Status of Forest Landscape Restoration in Kenya (Restoration of natural landscapes, to include mining areas, water catchment areas)

• Dr. Benjamin Kinyili (Kenya Forest Service)

Kenya has set an ambitious 15 Billion Tree Growing Strategy for Landscape and Ecosystem Restoration with goals to increase and maintain 30% tree cover by 2032, to restore 10.6 million ha of degraded landscape by 2032 and to reduce 32% of its greenhouse gas emissions by 2030. The Forest Landscape Restoration Implementation Action Plan (FOLAREP) 2022-2026 seeks to restore 2.55 million ha of degraded landscapes through integrated approaches and best practices. Additionally, a multi-stakeholder Technical Working Group on Restoration Monitoring has been convened to support sustainable Forest Landscape Restoration (FLR) efforts in the country. As part of the consultation process, seven engagement forums bringing together national government, all 47 counties, the Council of Governors and development partners were held between December 2021–March 2022. These engagements reveal that Kenya’s top barriers to restoration are financial constraints, inadequate policy and legislative frameworks, low sensitization on FLR, land ownership, and limited human and technical capacity on FLR. The top drivers to degradation are population pressure, poverty, overstocking, encroachment, and overgrazing. County Environment Committees (CECs), which are crucial to mainstreaming FLR at the county level, are active in 18 of the 47 counties. In addition, 25 of 47 counties mention county climate change entities as critical to enhance the CECs’ FLR functions. Top indicators selected by counties as important for a national restoration monitoring system include areas of restored forest and agricultural lands, biodiversity revived and access to safe water. Counties present unique FLR monitoring structures, with some entities and departments such the CECs, the Monitoring and Evaluation Committee and Units featuring structures across several counties.

HARNESSING COMMUNITY TRADITIONAL VALUES FOR ECOSYSTEM PRESERVATION: CASE OF KAPTAGAT FOREST OF ELGEIYO MARAKWET COUNTY OF KENYA. (The effect of culture and religion in climate change adaptation and mitigation)

• Dr (Amb) Joseph Kiplagat (Dept of Mechanical, Production & Energy Engineering, School of Engineering Moi University Eldoret Kenya)

The expansive Kaptagat forest is a scenic landscape of Elgeyo-Marakwet County in Kenya, covering over 6,000 hectares. It is a crucial water catchment area, serving the water needs of Elgeyo-Marakwet County-40% and Uasin Gishu county-55%. Eldoret City gets about 30,000m3/day. However, this forest’s fragile ecosystem is now greatly endangered by climate change and uncontrolled human activities like deforestation, overgrazing and charcoal production. Urgent remedial actions are required for its preservation. Harnessing the traditional values of the local community living next to the forest constitute one unique yet results laden action. The Keiyo History Culture & Heritage Centre: a coming together of community professionals, has initiated a number of activities to tap into this resource. The ages-old community traditional values which include strict adherence to ecosystem preservation have been passed from generation to generation. However, laxity in enforcement of the relevant principles have led to numerous infringements. The Kenya Forest Service and Kaptagat Forest Restoration Editions in collaboration with the local leadership have implemented various mitigative initiatives. One is to set up“cow banks” to keep community livestock in selected guarded spaces. Modern renewable energy technologies are slated for installation, to tap into the forest water streams, the abundant sunlight and strong winds. The Archimedes Screw turbine, which is a cost-effective, robust and simple hydro-power machine is suitable for application at the low-head sites of the rivers. Most households bordering Kaptagat forest, use charcoal and firewood for cooking. An optimized conical solar cooker, has been highly recommended as a viable ecosystem-friendly alternative, to reduce and finally stop use of charcoal and firewood from the forest. Installation of Wind Turbines at the edge of the forest escarpment, is under consideration, to tap the wind energy. Key words: Community, Ecosystem, Renewable Energy, Traditional Values.

LEVERAGING ON WETLAND MONITORING AND MANAGEMENT APP: A CASE OF KINGWAL AND YALA SWAMP AREAS (Management of hydrological systems, to include riparian lands, water towers, water reservoirs, clean rivers and wetlands)

• Kelvin Omieno (Kaimosi Friends University)

ABSTRACT Wetlands play a critical role in biodiversity conservation, water purification, and climate regulation. However, these ecosystems face increasing threats due to human activities, climate change, and inadequate monitoring frameworks. This study explores the development and implementation of a Wetland Monitoring and Management App designed to enhance the conservation and sustainable use of Kingwal and Yala Swamp areas in Kenya. The app leverages emerging technologies such as GIS mapping, remote sensing, IoT sensors, and AI-driven analytics to provide real-time data on wetland health, water levels, biodiversity status, and potential environmental threats. Through stakeholder engagement, including local communities, environmental agencies, and researchers, the app aims to facilitate informed decision-making and improve wetland governance. The study evaluates the effectiveness of the application in monitoring ecosystem changes, enhancing community participation, and supporting policy implementation. The findings underscore the importance of digital solutions in promoting sustainable wetland management and recommend strategies for scaling up technology-driven conservation initiatives. Key words: Wetland monitoring, environmental conservation, GIS, remote sensing, AI analytics, sustainable management, biodiversity conservation.

Modeling Potassium Phosphite Induced Pathogenic tolerance in Tomato plant to Bacterial Infection and Insect Herbivory (Climate change, food security and impact on livelihoods)

• Titus Rotich (Moi University)

Human population in the world is continually soaring high and the impact on the environment has led to global warming and food security issues. Innovation and the use smart technology in agricultural production has led to the mitigation food security issues. This advanced production techniques is not limited to genetic modification, but also encompasses mechanical advancement and investment in laboratory trials for improved varieties of propagative materials, high yields and tolerance to environmental stress and pathogens. Mathematical modelling is not left behind, as an invaluable tool that supplements laboratory and field experiments. In this research, a mathematical model was formulated to simulate induced defense mechanism of Tomato plant. This model was formulated using Enzyme-Substrate reaction pathways and simulated using SIMBIOlLOGY software, using eight variables and associated parameters. It was shown that tolerance to Bacterial, Fungal and Viral infection was seen to be significantly high as compared to untreated plants, and white fly herbivory reduced. This induced tolerance was triggered using Potassium Phosphite treatment as an elicitor, to initiate a cascade of Enzyme-Substrate reaction which activated the production of Tomatine, Phytogenesis-Related Proteins, and other Phytoalexins and defense genes. It was shown that treated tomato plants were less susceptible to infecetion, upto s≤0.15, while untreated tomato plants were highly susceptible up to over s≤0.69. The production of growth inhibitors was significantly reduced for treated plants and eventually the yield of treated plants increased by y≥57%. The results can also be applied to induce Systemic Acquired Resistance of crops to Insect herbivory, especially on desert Locust (Schistocerca gregaria) a real devastating factor to crop production.

Urban River Ecosystems; An Evaluation of the Proposed Restorative model for River Sosiani, Eldoret City (Management of hydrological systems, to include riparian lands, water towers, water reservoirs, clean rivers and wetlands)

• Dr. Silas K. Leting (The County Government of Uasin Gishu)

Urban river degradation resulting from rapid urbanization constitutes an acute sustainability challenge, exemplified by the Sosiani River in Eldoret—a once vibrant ecological corridor in early 1900s but now facing pollution, wetland encroachment (67% loss since 2005), and plummeting biodiversity. As Eldoret expands by 4.3% annually being the only city in Kenya's North Rift, the strain on urban ecosystems is expected to increase proportionately. The research proposes an integrated restoration framework that combines ecological science, intelligent technologies, and deliberate institutional reforms. Taking a cue from success stories like Cheonggyecheon (Seoul) and Singapore River, the framework employs geospatial mapping, hydrology modeling, and institutional diagnostics to determine root causes. Institutional problems—poor enforcement of the Water Act (2016) and fragmented urban governance— account for 68% of the ecosystem loss, study says. Failure to implement it will result in the loss of 40% of the remaining wetlands by 2045.The "modern urban river" plan employs optimized wastewater infrastructure, IoT water quality sensors, and blue-green infrastructure (i.e., bioswales, constructed wetlands) to build resilience. A County investment of KES 1.5 billion, out of which KES 500 million has been dedicated to fencing and restoring of the wetlands would decrease pollutants by 55%, lower flood risk by 40%, and yield a 9.2% per annum return on investment through eco-tourism, health savings, and disaster avoidance. The dream Sosiani River Restoration Authority (SRRA) would be grounded on enforcement, coordination, and adaptive governance. Grounded on Kenya's Climate Change Act (2016), SDGs 6, 11, and 15, and the Ramsar Convention, this dream substitutes Sosiani as a socio-ecological asset that offers a replicable model for resilient urban futures in Africa.

Thermal Neutron diffusion deceleration inside an infinite dimensions moderator. Calculating neutron age and slowing down of length for fission of neutrons, average energy to thermal energy of Graphite and Beryllium. (Green technologies, bio-innovations and sustainable chemistry)

• Joseph Maritim (Moi University)

Abstract: nuclear energy is clean energy technology as it produces zero greenhouse emissions. Most of the nuclear reactor products are from (n, y) reactions. This are free neutrons with kinetic energy and has large effective cross-section. Our objective was examined the solution of partial differential equation for the case in which the medium is unbound, calculated neutron age and thermal energy for C and Be. The stationary equation of the transfer of neutrons with simplifying assumption lead to the function S which describes the source of neutrons, the required quantity u(x,τ) is concentration of neutrons per unit time, reaching the age τ; consequently, u is the density of deceleration. The solution was found by introducing the Fourier map U(ξ,τ) of the density of deceleration U(x,τ). Taking into account the behavior of density of deceleration at infinity, we obtained u(ξ,τ)=(2π)^(-ξ) e^(-ξ^2 τ). When neutrons reach a specific velocity, they cease to lose energy and their motion can be described using classical theory of diffusion. If the medium is infinite, we introduced Fourier images for ρ and q; expressed through the value of the functionq(z). The calculated neutron age for graphite and beryllium were found to be 12 and 9 respectively. In order to simplify the calculation, a continuous loss of energy for slowing down neutrons was assumed in state of actual discontinuous energy loss.

Seed Banks for Tree Cover and Forest Restoration in Kenya (Seed banks for indigenous trees)

• Dr. Benjamin Kinyili (Kenya Forest Service)

The massive forest degradation caused by anthropogenic activities and exacerbated by climate change has signaled the need for forest habitat restoration efforts. The most appropriate way of restoring these forests is through tree planting where the need for seeds is paramount. Traditionally, seeds for restoration activities have mainly been sourced through collections from the wild, which is unsustainable. In order to ensure responsible restoration practice, Foresters and restoration practitioners continued to explore other options of economical, ethical and sustainable sourcing of seeds. Seed banks can leverage on technical and infrastructural capacity to play a greater and more direct role in supporting biodiversity and ecosystem conservation and restoration, particularly through the supply of quality ecologically and genetically suitable seeds. This paper reviews the use of seed banks in enhancing tree cover and forest restoration in Kenya. This review focuses on status of seed banks in Kenya, seed collecting, field-based seed bulking, handling and storage, seed quality control as well as experience and capacity in facilitating germplasm exchange. Five key roles of seed banks in Kenyan forestry sector include preserving genetic diversity, biodiversity conservation, protect species from extinction, plant breeding programmes and ecological restoration. Technical and physical capacity for ecosystem restoration seed supply available in seed banks in Kenya included availability of germplasm, seed processing, storage, quality assurance and control and germplasm exchange. In Kenya, seed banks have established close working relationships with various experts in making it easy to find information on species phenology, distribution patterns, optimum collecting time and sites with appropriate restoration seeds. Most restoration projects in Kenya give little consideration to seed quality control and assurance. There is a need to explore how the resources amassed through the largely successful ex situ conservation initiatives and efforts can be used to support in situ conservation and restoration activities.

In Vitro Evaluation of Green-Synthesized Silver Nanoparticles (AgNPs) for the Management of Xanthomonas citri and Tylenchulus semipenetrans (Climate change, food security and impact on livelihoods)

• Sadiq Bishir (Moi University)

Citrus production faces major threats from Xanthomonas citri subsp. citri, the causative agent of citrus canker, and Tylenchulus semipenetrans, the citrus nematode, both of which contribute to significant yield losses worldwide. Emerging evidence suggests potential interactions between these pathogens, exacerbating disease severity and complicating management. Conventional control methods, including chemical pesticides and antibiotics, pose environmental risks, contribute to antimicrobial resistance, and may negatively impact non-target organisms. Therefore, there is an urgent need for sustainable and eco-friendly management strategies. This study will investigates the efficacy of green-synthesized silver nanoparticles (AgNPs) in controlling X. citri and T. semipenetrans through in vitro assays. AgNPs will be synthesized using plant extracts as reducing and stabilizing agents, ensuring an environmentally friendly production method. Characterization of the synthesized AgNPs will be conducted using UV-Vis spectroscopy, Fourier-transform infrared (FTIR) spectroscopy, and scanning electron microscopy (SEM) to confirm their properties. The antibacterial activity against X. citri will be assessed using agar well diffusion and minimum inhibitory concentration (MIC) assays, while the nematicidal effect on T. semipenetrans will be evaluated through motility inhibition and mortality tests. Additionally, co-inoculation studies will be performed to investigate possible interactions between the bacterium and the nematode in vitro and assess whether AgNPs can disrupt these interactions. By developing a green nanotechnology-based alternative, this research aims to promote an environmentally sustainable and innovative approach to citrus disease management. The use of biosynthesized AgNPs could minimize reliance on chemical pesticides, reduce environmental contamination, and contribute to climate change mitigation by promoting sustainable agricultural practices.

SOIL STABILIZATION USING STEIN (Other cross-cutting areas)

• Joel Kibiiy (Moi University)

Soil in its natural state is usually unsuitable for engineering applications and must be treated to improve its load bearing characteristics. Emerging technologies make it possible to improve soil properties. STEIN is a commercial product that is mixed with cement and used for the stabilization of soil. It has been used in road pavements and in lining of water canals and other water retaining structures in south-east Asia and is now being introduced to Kenyan and Africa. There is little in the literature on its strength, hydraulic characteristics and environmental impacts. This paper presents the findings of laboratory experiments on soils stabilized with STEIN-cement. Six local soil types from different parts of Kenya were used: planosols, ferrosols, acrisols, andosols, nitisols, and unclassified local soil. X-ray diffraction tests was performed on the soils and the STEIN. Two types of cement were used: pozzolanic Portland cement (PPC) and ordinary Portland cement (OPC). The soils were stabilized in three categories: cement only (control); cement containing 3% STEIN; and cement containing 5% STEIN. The specimens were prepared, cured and tested for unconfined compressive strength (UCS) at 7, 14, and 28 days. The results showed that STEIN and cement consist of numerous similar minerals but in different proportions. There was significant increase in the strength of the soil when STEIN is introduced into the cement compared with stabilizing with cement only. The 5% STEIN-cement specimens gave higher UCS values than the 3% STEIN-cement specimens confirmed by the paired T-test. From the foregoing, it was inferred that STEIN-cement stabilizes soil by combined hydraulic and pozzolanic reactions leading to enhanced strength. The reactions are inorganic, cementatious and thus create stable medium for multi-purpose engineering use. However, further research is recommended on the cost,hydraulic characteristics and environmental impacts of the STEIN-cement stabilized soil. Key words:Soil stabilization,STEIN,Unconfined compressive strength

Farmers adaptation to climate change in Nakuru County, Kenya (Climate change, food security and impact on livelihoods)

• Leonard Karani (Moi University)

Abstract

Assessment of the Current and Future Energy Generation Mix in Uasin Gishu County, Kenya (Energy access)

• Dr. Silas Kering (Uasin Gishu County)

At the global level, local financing of energy generation in such regions has led to accelerated economic growth, reduced foreign reliance on energy, and improved system reliability. The Kenya Constitution of 2010 also set up a system of devolution that vested the responsibility of overseeing most sectors with the counties, including energy. Devolution to the Uasin Gishu County presents an opportunistic benefit in exploiting indigenous energy resources with a possibility of potentially exporting surplus power to neighboring counties and even abroad to contribute own-source revenues.This study evaluates the existing energy mix and future generations possible in Uasin Gishu County. To start with, the installed capacity is currently made up of solar (140 MW), hydro (2 MW), thermal (100 kW), and wind (less than 5 kW). Other investments in development by the private sector include the Kaptagat solar plant for ammonia production (195 MW) and the proposed Copper Hetero Junction Thin Films (Cu-HJT, 20 MW) at the African Economic Zone(AEZ). Understanding that the County is just 30 km away from Kerio Valley oil field, there is a reasonable basis to suggest that indeed it is a candidate for future oil exploration. The County has a significant scope in bio diesel (from big grain crops such as wheat, maize, and sugarcane) and biogas, with over 3,000 dairy farmers eligible for small-scale digester installation. A research on Hydrogen energy is being conducted by Moi University and will provide future opportunities in the sector. This paper attempts to approximate the collective potential energy production from such resources, quantify cost saving by reduced grid dependency, and conduct a cost-benefit analysis to assess whether an expansion in localized generation is economically viable. Key Words:Energy Mix, Solar, Wind, Hydro, hydrogen, Biodiesel, Biogas, Cu-HJT

Restoring our landscapes: The use of Artificial Intelligence in curbing Global warming (Restoration of natural landscapes, to include mining areas, water catchment areas)

• Jerome Dewane (Moi University)

Global warming, fueled by fossil fuel combustion, deforestation, and industrial pollution, endangers ecosystems, notably the biodiverse Great Rift Valley. This study explores four Artificial Intelligence (AI) strategies to mitigate climate change through landscape restoration: (1) AI-optimized agroforestry, boosting yields by 20% in India while sequestering carbon; (2) Integrated landscape initiatives in Africa, using drones to restore 500,000 hectares; (3) AI-driven forest fire management, predicting wildfires 48 hours in advance; and (4) Smart Archive Models, enhancing climate data accessibility to inform restoration policies. These approaches reduce greenhouse gas emissions by 15–20%, protect biodiversity, and foster sustainable rural development. Based on a systematic review of 200+ studies, we urge policymakers to invest in AI-driven solutions to restore 10 million hectares by 2030, safeguarding regions like the Great Rift Valley.

Climate change’ induced cost on soil security and its implication on food security in Homa-Bay County, Kenya (Climate change, food security and impact on livelihoods)

• Wicklife Ojalla (Moi University)

While there are studies on effect of climate change on food insecurity in Homa-Bay [1,3], studies relating to effect of climate change on soil quality and food security aren’t evident. This paper detailed influence of climate change on soil security and its implication on food security in the study area. It examined the cost of anthropogenic-based practices (ABPs) on climate change; interrogated their ripple effect on soil and food security situation. Praxeology theory was used to explore environmental consequences of ABPs. 250 respondents were sampled from 262,036 households for quantitative data and 20 Key Informants purposively identified for qualitative data. It was a cross-sectional survey study and quantitative data were analyzed descriptively and inferentially using Statistical Package for Social Sciences (SPSS) version 25.0. Opinions from FGDs, KII, and Field Observation were qualitatively analyzed. Results showed monoculture (96.2%), tractor tillage (71.4%), livestocking (82.3%), stone mining (92.4%), deforestation (89.1%), and hill slope-based practices (87.9%) induced climate change. Binary Logistic Regression Analysis (BLRA) indicated deforestation (B = -0.462, S.E = 0.381 and P< 0.032), stone mining (B= -0.756, S.E = 0.364 and P = 0.038), conventional tillage (B= -0.961, S.E = 0.489 and P = 0.05), slope-based activities (B= -0.801, S.E = 0.368 and P = 0.0290) predicted food insecurity. Study concludes that ABPs result to climate change, soil insecurity and significantly cause food insecurity in Homa-Bay County. The study recommends suspension of slope-based activities on elevated areas particularly on Homa-Hills, review stone extraction and tractor cultivation policies, intensive and purposive reforestation programs.

Assessment of Water Quality in Selected Fish Farms in Uasin Gishu County (Management of hydrological systems, to include riparian lands, water towers, water reservoirs, clean rivers and wetlands)

• Patricia Kosgei (University of Eldoret)

Abstract This study evaluated water quality across five farms to assess their suitability for fish farming. Efforts to promote fish farming in Uasin Gishu County persist, but research on enhancing fisheries productivity through better pond management remains limited. Most studies focus on production techniques or market development, neglecting the importance of effective pond management for sustainable growth. Key physicochemical parameters, including pH, Biological oxygen demand, Chemical oxygen demand, salinity, conductivity, and temperature, were measured in-situ in selected fish ponds using a Multi-probe HQ40D meter, while water samples for nitrate analysis were collected in triplicate and transported to the laboratory for further analysis. Data analysis involved ANOVA and Kruskal-Wallis tests, with Tukey’s and Dunn’s tests identifying variations and Fisher’s exact test assessing associations between water quality parameters and farm, pond, type, and measurement date (P ≤ 0.05).Most farms maintained suitable water temperatures (25–30°C), with salinity, pH, and TDS within acceptable limits. However, dissolved oxygen levels often fell below the recommended range (60–100% or 0.1–0.2 mmol/L), which could negatively impact aquatic life.Conductivity showed slight variations, while high COD and BOD levels (exceeding 50 mg/L and 20 mg/L, respectively) indicated organic pollution. Although nitrate levels remained stable, microbial contamination was a significant concern, with coliform and bacterial counts frequently surpassing 10,000 CFU. These findings highlight the need for improved water management to control pollution and ensure sustainable aquaculture. This study found most water quality parameters suitable for aquaculture, but low dissolved oxygen, high BOD and COD, and microbial contamination in some farms could harm fish health and productivity. To enhance water quality, regular pond cleaning, controlled feeding, and monitoring should be prioritized to reduce organic pollution, maintain optimal BOD and COD levels, and control microbial contamination. Keywords: Water quality, Aquaculture, coliforms, Nitrates.

Creating Sustainable Solid Waste Management Practices, An Analysis of the Proposed Solid Waste Management Solutions for Eldoret City, Kenya (Waste management including dump sites and landfills)

• Evans Kapkea (The County Government of Uasin Gishu)

The 20th century saw a radical shift in population dynamics, with rural-to-urban migration transforming small towns into mega cities. This rapid urbanization, particularly in low- and middle-income countries, has accessioned an increased generation of solid waste within the municipalities and major cities, thereby piling pressure on sustainable environmental programs, public health, and local government finances. Uasin Gishu County, home to the rapidly growing Eldoret City, is a case in point. Eldoret city chunks out approximately 250 metric tons of waste daily, of which 55% are organic, 23% recyclable, and 22% inert waste. The Kipkenyo dumpsite is already more than full, as is the case with other global landfill disasters such as Minamata (Japan) and Kiteezi (Uganda). Projections indicate a 220% volume growth in waste by 2044. Policy loopholes (70%) and infrastructural deficiencies (35%) cause waste management inefficiencies. This study proposes an integrated investment scheme of $12.3 million involving modular bioreactor landfills, composting facilities, PPP-funded recycling parks, and data-driven logistics optimization. Containerization has already reduced litter by 32%, and route optimization has reduced operational costs by 18%. The proposed system is projected to yield a 14% return on investment per annum, reduce disease incidence by 25%, and create over 1,200 green jobs. Sustainable solid waste management is positioned here as not merely an environmental necessity, but also a corner stone of urban resilience, inclusive economics, and climate-congruent governance. The model accommodates SDGs 11 and 12 and offers an export template for use in other fast-developing cities in the Global South.

Seasonal variation in diet quality of women and young children from two agro-ecological zones in Kenya (Climate change, food security and impact on livelihoods)

• Maureen Cheserek (Egerton University)

Background and objective: Climate change can disrupt food availability, reduce access to food, and affect diet quality. This study examined the effect of seasonality on household dietary diversity (HDDS) and diet quality of women and children in two agro-ecological zones of Rongai sub-county, Nakuru, Kenya. Methodology: A cross-sectional study of 388 mother-child pair was conducted during lean and plenty season. Household food insecurity access scale was used to measure food security. The HDDS were computed based on 12 food groups. A 24-Hour Dietary Recall was used to generate dietary diversity scores (DDS) of women and children. Results: The HDDS of households from low agricultural potential areas was not affected (P>0.05) by seasonality despite increased food access during plenty season (57.3%) as compared to lean season (36.8%). However, in high potential areas, food access increased (P>0.05) from 55.8% to 73.5% while HDDS decreased. Women who achieved minimum dietary diversity (MDD) increased [low potential areas (13.9% vs. 57.8%, P<0.001)] and high potential areas [20.0% vs. 49.1%, P<0.001)] in lean and plenty seasons respectively. Furthermore, children who achieved MDD significantly decreased from 58.9% in lean season to 47% during plenty season in low potential areas while there was no change in the dietary diversity of children from high potential areas. Binary logistic regression showed no effect of seasonality on child diet quality, however, seasonal changes significantly (P<0.001) reduced household food access, HDDS and diet quality of women. Conclusion and Recommendation: Child diet quality was not affected by seasonal variations in the two agroecological zones; however, it negatively affected household food access, household dietary diversity and diet quality of women. It is important to develop targeted season-specific nutrition interventions to adequately address food access and diet quality for improved nutrition outcomes.

Trends of Hypertension Prevalence in Kenya (Climate change and health)

• Eliud koech (MOI UNIVERSITY)

Abstract Aim: Hypertension prevalence in Kenya exhibits substantial variation across demographic and geographic groups, posing challenges for the development of universally effective interventions. This study aims to identify and analyse trends in hypertension prevalence disaggregated by age, sex, and county. Method: We analysed hypertension prevalence trends among males and females aged 15–49 years using data from the 2022 Kenya Demographic and Health Survey. Counties were categorised according to the 47 administrative units defined by the Kenya National Bureau of Statistics, and age was stratified into three groups: 15–24, 25–34, and 35–49 years. To assess prevalence inequalities across these groups, we employed a log-binomial regression model. Results: The risk of hypertension increases significantly with age. Compared to individuals aged 15–24 years, those aged 25–34 exhibit a 1.77-fold higher risk (p = 0.000118), while individuals aged 35–49 demonstrate a 5.67-fold increased risk (p < 0.0001). Females are at a significantly higher risk of hypertension compared to males, with a relative risk (RR) of 4.11 (p = 0.000489). High-risk counties include Nairobi, Kisumu, and Nakuru. In contrast, counties such as Wajir (RR ≈ 0.000004, p < 0.0001), Nandi (RR ≈ 0.08, p = 0.003), Elgeyo-Marakwet (RR ≈ 0.06, p = 0.015), and Kirinyaga (RR ≈ 0.15, p = 0.019) exhibit significantly lower risk levels. Conversely, females in Kirinyaga are at elevated risk (RR ≈ 3.64, p = 0.043). Notably, hypertension risk among females tends to decline with age, particularly among those aged 35–49 years (risk change: –0.60, p = 0.018). Conclusion: The findings highlight the need for targeted interventions for older adults and females, and call for further investigation into protective factors in low-risk counties to guide effective prevention strategies Keywords: hypertension prevalence, trends, logbinomial model, disaggregated.

Integrating Climate Smart Agriculture and Rehabilitation in Mining Affected areas;A proposed initiative in Kimwarer Flourspar Region (Restoration of natural landscapes, to include mining areas, water catchment areas)

• Eda Chebet Kapkea (Hug a cedar foundation)

Mining has long been a vital economic activity in the Kimwarer-Fluorspar region of Elgeyo Marakwet County. For years, fluorspar mining made Kimwarer a lively business town, offering jobs and attracting trade and services that sustained the local economy. However, this economic boost came with significant environmental consequences. Over time, deforestation, soil erosion, and the degradation of fertile land became widespread. These effects not only reduced the land’s agricultural value but also damaged local ecosystems, leaving behind barren landscapes and vulnerable livelihoods. The closure of the mine in 2016 intensified these challenges, leading to both economic and environmental decline. In 2024, with mining activities resuming, new opportunities for both economic revival and ecological restoration have emerged. This youth-led initiative proposes the integration of climate-smart agriculture, agroforestry, and sustainable land management in tandem with ongoing mining activities. The goal is to reclaim degraded land, restore soil fertility, and enhance environmental resilience while ensuring that mining and conservation work together for the benefit of the local community. Methods: Field visit to Kimwarer Fluorspar mine on 20th Feb 2025, interviews with local community members and analysis of secondary data were used to gather insights for this research. Findings: Findings show mining has degraded land and reduced agricultural value. However, community interest in land restoration and youth-led initiatives presents strong potential for integrating mining with sustainable environmental practices. Conclusion: Mining and environmental restoration can coexist. With youth-led initiatives, Kimwarer’s revival offers a chance to restore degraded land, improve livelihoods, and promote sustainable development aligned with climate action goals.

FORECASTING DROUGHT EVENTS IN KENYA ASALS REGION: A CNN-BASED FRAMEWORK USING CHIRPS PRECIPITATION DATA. (Big data and AI for climate change solutions)

• Bernice Mathenge (African Centre of Excellence Data Science)

**Aim:** Food insecurity and economic instability have resulted from the severe effects of droughts on agricultural output in Kenya's Arid and Semi-Arid Lands (ASALs). These regions have faced increasing vulnerability due to erratic rainfall patterns, resulting in severe crop failures and livestock losses. Despite efforts to forecast droughts, existing techniques have frequently been imprecise, thereby hindering timely intervention. By developing a CNN-based framework with CHIRPS precipitation data and the Standardised Precipitation Index (SPI), this study aimed to increase the precision of drought forecasts and provide actionable insights on managing the effects of drought in ASALs by describing past drought occurrences, analysing precipitation trends, and utilising machine learning. **Method:** The research involved preprocessing CHIRPS data, spanning from 1981 to 2024, to calculate SPI values and address missing data using the Inverse Distance Weighting (IDW) method. A CNN-based model that integrated precipitation's temporal and spatial characteristics was developed to forecast drought situations. The model was trained to identify spatial hotspots and forecast drought events across the 14 semi-arid counties in Kenya's ASAL region. **Results:** To facilitate more informed decision-making for drought mitigation, this framework aimed to increase the accuracy and timeliness of drought predictions. When compared to conventional techniques, the CNN model performed better, improving the capacity to predict drought occurrences with more accuracy and spatial precision. **Conclusion:** The results of this study offer a useful tool for enhancing resilience in Kenya's ASALs and informing proactive drought management strategies. **Keywords:** CNN-Based, Chirps Precipitation Data, Forecasting Drought

Optimizing Sweet Potatoes Yield: An Advanced Modelling using SORDs Constructed using Trigonometric Functions (Smart and sustainable agriculture)

• DENNIS MATUNDURA (MOI UNIVERSITY)

Sweet potato (\textit{Ipomoea batatas}) is a vital food crop with the potential to enhance global food security. However, its yield optimization remains a challenge due to soil fertility variations, climatic factors, and inefficient agronomic practices. Traditional experimental designs often fail to capture complex interactions between variables, necessitating advanced optimization techniques. This study employs second-order rotatable designs (SORD) constructed using trigonometric functions to model and optimize sweet potato yield under different organic fertilizer applications. The objective is to determine the most effective combination and application rate of poultry, goat, and rabbit manure for maximizing yield. A SORD with 23 design points was implemented to ensure uniform precision across the factor space. Field experiments were conducted using randomized block designs, and data were analyzed using response surface methodology (RSM). The results indicate that poultry manure significantly enhances sweet potato yield compared to goat and rabbit manure. However, a combination of poultry and goat manure in a 3:2 ratio provided the highest yield increase. The trigonometric-based SORD approach effectively captured interactions and quadratic effects, leading to precise yield optimization. The study concludes that SORD constructed with trigonometric functions offers an efficient framework for optimizing crop yield under varying soil fertility conditions. It is recommended that farmers adopt a mixed manure approach to improve sweet potato productivity sustainably. Further research should explore the integration of additional soil amendments, long-term soil health effects, and the impact of climate variability on sweet potato yield using advanced modeling techniques.

Spatiotemporal Dynamics of Drought in Kajiado County, Kenya: Insights from SARIMA Modeling and SPI Analysis (Big data and AI for climate change solutions)

• JUDITH ROTICH (Department of Animal Sciences, Egerton University, P.O. Box 536-20115, Egerton, Kenya.)

Understanding the spatiotemporal dynamics of drought is essential for managing climate-related risks in arid and semi-arid regions. This study investigates long-term trends in drought severity in Kajiado County, Kenya, using historical climate data from 1981 to 2023. The region, predominantly inhabited by pastoralist communities, is highly vulnerable to climatic fluctuations, particularly variability in precipitation and rising temperatures. To characterise temporal trends and project future climate variability, the study employs Seasonal Autoregressive Integrated Moving Average (SARIMA) models alongside the Standardised Precipitation Index (SPI). Monthly precipitation and temperature data from three subcounties; Kajiado East, West, and Central were analysed. Following preprocessing, stationarity was assessed using the Augmented Dickey-Fuller test, and SARIMA model parameters were optimised using ACF, PACF, and information criteria metrics. The best-fitting SARIMA models were identified for each subcounty, and forecasts extending to 2028 reveal consistent seasonal patterns, particularly rainfall peaks in April and November and troughs in July–August. SPI analysis on a 3-month scale enabled classification of wet and dry periods, revealing significant interannual variability with documented extreme droughts (for example, 1982–1984, 1994, 2000) and wet events (for example, 1998, 2010). The Mann-Kendall trend test and Sen’s slope estimator showed statistically significant upward trends in SPI values across all subcounties, suggesting a gradual shift towards wetter conditions. However, correlation analysis between SPI and temperature anomalies revealed weak to moderate negative relationships, indicating the compounding effect of warming on drought severity. This integrated modelling approach not only quantifies past and projected climatic trends but also enhances understanding of hydroclimatic variability crucial for informed adaptation planning. The findings underscore the importance of localised forecasting tools in supporting pastoralist resilience and policy formulation in the face of intensifying climate variability.

Application of Response Surface Methodology on the yield of maize as a fodder crop (Climate change, food security and impact on livelihoods)

• Silver Keny Jeptoo (Moi University)

Maize is one of the stable foods in Kenya, and it is gaining prominence as an animal fodder crop for cattle farmers. As technology improves, and people abandon the traditional nomadic pastoralism, there is a need to have adequate storage of animal feeds to sustain animals around the season. The most important quality of fodder crops is to be lush, tall, and bushy, a characteristic determined by nitrogen uptake, facilitated by water, phosphate, and potassium. In this research, the investigation sought to ascertain the optimal vegetative yield of maize with minimum water supply using Response Surface Methodology (RSM) in semi-dry soil enriched with NPK, in a controlled greenhouse environment. The experimental treatments were determined using the Central Composite Design based on varying levels of water supply (10%, 25%, and 50% of soil field capacity), nitrogen (10, 15, and 25 g hole-1), and phosphorus and potassium equally applied at (5, 10, 15g hole-1). The investigation's findings demonstrated that increased nitrogen fertilization rate positively influenced all agronomic traits, but left high nitrogen concentrations in the soil due to minimal absorption media. Nitrogen increased plant bush weight, and leave area, but minimal water supply curtailed the plant height and agronomic attributes. The optimal levels of irrigation and nitrogen fertilizer were found to be 42.73 – 47.80%, and 3.38–5.69 g hole-1 respectively. The optimal amounts for NPK retention in soil and plant uptake were 82.57 – 98.00%, and 4.20–5.98 g hole-1, respectively. The study concluded that plants with minimal water supply, like that of semi-arid areas, require nitrogen levels not greater than 50% per hole, since excess was seen to cause leave necrosis. The availability of other nutrients was however seen to plant biomass and enhance nutrient uptake.

The effect of Coumarin additives on optoelectronic properties and power conversion efficiency of Formamidinium based-perovskite solar cells. (Research and innovation towards green energy: hydrogen cells, carbon dioxide batteries, and hybrid technologies among others)

• Naomy Chepngetich (Chepngetich N)

Perovskite solar cell (PSC) is among the emerging photovoltaic technologies known for their high solar power conversion efficiency (PCE) and low manufacturing costs. However, their solution- based processing leads to the formation of defects within the bulk of the perovskite layer and at its interfaces with the charge transport layers. These defects act as charge trapping centers and provide the degradation routes which not only reduces the PCE of perovskite solar cells but also leads to instability issues. Various defect passivation strategies have been developed but the use of additives appears to have gained preferences over the others. In this work, 1-D Solar cell capacitance simulator (SCAPS-1D) was employed to study the effects of Coumarin additive on the PCE of formamidinium-based PSC. Parametric studies were carried out on the Coumarin modified PSC device in order to identify routes for further improvement in the PCE. It was found that a further reduction in defect density, band gap and series resistance together with an increase in the charge carrier mobilities are important in achieving higher PCE. This study provides an insight into the role of additives in enhancing the PCE of PSC and the output serves as a reference to guide the design of effective experimental model PSC devices. Keywords: Coumarin additive, perovskite film, power conversion efficiency, SCAPS-1D.

Assessing the Diversity of Parasites and Microbes in Fish from Selected Fish Farms in Uasin Gishu County (Livestock keeping, marine and aquatic systems and the blue economy)

• Edwin Mutai (University of Eldoret)

Abstract Fish farming plays a crucial role in food security and economic development, yet bacterial and parasitic infections threaten productivity and fish health. This study investigates the distribution and prevalence of bacterial and parasitic species in fish organs across different farms, ponds, and pond types in Uasin Gishu County, Kenya. A total of 468 fish samples were analyzed, yielding 154 bacterial isolates and various parasitic infestations identified through cultural, biochemical, and microscopic characterization. The Kruskal-Wallis test revealed significant differences (p ≤ 0.05) in bacterial prevalence across fish organs, farms, and measurement dates. Dunn’s post hoc test further highlighted significant pairwise differences. The results revealed significant differences (p ≤ 0.05) in bacterial and parasitic prevalence across fish organs, farms, and measurement dates. Escherichia coli was the most prevalent bacterial species, followed by Pseudomonas aeruginosa, Vibrio harveyi, and Vibrio alginolyticus. The gills exhibited the highest bacterial diversity, while the kidneys had the lowest. Parasitic infestations, including nematodes, cestodes, and protozoa, were predominantly found in the intestines and gills, with variations influenced by farm location, pond type, and seasonal factors. To mitigate these infections, regular water quality assessments, improved biosecurity measures, routine fish health monitoring, and antiparasitic treatments should be implemented. Further research on antibiotic resistance and parasitic control strategies is recommended to enhance sustainable aquaculture management and minimize disease risks. Keywords: Bacterial diversity, parasitic infections, fish farming, aquaculture management

Neutron capture reaction of 〖Au〗^197characterized by Γ_y=0.124eV and Γ_n=0.007E^(b 1⁄2) eV and the role of exotic neutron rich nuclei (Solar, wind and geothermal sources of energy)

• Joseph Maritim (Moi University)

Abstract: The use of nuclear energy offers numerous peaceful applications in the generation of electricity, medical diagnostics and treatment, agricultural advancement and food preservation. The main aim was to apply the concept of the cross-section to resonance in a quantitative manner. It gave the value of a single resonance level formed by an incident particle with zero angular momentum and charge zero so that the spin and the coulomb effects were not taken into consideration. The level of compound nucleus is bound, the excitation by incident particle was treated as oscillation produced by electromagnetic wave. We varied the nuclear cross-section with the incident energy, the same way the energy in a forced oscillation varies with incident frequency. In classical treatment, resonant circuits absorb energy because of resistive levels. For the case of nuclear, damping arises because of decay possibilities, hence nuclear states have a finite width Γ. A decaying state wave function of mean energy E_0 corresponds to an exponential decrease of intensity of excitation. It is via the r-process that exotic neutron rich nuclei play an important role in the formation of heavy elements. The result showed that a decaying state is not a function of definite energy E_ . A sharp resonance corresponds to a narrow width, hence the peak cross-section is 3.446×〖10〗^43 barns and was analogous to the dispersion formula. The compound formed nucleus in this resonance absorption has a spin 2. Improved nuclear structure and reaction calculation gives a better understanding of radiative capture rates of light-nuclei and medium-nuclei which affects the abundance of heavier nuclei.

AI and Big Data Technologies For Renewable Energy Management (Big data and AI for climate change solutions)

• IRINE SAMOEI (Moi University)

Energy is an essential element, but its negative consequences such as environmental deterioration, resource depletion and energy dependencies puts energy efficiency alternatives/or solutions in the spotlight. Therefore there is need for the fusion of AI and Big data in promoting sustainable growth in the renewable energy sector, AI and Big Data focuses on optimizing algorithms, reducing computational needs, and using renewable energy. These technologies are main drivers for transformative approach towards achieving Sustainable Development Goals (SDG), Mainly SDG 7(Affordable and clean energy),SDG 9(Industry, Innovation and Infrastructure) and SDG 13 (Climate Action).This study will explore the role of AI and Big Data in renewable energy and sustainable development. The methodology will employ text mining techniques to refine AI and Big Data concepts into targeted keywords, with further filtering via the All Science Journals Classification system and SDG-mapping tools to identify publications most relevant to renewable energy applications. The research specifically investigates how predictive analytics can forecast future energy demands, assess climate risks, and identify renewable energy potential across different regions. By identifying best practices and innovation opportunities at this intersection, this study aims to provide a framework that can accelerate progress toward energy sustainability and support global efforts to achieve a net-zero future. Keywords (Artificial Intelligence, Big Data, Sustainable Development Goals, Renewable Energy, Net Zero)

Mathematical Modeling and Parameter Estimation of an Optimal Solar Food Dryer (Solar, wind and geothermal sources of energy)

• Kenneth Korkoren (Moi University)

Eminent threat caused by post-harvest losses due to inadequate drying and poor storage is responsible for up to 40-60% loses of agricultural produce each season. In order to address this issue, this paper seeks to formulate a mathematical model and simulate the characteristics of a solar dryer for the purpose of designing an effective and sustainable, low cost thermal solar dryer suitable for dehydrating a variety of agricultural products. The modeled solar food drier has four major parts, namely: Solar heat collector: Closed loop pipe network: Heat exchangers: and the Drying Chamber. The mathematical model was formulated using differential equations, and simulation using SIMULINK. The simulation results showed that, a solar collector with aperture area of A_c=14.4m^2 and a fluid volume of V_c=500l, when exposed to solar irradiation of I_c=1.367KW/m^2 at η_c=80% efficiency is able to heat water from 〖T_in=22〗^0 C to T_co=〖70〗^0 C in 12 hours at a flow rate of v ̇_c=1.128l/s. This energy if transmitted by insulated pipes to a set of 5 heat exchangers each of area A=1m^2, and radiative heat transfer coefficient h_r=100W/m^2 K cumulatively dissipates hot air of maximum 〖230〗^0 C at v ̇=250cm^3/s, and minimum of 〖90〗^0 C at v ̇=2000cm^3/s air mass flow rate. This output temperatures of dry air is regulated as desired according to the specifications of the food products to be dried. In absence of solar energy, Liquefied Petroleum Gas is intermittently used depending on the level of solar insolation. It was found that the optimal cost of the gas in this energy mix is reduced by over 67.86%. This strongly makes the use of solar in food dryers an ideal green energy to be used in mitigating post-harvest losses.

Pretreatment of Lignocellulosic Materials for Improved Biogas Production. A Review (The future of biofuels)

• Nathan Bogonko (Kenya Industrial Research and Development Institute (KIRDI))

The increase in Population and industrialization has resulted to an increase in energy demand and consumptions. Currently fossil fuels are the major source of staple energy to meet this demand. Over relying on non-renewable energy forms that are expensive, depletable and emitting large amounts of greenhouse gases hence causing adverse effects to both humans and environment. Due to these effects, there is an urgent need to explore and develop alternative and sustainable energy technologies. Use of renewable energy sources are not only sustainable but friendly both for the user and the environment and offers the best solution to address these global energy challenges. One of the sustainable energy sources is biogas that is produced by anaerobic digestion (AD)using different wastes such as agricultural residues, animal manure, and other organic wastes. Despite the availability of large amounts of agricultural waste, the use of lignocellulosic biomass for biogas production by anaerobic digestion has not been widely adopted due to the complicated structure of the plant cell wall making it resistant to microbial attack. This therefore calls for pretreatment of the lignocellulosic biomass in order to achieve the high biogas yields. This paper reviews the various pretreatment techniques, of lignocellulosic biomass for enhanced biogas production. It also highlights the limitations of these pretreatment technologies and the need to develop environmentally friendly technologies using locally available materials.

Intelligent Optimization of PI-Controlled Grid-Connected Inverters for Enhanced Power Quality (Solar, wind and geothermal sources of energy)

• Tiku Fidelis Etanya (PhD Student)

The increasing penetration of renewable energy sources (solar and wind energy) into modern power grids introduces significant power quality challenges, notably power fluctuations due to their intermittent nature and total harmonic distortion (THD) caused by power electronic-based interface devices, such as grid-connected inverters. Addressing these issues requires robust control strategies to enhance system stability and efficiency. This study implements a proportional-integral (PI) current control strategy optimized using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), with Ziegler-Nichols (Z-N) tuning serving as a benchmark. The performance of the control strategy is evaluated using the Integral Time Absolute Error (ITAE) metric. Simulation results demonstrate that PSO yields superior control accuracy, reducing ITAE to 0.1605 for the D-axis and 0.1491 for the Q-axis control, followed by GA with 0.2053 and 0.1519, while Z-N records significantly higher values of 1.7658 and 1.6595, respectively. In terms of power quality, the total voltage harmonic distortion (THD_V) remains at 0.0% due to effective filtering, while the total current harmonic distortion (THD_i) is minimized to 0.17% with PSO, compared to 0.21% for GA and 1.98% for ZN. The optimized PI control strategy ensures that THD values comply with IEEE 519-2014 and IEC 61000-3-6 Standards, demonstrating its effectiveness in mitigating power fluctuations, reducing harmonics, and improving grid stability. These findings emphasize the critical role of intelligent optimization in enhancing power quality for grid-connected renewable energy systems.

Mathematical Modelling of Energy Mix and Optimization of Renewable Energy (Energy access)

• Robert Sigei (Moi University)

With energy as direct and indirect fundamental life supporting resource, the domestic and industrial demands for energy has been rising due to technological advancement, population increase, and economic growth. Various sources of energy including use of fuels, hydro-electric energy, geothermal energy, wind energy, solar energy and nuclear energy are all available alternative sources of energy in different proportions. Production and distribution of energy in an attempt to satisfy the inhomogeneous individual needs, in tandem with the desire to conserve the environment, has been a complex problem, with pertinent constraints including demand, supply, production, distribution and environmental impact dynamics. Mathematical Modelling of Energy Mix and stability in the interchange is considered in this research as a feasible solution to the losses through leakage and wastage, caused by distribution of unused power loading. Through the analysis of individualized demands and associated production and distribution cost. The objectives of this study is to formulate a mathematical model to analyse and determine the desired parameter thresholds that guarantee stability and robustness of energy variation. This is done using Neural Networks feedback control algorithms, with adaptation so as to automatically control and maintain the optimal stability of energy levels during changeover. Using three types of users: Household, School and Small Commercial Entreprise, simulated results show that energy shifts is stable, with a peak time t_p=0.4s and power overshoot of 18.5%. This is stabilized to acceptable tolerance of 2% in a settling time of t_s=4.35s. Energy cost analysis showed that the Energy Mix of Hydro Electicity (E), Solar Power (S) and use of LPG Gas (G) is optimal when used in the ratio E:S:G=6:129:1. Using a Smart Grid system, all sources of energy can be intelligently mixed for the achievement of optimal individualized energy consumption and distribution mix.

A case of a 5 MW, 10 MWH off Grid Solar Powered Street Lighting Project for Eldoret City, Kenya (Solar, wind and geothermal sources of energy)

• Dr. Silas K. Leting (The County Government of Uasin Gishu)

Street lighting, a devolved function under Kenya’s Constitution (2010), is managed by County Governments. However, infrastructure is often controlled by external agencies, with one operator charging Uasin Gishu County USD 2 million annually for street lighting services, projected to rise to USD 4 million in 10 years due to tariff increases. Eldoret City enjoys high solar irradiance (2,000 kWh/m²/year,SD ≈ 50 kWh/m²/year) and approximately 65% sunny days annually.Uasin Gishu County hosts key solar projects, including the operational 55 MW Kesses 1 Solar Plant, the operational 40 MW Radiant Solar Plant, and the 40 MW Eldosol Solar Plant (construction completed and commissioning), totaling approximately 135 MW of installed solar capacity which is fed to the grid and about 20 MW that is captive power.This paper evaluates both technical and financial feasibility of constructing a 5 MW, 10 MWh off-grid solar plant to power 20,000 LED street lanterns (60 W, 12 h/day, 5,256 MWh/year) in Eldoret City, comparing its financial implications with the current operator-based model. If the current model is maintained, it is projected that the County will spend 92 Million USD in the next 15 years for expansion, repair and maintenance and bills payment to the independent operator (driven by the annual cost escalation of 8.2%) compared to 23 Million USD required to set up, operate and maintain the proposed off grid solar plant over the same period. Additional benefits include potential carbon credit revenues ~USD 0.552 million (USD 10/tCO₂e, 3,679 tCO₂e/year, SD ≈ 200 tCO₂e) and enhanced system reliability. The opportunities for financing of the project through Public Private Partnerships (PPP) is reviewed as a probable financing model to bridge the gap of huge initial capital costs of the project at the start which may not be accommodated within the County budget.

Mainstreaming Gender and Youths in Climate Governance: Re-imagining Resilience through Marginalized Groups Political Ecology and Decentralized Innovations in Uasin Gishu, Kenya (The effect of culture and religion in climate change adaptation and mitigation)

• Jonathan Bii Chelilim (Uasin Gishu County Government)

Gender disparities and youth exclusion in the political ecology are significant barriers to both social and environmental resilience development in Kenya. This study utilizes a mixed-methods approach that includes quasi-experimental analysis, participatory GIS mapping, and institutional ethnography to assess how structural exclusions such as patriarchal land tenure (where just 18% of women own formal land titles) and youth and women's exclusion from policy design limit their agency in climate action.Despite such constraints, women's groups have established wetland rehabilitation programs and agro ecology, and youth groups have organized clean-up initiatives, civic education platforms, and biogas installations for reducing firewood reliance by 30–40%. However, many of these groups remain unregistered and informal, which precludes them from fully benefiting from institutional support and funding mechanisms. As a result, they are unable to access the financial resources and opportunities available within the county's climate budget, which is often directed toward formally recognized entities. Additionally, capacity development programs ignore local cultural constraints, e.g., gendered land inheritance patterns.This paper advocates for three key reforms: (1) the enforced implementation of 30% binding quotas for the representation of women and youth in decision-making bodies; (2) the establishment of climate finance mechanisms to support microloans for gender-responsive innovations; and (3) the integration of inter sectional vulnerability analysis into both the Kenya Climate Change Act and the Uasin Gishu Climate Change Act. These reforms are essential, as inclusive governance not only advances SDGs 5, 13, and 17, but also serves as a cornerstone for achieving sustainable climate resilience and advancing gender and youth equality in the long term.