Search Results (181)

In a warming climate, rising temperature are expected to influence atmospheric humidity. This study examined the spatio-temporal dynamics of temperature (TEMP) and relative humidity (RH) across Equatorial Africa from 1980 to 2020. The analysis used RH data from European Centre of Medium-range Weather Forecasts Reanalysis v.5 (ERA5) reanalysis, TEMP and precipitation (PRE) from Climate Research Unit (CRU), and soil moisture (SM) and evapotranspiration (ET) from the Global Land Evaporation Amsterdam Model (GLEAM). In addition, four teleconnection indices were considered: El Niño-Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), North Atlantic Oscillation (NAO), and Pacific Decadal Oscillation (PDO). This study used the Mann–Kendall test and Sen’s slope estimator to analyze trends, alongside multiple linear regression to investigate the relationships between TEMP, RH, and key climatic variables—namely evapotranspiration (ET), soil moisture (SM), and precipitation (PRE)—as well as large-scale teleconnection indices (e.g., IOD, ENSO, PDO, and NAO) on annual and seasonal scales. The key findings are as follows: (1) mean annual TEMP exceeding 30 °C and RH less than 30% were concentrated in arid regions of the Sahelian–Sudano belt in West Africa (WAF), Central Africa (CAF) and North East Africa (NEAF). Semi-arid regions in the Sahelian–Guinean belt recorded moderate TEMP (25–30 °C) and RH (30–60%), while the Guinean coastal belt and Congo Basin experienced cooler, more humid conditions (TEMP < 20 °C, RH (60–90%). (2) Trend analysis using Mann–Kendal and Sen slope estimator analysis revealed spatial heterogeneity, with increasing TEMP and deceasing RH trends varying by region and season. (3) The warming rate was higher in arid and semi-arid areas, with seasonal rates exceeding annual averages (0.18 °C decade⁻¹). Winter (0.27 °C decade⁻¹) and spring (0.20 °C decade⁻¹) exhibited the strongest warming, followed by autumn (0.18 °C decade⁻¹) and summer (0.10 °C decade⁻¹). (4) RH trends showed stronger seasonal decline compared to annual changes, with reduction ranging from 5 to 10% per decade in certain seasons, and about 2% per decade annually. (5) Pearson correlation analysis demonstrated a strong negative relationship between TEMP and RH with a correlation coefficient of r = − 0.60. (6) Significant associations were also observed between TEMP/RH and both climatic variables (ET, SM, PRE) and large scale-teleconnection indices (ENSO, IOD, PDO, NAO), indicating that surface conditions may reflect a combination of local response and remote climate influences. However, further analysis is needed to distinguish the extent to which local variability is independently driven versus being a response to large-scale forcing. Overall, this research highlights the physical mechanism linking TEMP and RH trends and their climatic drivers, offering insights into how these changes may impact different ecological and socio-economic sectors. Full article

The intensive use of nitrogen (N) fertilizers in maize (Zea mays L.) cropping in sub-Saharan Africa (SSA) contributes significantly to nitrous oxide (N₂O) emissions. Due to limited data on emissions and emission factors (EFs) in SSA, this study investigates GHG emissions and proposes EFs under different fertilization regimes in maize cropping in Burkina Faso (West Africa). A randomized complete block design was used with five treatments: (i) control: no fertilizer (CK), (ii) cattle manure (M), (iii) chemical fertilizer (NPK), (iv) a combination of chemical fertilizer and cattle manure (NPKM) at the national recommended rate, and (v) farmers’ practices, which involve chemical fertilizer combined with manure at the farmers’ rate (NPKM+). Cumulative N₂O emissions varied significantly among treatments (p < 0.05), with the highest under NPKM (2.86 kg N₂O-N ha⁻¹) and the lowest under CK (1.93 ± 0.11 kg N₂O-N ha⁻¹). NPKM also showed the highest methane (CH₄) uptake (−0.62 kg CH₄-C ha⁻¹; p < 0.001), while CK exhibited an increasing trend (0.74 kg CH₄-C ha⁻¹). The highest N₂O EF was recorded for NPK (0.37 ± 0.05%), 63% lower than the Intergovernmental Panel on Climate Change default value. Although NPKM treatment resulted in the highest global warming potential and maize yield, it also achieved the lowest greenhouse gas intensity per unit of yield, highlighting a more efficient trade-off between productivity and climate impact with nitrogen fertilizer use. NPKM+ was the most effective in maintaining high maize productivity with lower yield-scaled N₂O emissions and GHG intensity. These findings suggest that an integrated approach combining organic and inorganic fertilizers can mitigate soil GHG emissions. Further research is needed to refine climate-smart fertilizer combinations for sustainable maize production in SSA. Full article

Sorghum (Sorghum bicolor, (L.) Moench.), is one of the most important cereals in semi-arid and subtropical regions of Africa. However, in these regions, sorghum cultivation is often faced with several constraints. In Mali, terminal or post-flowering drought, caused by the early cessation of rains towards the end of the rainy season, is one of the most common constraints. Sorghum is generally adapted to harsh conditions. However, drought combined to heat reduce its yield and production in tropical and subtropical regions. To identify parents of sorghum hybrids tolerant to post-flowering drought for commercial hybrids development and deployment, a total of 200 genotypes, including male and female parents of the hybrids, were evaluated in 2022 by lysimeters under two water regimes, well-irrigated and water-stressed, at ICRISAT in Niger. Agronomic traits such as phenological stages, physiological traits including transpiration efficiency, and morphological traits such as green leaf number were recorded. Genotype × environment (G × E) interaction was significant for harvest index (HI), green leaf number (GLN), and transpiration efficiency (TE), indicating different responses of genotypes under varying water conditions. Transpiration efficiency (TE) was significantly and positively correlated with total biomass (BT), harvest index (HI), and grain weight (GW) under both stress conditions. Genotypes ICSV216094, ICSB293, ICSV1049, ICSV1460016, and ICSV216074 performed better under optimal and stress conditions. The Principal Component Analysis (PCA) results led to the identification of three groups of genotypes. The Groups 1 and 3 are characterized by their yield stability and better performance under stress and optimal conditions. These two groups could be used by breeding programs to develop high yield and drought tolerant hybrids. Full article

Flood risk mapping is spreading in the Global South due to the availability of high-resolution/high-frequency satellite imagery, volunteered geographic information, and hydraulic models. However, these maps are increasingly generated without the participation of exposed communities, contrary to the Sendai Framework for Disaster Risk Reduction 2015–2030 priorities. As a result, the understanding of risk is limited. This study aims to map flood risk with citizen science complemented by hydrology, geomatics, and spatial planning. The Niger River floods of 2024–2025 on a 113 km² area upstream of Niamey are investigated. The novelty of the work is the integration of local and technical knowledge in the micro-mapping of risk in a large area. We consider risk the product of a hazard and damage in monetary terms. Focus groups in flooded municipalities, interviews with irrigation perimeter managers, and statistical river flow and rainfall analysis identified the hazard. The flood plain was extracted from Sentinel-2 images using MNDWI and validated with ground control points. Six classes of assets were identified by visual photo interpretation of very high-resolution satellite imagery. Damage was ascertained through interviews with a sample of farmers. The floods of 2024–2025 may occur again in the next 12–19 years. Farmers cannot crop safer sites, raising significant environmental justice issues. Damage depends on the strength of the levees, the crop, and the season. From January to February, horticulture is at a higher risk. Flooding does not bring benefits. Risk maps highlight hot spots, are validated, and can be linked to observed flood levels. Full article

This study evaluates the techno-economic feasibility of solar-based green hydrogen potential for off-grid and utility-scale systems in Niger. The geospatial approach is first employed to identify the area available for green hydrogen production based on environmental and socio-technical constraints. Second, we evaluate the potential of green hydrogen production using a geographic information system (GIS) tool, followed by an economic analysis of the levelized cost of hydrogen (LCOH) for alkaline and proton exchange membrane (PEM) water electrolyzers using fresh and desalinated water. The results show that the electricity generation potential is 311,617 TWh/year and 353,166 TWh/year for off-grid and utility-scale systems. The hydrogen potential using PEM (alkaline) water electrolyzers is calculated to be 5932 Mt/year and 6723 Mt/year (5694 Mt/year and 6454 Mt/year) for off-grid and utility-scale systems, respectively. The LCOH production potential decreases for PEM and alkaline water electrolyzers by 2030, ranging between 4.72–5.99 EUR/kgH₂ and 5.05–6.37 EUR/kgH₂ for off-grid and 4.09–5.21 EUR/kgH₂ and 4.22–5.4 EUR/kgH₂ for utility-scale systems. Full article

Weather and climate forecasting, using climate models, have become essential tools and life-savers in the West African region; in spite of the fact that climate models do not fully comply with attributes of forecast qualities—RASAP: reliability, association, skill, accuracy, and precision. The objective of this paper is to quantitatively evaluate, in comparison to CRU and ERA5 datasets, the RASAP compliance-level of the weather@home2 modeling system (w@h2). Findings from some statistical evaluations show that, to a moderately significant extent, w@h2 model provides useful information during the monsoon seasons; skills to capture the Little Dry Season over the Guinea zone; predictive skills for the onset season; ability to reproduce all the annual characteristics of the surface maximum air temperature over the region; as well as skill to detect heat waves that usually ravage West Africa during the boreal spring. The model displays traces of attributes that are needed for seasonal climate predictions and applications. Deficiencies in the quantitative reproducibility point to the facts that the model does provide a reliability akin to that of regional climate models. This paper further furnishes a prospective user with information on whether the model might be “useful or not” for a particular application. Full article

Although sweet potato (Ipomoea batatas) is gaining importance in West Africa, it remains uncertain whether the research is adequately advanced to support the promotion of this crop in the region. Consequently, this systematic review of 125 articles provides a detailed overview of studies focused on sweet potatoes in West Africa. The paper explores various bibliometrics, the research geographic spread, and the topics discussed (e.g., food security and nutrition, climate resilience, livelihoods). The study indicates that sweet potato has the potential to address multiple issues in West Africa, including food and nutrition insecurity (especially micronutrient deficiencies, e.g., vitamin A) as well as poverty. However, it also reveals significant research gaps in terms of geographical and thematic areas. From a geographical perspective, research is primarily conducted in Nigeria and Ghana. From a thematic perspective, there are deficiencies in areas like economics and social sciences, applications in animal husbandry, marketing, use of leaves, irrigation methods, and impacts on climate resilience and livelihoods. There is a pressing need for collaborative research and knowledge exchange among nations to fully realize the potential of sweet potato and develop its value chains to contribute to sustainable socio-economic development across West Africa. Full article

Accurate solar radiation data are crucial for solar energy applications, yet ground-based measurements are limited in many regions. Satellite-derived and reanalysis products offer an alternative, but their accuracy varies across spatial and temporal scales. This study evaluated the performance of four widely used GHI products—CAMS, SARAH-3, ERA5 and MERRA-2—against ground measurements at hourly, daily (summed from hourly) and monthly (averaged from daily) timescales. The analysis also examined how temporal aggregation influenced error characteristics using correlation coefficients, the rMBD, the rRMSD and the combined performance index (CPI). At an hourly scale under clear-sky conditions, satellite products outperformed reanalysis products, with $\mathrm{r}\approx 1$ and ${\mathrm{R}}^2\approx 0.9$ and the rMBD, rRMSD and CPI ranging from 0.1%, 11.4% and 11.8% to −14.7%, 33.3% and 75.1% for CAMS; 0.2%, 11.4% and 10.9% to 13.5%, 22.4% and 120.7% for SARAH-3; −0.2%, 21.6% and 23.8% to 21.5%, 40.9% and 128.8% for MERRA-2; and 0.8%, 14.6% and 16.3% to 22%, 48.2% and 88.3% for ERA5. Under cloudy conditions, all products overestimated GHI, with the rMBD reaching up to 39.7% (SARAH-3), 35.9% (CAMS), 22.9% (MERRA-2) and 28% (ERA5), while the rRMSD exceeded 40% for all. Overcast conditions yielded the poorest performance, with the rMBD ranging from 45.8% to 124.6% and the CPI exceeding 800% in some cases. From the hourly to daily and monthly datasets, aggregation reduced errors for reanalysis products by 5.5% and up to 12.4%, respectively, in clear-sky conditions, but for satellite-based products, deviations slightly increased up to 3.1% for the monthly dataset. Under all-sky conditions, all products showed reductions up to 23%. These results highlight the significant challenges in estimating GHI due to limited knowledge of aerosol and cloud dynamics in the region. They emphasize the need for improved parameterization in models and dedicated measurement campaigns to enhance satellite and reanalysis product accuracy in West Africa. Full article

Background and Objectives: The aims of this study were to assess the impact of smoking on cervical histopathology in women with high-risk HPV types 16 and 18 (the most common types) utilizing comprehensive clinical data and to conduct a risk analysis based on smoking pack-years. Materials and Methods: Between 2022 and 2024, 1048 high-risk HPV-positive women aged 25 to 65 years were categorized into two groups: smokers and non-smokers. Data acquired from a histopathological examination of samples collected during a colposcopic evaluation of these women were compared individually regarding clinical and demographic factors, specifically age, gravida, parity, and alcohol consumption. Subsequently, the impact of prolonged and excessive smoking on histopathological cellular changes was assessed in women with the same characteristics. A case–control study was performed on 312 smokers and 312 non-smokers following mutual matching. Results: The women were matched one-to-one regarding gravida, parity, and alcohol consumption. Subsequently, they were paired within a ±2-year age range. The mean age of the smoker group was 47.1 ± 8.8, while that of the non-smoker group was 47.2 ± 8.5 (p: 0.904). In all cases of high-risk HPV positivity, the rate of normal cervical cytological results was 14% in women who smoked and 29% in women who did not smoke. The LGSIL, HGSIL, ASC-H, and AGC-NOS rates were elevated in the smoker group, and a statistically significant difference was observed between the two groups in terms of abnormal cervical cytological results (p < 0.001). After a colposcopic biopsy, the smoker group exhibited higher rates of HGSILs, LGSILs, AGC-NOS, and CIS pathological lesions (28% vs. 23%), whereas the non-smoker group exhibited higher rates of chronic cervicitis (23% vs. 16%). However, no statistically significant difference was found between the two groups (p: 0.092). In a comparison of endocervical curettage (ECC) samples, it was observed that the HGSIL, CIS, and AGC-FN rates in the smoker group were almost the same as those in the non-smoker group. However, the LGSIL histopathology results (32% vs. 18%) were higher, and the rate of negativity with no pathology was higher in the non-smoker group (72% vs. 59%). A statistically significant difference in ECC histopathology was noted between the two groups (p < 0.001). An ROC analysis conducted between smoking pack-years and the colposcopic and endocervical curettage biopsy results revealed that the cutoff value for the colposcopic abnormal histopathological results increased, with 40% sensitivity and 76% specificity above 20 pack-years (AUC: 0.592 and p: 0.025). Additionally, the abnormal histopathology rates for endocervical curettage exhibited 81% sensitivity and 32% specificity above 13 pack-years (AUC: 0.586 and p: 0.008). The rate of abnormalities in the colposcopic biopsy results was 2.19 times higher for individuals with over 20 pack-years, and the rate of abnormalities in the ECC results was 2.08 times higher for those with over 13 pack-years; additionally, statistically significant results were obtained (p-values of 0.027 and 0.008, respectively). Conclusions: The most important cause of neoplastic changes in the cervix uteri is high-risk HPV infection, with evidence indicating that prolonged excessive smoking significantly exacerbates the persistence and progression of HPV infection, thereby influencing neoplastic changes in the cervix uteri. It is crucial for women to cease smoking in order to eradicate HPV infection from the body. Full article

With the increasing frequency of floods in recent decades, particularly in West Africa, many regions have faced unusual and recurrent flooding events. Communities in flood-prone areas experience heightened insecurity, loss of property, and, in some cases, serious injuries or fatalities. Consequently, flood risk assessment and mitigation have become essential. This comparative study between Niamey and Lokoja employs Geographic Information Systems (GIS) and the Analytical Hierarchy Process (AHP) to delineate flood susceptibility, vulnerability, and risk zones. The study utilized a comprehensive range of thematic layers, with weight percentages assigned to each parameter as follows: 29% for elevation, 24% for slope, 15% for the Topographic Wetness Index (TWI), 9% for drainage density, 9% for distance from rivers, 4% for both precipitation and the Normalized Difference Water Index (NDWI), and 2% each for the Normalized Difference Vegetation Index (NDVI) and soil type. To validate these weightings, a consistency ratio was calculated, ensuring it remained below 10%. The findings reveal that 32% of the Niamey study area is at risk of flooding, compared to approximately 15% in Lokoja. The results highlight a very high flood potential, particularly in areas near the Niger River, with this potential decreasing as elevation increases. Given the current prevalence of extreme weather events in West Africa, it is crucial to employ effective tools to mitigate their adverse impacts. This research will assist decision-makers in quantifying the spatial vulnerability of flood-prone areas and developing effective flood risk assessment and mitigation strategies in the region. Full article

Despite nearly a century of research on water-related issues, water erosion remains one of the greatest threats to soil health and soil ecosystem services around the world. Yet, to date, data on water erosion needed to develop mitigation strategies are scarce, especially in the Sahelian regions. The current study therefore sets out to estimate annual soil losses caused by water erosion and to analyze trends over the period of 1981–2020 in the Mékrou watershed, located in the Middle Niger river sub-basin in West Africa. The Revised Universal Soil Loss Equation, remote sensing, and the Geographic Information System (GIS) were deployed in this study. Several types of data were used, including rainfall data, sourced from meteorological stations and reanalysis datasets, which capture the temporal variability of erosive forces. Soil properties, including texture and organic matter content, were derived from FAO global soil databases to assess soil erodibility. High-resolution digital elevation models (30 m) provided detailed topographic information, crucial for calculating slope length and steepness factors. Land use and land cover data were extracted from satellite imagery, enabling the analysis of vegetation cover and anthropogenic impacts over four decades. By integrating and treating these data, this study reveals that the estimated average annual amount of water erosion in the Mékrou watershed is 6.49 t/ha/yr over 1981–2020. The dynamics of the ten-year average are highly variable, with a minimum of 3.45 t/ha/yr between 1981 and 1990, and a maximum of 8.50 t/ha/yr between 1991 and 2000. Even though these average soil losses in the Mékrou basin are below the tolerable threshold of 10 t/ha/yr, mitigation actions are needed for prevention. In addition, the spatial dynamics of water erosion are noticeably heterogeneous. The study reveals that 72.7% of the surface area of the Mékrou watershed is subject to slight water erosion below the threshold, compared with 27.3%, particularly in the mountainous south-western part, which is subject to intense erosion above the threshold. This research is the first study of soil erosion quantification with the RUSLE method and GIS in the Mékrou watershed, and fills a critical knowledge gap of the water erosion in this watershed, providing insights into erosion dynamics and supporting future sustainable land management strategies in vulnerable Sahelian landscapes. Full article

The use of plants for therapeutic purposes is an ancestral practice that dates back to the earliest times in the history of mankind. Even today the exploitation of plants for medicinal purposes plays a big role for the communities, especially in Africa, despite advances in modern medicine. According to the World Health Organization, about 80% of the population in developing countries use plants for their primary health care. In Niger, the use of medicinal plants is a foundation of traditional medicine across all ages. It remains a very common practice, especially in rural areas. This practice concerns all ages of life, including mother–child care. In infants and young children, mothers use plants as fortifiers for their prophylactic or curative powers, or to facilitate growth and weight gain, and also to fight major causes of infant morbidity and mortality. Mothers also use medicinal plants for their galactogenic power to stimulate lactation. This is even more important in rural areas where breastfeeding is the main source of infant nutrition. Over the years, these medicinal plants have been the subject of chemical and biological investigations to back up their therapeutic potential and virtues. This study aims to summarize current knowledge on the most commonly used medicinal plants in Niger in mother–child care. This helps emphasize the validation of ancestral medicinal plants through the scientific evaluation of the bioactive components and mechanisms. Elements of sustainability are discussed in future developments. Full article

Satellite precipitation estimates are crucial for managing climate-related risks such as droughts and floods. However, these datasets often contain systematic errors due to the observation methods used. The accuracy of these estimates can be enhanced by integrating spatial and temporal resolution data from in situ observations. Nevertheless, the accuracy of the merged dataset is influenced by the density and distribution of rain gauges, which can vary regionally. This paper presents an approach to improve satellite precipitation data (SPD) over Burkina Faso. Two bias correction methods, Empirical Quantile Mapping (EQM) and Time and Space-Variant (TSV), have been applied to the SPD to yield a bias-corrected dataset for the period 1991–2020. The most accurate bias-corrected dataset is then combined with in situ observations using the Regression Kriging (RK) method to produce a merged precipitation dataset. The findings show that both bias correction methods achieve similar reductions in RMS error, with higher correlation coefficients (approximately 0.8–0.9) and a normalized standard deviation closer to 1. However, EQM generally demonstrates more robust and consistent performance, particularly in terms of correlation and RMS error reduction. On a monthly scale, the superiority of EQM is most evident in June, September, and October. Following the merging process, the final dataset, which incorporates satellite information in addition to in situ observations, demonstrates higher performance. It shows improvements in the coefficient of determination by 83%, bias by 11.4%, mean error by 96.7%, and root-mean-square error by 95.5%. The operational implementation of this approach provides substantial support for decision-making in regions heavily reliant on rainfed agriculture and sensitive to climate variability. Delivering more precise and reliable precipitation datasets enables more informed decisions and significantly enhances policy-making processes in the agricultural and water resources sectors of Burkina Faso. Full article