eastern Uganda over the historical period. RH was characterized by high to very high magnitudes, except the northern tips of the country, where RH was low for the historical period. Seasonally, both windspeed and RH demonstrated modest variations, with June–July–August (JJA) and September–October–November (SON) having the highest magnitudes, respectively. Similarly, both variables are forecasted to have significant distribution and magnitude changes. For example, windspeeds will be dominated by decreasing trends, while RH will be dominated by increasing trends. Finally, the correlation analysis revealed a strong negative correlation between windspeeds and RH for both the past and future periods, except for the March–April–May (MAM) and September–October–November (SON) seasons, where positive correlations were observed. These findings have practical applications in agriculture, hydrology, thermal comfort, disaster management, and forecasting, especially in the northern, eastern, and Lake Victoria basin regions. The study recommends further finer-scale research at various atmospheric levels and for prolonged future periods and scenarios. Full article

(This article belongs to the Section Climate Dynamics and Modelling)

► Show Figures

Figure 1

Journal Description

Climate

Latest Articles

Journal Menu

Journal Browser

Highly Accessed Articles

Latest Books

E-Mail Alert

News

Topics

Conferences

Special Issues

Topical Collections

Further Information

Guidelines

MDPI Initiatives

Follow MDPI